Download Institutionen för medicin och hälsa Department of Medical and Health Sciences

Institutionen
för medicin och hälsa
Department of Medical and Health Sciences
Master Thesis
Synthetic MRI for visualization of quantitative MRI
Examensarbete utfört i medicinsk teknik
vid Tekniska högskolan i Linköping
av
Erika Peterson
LITH-IMH/RV-A--10/001--SE
Linköping 2008
Department of Medical and Health Sciences
Linköpings universitet
SE-581 83 Linköping, Sweden
Linköpings tekniska högskola
Linköpings universitet
581 83 Linköping
Synthetic MRI for visualization of quantitative MRI
Examensarbete utfört i medicinsk teknik
vid Tekniska högskolan i Linköping
av
Erika Peterson
LITH-IMH/RV-A--10/001--SE
Supervisor:
Marcel Warntjes
CMIV, Linköpings universitet
Examiner:
Peter Lundberg
IMH, Linköpings universitet
Linköping, 4 September, 2008
Avdelning, Institution
Division, Department
Division of Medicine and Health
Datum
Date
Department of Medical and Health Sciences
Linköpings universitet
SE-581 83 Linköping, Sweden
Språk
Language
Rapporttyp
Report category
ISBN
Svenska/Swedish
Licentiatavhandling
ISRN
Engelska/English
Examensarbete
C-uppsats
D-uppsats
Övrig rapport
2008-09-04
—
LITH-IMH/RV-A--10/001--SE
Serietitel och serienummer ISSN
Title of series, numbering
—
URL för elektronisk version
http://urn.kb.se/resolve?urn=urn:nbn:se:
http://www.imh.liu.se
liu:diva-102651
http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-ZZZZ
Titel
Title
Syntetisk MRT som visualisering av kvantitativ MRT
Synthetic MRI for visualization of quantitative MRI
Författare Erika Peterson
Author
Sammanfattning
Abstract
Magnetic resonance imaging (MRI) is an imaging technique that is used in
hospitals worldwide. The images are acquired through the use of an MRI scanner
and the clinical information is provided through the image contrast, which is
based on the magnetic properties in biological tissue. By altering the scanner
settings, images with different contrast properties can be obtained. Conventional
MRI is a qualitative imaging technique and no absolute measurements are
performed. At Center for Medical Imaging and Visualization (CMIV) researchers
are developing a new MRI technique named synthetic MRI (SyMRI). SyMRI is
based on quantitative measurements of data and absolute values of the magnetic
properties of the biological tissue can be obtained.
The purpose of this master thesis has been to take the development of
SyMRI a step further by developing and implementing a visualization studio
for SyMRI imaging of the human brain. The software, SyMRI Brain Studio,
is intended to be used in clinical routine. Input from radiologists was used to
evaluate the imaging technique and the software. Additionally, the requirements
of the radiologists were converted into technical specifications for the imaging
technique and SyMRI Brain Studio. Additionally, validation of the potential in
terms of replacing conventional MRI with SyMRI Brain Studio was performed.
The work resulted in visualization software that provides a solid formation
for the future development of SyMRI Brain Studio into a clinical tool that can
be used for validation and research purposes. A list of suggestions for the future
developments is also presented. Future clinical evaluation, technical improvements
and research are required in order to estimate the potential of SyMRI and to
introduce the technique as a generally used clinical tool.
Nyckelord
Keywords
magnetic resonance imaging, absolute quantification, synthetic magnetic resonance
imaging, visualization
Abstract
Magnetic resonance imaging (MRI) is an imaging technique that is used in hospitals worldwide. The images are acquired through the use of an MRI scanner and
the clinical information is provided through the image contrast, which is based
on the magnetic properties in biological tissue. By altering the scanner settings,
images with different contrast properties can be obtained. Conventional MRI is a
qualitative imaging technique and no absolute measurements are performed. At
Center for Medical Imaging and Visualization (CMIV) researchers are developing
a new MRI technique named synthetic MRI (SyMRI). SyMRI is based on quantitative measurements of data and absolute values of the magnetic properties of the
biological tissue can be obtained.
The purpose of this master thesis has been to take the development of SyMRI
a step further by developing and implementing a visualization studio for SyMRI
imaging of the human brain. The software, SyMRI Brain Studio, is intended to be
used in clinical routine. Input from radiologists was used to evaluate the imaging
technique and the software. Additionally, the requirements of the radiologists were
converted into technical specifications for the imaging technique and SyMRI Brain
Studio. Additionally, validation of the potential in terms of replacing conventional
MRI with SyMRI Brain Studio was performed.
The work resulted in visualization software that provides a solid formation for
the future development of SyMRI Brain Studio into a clinical tool that can be
used for validation and research purposes. A list of suggestions for the future developments is also presented. Future clinical evaluation, technical improvements
and research are required in order to estimate the potential of SyMRI and to
introduce the technique as a generally used clinical tool.
v
Acknowledgments
I wish to acknowledge and thank all those people who helped and inspired me
throughout the work! A special thanks to:
Marcel Warntjes, my supervisor, for his never-ending optimism, knowledge,
teaching and support.
Janne West, for being an invaluable source of information when it comes to
just about anything concerning computers.
Peter Lundberg, for serving as my examiner and giving me useful tips concerning the written report.
All the people at CMIV, for an encouraging and inspiring research environment with heaps of passion and nice coffee breaks.
The Radiologists who devoted some of their time on giving valuable input to
this master thesis.
Mum, Dad and Simon, for support and encouraging discussions about what
to do with my life. And thanks to you, Mum, for wise suggestions regarding the
scientific work.
Marcus, for not caring too much about what I do, just liking me as I am.
vii
Contents
1 Introduction
1.1 Problem Description . . . . . . . .
1.1.1 Previous Research . . . . .
1.2 Thesis Objectives . . . . . . . . . .
1.2.1 SyMRI Brain Studio . . . .
1.2.2 Radiologist Interaction . . .
1.2.3 Validation of the Technique
1.2.4 Research Questions . . . . .
1.2.5 Scope . . . . . . . . . . . .
1.3 Previous Knowledge . . . . . . . .
1.4 Method . . . . . . . . . . . . . . .
1.5 Target Audience . . . . . . . . . .
1.6 Outline of the Report . . . . . . .
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2 The MRI Scanner
2.1 Magnetic Resonance Imaging . . . . . . . . . . . .
2.1.1 The net magnetisation, M̂0 . . . . . . . . .
2.1.2 The RF-pulse & its B1 -field . . . . . . . . .
2.1.3 Spatial dependence - The Gradient Coils . .
2.1.4 Spin Relaxation . . . . . . . . . . . . . . . .
2.1.5 From Signal Detection to Image Processing
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3 Conventional Contrast-Weighted Imaging
3.1 Contrast Weighted Imaging . . . . . . . .
3.1.1 PD-weight . . . . . . . . . . . . . .
3.1.2 T1 -weight . . . . . . . . . . . . . .
3.1.3 T2 -weight . . . . . . . . . . . . . .
3.1.4 FLAIR . . . . . . . . . . . . . . .
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4 Quantitative MRI
4.1 The Concept of qMRI . . . . .
4.2 MR Parameters to Quantify . .
4.2.1 Tissue Characterisation
4.3 Data Acquisition . . . . . . . .
4.3.1 QRAPMASTER . . . .
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x
Contents
4.4
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6 SyMRI Brain Studio
6.1 Architecture . . . . . . . . . . . . . . . . . . . . . . .
6.2 Main Features . . . . . . . . . . . . . . . . . . . . . .
6.2.1 Quantification Maps . . . . . . . . . . . . . .
6.2.2 Display of SyMRI Contrast-Weighted Images
6.2.3 Graphical User Interface . . . . . . . . . . . .
6.2.4 Autoscale . . . . . . . . . . . . . . . . . . . .
6.2.5 Colormap . . . . . . . . . . . . . . . . . . . .
6.2.6 Colorbar . . . . . . . . . . . . . . . . . . . . .
6.2.7 The Font . . . . . . . . . . . . . . . . . . . .
6.3 SyMRI Brain Studio Releases . . . . . . . . . . . . .
6.3.1 v.1.0.0 . . . . . . . . . . . . . . . . . . . . . .
6.3.2 v.3.1.0 . . . . . . . . . . . . . . . . . . . . . .
6.3.3 v.3.2.0 . . . . . . . . . . . . . . . . . . . . . .
6.3.4 v.4.1.0 . . . . . . . . . . . . . . . . . . . . . .
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Brain.
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4.5
Fitting the Data to the Mathematical Models
4.4.1 Quantification Maps . . . . . . . . . .
4.4.2 SyMRI BrainStudio Fitting Tool . . .
Synthetic MRI . . . . . . . . . . . . . . . . .
4.5.1 Synthetic Contrast Weighted MRI . .
4.5.2 Tissue Segmentation . . . . . . . . . .
4.5.3 Normalization . . . . . . . . . . . . . .
5 Methods
5.1 SyMRI Brain Studio . . . . .
5.1.1 System Environment .
5.2 Radiologist Interaction . . . .
5.2.1 Radiologist Interaction
5.2.2 Radiologist Interaction
5.2.3 Radiologist Interaction
5.2.4 Radiologist Interaction
5.2.5 Radiologist Interaction
5.3 Validation of the Technique .
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III
IV
V
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7 Radiologist
7.1 Radiologist Interaction I . . . . . . . . . . . . . . . . . . .
7.1.1 Drawbacks . . . . . . . . . . . . . . . . . . . . . .
7.1.2 Advantages SyMRI . . . . . . . . . . . . . . . . . .
7.1.3 Future Potential of SyMRI . . . . . . . . . . . . .
7.2 Radiologist Interaction II . . . . . . . . . . . . . . . . . .
7.2.1 The Clinical Routine - an MRI Examination of the
7.2.2 Interaction with SECTRA IDS 5 . . . . . . . . . .
7.2.3 Autoscale . . . . . . . . . . . . . . . . . . . . . . .
7.2.4 The SyMRI Software . . . . . . . . . . . . . . . . .
7.3 Radiologist Interaction III . . . . . . . . . . . . . . . . . .
Contents
xi
7.4
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7.5
Radiologist Interaction IV . . . . . . . . . . . . . . . . . . . . . . .
7.4.1 Follow up - Drawbacks . . . . . . . . . . . . . . . . . . . . .
Radiologist Interaction V . . . . . . . . . . . . . . . . . . . . . . .
8 Validation of the Technique
8.1 Required Characteristics . . . . . .
8.2 Potential of SyMRI Brain Studio .
8.2.1 Scan Time . . . . . . . . .
8.2.2 The All-in-One Approach .
8.2.3 Quantitative Measurements
8.3 SyMRI Today . . . . . . . . . . . .
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9 Discussion
9.1 SyMRI Brain Studio . . . . . . . . . . . .
9.1.1 Design Decisions . . . . . . . . . .
9.2 Radiologist Interaction . . . . . . . . . . .
9.2.1 Selection of Radiologists . . . . . .
9.2.2 Data Sets . . . . . . . . . . . . . .
9.2.3 Lack of Anatomic Detail in SyMRI
9.2.4 MRI Knowledge - MRI Experience
9.3 Validation . . . . . . . . . . . . . . . . . .
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10 Conclusions and Future Research
10.1 Research Questions . . . . . . . . . .
10.2 Future Research . . . . . . . . . . .
10.3 Development Suggestions . . . . . .
10.3.1 SyMRI SECTRA PACS IDS5
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in &
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SyMRI Brain
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Studio
Bibliography
A Magnetic
A.0.2
A.0.3
A.0.4
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Resonance
Nuclear Spin . . . . . . . . . . . . . . . . . . . . . . . . . .
Magnetic Properties & Energy Levels of Nuclear Spin . . .
A Macroscopic Net Magnetization . . . . . . . . . . . . . .
B Abbreviations
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List of Figures
2.1
2.2
2.3
2.4
2.5
2.6
2.7
2.8
2.9
2.10
2.11
2.12
MRI Scanner . . . . . . . . .
Spin-Echo Pulse Sequence . .
The Net Magnetization, M̂0 .
90◦ pulse . . . . . . . . . . .
Slice Selecting Gradient . . .
Phase Encoding Gradient . .
Frequency Encoding Gradient
Spin Relaxation . . . . . . . .
FID . . . . . . . . . . . . . .
T1 -relaxation curves . . . . .
T2 -relaxation curves . . . . .
K-space . . . . . . . . . . . .
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3.1
3.2
3.3
3.4
PDw image .
T1 w image . .
T2 w image . .
FLAIR image
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20
20
21
22
4.1
4.2
4.3
4.4
4.5
qMRI vs MRI . . . . . . . . . . . .
T1 , T2 and PD . . . . . . . . . . .
QRAPMASTER Scanner Sequence
Fit of Data . . . . . . . . . . . . .
T1-map . . . . . . . . . . . . . . .
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24
24
26
26
27
6.1
6.2
6.3
6.4
6.5
6.6
6.7
6.8
6.9
6.10
6.11
The Visualization Pipeline . . . . . . . . . . . . . . .
Quantification Maps: T1 , T2 , PD . . . . . . . . . . .
Quantification Maps: B1 , Mean Erros . . . . . . . .
Region of Interest . . . . . . . . . . . . . . . . . . . .
R1 R2 -plot . . . . . . . . . . . . . . . . . . . . . . . .
SyMRI Brain Studio: Default Four Viewport Display
Navigation Window . . . . . . . . . . . . . . . . . .
Fat Suppression . . . . . . . . . . . . . . . . . . . . .
T1 Enhanced Image . . . . . . . . . . . . . . . . . . .
Popup Menu . . . . . . . . . . . . . . . . . . . . . .
Colorbar . . . . . . . . . . . . . . . . . . . . . . . . .
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34
34
35
35
36
37
37
38
38
39
41
7.1
7.2
Pixel Resolution . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Artifacts SyMRI . . . . . . . . . . . . . . . . . . . . . . . . . . . .
46
47
A.1
A.2
A.3
A.4
Nuclear Spin . . . . . . . . . . . . .
Nuclear Spin Orientations for H + . .
Hydrogen Nuclei in a Magnetic Field
The Net Magnetization, M̂0 . . . . .
72
72
73
74
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2
Contents
List of Tables
6.1
6.2
MR parameter values: Brain Tissue . . . . . . . . . . . . . . . . .
Default Scanner Parameters . . . . . . . . . . . . . . . . . . . . . .
36
37
Chapter 1
Introduction
Magnetic Resonance Imaging (MRI) is an important and widely used medical imaging technique used in the routine clinical workflow worldwide, particularly for soft
tissue visualizations in neurological applications. The technique was first put into
clinical use in the 1980s [1] and it has developed rapidly ever since. In 2007, approximately 40 million MRI examinations were performed [2]. An advantage of
MRI compared to imaging modalities such as x-ray and computed tomography is
the absence of ionizing radiation. Instead, MRI uses magnetic fields and radio
frequency pulses to yield diagnostic images. At Center for Medical Imaging Science and Visualization (CMIV) researchers are developing a new MRI technique
named synthetic MRI (SyMRI). Based on the quantification of four magnetic resonance (MR) parameters SyMRI provides a new approach to MRI, where quantitative rather than qualitative data is measured. The technique is believed to have a
promising future and the long-term goal is to develop and establish SyMRI as a new
MRI technique providing faster examinations with improved clinical information
[3].
1.1
Problem Description
SyMRI is based on quantitative measurements of data opposed to conventional
contrast-weighted MRI where no absolute values are measured. The quantitative approach provides additional information through the absolute values given.
Moreover, in theory a single quantitative measurement makes it possible to postsynthesize an infinite number of contrast-weighted images that with the conventional technique each need a separate scan to be acquired. The approach of quantitative MRI (qMRI) has been discussed since the end of the 1990s [4], but has until
now been constrained from being generally used in clinical applications. The main
reasons for this have been the absence of measurement methods and data processing techniques that provide adequate information within a clinical acceptable time
frame [3].
3
4
Introduction
1.1.1
Previous Research
At CMIV, a scanning technique allowing fast quantification of the four MR parameters longitudinal relaxation (T1 ), transverse relaxation (T2 ), proton density
(PD) and the amplitude of the local B1 -field has been developed. The scanner
sequence, Quantification of Relaxation times And Proton density by Multi-echo
Acquisition of a Saturation recovery using TSE Read-out (QRAPMASTER), allows the volume of a head to be examined in about five minutes [3], which is a
clinically acceptable time. Hence, QRAPMASTER provides the raw data needed
for SyMRI. An additional development in the direction to integrate SyMRI into the
clinical workflow is the development of the SyMRI SECTRA IDS 5 Plugin. The
plug-in provides a framework for the development of fitting tools and visualization
studios for SyMRI as a plug-in to the SECTRA Picture Archiving and Communication System (PACS) workstation IDS 5, used by hospitals worldwide. The
plug-in has an implemented cardiac visualization studio, Cardiac Studio, which is
under clinical evaluation [5].
1.2
Thesis Objectives
In spite of the promising theories there are persisting challenges that need to be
overcome in order to introduce SyMRI as a widespread clinical tool. First of all
radiologists have no experience in interpretation based on quantified data and they
are familiar with and completely rely on the conventional set of contrast-weighted
images. This master thesis aims to take the development of SyMRI further by
implementing a visualization studio for SyMRI of the brain and work on the interaction between the imaging technique and the radiologists. The project is divided
into three somewhat integrated parts, the development and implementation of a
visualization studio for SyMRI of the brain (SyMRI Brain Studio), the analysis
and optimization of the interaction between the radiologists and the technique
(Radiologist Interaction), and a validation on how many of today’s conventional
MRI examinations that can be replaced with the new technique in the future
(Validation of the Technique).
1.2.1
SyMRI Brain Studio
The work with SyMRI Brain Studio includes the continuous development and
implementation of the visualization tool SyMRI Brain Studio in SyMRI SECTRA IDS 5 Plugin (Visual C++ 6, Microsoft 1995). SyMRI Brain Studio should
allow radiologists to compare SyMRI with conventional contrast-weighted MRI
but also have features taking advantage of the extended potential of SyMRI. The
work and the code should be implemented and documented in a way that enables
smooth continuous development of SyMRI Brain Studio into software for clinical
use. Brain Studio should include:
• Post-exam synthesis of conventional contrast-weighted images (T1 w, T2 w,
P Dw and Fluid-Attenuated Inversion Recovery (FLAIR)).
1.2 Thesis Objectives
5
• Display of quantification maps.
• A Graphical User Interface (GUI) allowing the user to experience the enhanced features and possibilities of qMRI.
• Aim to become a visualization studio for routine clinical examinations using
SyMRI.
1.2.2
Radiologist Interaction
By working on the interaction between the radiologist and SyMRI, the aim is to
increase the understanding on how SyMRI visualizations can be developed in order
to optimize their clinical use. This part of the work should:
• Serve as a background and source of information for the continuous development of SyMRI Brain Studio during the time frame of this master thesis.
• Convert demands and requirements from radiologists into technical requirements on SyMRI Brain Studio.
• Present suggestions on further developments of SyMRI SECTRA IDS 5 Plugin and SyMRI Brain Studio.
1.2.3
Validation of the Technique
The validation phase should result in an estimate on how many of today’s conventional MRI examinations that can be replaced by the new technique in the
future.
1.2.4
Research Questions
• How can the quantitative data set be introduced and presented in a visualization tool in an efficient way?
• What technical improvements are required to satisfy the demands of the
radiologist?
• How should the GUI of SyMRI Brain Studio be developed in order to optimize the interaction between SyMRI and the radiologist?
• How many of today’s conventional MRI examinations can be replaced with
the new technique in the future?
1.2.5
Scope
Factors such as the time frame (30 ECTS credits, 20 full-time weeks) and previous
knowledge within the area of research set the limitations of this master thesis.
The project does not aim to present a fully developed clinical visualization tool
for SyMRI of the brain, but to provide a basis for such a future development.
6
Introduction
1.3
Previous Knowledge
The author possesses four and a half year of undergraduate studies within the area
of engineering biology, including basic knowledge in image processing, computer
programming, scientific visualizations and medical imaging. The author has no
previous knowledge in the clinical use of MRI, the quantification of MR data or
GUI development.
1.4
Method
The thesis work has been performed in an iterative manner by combining literature
studies, software development and input from radiologists and researchers. A
weekly MRI course as well as a practical introduction to the MRI scanner was
followed in order to get an enhanced understanding within the area of MRI. A
more detailed method specification can be found in chapter 5.
1.5
Target Audience
The report is written in an attempt to reach an as wide audience as possible
although the focus is individuals with technical background and an interest in
MRI. No previous knowledge in MRI is required but basic knowledge in imaging, anatomy and physics will help the understanding. The abbreviation list in
Appendix B of the report is present in order to straighten out possible question
marks.
1.6
Outline of the Report
• Introduction
Chapter 1 provides the reader with an introduction to this master thesis. The
chapter is divided into a number of sections including problem description,
thesis objectives, previous knowledge of the author, method used, target
audience and outline of the report.
• Background
Chapters 2, 3 and 4 will together accommodate the reader with the technical
background needed to understand the work of this master thesis. Chapter 2
describes how the properties of the phenomenon forming the basis of MRI,
the magnetic resonance, is used to create medical images using an MRI
scanner. Chapter 3 explains how MRI is used to yield conventional contrastweighted MRI images with today’s conventional MRI techniques. Chapter
4 explains the concept of qMRI, which forms the basis of SyMRI through
the quantitative data acquisition and the fitting of the data to mathematical models. Furthermore, the chapter describes the approach of SyMRI
visualizations.
1.6 Outline of the Report
7
• Methods
Chapter 1 gives a short overview of the general method used, while chapter
4 provides a more detailed description of the methods used in the different
parts of the work.
• Result
Chapter 6, 7 and 8 explain the different steps and outcomes of the work.
Chapter 6 describes the features and development of SyMRI Brain Studio.
Chapter 7 give details about the radiologist interactions and their outcome,
while chapter 8 contains the validation of the technique and its potential to
replace conventional contrast-weighted MRI in the clinical routine.
• Discussion
Chapter 9 contains a discussion regarding the work and outcome of the
different parts of this master thesis.
• Conclusions and Future Development
In chapter 10 the research questions are answered and future work within
the area is proposed together with future development suggestions for the
SyMRI Sectra IDS 5 plugin and SyMRI Brain Studio.
Chapter 2
The MRI Scanner
The chapter introduces magnetic resonance imaging (MRI). In the end of the chapter, the reader should have a basic understanding on how MR enables the generation of medical contrast weighted images through the application of magnetic fields
and radio frequency pulses (RF-pulses) to biological tissue.
2.1
Magnetic Resonance Imaging
Figure 2.1. MRI scanner.
A schematic picture of a MRI scanner is shown in Fig 2.1. During the clinical
examination, the patient is lying on the patient table inside the bore of the magnet. The magnet supplies a large homogeneous and static magnetic B0 -field, which
causes a magnetization M̂0 of the patient volume. Through a scanner pulse sequence MRI images are given. The pulse sequence contains hardware instructions
causing the components of the MRI scanner to stimulate magnetic interaction in
a pre-defined manner in the patient volume (Fig 2.2). The first line in the pulse
sequence displayed in Fig 2.2 describes the RF-pulse (Section 2.1.2). The RFpulse tips M̂0 into a plane where it can be processed and measured. The three
following rows describe the behaviour of the three magnetic field gradients used to
9
10
The MRI Scanner
distinguish different spatial locations within the patient volume (Section 2.1.3).
The last section of the pulse sequence contains the data acquisition, where the
analogue digital converter (ADC) converts the continuous analogue signal to digital sample points. The pulse sequence is then repeated for each required data line
by altering the phase encoding gradient at each repetition. The period between
two repetitions is called repetition time (TR). The design of pulse sequences is an
entire research field alone aiming to get the optimal image coverage in shortest
time possible.
Figure 2.2. Spin-echo pulse sequence illustrating the hardware instructions of the MRI
scanner.
2.1.1
The net magnetisation, M̂0
The net magnetization of the patient volume, M̂0 (Fig 2.3), is predominantly
formed through the magnetic properties of hydrogen nuclei in biological tissue.
In presence of the external magnetic field B̂0 , the hydrogen nuclei, which consist
of a single proton, will precess around B̂0 with a certain precessional frequency,
the Larmor frequency (fL ). Nuclei precessing with the same fL are said to be in
magnetic resonance and are referred to as an isochromat. Inside B̂0 , a thermal
equilibrium of the isochromat is reached, giving an excess number of nuclei that
precess in the positive direction of B̂0 . The excess of spins cause the net magnetisation M̂0 to appear. M̂0 precesses around B̂0 , but is often illustrated as a
net vector in a rotating frame (Fig 2.3). A deeper introduction to the quantum
physics underlying MRI is available in Appendix A.
2.1 Magnetic Resonance Imaging
11
Figure 2.3. In presence of a magnetic field B0 a resulting net magnetization will appear
due to an excess number of spins in the direction of B̂0 .
2.1.2
The RF-pulse & its B1 -field
The RF-pulse induced by the RF-coil will apply an oscillating magnetic field, B̂1 ,
in the xy-plane orthogonal to B̂0 . Net magnetization caused by isochromats in resonance with the rotational frequency of B̂1 will then experience a static magnetic
field causing the magnetization to additionally precess around B̂1 . In the rotating
frame a tipping of M̂0 can be seen proceeding between two states, M̂0 and −M̂0 .
By choosing the bandwidth of the RF-pulse, it can be determined which isochromats in an inhomogeneous magnetic field that will experience a static B1 -field.
Figure 2.4. 90◦ pulse in the rotating frame of reference.
1t
The duration of the RF-pulse determines the tip-angle α according to α = γB
2π .
An RF-pulse that will tip the net magnetization into the xy-plane is referred to as
a 90◦ pulse (Fig 2.4). The RF-pulse will cause the spins to be in phase coherence
pointing in the same direction in the xy-plane [1]. However, immediately after
the RF-pulse different relaxation mechanisms will cause the magnetization to relax
back to its thermal equilibrium M0 . The relaxation mechanisms are crucial for
the image contrast achieved in MRI and are explained in section 2.1.4.
12
2.1.3
The MRI Scanner
Spatial dependence - The Gradient Coils
The three orthogonal gradient coils inside the MRI scanner are applying magnetic
field gradients across the patient volume in order to make the magnetization spatial
dependent according to:
B̂i = B̂0 + GˆT × rˆi
(2.1)
ˆ
GT is the summation of gradients at a location rˆi [6]. The application of
gradients will create isochromats throughout the patient volume with distinguished
resonance frequencies:
fi = γ(B0 + GˆT × rˆi )
(2.2)
Slice Selecting Gradient
Figure 2.5. Slice Selecting Gradient.
The slice selecting gradient (Gss ) is introduced at the time of the RF-pulse in
order to make the RF-pulse slice selective (Fig 2.5). The thickness of the slice is
proportional to the RF-pulse bandwidth and inversely related Gss , SLICEwidth =
RFbandwidth
[1]. The direction of the slice is determined by the direction of the
γGss
gradient. After Gss a rephasing gradient is needed in order to realign the spins due
to the dephasing caused by the excitation. In multi-slice imaging where a number
of slices are used to visualize the patient volume Gss is normally kept constant
while alternating the frequency of the RF-pulse.
Phase Encoding Gradient
Figure 2.6. Phase Encoding Gradient.
The phase encoding gradient (Gpe ) gives spatial phase variation and is applied
after the RF-pulse but before the data acquisition (Fig 2.6)[7]. The spins in the
2.1 Magnetic Resonance Imaging
13
sample dephase until Gpe is turned off after which they return to their original
frequency keeping their phase angle. The phase differences cause phase encoding in one of the in-plane directions of the slice. The phase differences remain
until another gradient is applied or the MR-signal decays due to T2 -relaxation
(Section 2.1.4)[1].
Frequency Encoding Gradient
Figure 2.7. Frequency Encoding Gradient.
The frequency encoding gradient or read out gradient, Gro , will add or subtract from the magnetization along the second dimension within the image slice
(Fig 2.7). The gradient is applied during the data acquisition making the signal
consisting of a number of different frequencies corresponding to different locations
within the second in-plane axis of the slice.
2.1.4
Spin Relaxation
Figure 2.8. Spin relaxation back to thermal equilibrium.
Spin relaxation is the process following an RF-pulse when the isochromats release and redistribute absorbed energy as they go back to their thermal equilibrium
state M̂0 (Fig. 2.8). Two different relaxations can be measured, the longitudinal
relaxation (T1 -relaxation) and the transverse relaxation (T2 -relaxation). The relaxations are dependent on two distinguished relaxation mechanisms, those who
transfer energy away from the spins to the lattice and those who redistribute energy within the spin system itself [4]. The relaxation is dependent on a number of
14
The MRI Scanner
tissue specific properties such as intra- and intermolecular interactions. Together
with the proton density, the spin relaxation will form the basis of image contrast
in MRI.
Bloch Equations
The behaviour of the magnetization during the excitation through RF-pulses and
the following relaxation has been modelled in a set of differential equations by
Bloch [6]. Bloch’s equations are solely based on classical mechanics and are considering the net magnetization. The Bloch equations and their solutions are shown
in the equations below.


(My Bz − Mz By )i
dM̄
= γ M̄ × B̄ = γ  (Mz Bx − Mx Bz )j 
dt
(Mx By − My Bx )k
(2.3)
Mz (t) = [Mz (o) − Mo ]et/T1 + M0
Mx (t) = [Mx (0)cos(ωo t) + My (0)sin(ωo t)]et/T2
My (t) = [Mx (0)sin(ωo t) − My (0)cos(ωo t)]et/T2
Mxy =
q
Mx2 + My2
After a 90◦ RF-pulse, the solutions to the Bloch equations models Mxy as
a decaying signal oscillating with the Larmor frequency, while Mz exponentially
grows back to M0 . The precessing magnetic field Mxy will induce a voltage in the
RF-coil and the signal, a free induction decay (FID) can be modelled according to
S(t) = S0 e−t/T2 eiωL t (Fig. 2.9). In MRI, either the FID or one or several echoes
created from the FID are measured.
Figure 2.9. Free induction decay.
2.1 Magnetic Resonance Imaging
15
Figure 2.10. The T1 -relaxation curve of two tissues with different T1 .
T1 -relaxation
The exponential recovery of Mz back to its thermal equilibrium state M0 after a
RF-pulse is called longitudinal relaxation, spin-lattice relaxation or T1 -relaxation.
The T1 -value (T1 ) serves as an absolute measurement of the T1 -relaxation and
is the time when Mz has recovered to 63% of |M0 − Mz0 | (Fig 2.10). Apart
from molecular dependencies, T1 is dependent on the scanner field strength and
temperature [1]. The inverted T1 is often referred to as T1 -relaxation rate (R1 ).
T1 -relaxation is induced as the isochromats release their energy to the surrounding lattice and is strongly correlated with molecular motion. Molecular motion
in surrounding molecules will cause local magnetic fields tumbling with different
frequencies. Tumbling with fL perpendicular to B0 will due to the resonance condition induce energy transfer from the spin system to its surroundings.
T2 -relaxation
Figure 2.11. The T2 -relaxation curve of two tissues with different T2 .
The transverse relaxation, spin-spin relaxation or T2 -relaxation is present in the
xy-plane after the RF-pulse. The T2 -value (T2 ) serves as an absolute measurement
of the T2 -relaxation and is the time when Mxy has decreased to 37% of the value
immediately after a RF-pulse (Fig 2.11). T2 is dependent on the scanner field
strength as well as temperature. The inverted T2 is referred to as the T2 -relaxation
rate (R2 ) [1]. T2 -relaxation is affected by relaxation mechanisms redistributing
energy within the spin system as well as the energy transfer from the spins to the
lattice. Hence, T2 is always shorter than or equal to T1 . The T2 -relaxation caused
by redistribution of energy within the spin system is caused when the isochromats
16
The MRI Scanner
lose the phase coherence gained through the RF-pulse. The relaxation is induced
by fluctations in the magnetic field experienced by the isochromats, making the
precess with slightly different frequencies.
2.1.5
From Signal Detection to Image Processing
The pulse sequence makes it possible to distinguish the signal from different spatial
locations within the patient volume. The signal measured and sampled are often
one or several echoes from the appearing FID. The time between the exciting
RF-pulse and the created echo are called echo time (TE). Echoes are created
in two major ways using spin echo (SE) or gradient echo (GE) techniques. Both
techniques create an echo of the signal in the transverse xy-plane that the receiving
coil detects by measuring the induced voltage (Eq. 2.4).
I
d
Mtot Brec ]
(2.4)
emf = − [
dt
Sample
emf = electro motive force, Brec = receiving coil sensitivity
A schematic image of a SE sequence is shown in Fig. 2.2. The SE is formed
using a refocusing 180◦ pulse that flips the magnetization around the y-axis at
time T2E after the initial RF-pulse. The pulse will refocus the transverse spins
that have dephased due to T2 -relaxation. The spins will now come back into
phase coherence creating an echo at time T E according to SSE = S0 e−T E/T2 .
In GE sequences, a negative gradient lobe is used to form the echo. Turbo spin
echo (TSE) is an approach where several refocusing pulses are applied during each
repetition in order to form several echoes from a single excitation pulse.
Analog to Digital Converter
The analogue-to-digital converter (ADC) digitalizes the emf and stores it in numeric form in a computer. The raw data space where the data storage is done is
called k-space.
K-space
K-space is a two or three dimensional data space used in MRI, with one frequency
encoding and one phase encoding direction. K-space is often looked upon as a
trajectory path for the phase encoding and frequency encoding gradients. The rows
in k-space are collected throughout the repetitions of the pulse sequence as the
gradients are changed. The middle of k-space collects low frequencies containing
SNR and contrast and the outer rows will collect high frequencies containing edges,
boundaries and image resolution [1]. The number of sample points in the frequency
encoding direction of k-space will determine the number of sample points collected
during each echo. The number of sample points in the phase encoding direction
will determine how many times the sequence has to be repeated to fill all the
lines in k-space. The number of data points sampled and the image resolution
2.1 Magnetic Resonance Imaging
17
determines the field of view (FoV). The reconstruction from k-space to a spatial
image is made through a 2D Fourier transform (Fig 2.12).
Figure 2.12. An MRI image and corresponding k-space.
Sensitivity encoding (SENSE) is a technique giving shorter acquisition times
by not acquiring data to all lines in k-space, instead several receiving coils are
used. This will cause aliasing that appears when signals are superimposed on each
other due to a too large FoV. Through knowledge of the sensitivity of the receiving
coil elements and a coil sensitivity that varies in space, a defined equation system
can be generated (Eq. 2.5). The system can be used to unwrap the pixels and a
complete image can be restored.
mi = s1i p1 + s2i p2
(2.5)
mi is the measured signal of a coil, s is the sensitivity of the receiving coil and
p is the signal at each pixel.Another technique to achieve faster image acquisition
is echo planar imaging (EPI). With EPI a number of lines are collected in k-space
during each repetition using gradients.
Chapter 3
Conventional
Contrast-Weighted Imaging
The chapter will give the reader an insight on how the conventional set of contrastweighted MRI images is achieved and used is in today’s clinic.
3.1
Contrast Weighted Imaging
In conventional contrast-weighted MRI, tissue can be distinguished through differences in image pixel intensity. The image contrast is caused by differences in
signal amplitude at different locations of the patient volume. The signal amplitude is dependent on proton density (PD), T1 -relaxation and T2 -relaxation and a
number of scanner parameters. The scanner parameters TE and TR are used to
create images with fixed contrast behaviour. TE and TR can be varied to produce
images whose contrast is mainly dependent on T1 -relaxation, T2 -relaxation, PD or
a combination of these. The images are said to have a certain T1 -weight (T1 w),
T2 -weight (T2 w) and PD-weight (PDw). TE determines the amount of T2 w. With
a relatively long TE the signal amplitude will be dependent on the T2 -relaxation.
Tissue compartments with short T2 will dephase faster than tissue compartments
with long T2 and hence have a more attenuated signal at the formed echo. With
short TE, very limited T2 w is present. TR is the time between the applications of
the excitation RF-pulses and determines the amount of T1 w in the image. With
a long TR, all tissue compartments will have time to relax back to their thermal
equilibrium M0 before the application of an additional RF-pulse. Contrarily, with
a short TR only tissue compartments with short T1 will have time to recover before a new RF-pulse is applied. Hence, the signal from tissue compartments with
a long T1 will be attenuated.
An additional not yet mentioned scanner parameter is the inversion time (TI). TI
is present in the case of an inversion recovery sequence, with an inversion prepulse
at time TI before the exciting RF-pulse. The inversion pre-pulse can be used to
cancel out signals from a certain tissue. The inversion pre-pulse is an 180◦ -pulse
19
20
Conventional Contrast-Weighted Imaging
that initially inverts the magnetization M0 . The application of the RF-pulse at
time TI will cancel out signals from tissue passing the zero-signal line at that time.
3.1.1
PD-weight
(a)
(b)
Figure 3.1. A PDw image is given using long TR and short TE.
P Dw is achieved using long TR and short TE, which keep the T1 w and T2 w
to a minimum (Fig 3.1.1). P Dw-images are not normally a part of general MR
protocols of the brain. PD is strongly correlated with water content, which is
rather similar in brain tissue, therefore P Dw-images do not yield very good image
contrast for brain applications.
3.1.2
T1 -weight
(a) T1w Image
(b) NavigationT1w
Figure 3.2. A T1 w image is given using short TR and short TE.
3.1 Contrast Weighted Imaging
21
T1 w-images are often referred to as anatomical scans since the T1 -relaxation in
different brain tissues are varying yielding good contrast between different tissues
in the brain (Fig 3.1.2). In T1 w-images the boundaries between tissues can be
seen clearly. Fluids have almost no signal intensity due to the long T1 -values
while water based tissues appear mid-grey and fat based tissue very bright due
to the short T1 . The signal from PD and T1 -relaxation counteracts each other in
T1 w-images, since grey matter has higher PD but longer T1 than white matter.
3.1.3
T2 -weight
(a) T2 w Image
(b) Navigation T2
Figure 3.3. A T2 -weighted image is given using long TR and long TE.
Fluids get the highest pixel intensity in T2 w-images due to long T2 -relaxation
while water- and fat-based tissues appear mid-grey. In brain imaging T2 w images
are often referred to as ’pathology scans’ since many pathological processes in
the brain result in an increased water content, making them easy to spot in T2 w
images as the image intensity is increased.
3.1.4
FLAIR
FLAIR images (Fig 3.4) are achieved by applying an inversion pre-pulse to a T2 wimage in order to cancel out the signal from cerebrospinal fluid (CSF). FLAIR
images show brain interfaces very good and make it possible to distinguish cerebrospinal fluid (CSF) from other tissues or diseases that appear bright in T2 wimages [8].
The Image - Pixel by Pixel
An image stack used in MRI consists of a number of images representing the slices
collected throughout the patient volume. The FoV and the number of sample
points measured in the frequency encoding direction will together with the number
of repetitions determine the image resolution. Each pixel in the image represents
the signal from a voxel of the patient volume. Partial volume is a phenomenon
22
Conventional Contrast-Weighted Imaging
Figure 3.4. In the FLAIR image the signal from CSF is cancelled out.
that arises when a voxel contains a number of tissue compartments with different
relaxation rates.
Chapter 4
Quantitative MRI
The chapter explains the concept of qMRI throughout the process of data acquisition, fitting of the data and post processing through the rendering of SyMRI images
and the display of quantification maps.
4.1
The Concept of qMRI
While conventional contrast-weighted MRI is a qualitative technique where the
intensity of a pixel in the final image have no absolute value, qMRI is a quantitative
approach taking MRI into the area of measurement science [4]. In qMRI the
quantitative and absolute values of the different MR parameters are measured for
each voxel within the slices in the patient volume. The measured values can later
be used for different kind of data analyses and image rendering. To illustrate
the difference between the two techniques, conventional MRI can be described as
a snap-shot imaging technique where a scanner sequence with predefined settings
sample signals at time-points were good contrast between clinical important tissues
are given. In the quantitative approach, the scanner sequence is used to collect
data points in order to estimate the behaviour of the complete relaxation within
the tissue and measure T1 , T2 and PD (Fig 4.1). QMRI opens the possibility for
reproducible and comparable measurements allowing reliable multi-centre studies
and studies of disease progress and response to treatment in patients. There are
researchers claiming that qMRI opens the possibilities for a paradigm shift in the
medical MR science. Until now clinical qMRI has been constrained from being
generally used, due to excessive scan times and extensive post-data processing [3].
4.2
MR Parameters to Quantify
In qMRI the three MR parameters of clinical importance are T1 , T2 and PD
(Fig. 4.2). T1 and T2 provide information about the spin relaxation of the biological
tissue while PD corresponds to proton density of the tissue. From a technical
point of view, other MR parameters might be necessary to measure in order to
23
24
Quantitative MRI
Figure 4.1. QMRI enables tissue to be
accurately characterized through the absolute values of the MR parameters. In
the figure the quantitative values of the
four pixels indicates white matter or white
matter looking tissue. The information is
given regardless of the greyscale mapping
of the image and neighbouring pixel intensities. Using conventional contrast MRI,
the intensities of the pixels will not supply
any quantitative information on the characteristics of the tissue. The clinical interpretation needs to be based on the image
contrast and given knowledge about the
specific scanner sequence used.
get accurate and reproducible measurements. One such parameter is the B1 -field
strength to correct for B1 -field inhomogeneity resulting in inaccurate flip-angles.
Figure 4.2. The graph shows T1 , T2 and PD and how they are related to the relaxation
behaviour of tissue.
4.2.1
Tissue Characterisation
By creating a 3D Cartesian grid with PD, R1 and R2 on the axes, tissue specific
clusters can be identified in order to characterize tissue. At the moment, several
research projects are aiming to investigate and map the MR parameter values in
healthy and diseased tissues in order to use the absolute values as diagnostic tools,
both for characterisation of disease and normal tissue. For example, T1 has been
shown to be affected in a number of neurological diseases such as multiple sclerosis
(MS), intracranial tumours, stroke and dementia [4].
4.3 Data Acquisition
4.3
25
Data Acquisition
In qMRI, the scanner sequence performs the signal acquisition at a number of timepoints during the magnetic relaxation following the RF-pulses. The collected data
points are used to fit the data to the relaxation behaviour predicted by the Bloch
equations. The scanner sequence has to provide enough data to achieve acquired
dynamic range of the parameters to be measured as well as sufficient SNR and
resolution of the image. Due to the long scan times needed to achieve good SNR
and reliable measurements, many scanners sequences will quantify only one of the
MR-parameters. As an example, the present gold standard for T1 quantification
is the inversion recovery sequence. By repeating the scan and measure the signal
with a number of different TIs, the complete T1 -relaxation can be estimated. Multi
echo acquisition methods are needed in order to measure T2 and PD [4]. The
sequence used for data acquisition within the synthetic imaging project at CMIV
is QRAPMASTER [3].
4.3.1
QRAPMASTER
QRAPMASTER performs simultaneous quantification of T1 , T2 , PD and B1 -field
strength throughout the patient volume. The sequence was developed in order to
scan a head within a clinical acceptable period of five minutes. The T1 measurements are given through a spoiled saturation pulse, which also allows measurements of the B1 -field strength. By dividing the scanner sequence into a saturation
block and an acquisition block performing saturation and acquisition on different
slices QRAPMASTER provides fast enough measurements. The number of scans
and the delay times (TD) in between them determine the dynamic range of T1 . T2
is measured using a fast multi echo gradient spin echo sequence (GRaSE) which
uses EPI. The number of echoes and the spacing in between them determine the
dynamic range of T2 . Additionally, the sequence includes a REST slab that is
placed a distance away from the image volume. The REST slab saturates the
signal from blood to prevent motion artefacts. This will cause all flowing blood
to appear black in the images. A schematic picture of the sequence can be seen
in Fig 4.3. PD is given in relation to M0 , which is calculated from T1 , T2 and
B1 -field strength.
4.4
Fitting the Data to the Mathematical Models
After the data acquisition, fitting of the data to the relaxation models are needed
to calculate T1 , T2 and PD. The most basic way to fit T1 and T2 is to assume
a monoexponentional relaxation curve in each measured voxel. By doing so the
relaxation within each voxel can be fitted by a least square fit to a monoexponential
curve (Fig. 4.4), minimum two data points are needed. When using the golden
standard for T1 measurement as described in Section 4.3 the data can be fitted to
the following equation S(T I) = S0 (1 − 2e−T I/T 1 ) where S0 is the signal achieved
from M0 [4].
26
Quantitative MRI
Figure 4.3. Schematic schedule of the QRAPMASTER scanner sequence (Ref [3], Page
321)
Figure 4.4. The data points are fitted to the mathematical models describing the
relaxation.
In reality multiexponentional relaxation is common due to partial volume effects within the voxels. Simplification to a monoexponential fit is reasonable when
the relaxation exchange between the compartments within the voxel is larger than
the relaxation rate within each compartment [4]. In brain tissue, T1 is often monoexponential while T2 is bi- or multiexponential. If multiexponential relaxations are
fitted to monoexponential curves the data will be scanner parameter dependent.
4.4.1
Quantification Maps
Quantification maps are used to visualize the measured MR parameter values
in each voxel. In Fig 4.4.1, a T1 -map is displayed were the color of the pixels
correspond to T1 in milliseconds. The image analysis of the quantified values can
be made in a number of ways including for example a region of interest (ROI),
histogram analysis or voxel based group mapping [3].
4.5 Synthetic MRI
27
Figure 4.5. T1-map (Image retrieved from Contrast Predictor)
4.4.2
SyMRI BrainStudio Fitting Tool
The SyMRI BrainStudio Fitting Tool is used to create T1 , T2 and PD maps from
the data acquired with QRAPMASTER. The SyMRI fitting tool uses a least square
fit to a monoexponential curve for T1 and T2 . B1 -field strength is given from the
saturation pulse and is together with T1 and T2 used to calculate an appropriate
M0 . PD is then given from T1 , T2 , M0 and a number of scaling factors in order to
correct for a number of scanner parameters.
4.5
Synthetic MRI
SyMRI uses T1 , T2 and PD maps to post-synthesize contrast-weighted MRI images.
4.5.1
Synthetic Contrast Weighted MRI
The image contrast that would have been given through a conventional scanner
sequence can be post-synthetisized using Eq. 4.1 [3]. The equation predicts the
signal intensity from a voxel with a certain T1 , T2 and PD given the scanner
settings TE and TR. This can be done since the quantified parameters give enough
information to predict the complete relaxational behaviour of the tissue. To postsynthesize a contrast-weighted image that would have been given from an inversion
recovery sequence, Eq. 4.2 is used in order to take account for the influence of the
inversion prepulse [3].
1 − e−TR /T1
e−TE /T2
1 − e−TR /T1 cosα
(4.1)
1 − 2e−TI /T1 + e−TR /T1 −TE /T2
e
1 − e−TR /T1 cosα
(4.2)
S ∝ PD
S ∝ PD
28
4.5.2
Quantitative MRI
Tissue Segmentation
Synthetic images can also be calculated on a purely quantitative basis using tissue
characterisation. In this way images can be displayed in a way that is not possible
in conventional contrast-weighted MRI. The 3D Cartesian grid with PD, R1 and
R2 on the axis will provide a foundation for tissue segmentation and the creation
of contrast-weighted images with certain tissues suppressed.
4.5.3
Normalization
In all conventional contrast-weighted images there is a certain amount of PDw since
the proton density supply the origin of the signal detected by the MRI scanner.
Since the PD contribution from each voxel is known using qMRI the images can
be normalized excluding the contrast dependence on PD giving images with pure
T1 w or T2 w.
Chapter 5
Methods
The chapter describes the methods used in this master thesis throughout the implementation and development of SyMRI Brain Studio, the interaction with radiologists and the validation of the technique.
5.1
SyMRI Brain Studio
SyMRI Brain Studio was developed and implemented in an iterative manner in
parallel with the continuous development of the SyMRI Plugin framework (Synthetic MR Technologies AB, 2007) and the improvement of the SyMRI Brain
fitting tool and the scanner sequence settings. A number of versions of SyMRI
Brain Studio were developed throughout the work. SyMRI Brain Studio v.1.0.0
was the first version developed, which was used for a first validation of an onsite radiologist (Sec 5.2.1). Together with user input from other radiologists and
researchers SyMRI Brain Studio v.3.1.0 was developed and sent to a number of
off-site hospitals for validation. SyMRI Brain Studio v.3.1.0 was additionally installed at CMIV for research and validation purposes and later upgraded with the
successive versions v.3.2.0., v.3.3.0 and v.4.1.0.
5.1.1
System Environment
SyMRI Brain Studio is developed as a visualization studio for SyMRI SECTRA
IDS 5 Plugin in Microsoft Visual C++ 6.0. The SyMRI SECTRA Plugin provides
a framework for SyMRI fitting tools and visualization modes using raw data stored
as DICOM [9] files in SECTRA IDS 5.
5.2
Radiologist Interaction
Radiologists with an interest in SyMRI were asked to participate in the work.
Since the technique introduces a new concept of MRI, the most important issue
was to find radiologists prepared to put their time on evaluating a not yet clinical
29
30
Methods
introduced imaging technique. The meetings with the radiologists were arranged
for two reasons. First, there was an interest in evaluating the technique from a
radiologist’s point of view, and to convert the demands from the radiologist into
technical demands on SyMRI. Secondly, there was an interest in getting familiar
with and understand the radiologist’s working environment. The interaction with
the radiologists was done under the principle that it is easier to learn about the
users’ need and problems by learning the way they are working, rather than to ask
questions about what they would expect from a new quantitative MRI technique.
5.2.1
Radiologist Interaction I
Title: Comparison: Conventional T1w, T2w and FLAIR vs SyMRI
Software: SyMRI Brain Studio v.3.0.0, Contrast Predictor v.1.1 beta, SECTRA
IDS 5
Resolution: Conventional MRI 0.8mm, SyMRI: 1 mm
Slice thickness: Conventional MRI 3mm, SyMRI: 5mm
The aim with the meeting was to get an idea on how an experienced radiologist
would sense the new technique and find it in comparison to conventional contrastweighted MRI. A week prior to the meeting, the radiologist had been given a short
introduction to SyMRI Brain Studio and Contrast Predictor in order to be able
to use and interact with the software independently. During the meeting the radiologist looked at SyMRI images alone as well as compared SyMRI to conventional
contrast-weighted MRI. Information was also gathered regarding preferences on
the user interface as well as windowing options and the possibilities of auto contrast. Additionally, an observation was made on how the radiologist interacts
with IDS 5. During the day, a number of the SyMRI unique concepts were introduced in order to observe the radiologist’s reaction on features such as contrast
optimization, post-examination tissue nulling and PD normalisation that are only
possible using SyMRI. The observer (i.e. the author) was taking basic notes in
a continuous manner in order to collect as many thoughts and observations as
possible without interfering with the workflow. The notes were put together into a
document [10] which were read through and commented by the radiologist before
finished. The document was written in Swedish to prevent language difficulties to
interfere with the findings. The documentation was written in such a way that it
could be used to evaluate future versions of SyMRI Brain Studio. Problem with
the data transfer resulted in only one subject with available data for conventional
contrast weighted MRI and SyMRI through SyMRI Brain Studio. Additionally
six data set for SyMRI visualizations in Contrast Predictor were used from which
four also were available in PACS. In total seven subjects were investigated, out
of them three were diagnosed with multiple sclerosis (MS) and three with brain
tumours.
5.2.2
Radiologist Interaction II
Title: How are IDS 5 used by the radiologist today?
Software: SECTRA IDS 5
5.3 Validation of the Technique
31
The meeting was made as an observation and discussion in order to observe how
the radiologist uses conventional contrast-weighted MRI in the clinical routine.
The radiologist was asked to explain the routine clinical work using a standard
protocol for a brain examination. Additionally an observation was made on how
the radiologist interacted with the SECTRA IDS 5. Notes were taken during the
session and the findings where put together into a document [11].
5.2.3
Radiologist Interaction III
Title: Introduction to SyMRI
Software: SyMRI Brain Studio v.4.1.0, SECTRA IDS 5
The radiologist was briefly introduced to the concept of SyMRI and a discussion
about the SyMRI images and features was hold. Three different SyMRI data sets
were looked at.
5.2.4
Radiologist Interaction IV
Title: Comparison: Conventional T1w, T2w and FLAIR vs SyMRI - follow up
Software: SyMRI Brain Studio v.3.1.0, Contrast Predictor v.1.1 beta, SECTRA
IDS 5
Resolution: Conventional MRI 0.8mm, SyMRI: 1 mm
Slice thickness: Conventional MRI 3mm, SyMRI: 5mm
A follow up was made on Radiologist Interaction I in order to see what progress
that had been achieved concerning the drawbacks found during the first meeting (Section 7.1). The data set that were used in Radiologist Interaction I was
re-looked upon and additionally two data sets available for comparison between
conventional contrast-weighted MRI and SyMRI Brain Studio.
5.2.5
Radiologist Interaction V
Title: Response Leiden University Medical Centre (LUMC)
Resolution: Conventional MRI 0.8mm, SyMRI: 1 mm
Slice thickness: Conventional MRI 3mm, SyMRI: 5mm
Software: SyMRI Brain Studio v.3.1.0
SyMRI Brain Studio was sent to LUMC in Leiden, Holland for validation on a 3T
MRI scanner and to analyse the potential for SyMRI imaging of infants and small
children. Their response was used as an additional input for this master thesis.
5.3
Validation of the Technique
The validation was made as a discussion based on the information and knowledge
gained from the work with the master thesis.
Chapter 6
SyMRI Brain Studio
SyMRI Brain Studio is a visualization studio developed to visualize quantitative
MR data of the brain using quantification maps and SyMRI. This chapter explains
the features of Brain Studio, its design and the successive development of the different versions of the software.
6.1
Architecture
Brain Studio is implemented in C++ as a class inheriting the SyMRI Plugin’s
virtual CSyMRIImage class. Necessary modifications in the source code of the
SyMRI Plugin framework were made as described in the extensibility chapter in the
SyMRI SECTRA IDS 5 Plugin Design document [5]. The architecture of SyMRI
Brain Studio is divided into three sections, each with local functions implemented
to customize the visualization mode and create the final user interface.
• Rendering
Overridden functions: DrawImage()
The rendering section calculates and visualizes the SyMRI images and quantification maps based on the user defined settings. A synthetic T2 w image is
displayed as default.
• Heads Up Display (HUD)
Overridden functions: DrawHUD(), SetUpHudData()
The HUD gives the end-user information about patient data, the quantitative
data inside the region of interest (ROI) as well as the SyMRI settings of
displayed contrast images.
• User Event Handler
Overridden functions: HandleMenuSelection(), ModifyMenu(), OnKeyDown(),
OnLMouseDown(), OnLMouseUp(), OnMouseMove().
User events are handled through menu selections, short commands and
mouse bottom clicks.
33
34
SyMRI Brain Studio
Figure 6.1. The visualization pipeline contains several steps ranging from the initial
data acquisition to the rendering of images. SyMRI Brain Studio renders and visualizes
the data through the quantification maps provided by the SyMRI fitting tool.
An overview of the SyMRI visualization pipeline can be seen in Fig 6.1. The raw
data is retrieved and handled as DICOM images by the SyMRI plugin framework.
The quantified data is retrieved by the fitting tool and used by the visualization
studio were the rendering of quantification maps and post-synthesized images are
made. The SyMRI framework enables a debug mode that has been used for error
search.
6.2
6.2.1
Main Features
Quantification Maps
The quantification maps display the quantified MR data pixel by pixel throughout
each slice of the brain. In the four viewport default mode a T1 -map, a T2 -map
and a PD-map is rendered and displayed together with the latest active contrast
weighted SyMRI image (Fig 6.2). The quantification maps are visualized using
a rainbow colormap and are autoscaled based on the absolute T1 , T2 and PD
values present in human brain (Table 6.1). Two additional quantification maps
are accessible through the popup menu, the B1 -map displaying variations in the
B1 -field and the mean-error-map supplying information about estimated errors in
the fitting algorithm (Fig 6.3).
Figure 6.2.
Default
display of quantification maps using four
viewports.
Upper left: T2 w
Upper right: T1 -map
Lower left: T2 -map
Lower right: PD-map
6.2 Main Features
35
Figure 6.3.
Additional
quantification maps.
Left: B1 map
Right:
Mean Error
Map
Region of Interest
The region of interest (ROI) is used to display information about the quantitative
MR parameters of the pixels (Fig 6.4). The size of the ROI can be determined
by the user, but are limited to a rectangle with a minimum of six viewport pixels.
The measurement values of the pixels inside the ROI are displayed in the upper
right corner of the HUD, displaying the mean and standard deviation of T1 , T2 ,
PD, the pixel intensity value inside the ROI and the ROI position in viewport
coordinates. The relaxation rates within the ROI are plotted in the R1 R2 -plot.
Figure 6.4. ROI and the supplied info displayed in the HUD
R1 R2 -plot
In the R1 R2 -plot, the relaxation rates are forming the two axes in a 2D Cartesian
grid (Fig 6.5). Clusters characterising white matter, central white matter, internal
capsule, putamen, grey matter and CSF are defined based on the mean values in
Table 6.1 and are indicated in the plot as ellipses. The area of each cluster is based
on empirical studies and on-going projects at CMIV working on the classification
of the clusters given by the QRAPMASTER sequence. The bounding lines in
between the clusters illustrate relaxation values possible caused by partial volume
effects. The relaxation rates inside the ROI are plotted in the graph and each
data point is stretched over an area corresponding to 0.05 ± 0.01s−1 in the R1 direction and 0.4 ± 0.08s−1 in the R2 -direction. The intensity value given each
pixel is linearly related the maximum distance in the x- or y-direction from the
actual data point. Finally the pixel intensities are scaled in the interval [-mean/2
36
SyMRI Brain Studio
mean/2] and are displayed with a threshold discriminating intensity values initially
below zero. This is done in order to get a weighted plot.
Figure 6.5. The relaxation rates are plotted and specific clusters indicate different types
of brain tissue
Table 6.1. MR parameter values for brain tissue.
Tissue
White Matter
Central White Matter
Internal Capsule
Putamen
Grey Matter
CSF
Fat
6.2.2
T1
570
630
665
800
1100
3800
320
T2
75
85
68
73
96
1800
90
Display of SyMRI Contrast-Weighted Images
The contrast images are rendered based on the measured MR parameters and the
current settings for TE, TR (Eq. 4.1), and TI (Eq. 4.2) in the case of a simulated
inversion pre-pulse. The default settings with values corresponding to generally
used scanner parameters (Table. 6.2) are accessed through the popup menu and
keyboard accelerators. The parameters can be modified by the end user through
menu options and the left mouse bottom to render any contrast-weighted image
possible. The additional image settings: colormap, interpolation, modulus/real
and autoscale are modified through the popup menu and keyboard accelerators.
Fig 6.6 show the four viewport default display with a T1 w image, a T2 w image, a
P Dw-image and a FLAIR image.
6.2 Main Features
37
Figure 6.6.
Upper left: default T1 w
Upper right: default
T2w
Lower left:
default
PDw
Lower right: default
FLAIR
Table 6.2. Default Scanner Parameters
Image
T1 w
T2 w
PDw
FLAIR
TR
350
4500
6000
6000
TE
10
100
10
120
TI
200
Mode
Modulus
Navigation Window
The navigation window shows the current contrast-weight of the image in the
viewport (Fig 6.7) and is displayed in the HUD in order to navigate the user to
the current image-weight while freely selecting the scanner parameters TR and
TE.
Figure 6.7. The navigation window allows for user guidance when adjusting the current
image-weight.
38
SyMRI Brain Studio
Fat Suppression
Menu options and keyboard accelerators for fat suppression are available (Fig. 6.8).
When calculating the image a mask is applied that excludes the intensity contributions from fat. The fat suppression is unique to SyMRI and can not be achieved on
the same basis in conventional imaging as the selection is based on the measured
MR parameters.
(a) T2 w Image
(b) T2 w Image with Fat Suppression
Figure 6.8. Fat Suppression is used to exclude the signal contribution from fat.
T1 Enhanced Image
(a) T1w Image
(b) Enhanced T1 w Image
Figure 6.9. The contrast between white and grey matter is enhanced through the
PD-normalization.
By excluding the PD-contribution in Eq 4.1 & Eq. 4.2 a PD-normalized image
can be calculated neglecting the signal contribution from PD. This will create
enhanced contrast between grey matter and white matter in T1 w images since the
T1 and PD effects counteract each other in a conventional T1 w- image. (Fig. 6.9).
6.2 Main Features
6.2.3
39
Graphical User Interface
The GUI is divided into a number of features, the popup menu, the HUD and the
keyboard accelerators.
PopUp Menu
The pop-up menu is divided into four sections (Fig 6.10). The image settings
section is partly pre-defined by the SyMRI framework and handles general image
settings: pan, zoom, interpolation of the image, linking between slice selection in
IDS5 and the plugin, autoscale, colormap, modulus or real image, linked viewports,
settings of the R1 R2 -plot and the number of viewports displayed. The second
section allows easy to use pre-defined default values for SyMRI contrast-weighted
images, either one by one or as a four viewport default option supplying the
user with the conventional set of contrast images for typical brain applications
in addition with a P Dw image (Fig. 6.6). The third menu section visualizes the
quantification maps one by one or as a four-viewport default option (Fig. 6.2). The
fourth section provides options for modification of the simulated scanner parameter
settings TE, TR and TI as well as the simulation of an inversion pre-pulse and
qMRI features in terms of fat suppression, PD-normalization and T1 enhancement.
Additionally there is a stack tile sub-menu and a close bottom provided by the
SyMRI framework.
Figure 6.10. Popup Menu
Heads Up Display
The HUD supplies the user with information regarding the examination, the patient, the image settings and the quantified data inside the ROI. Information on the
40
SyMRI Brain Studio
name of the patient, date of birth, date and time of examination, sequence used,
slice thickness, FoV, current slice number and position within slices are retrieved
from the SyMRI framework and displayed in SyMRI Brain Studio. Information
about the SyMRI contrast image settings are displayed in terms of the current
TE, TR, TI and through the navigation window. In the case of default contrast
images, active T1 enhancement or active fat suppression a label indicating their
presence is shown in the central upper part of the HUD. The software version and
a caution label indicating that the software is an investigational device are also
displayed. The ROI information is displayed as explained in section 6.2.1. In the
upper right corner the scale window parameters are shown, C indicating window
centre and W indicating window width.
Keyboard Accelerators
The keyboard accelerators are available to give the end user a smooth working
environment. The accelerators are based on the name of the features - autoscale A, fat suppression F, inversion pre-pulse I etc. The default contrast SyMRI images
are indexed by numbers ranging from one to five and the numbers seven to zero
are dedicated to the different quantification maps.
6.2.4
Autoscale
The autoscale algorithm for contrast-weighted images was given through multiple
regression analysis resulting in the following equations: W = −100+2∗abs(mean),
C : 80 + 1.7 ∗ C + 0.6 ∗ mean. The equations were derived based on the mean
value and standard deviation of the pixels in the images as well as the width and
centre of satisfying scaling windows. Synthetic T1 w, T2 w, P Dw and FLAIR images
with satisfying image contrast from three complete data sets were analysed. The
quantification maps all have individual scaling settings based on their T1 , T2 and
P D value. The autoscale is automatically turned off in between slices in order to
get a constant colormap throughout the brain.
6.2.5
Colormap
The colormap used for all colored images is the hue based rainbow colormap ranging from blue to cyan, green, yellow and red. Blue indicates the lowest pixel
value.
6.2.6
Colorbar
The colorbar is displayed in the HUD for all coloured images and is integrated in
the SyMRI logo. The colorbar ticks indicate max value, min value and window
centre (Fig 6.11).
6.3 SyMRI Brain Studio Releases
41
Figure 6.11. The colorbar.
6.2.7
The Font
The font used is Arial and the font size is optimized to be as large as possible
without interfering with the display of the calculated image. The font size is
implemented in the function GetPerfectFont(). In the case of a too small viewport
no HUD is displayed and an error message appears on the screen.
6.3
SyMRI Brain Studio Releases
The previous parts of this chapter have explained SyMRI Brain Studio as it appeared in the end of the work with this master thesis. The following section
will guide the reader through the successive development throughout the different
versions of SyMRI Brain Studio.
6.3.1
v.1.0.0
SyMRI Brain Studio v.1.0.0 was the version used in the first radiologist interaction
(Section 5.2.1). All possible SyMRI images could be rendered using TR, TE and
TI modifications and a simple R1 R2 -plot and a navigation window were displayed
in the HUD.
6.3.2
v.3.1.0
Based on the findings in Radiologist Interaction I and II (Section 5.2.1 & 5.2.2)
SyMRI Brain Studio v.3.1.0 was developed. Major changes were the re-arrangement
of the information to be found in the HUD and the extended and developed R1 R2 plot. The HUD was divided into a more logical way, the navigation window was
made smaller and the navigation curse was made circular instead of squared. Additionally keyboard accelerators were introduced in order to make the user interface
easier. Also the algorithm for choosing font size were improved in order to enlarge
the font when possible, to be compatible with the split of screens in IDS5 and to fit
the R1 R2 -plot even within small viewports. A major improvement for v.3.1.0 was
the improved implementation of the R1 R2 -plot. The time needed to plot the graph
42
SyMRI Brain Studio
was enormously reduced by introducing a bitmap back-buffer instead of plotting
the values one by one in the present device context. This improvement eliminated
the previous problem with too slow calculations making it almost impossible to
plot data from a whole slice as well as scroll between slices and to use the R1 R2 plot within more than one viewport. Additionally the R1 R2 plot was improved
by weightening the plot which allowed for an assessment of a ROI containing the
complete image slice without getting a completely white graph since all pixels were
hitted at least once. In addition, a median filter was applied to get rid of some
noise assuming that all important features of the brain are at least nine voxel in
size. Axis and ticks were added to the plot to give more information to the user.
Additionally, all options for image settings in the popup menu were moved to the
submenu called image settings in order to reduce the size of the menu.
6.3.3
v.3.2.0
Additional SyMRI image options were added through T1 enhancement and an
IR Real image. An additional general R1 R2 -plot in order to allow examination of
other parts of the body than the brain using SyMRI Brain Studio was implemented.
6.3.4
v.4.1.0
This version was mainly not developed by the author, except from minor changes
in the structure of the code. The version is equipped with a segmentation mode,
which is neither explained nor evaluated in this master thesis.
Chapter 7
Radiologist
The chapter explains the outcome of the interactions with the radiologists and
describes how they effected the development of SyMRI Brain Studio and the underlying imaging technique. Future development suggestions and conclusions made
can be found in Chapter 9 and 10.
7.1
Radiologist Interaction I
Radiologist: Bengt Petré, University Hospital in Linköping, Sweden
Date: 3/3/2008
A number of factors made the radiologist experience SyMRI Brain Studio insufficient in comparison to conventional contrast-weighted MRI. The radiologist had
the opinion that these shortcomings should be rectified before further evaluation
of the software. A list of eight major drawbacks were found, which were analysed
in order to conclude the technical changes needed (Section 7.1.1). Additionally,
the radiologist pointed out some clear advantages with SyMRI (Section 7.1.2) and
a list of possible future applications was made (Section 7.1.3). The complete document from the meeting can be found in [10]. Furthermore, the day resulted in a
number of development suggestions on the SyMRI Brain Studio interface and the
SyMRI plugin as a whole.
7.1.1
Drawbacks
• Insufficient Pixel Resolution
The radiologist found the images displayed in SyMRI Brain Studio to have
bad pixel resolution in comparison to the conventional MRI images (Fig 7.1.1).
One reason for this is the slightly decreased spatial resolution of the SyMRI
images, but the main reason is that no interpolation was used when displaying images in SyMRI Brain Studio v.1.0.0. In IDS 5 interpolation is
used when displaying enlarged pixels. A function for image interpolation
was implemented in the SyMRI framework using bilinear interpolation.
43
44
Radiologist
• The complete brain is not covered in the examination
In order to keep down the scan time, the complete head of the patient was not
included in the FoV. The radiologist found this insufficient as it is important
to get a general overview of the complete brain when examining a patient,
even when the searched disease is present in restricted parts. By increasing
the number of slices acquired in the QRAPMASTER sequence, data from
the complete brain could be measured.
• The most posterior image slice has insufficient image quality
In the slice closest to the neck deviating pixel intensities and several artefacts
are present. The artefacts appear due to the REST slab placed at the neck
of the patient. To reduce the artefacts the REST slab where moved further
away from the most posterior image slice.
• Lack of anatomic details
The radiologist experienced a lack of anatomic detail in the synthetic images
in cerebellum, tractus opticus and some other parts of the brain (Fig 7.2(b)D).
The lack of anatomic detail can be caused by insufficient spatial resolution,
insufficient SNR or errors introduced in any of the post-examination calculations, i.e. the fitting algorithm or the synthetic calculations. The resolution
in the image can theoretically be improved, but there is a strong correlation
between the resolution, SNR and scan time. For a spin echo sequence such as
QRAPMASTER, the SNR can be explained through Eq 7.1. The effect on
the SNR when changing the imaging parameters can be explained as a ratio,
oVi
, Eq 7.1 gives Eq 7.2.
given that the FoV is kept constant and Ni = F δi
SN R ∝ δxδyδz
p
p
Nacq Nx Ny Nz δt
(7.1)
where δx, δy, δz is the resolution in each axis, Nacq = number of
acquisitions, Nx , Ny , Nz = number of data points sampled in each
direction, δt = acquisition time at each echo.
SN RABratio
√
3/2
3/2
δxA δyA δzA δtA
= 3/2 3/2
√
δxB δyB δzB δtB
(7.2)
As shown, increased resolution will decrease SNR and additionally increase
the scan time as there are additional number of lines to be measured in the
phase encoding direction. Scans with improved resolution were made using
an in-plane resolution of 0.7 mm rather than 1 mm. The scan time was kept
constant but the SNR were affected.
• Artefacts around the cranium and the dorsal parts of the Brain
The artefacts in Fig 7.2(a)B are appearing due to a water-fat shift in the frequency encoding direction. Looking at the images the radiologist concludes
that the chemical shift interfere with the signals of the brain. The water-fat
7.1 Radiologist Interaction I
45
shift is caused by an always-present difference in the Larmor frequency between the protons in water and the protons in lipids, even though exposed
the same magnetic field strength. The difference of 3.4 ppm is caused by the
differences in molecular structure between the two compounds [4]. Since the
spatial encoding in the frequency encoding direction is based on frequency
differences as described in Eq. 2.1, the difference in the Larmor frequencies
will lead to a misregistration of the signal. The signal from fat, which will
have the lower frequency, will be mapped to a pixel that is not corresponding to the voxel the signal comes from. The water-fat shift in mm can be
calculated as
W Fshif t =
fdif f NRO F oVRO
BWrec NRO
(7.3)
W Fshif t = the water-fat shift in mm, fdif f = the water-fat shift in Hz,
NRO = number of pixels in the frequency encoding direction, F oVRO =FoV
in the frequency encoding direction, BWrec = receiver bandwidth.
To reduce the water-fat shift BWrec was decreased resulting in a shorter
acquisition time for each echo. A larger number of echoes were then needed
in order to collect all data points and avoid a negative effect on the SNR.
The scan time was not affected as other parameters of the scan where slightly
changed. This resulted in a water-fat shift reduced by a factor 2.
• Problem with visualization of tissue with high water content
In the synthetic FLAIR images, the visualization of the CSF appears insufficient as it is speckled rather than black which is the case and purpose
of a conventional FLAIR image (Fig 7.2(a)A). The artefacts are probably
caused by a too low SNR or by miscalculations in the fitting algorithm or the
synthetic equations. The low SNR is apparent due to the long T1 and T2 of
CSF. The large values will be at the edge of the dynamic range of measurements, making the measurements uncertain and noisy. The visualizations
might be improved with an increased dynamic range or increased SNR, but
as already explained in Eq 7.1, there is a trade-off between SNR, scan time
and resolution. The fitting algorithm where improved in attempt to get an
improved visualization.
• Artefacts make healthy matter look diseased
The artefacts (Fig 7.2(a)C) make healthy tissue appear diseased, as the high
pixel intensity would indicate inflammation in a conventional MRI image.
The artefacts are mainly seen in the synthetic FLAIR images but are also
present in the left dorsal part of the brain in other images. The artefacts are
present in and around wrinkles and in the boundaries between CSF and other
tissue, especially in the anterior parts of the brain. Noise, motion artefacts,
water-fat shift or partial volume could be the reason to the artefacts.
• Insufficient contrast in T1 w images
When comparing the synthetic T1 w-images to conventional T1 w-images the
46
Radiologist
contrast between white and grey matter is insufficient in the synthetic images. The reason to the lack of contrast is not yet clarified. The method
used for the synthetic calculations is following published equations for reconstructed T1 w-images [3]. At the moment, research is done in order to
evaluate whether the scanner sequence or any of the post-examination calculations are the reason for the lack of contrast. In some synthetic images
visualized in Contrast Predictor using data sets from 2007 there are a rather
good contrast between white and grey matter. The same images also show
improved visualizations of fluids in FLAIR images. One thesis is that the
enhanced contrast is caused by the fact that a quadrate head coil rather
than a SENSE head coil was used during these examinations. Theoretically,
the SENSE coil should have a higher SNR, since it allows SENSE, shorter
scan times can be achieved. Since the coil has passed the manufacturer’s
quality assessment it is hard to affect this aspect of the problem. In order
to compensate for the lack of contrast between white and grey matter, the
T1 enhancement was introduced in Brain Studio (Section 6.2.2).
Figure 7.1. The pixel resolution in SyMRI Brain Studio is low compared to the images
in IDS 5.
7.1.2
Advantages SyMRI
• Short Scan Time
In a conventional image protocol each contrast-weighted image takes between two to five minutes to acquire. With a single scan that provides
enough information to recreate all possible contrast-weighted images there
are possibilities for a clear advantage using SyMRI, not only in terms of scan
time but also in terms of stored information.
• Improved information
A single pixel in a conventional MRI image does not contain any absolute
information regarding the underlying tissue. SyMRI adds a quantitative
7.1 Radiologist Interaction I
47
Figure 7.2. A) Noisy visualization of CSF, B) Large water-fat shift, C) Healthy tissue
appear diseased, D) Lack of anatomic detail.
dimension to the data which supplies additional information with potential
to improve the diagnosis.
• Easy to change between images
In IDS 5 it is not possibility to shift between different contrast-weights while
keeping the visual point of the eye. In SyMRI you can easy look and compare
images in the same viewport shifting between different weights using a single
bottom press or continuous adjustments.
7.1.3
Future Potential of SyMRI
• Acute Examination of Patients
The decreased scan time might allow the possibility of an increased patient
throughput giving shorter patient queues and also the possibility to examine
patients that have not been able to be examined using MRI before due to
the long examination times.
• Easy tissue nulling
Using either simulated inversion pre-pulses or tissue classification, tissues
can easily be cancelled out as in conventional Short TI Inversion Recovery
(STIR) and FLAIR images. This is done with a mouse click rather than a
new scan.
• Segmentation as screening
By using tissue segmentation all normal appearing tissue could be selected
leaving non-healthy or unknown tissue. By presenting this information as
an overlay to a contrast-weighted image, the data could be used as screening
in order to make the radiologist observant on critical parts of the image.
• Examination of tumours
In today’s clinic it is hard to distinguish brain tumours from oedema. Looking at the SyMRI data sets, tissue nulling seems to have the potential to
48
Radiologist
distinguish between oedema and gliosis. If SyMRI could discern between
the two states, it might be used as a tool to plan cancer treatments such as
brain surgery and radiation therapy fields.
• Disease Specific Layouts
By creating disease specific layouts of SyMRI Brain Studio, the software
could provide the radiologist with predefined visualization suitable for the
specific examination. An MS-examination might for example contain the
synthesis of a normal MRI image protocol including T1, T2 and FLAIR
images, together with a segmentation of MS-plack indication the number of
MR-placks, their volume and type.
The SyMRI Software
Some improvements needed in the SyMRI framework and in SyMRI Brain Studio
were discovered. The framework and the font size need to be compatible with the
split of screens in IDS 5 and probably the fact that only one application of the
SyMRI plugin can be open at a time will be a disadvantage in the future as it restricts the user to look at one examination at the time. It was also concluded that
the introduction of keyboard accelerators in order to manoeuvre and flick between
specific image weights would simplify the user interactions. The question on how
to change the imaging parameters TE, TR and TI was raised as the radiologist
intuitively dragged in the circle in the navigation window in attempt to change
the image contrast.
IDS 5 does not provide any function for autocontrast of MRI images. The radiologists at Linköping’s University Hospital (US) are using the autocontrast button
for CT images to get a rough scale window setting from which they modify the
window to achieve desired grey scaling of the images. In T1 w images good contrast
between grey and white matter is desired, in addition with good visualization of
the anatomic features inside the ventricles, in FLAIR images the boundaries of
CSF are of clinical interest and therefore over express signal from fluids is not
desirable.
The Quantitative Imaging Technique
Some additional of SyMRI were pointed out during the meeting. In conventional
MRI examinations two different image projections are often used. This is done in
order to evaluate findings that are unclear in one of the projections. To acquire
an additional image stack in a different projection using SyMRI, an additional five
minutes scan is needed. Another difference the radiologist noticed in the synthetic
images is the visualization of veins and arteries due to the appearance of the REST
slab.
7.2
Radiologist Interaction II
Radiologist: Leif Danielsson, University Hospital in Linköping, Sweden
Date: 18/3/2008
7.2 Radiologist Interaction II
7.2.1
49
The Clinical Routine - an MRI Examination of the
Brain.
After receiving referrals of patients in need of MRI examinations the radiologist
make a priority list based on the urgency of each case. The MRI technicians
perform the MRI examination after the MRI scanner protocol determined by the
radiologist and during the examination the radiologist is contacted to confirm
whether the image quality is sufficient or any of the image sequences need to be
retaken. After the examination the technician transfer the images to the PACS
system and performs a ’system hanging’ in SECRA IDS 5, which includes organisation of the different stack of images in a way that give the radiologist easy access
to the images. The radiologist can then get access to the images through the PACS
system on his computer. After some changes in the ’system hanging’, including
adjustment of the scale window the radiologist scrolls through the image stacks
and make his judgement in accordance with other patient information available.
The radiologist has the possibility to make notes and measurement in the images
while working and save these notes in the PACS system. Afterwards the radiologist dictates his findings, which are later transferred into the PACS system by a
secretary.
7.2.2
Interaction with SECTRA IDS 5
The workstation used by the radiologist includes three computer screens, one used
to handle the patient data and manoeuvre the software and two additional screens
displaying the images. The screens can be split into several viewports each displaying an image stack. During the validation of the images there is limited user integration with the PACS system. The radiologist uses the mouse to scroll through
the image stacks and to obtain desired grey scaling of the images. The radiologist
also interacts with the software when making measurements and adding notes to
the images, when linking viewports to each other in order to simultaneously scroll
several image stacks and when saving personal settings. The keyboard accelerators
used are the one for CT autoscale settings ’F1’ and linking viewports ’+’.
Learning
The radiologist can not recall that any education of SECTRA IDS 5 has been
available except for a minor introduction when the system was new. Instead his
knowledge about the system is based on trial-and-error and exchanging knowledge
between colleagues in order to get a sufficient and efficient workflow.
7.2.3
Autoscale
The scale windows the radiologist are looking for in the different contrast-weighted
images are confirming the findings from Radiologist Interaction I. In FLAIR images
it is of importance not to oversteer the signal from liquids to get a good image
50
Radiologist
of the boundaries of CSF, in T1 w-images the anatomical structures inside the
ventricles are of importance and so are the image contrast between grey and white
matter. In T2 -images it is of interest not to oversteer the signal from the veins
and arteries and to achieve a good contrast between grey and white matter and
the grey matter and abnormal tissue. The radiologist points out that it is often
not possible to get a grey scaling that give good image contrast for all anatomical
features and therefore priority is on the most critical parts.
7.2.4
The SyMRI Software
As in Radiologist Interaction I, the importance of being able to open several copies
of the software is stressed, in order to use all screens. Additionally the importance
of being able to do measurements and save data about the measurements is raised
as well as being able to do ’system hanging’ and save customised scaling windows
and other user settings.
7.3
Radiologist Interaction III
Due to the limited time set for the meeting and the vast amounts of information
that was introduced to the radiologist by the author and others, the outcome
was limited. According to the radiologist the most important feature of an MRI
image is the clinical information it is providing. Therefore the radiologist had
the opinion that the SyMRI images could have a lower spatial resolution than
the conventional contrast-weighted images as long as they provide enough clinical information. The radiologist suggests that the decreased resolution could be
compensated by the quantitative information and the short scan time the technique provides. A shortcoming of the synthetic T1 w-images is notified as some
MS-placks present in the conventional T1 w-image cannot be seen. When comparing the T1 w-image to the T1 enhanced image the plack is visible. The radiologist
suggests that the T1 enhancement might be good for the evaluation of burned out
plack. During the meeting the radiologist did not change the scale window in the
synthetic images as a cause of the implemented autocontrast function.
7.4
7.4.1
Radiologist Interaction IV
Follow up - Drawbacks
Three of the eight drawbacks found in Radiologist Interaction I were improved.
As a result of the implemented autocontrast function, the radiologist did not need
to change the scale window in the default contrast-weighted images, but changing
TR, TE and TI to extreme values resulted in pore scale window settings.
• Insufficient Pixel Resolution
With introduced image interpolation in the SyMRI software, the radiologist
experiences a satisfying pixel resolution equal to the one in the conventional
images.
7.5 Radiologist Interaction V
51
• The complete brain is not covered in the examination
By increasing the number of slices obtained, the FoV covered the complete
brain and the radiologist was satisfied.
• The most inferior image slice has insufficient image quality
The artefacts in the most posterior image slice are reduced but still present.
The slice is not usable for clinical evaluation.
• Lack of anatomic details
The images with higher resolution became too noisy to be used for further
clinical evaluation.
• Artefacts around the cranium and the dorsal parts of the brain
After reducing the water-fat shift the signal from the fat around the brain
does no longer interfere with the signals from the brain. The water-fat shift
is according to the radiologist no longer interfering with important features
of the image.
• Problem with visualization of tissue with high water content
In some data sets the visualization of liquids was better, but it was not
sufficient in some of the other data sets.
• Artefacts make healthy matter look diseased
With a reduced water-fat shift the artefacts in the left dorsal part of the brain
disappeared. The artefacts still appears in the wrinkles and the boundaries
to CSF in FLAIR images with insufficient visualization of CSF.
• Bad contrast in T1 w images
The T1-enhanced images appears appealing to the radiologist in terms of
achieved image contrast between white and grey matter.
7.5
Radiologist Interaction V
The response from the radiologists and researchers at LUMC where recieved
through an email [12] sent to Dr Marcel Warntjes. The radiologist and clinical scientists are satisfied with the scanning procedure and the transfer of images
to the IDS 5 as well as the launching of SyMRI Brain Studio. Four radiologists
evaluated the images obtained and a number of problems were called. The radiologists experience a decreased SNR in the centre of the skull. The FLAIR images, as
concluded in radiologist interaction I and IV were not satisfying due to insufficient
visualization of the CSF. Major problems werepresent when examinating children,
images gets heavy speckles and the T1 w image could not be visualized at all.
Chapter 8
Validation of the Technique
The chapter contains a discussion regarding to what extent SyMRI Brain Studio
could replace conventional contrast-weighted MRI examinations in the clinical routine.
8.1
Required Characteristics
What is required from a new imaging technique in order to be put into clinical use?
According to the radiologist talked to in Radiologist Interaction I - IV, there are
several aspects to consider. Their input has resulted in the following assumptions:
In order to be introduced as a clinical tool used in the daily routine SyMRI Brain
Studio and the underlying imaging technique should:
• Answer to the clinical information given in today’s conventional MRI examinations.
• Be clinically validated.
Additionally, SyMRI Brain Studio has to provide at least one of the following
characteristics in order to replace conventional MRI examinations:
• Reduced scan time.
• Reduced medical costs.
• Improved clinical information.
• Improved patient security.
53
54
8.2
Validation of the Technique
Potential of SyMRI Brain Studio
Three major characteristics of SyMRI Brain Studio and the underlying imaging
technique suggest that the technique could comply with the last four requirements
set in the previous section. The scan time, the all-in-one approach and the quantitative measurements together have the potential to reduce scan time and medical
costs as well as improve the given clinical information and patient security.
8.2.1
Scan Time
A decreased scan time would not only provide improved patient comfort in terms of
less time inside the MRI scanner, it could also allow an increased patient throughput, which might give shorter patient queues and decreased medical costs. Additionally, a reduced scan time might allow MRI to be used in favour of CT in
applications where MRI is too time consuming to be used today. This would increase the patient security as the radiation dose from the CT scan is eliminated.
The QRAPMASTER sequence allows complete data acquisition of a head within
five minutes and provides data enough to reconstruct all possible contrast-weighted
images in one image projection. To this, as in all MRI-examinations, a prescanning procedure is needed in order to set the scanner field. Together it adds up
to a total scan time of approximately seven minutes [13]. The call for additional
image projections and the use of contrast-agents will add to the scan time.
Dependent on the purpose and number of scans needed in the conventional MRI
protocol the time saving aspect of using SyMRI will differ. The MRI protocol
used for MS-examinations at CMIV today, takes 27 minutes [13] and requires twp
different image projections. The figures suggest that by using SyMRI Brain Studio the scan time can be decreased with 15 minutes, as two image projections will
result in a SyMRI scan time of 12 minutes.
8.2.2
The All-in-One Approach
One quantitative scan using the QRAPMASTER sequence and SyMRI Brain Studio theoretically provides data for post-examination calculations of all conventional
contrast-weighted images in a certain projection. As SyMRI allows the image contrast to be optimized after the scan, images with optimal contrast between desired
tissues can be obtained, giving additional clinical information without increasing
the scan time. In that case, SyMRI Brain Studio can provide improved clinical
information and reduced scan time in comparison to conventional examinations.
8.2.3
Quantitative Measurements
Apart from the synthetic contrast-weighted images, the quantitative data has additional potential. As the quantitative measurements provide absolute information,
SyMRI Brain Studio allow for a number of imaging features through tissue characterization. If healthy and diseased tissue can be accurately characterized using the
MR parameter values, segmentation could be of large clinical value, for example in
the diagnosis of MS. If the measurements can be proved to be scanner independent
8.3 SyMRI Today
55
and reproducible, SyMRI can additionally provide accurate multi-centre studies
and comparison between examinations which is not possible using MRI today as
the measurements are heavily scanner dependent.
8.3
SyMRI Today
In the following section, the potential of SyMRI Brain Studio as it appears today
is discussed based on the statements presented in section 8.1.
Answer to the clinical information given in today’s conventional MRI examinations
There are three shortcomings in the synthetic contrast-weighted images that are
known to prevent SyMRI Brain Studio from providing the same clinical information as the conventional images do: the problem with visualization of fluids in
FLAIR images [10, 14, 15], the lack of anatomic detail [10] and the shortage of
image contrast in T1 w images [10, 14]. Additionally, it is not evaluated if any valuable information is lost due to the reduced spatial resolution or the black-blood
imaging. How much these aspects affect the clinical information will depend on the
purpose of the examination. However, to answer to the clinical information given
in the conventional examinations SyMRI Brain Studio does not necessary has to
provide identical information, in case the clinical information from the quantitative
data can compensate for these shortcomings.
Be clinically validated
SyMRI Brain Studio is not yet clinical validated and neither is the underlying
imaging technique, this has to be done before the technique can be put into use
in the clinical routine. For clinical validation, large studies on patients are needed
to prove the accuracy of the method.
Reduce scan time
In MS-examinations there is a significantly reduced scan time which could improve
patient throughput. The amount of time saved in other applications will depend
on the number of image projections and whether contrast agents are needed.
Reduce medical costs
The reduced medical costs are strongly correlated to reduced scan time but also
to the clinical information given in the examination. Today, SyMRI seems to have
the potential to increase the patient throughput and hence decrease the medical
costs, assuming that the SyMRI images will not acquire extra time when it comes
to interpret the images.
56
Validation of the Technique
Improve clinical information
To date, the tissue characterisation is based on empirical studies and limited statistics. The result of the ongoing characterisation study at CMIV [16] might provide
additional indications in this question. In Radiologist Interaction I it was suggested
that SyMRI Brain Studio could be used for examination of tumours, stroke, MS
and migration diseases.
Improve patient security
In the case SyMRI Brain Studio can replace a CT examination due to reduced
scan time or improved clinical information, there is an increase of patient security
as the radiation dose is eliminated.
Chapter 9
Discussion
The purpose of this master thesis was to develop a visualization studio for SyMRI
images of the human brain. The visualization studio should allow comparison between conventional contrast-weighted MRI and SyMRI, exemplify the advantages
of SyMRI and be intended for clinical use. Meetings with radiologists were organized in order to obtain user input regarding the improvements needed for such a
development. The information gained was also used to estimate the potential of
SyMRI Brain Studio in terms of replacing conventional MRI in the clinical routine. This chapter discuss the results obtained during the work as described in
Chapter 6, 7 and 8.
9.1
SyMRI Brain Studio
With SyMRI Brain Studio, the SyMRI images can be easily compared to conventional contrast-weighted images using SECTRA IDS 5. The pop-up menu
(Fig 6.6) and available keyboard accelerators gives the user easy access to one
or four viewport displays of T1 w, T2 w, PDw and FLAIR images. Additionally,
SyMRI Brain Studio allows the radiologist to experience the enhanced potential of SyMRI through the ROI, the R1 R2 -plot, the quantification maps, the MR
parameter based fat suppression, the T1 enhancement and the possibilities of continuously modifying the image contrast through TE, TR and TI.
As stated in the introduction the aim with SyMRI Brain Studio was to develop a
software intended for clinical use. Apart from Contrast Predictor, which is not connected to any PACS system, SyMRI Brain Studio is the only software available for
advanced visualizations of qMRI data and SyMRI images. Consequently, SyMRI
Brain Studio has already been used for SyMRI visualizations in several research
projects at CMIV. Additionally, the software has been displayed for commersial
purposes at the European Congress of Radiology in Vienna (February 2008) and at
the annual congress of the Nordic Association for Neuroradiology in Visby (June
2008). This has certainly been encouraging, but might at some stages have taken
the focus away from developing SyMRI as a clinical tool in favour of making modifications needed for the current research and marketing purposes. This might not
57
58
Discussion
necessary be a drawback as further research and validation is needed in order to
introduce the software as a clinical tool.
9.1.1
Design Decisions
In this section some of the design decisions made during the implementation of
SyMRI Brain Studio are discussed.
ROI
In the current version of SyMRI Brain Studio the mean and standard deviation
of T1 , T2 , PD and the pixel intensities inside the ROI are displayed in the HUD,
together with the position of the ROI. At CMIV, researchers have pointed out that
other statistics might be of interest for research purposes and additionally, ROIs of
different shapes could be useful when making analysis for tissue characterization.
Apart from the PD values, which are closely related to the water content in tissue,
the radiologists have shown little interest in the ROI statistics, probably since
equivalent information can be obtained from the R1 R2 -plot, which is more spot
on to interpret. This suggests that all ROI information displayed in the HUD
might not be needed in general applications and that the R1 R2 -plot together with
the PD values might provide sufficient information to the radiologist. One possible
development could be to develop a statistic toolbox to where the ROI statistics
is moved and supplemented with additional statistics as well as print and saving
options.
R1 R2 -plot
The clusters used to indicate brain tissue in the current R1 R2 -plot are based
on limited statistics and the correlation between R1 and R2 is purely based on
empirical studies. Note that the values are dependent on the scanner field strength
and that the research done at CMIV is based on a 1.5T MRI scanner. Hence,
further research is needed to achieve properly shaped and placed clusters. Also,
data for 3T MRI scanner is needed.
Navigation Window
Several radiologists [14, 15, 17] have intuitively tried to drag the image weight
indicator in the navigation window in order to change the image weight of the
synthetic images. In the current version of SyMRI Brain Studio, the image weight
can only be changed using menu options followed by mouse action. This is rather
time consuming and in addition the mouse modifies different imaging parameters
depending on whether an inversion prepulse is included in the calculations or not.
The reason for this is that from a technical point of view, it was assumed that in
the case of an inversion prepulse the user would be interested in changing TR and
TI, otherwise TR and TE. However, this seems to cause confusion, especially since
TI does not influence the general contrast-weight of the image. To simplify the
user interface it is suggested that code should be implemented so that the image
9.1 SyMRI Brain Studio
59
weight indicator can be used to change the contrast-weight of the image and that
the mouse actions modifies so that a certain menu option always modifies the same
imaging parameters.
T1 Enhancement
The T1 enhancement might serve as a complement or replacement to the synthetic
T1 w images that lack image contrast between white and grey matter. The radiologists that looked at the T1 enhanced images found them appealing and interesting
[14, 15]. Further evaluation is needed in order to determine whether the clinical
information provided is accurate and sufficient in comparison to the one obtained
in conventional T1 w images.
GUI
During the meetings with the radiologists, it became clear that a simple user
interface is required, both in order to provide a smooth and efficient working environment, but also to allow for users with limited computer knowledge. The
software has to be easy to learn and provide a smooth workflow with visualizations easy to interpret. The possibilities of post-examination adjustments easily
introduce requirements of knowledge regarding the theoretical background of the
technique when using the software. To avoid that, user guided features such as
the navigation window and the default image options were developed. However,
the adjustment of TI and the search for optimal image contrast through TR and
TE adjustments, are features in SyMRI Brain Studio that requires the user to
have theoretical knowledge in order to achieve desired visualizations. By developing functions that provide automatic cancellation of desired tissue and automatic
contrast optimization this aspect of the GUI could be developed further in terms
of user friendliness. Additionally, disease specific layouts could be introduced, as
suggested in Radiologist Interaction I [10].
The popup menu currently contains about twenty five entries, which makes it is
rather long and complicated to navigate. One suggestion for future development
is to introduce a number of submenus. Also the keyboard accelerators are introduced to allow a smooth user interaction and there have been second thoughts
about what commands to use. Since the software is written in English but intended to be used in a number of countries, the keyboard accelerators have been
related to the English name of the action rather than the ergonomic location on
the keyboard, as different countries have different keyboard standards. Apart from
that, it would be preferable to have commands for similar things present in the
same area of the keyboard.
In order to compliance with the initial assumption that SyMRI Brain Studio should
allow similar features as SECTRA IDS 5 it is necessary to introduce a toolbox
which allows for measurements and notes to be made in the images, as well as user
defined settings and saving options.
60
Discussion
Autoscale
The equations used to calculate the scale window parameters in the contrastweighted images were derived through multiple regression analysis using images
of satisfying grey scaling. Due to the limited time available with radiologists, the
knowledge gained in Radiologist Interaction I and II was used to set the scaling
window in the analysed images. The data would have been more reliable in the case
an experienced radiologist had set the scaling parameters. However, in the two
meetings with radiologists were the function for autoscaling had been implemented
to the software [14, 15] neither of the radiologists changed the grey scaling of
the synthetic contrast-weighted images when looking at default T1 , T2 , PD or
FLAIR images. This implies that the autoscaling in SyMRI Brain Studio might
be sufficient for autoscaling of common contrast-weighted images. Further studies
are needed to determine if any functions can be derived that allows sufficient
autoscaling of all possible contrast-weighted images.
Colormap
The colormap used in SyMRI Brain Studio, the rainbow colormap, is a hue-based
colormap ranging from blue to red in the blue-green-red color space. The reason to
the choice of colormap is that the same colormap is used in SyMRI Cardiac Studio
and Contrast Predictor. The rainbow colormap are commonly used in different
visualization but are also thoroughly questioned as an accurate tool for scientific
visualizations [18, 19, 20, 21]. There are several reasons for this, one is that the
rainbow colormap is a linear colormap that gives a nonlinear interpretation of the
data since the human vision will divide the data into five large segments represented by the colors, blue, cyan, green, yellow and red [19, 20]. Additionally the
yellow areas of the image will draw extra attention to the eye. It has also been
showed that hue-based colormaps are not useful for visualizations of magnitudes
as it generates false interpretations of the contours of the data as it does not
accurately represent spatial low-frequency features. Instead, luminance or saturation based colormaps are considered better for such purposes [19, 21]. Due to
the limited time and the rather extensive task to create a useful and reliable colormap, this issue has not been further investigated in this thesis, even though it is
strongly suggested to do so in the future. So far, none of the radiologist introduced
to SyMRI Brain Studio has shown any interest in the information visualized in
the quantification maps. By using a meaningful colormap it might be an increased
possibility that they do so.
The Font
The font used in SyMRI Brain Studio does not have a fixed character width. The
initial reason for the choice of font was that it should be identical to the font used
in SyMRI Cardiac Studio. As the width of a word containing a certain number
of character can not be foreseen this introduce unnecessary complications when
implementing features that will control the font size and size of alignments needed
when displaying text in the HUD. The current version of SyMRI Brain Studio has
9.2 Radiologist Interaction
61
shortcomings in terms of handling output on the computer screen, for example long
patient names will create overlapping texts in the HUD. By introducing a font with
fixed character width it would be easier to implement a secure and accurate screen
output.
9.2
Radiologist Interaction
The aim with the Radiologist Interaction I - IV was to get input from radiologists in order to get information and knowledge regarding the radiologists working
environment, their integration with the PACS system as well as input for the
development of SyMRI Brain Studio. The information should be used to detect
technical improvements needed and to develop efficient visualizations of the quantitative data.
9.2.1
Selection of Radiologists
The radiologists consulted in Radiologist Interaction I - IV were working in the
same radiology department at US. This might have contributed to their similar
opinions and aligning thoughts regarding SyMRI. Ideally, radiologists from different hospitals should have been selected in order to get a broader input. A
radiologist from another hospital was asked to participate but denied due to lack
of time and insufficient knowledge about SyMRI. At the beginning of this thesis
work, no radiologists were connected to the project and throughout the work, the
radiologists were asked to participate in one meeting at the time. For future research it is advised that the radiologists are asked to participate and put a certain
amount of time into the project already during the start up phase and that the
purpose of each meeting is clarified in order to get the desired output.
9.2.2
Data Sets
During the development and validation of features of SyMRI Brain Studio that
are connected to the quality of the measured data, a major limitation in the development process has been the limited access to relevant data. During Radiologist
Interaction I, one data set was available for examination in SyMRI Brain Studio.
Therefore, most data sets were examined using Contrast Predictor, which reduced
the input concerning the user interface of SyMRI Brain Studio. The collection of
patient data is time-consuming, costly and needs ethical approval. In addition,
a number of technical issues concerning data transfer and modifications in the
scanner software have restricted the number of data set available. As some of the
shortcomings discovered in Radiologist Interaction I required changes in the scanner sequence parameters, data sets obtained with older scanner settings became
out of date in terms of evaluating the image quality. Due to the limited number
of data sets, further evaluation is needed in order to prove that the improvements
found in Radiologist Interaction IV are appearing in a large number data sets.
62
9.2.3
Discussion
Lack of Anatomic Detail in SyMRI images
It is possible that the lack of interpolation in SyMRI Brain Studio v.1.0.0 made the
radiologist experience an additional but imaginary reduction of the spatial resolution that added to the experience of insufficient anatomic detail in the synthetic
images. The short time scheduled for Radiologist Interaction IV and the limited
number of data sets available restricted this from being investigated within the
time frame of this master thesis. Interpolation and reconstruction does not add
any information to the image but creates a smoother visualization, which gives a
feeling of an improved image resolution as the pixel resolution is increased. Using
interpolation introduces a risk, as it might cause loss in the image quality as the
measured values are blurred.
9.2.4
MRI Knowledge - MRI Experience
A remaining impression after Radiologist Interaction I & II is how the radiologists are used to and completely rely on the conventional set of contrast-weighted
images including T1 w, T2 w, and FLAIR images. As MRI so far has been a qualitative imaging technique all clinical information is given through the anatomical
structures visualized and the contrast behaviour different tissues obtain when using different scanner parameter values. Limited knowledge about the underlying
physics are needed to make a diagnosis from the images, instead thirty years of
experience have resulted in the knowledge about MRI that are present today.
In SyMRI, the approach has the possibility to become completely different as all
clinical information is given through the three MR parameters measured. In Radiologist Interaction I the radiologist suggested that no further evaluation of SyMRI
Brain Studio should be done before the drawbacks found were taken care of. A
major reason for this opinion was the insufficient visualizations of the conventional
set of contrast-weighted images. The radiologist had the opinion that SyMRI could
only replace conventional MRI as long as the same clinical information was provided. In Radiologist Interaction IV where improved features of SyMRI could be
displayed, the radiologist slightly change his point of view, suggesting that SyMRI
could provide improved clinical information although the conventional set of contrast images can not be accurately reconstructed. This suggests that SyMRI Brain
Studio not necessary has to provide accurate reconstructed contrast-weighted images as long as other valuable information is to be found. However, the radiologists
have no experience of interpreting quantitative information and hence it is easy to
see that correct synthetic T1 w, T2 w, and FLAIR images would be a smooth way
to introduce the SyMRI technique.
9.3
Validation
The shortcomings in terms of visualization quality and accuracy in the contrastweighted images and the lack of statistics and validation of the tissue specific characterisation, makes that SyMRI Brain Studio cannot replace any conventional MRI
examinations today. As it does not live up to the quality of the clinical informa-
9.3 Validation
63
tion gained in any conventional contrast-weighted MRI examination and neither
provide any proved additional clinical information through the quantified imaging
parameters. A potential current clinical application could be in the purpose of
screening where SyMRI could be used as a pre-scan in order to determine the optimum scanner parameters to use in a conventional scan. SyMRI Cardiac Studio
is used for such purposes at US.
To estimate the future potential of SyMRI Brain Studio is difficult. In order to replace conventional MRI examinations the artefacts shown in the contrast-weighted
images need to be corrected or the clinical information needs to be obtained from
the quantified features of SyMRI. In the example of MS-plack, tissue characterization has the possibility to allow determining the amount of MS-plack in the
patient and also the status of each plack can be validated. If this could be done,
conventional MRI might not be needed for MS examinations. In a similar way,
other examinations could be replaced, in Radiologist Interaction I it was indicated
that SyMRI could be used for examination of tumours and migration diseases.
Chapter 10
Conclusions and Future
Research
The chapter present the conclusions made and list a number of suggestions for
the further research and development of SyMRI Brain Studio and the underlying
imaging technique.
10.1
Research Questions
The research questions were first stated in Chapter 1. In this section the findings
in this master thesis is summarized based on the questions stated.
How can the quantitative data set be introduced and presented in a visualization tool in an efficient way?
Today, the conventional set of contrast-weighted images is the golden standard
for MRI examinations of the brain. In order to easily introduce SyMRI to the
radiologists synthetic contrast-weighted images will be the short-cut key. These
should be provided in addition with easy to use and easy to interpret visualization
tools that make used of the enhanced potential of SyMRI. One way to do so, could
be to introduce disease specific layouts and use automatic visualizations.
What technical improvements are required to satisfy the demands of the radiologist?
In order to live up to the present clinical information in the conventional contrastweighted images, the synthetic contrast-weighted images needs to be improved in
the following aspects:
• The contrast in the T1 w images must be better or the T1 enhanced image
has to be proved to provide the same information as the T1 w does today.
65
66
Conclusions and Future Research
• The visualizations in the FLAIR images need to be improved.
• The lack of anatomic detail has to be taken care of.
Additionally the following things need to be evaluated to see if any technical
improvements are needed:
• The decreased resolution
• The black-blood imaging
How should the GUI of SyMRI Brain Studio be developed
in order to optimize the interaction between SyMRI and the
radiologist?
SyMRI Brain Studio provides a good basis for future development of the software
into a clinical tool. It is already used for research purposes in order to develop
SyMRI [16]. Comparison between SyMRI and conventional MRI can easily be
made and in additional the potential of SyMRI in terms of a quantitative imaging technique is clearly displayed. Apart from the complicated way in terms of
changing the contrast-weight through TE, TR and TI, the lack of an automatic
function for optimized image contrast and the rather extensive popup menu, the
GUI is clear and easy to manoeuvre. Additional development suggestions can be
found in Section 10.3.1.
How many of today’s conventional MRI examinations can be
replaced with the new technique in the future?
Today it is not possible to estimate such a figure. During the work with this
master thesis a number of shortcomings of the technique and a number of potential
advantages have been found. Before it is valuated whether the problems can
be corrected and further research is made it can neither be concluded that any
conventional examinations can be replaced, nor that any can not.
10.2
Future Research
Interesting future research based on the findings in Radiologist Interaction I would
be to further evaluate how the examination of tumours, migration diseases and
stroke can be made using SyMRI Brain Studio.
10.3 Development Suggestions
67
10.3
Development Suggestions
10.3.1
SyMRI SECTRA PACS IDS5 Plug in & SyMRI Brain
Studio
• SyMRI Brain Studio needs to be developed to allow for measurements &
notes to be made in the images.
• Saving Options for scale window settings, system hanging, measurements,
notes and other user defined settings needs to be implemented in the plugin
framework.
• In SyMRI Brain Studio it needs to be easier to manoeuvre the settings for
modified image contrast and automatic functions for contrast optimization
• The popup menu needs to be clarified using submenus handling different
topics.
• The plugin framework needs to be developed so that several applications of
the plug-in can be used at the same time or the plug-in can be used over
several screens and handle several examinations in one application.
• The choice of colormap used when displaying color images should be investigated and evaluated.
Further design decisions need to be taken when it is evaluated in what aspects
SyMRI can be used in the clinical routine. SyMRI Brain Studio is developed
under the assumptions that the contrast-weighted images will form the basis of
SyMRI, if the shortcomings found can not be corrected, this might not be the case.
Not so much the software as the underlying technique that need to be evaluated.
The current SyMRI Brain Studio is a software to show the potential of SyMRI
and to use for further evaluation of the technique and the software as a tool for
clinical use.
Bibliography
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Second edition, 2007. ISBN 0-51-86527-1.
[2] Amersham Homepage. Visionaries, imaging market. Retrieved 30/06/2008
from http://www.amersham.com/ar2000/Visionaries/07.html.
[3] J.B.M. Warntjes et. al. Rapid Magnetic Resonance Quantification on the
Brain: Optimization for Clinical Usage. Magnetic Resonance in Medicine,
60(320-329), 2008.
[4] P. S. Tofts. Quantitative MRI of the Brain measuring changes caused by
diseases. Wiley, 2004. ISBN 0-470-84721-2.
[5] J. West. SyMRI SECTRA IDS 5 Plugin, Synthetic MR Technologies, November 2007. Unpublished Material.
[6] M.A. Brown and R.C. Semelka. MRI BASIC PRINCIPLES AND APPLICATIONS. WILEY & SONS INC, Third edition, 2003. ISBN 978-0-471-43310-1.
[7] J. West. Synthetic MRI Visualization Principles and Application. Master’s
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[8] P. Raimer, P.M Parizel, and F-A. Stichnoth. Clinical MR Imaging - A Practical Approach. Springer, Second edition, 2003. ISBN 978-3-540-43467-2.
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[10] E. Peterson. OBSERVATION & DISKUSSION Jämförelse: konventionell
T1w, T2w, FLAIR vs. SyMRI. Unpublished In-house Material, CMIV, march
2008.
[11] E. Peterson. OBSERVATION Hur används SECTRA IDS 5 PACS av radiologerna idag. Unpublished In-house Material, CMIV, april 2008.
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[13] 1.5T Philips Achieva, august 2008. Data retreived from the workstation of
the MRI scanner at CMIV.
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[15] B. Petré. Follow up - Drawbacks. Discussion hold at CMIV. Interviewer:
Erika Peterson, july 2008.
[16] J. Örter. Working title: Quantitative Magnetic Resonance Imaging Analysis
of Multiple Sclerosis in the human brain. on-going project, planned account:
September 2008.
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[18] R.M. Taylor II D. Borland. Rainbow Color Map (Still) Considered Harmful.
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[19] L.A. Treinish B.E. Rogowitz.
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[20] T. Munzer.
Information visualization.
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Appendix A
Magnetic Resonance
The quantum mechanical model in this section should not be considered complete,
but is chosen in order to provide the reader with a basic overview of the quantum
physics underlying the concept of MRI.
A.0.2
Nuclear Spin
Spin is an intrinsic quantum mechanical property of elementary particles in atoms,
ˆ Jˆ is directed clockwise
which gives the particles an intrinsic angular momentum, J.
around the axis of the spin and gives rise to an associated magnetic moment, µ̂,
proportional to Jˆ (Eq. A.1) [22].
µ̂ = γ Jˆ
(A.1)
γ =gyromagnetic ratio
In atom nuclei with an odd number of protons and/or an odd number of neutrons, the individual spin of the elementary particles will combine into a resulting
net spin of the atom nuclei. The net spin is referred to as nuclear spin (Fig A.1).
All nuclei have a characteristic spin quantum number I and a spin magnetic quantum number MI = I, I − 1, ..., −I, which determinates their quantum mechanical
behaviour. Jˆ is related to I according to Eq. A.2 and the number of spin states is
determined by MI [22].
ˆ =
|J|
p
I(I + 1)2 ~
(A.2)
~ =Planck’s constant/2π
Nuclear Spin in Biological Tissues
In MRI, hydrogen nuclei form the basis for the visualization of biological tissue
[4]. Hydrogen is heavily present in the human body, particularly in water, which
make up about 70 - 90 % of most soft tissue [1]. Hydrogen nuclei consist of a single
71
72
Magnetic Resonance
Figure A.1. Nuclear Spin. Atom nuclei with nuclear spin possess a magnetic moment
making them act as magnetic dipoles.
proton, H + , and have I = 12 and γ = 42.58 [MHz/T] [4]. The intrinsic properties
give the hydrogen nuclei two measurable spin states often referred to as ’spin up’
and ’spin down’ (Fig A.2) and µ̂ = 36.87~ according to Eq. A.1 & Eq. A.2.
Figure A.2. The nuclear spin of hydrogen has two measurable orientations. The
spin up state corresponding to MI = 12
and the spin down state corresponding to
MI = − 21 .
A.0.3
Magnetic Properties & Energy Levels of Nuclear Spin
The magnetic moment, µ̂, makes the positive hydrogen nucleus act as a magnetic dipole. Hence, an external homogeneous and static magnetic field will make
the nucleus experience a torque, forcing it to precess around the magnetic field
(Fig A.3) [22]. Quantum mechanical laws demanding a conserved intrinsic angular
momentum restrict the nucleus from completely align with the external magnetic
field and it will instead precess around it (Fig. A.3). The precessional behaviour of
the angular momentum is explained by Eq. A.3, from which a specific precessional
frequency can be derived, the Larmor frequency fL (Eq A.4 & Eq. A.5) [22]. In
this thesis as in general MRI notation, the homogeneous external magnetic field
in a predefined ẑ-direction will be referred to as B̂0 .
|
dJˆ
| = γ JˆB̂0 sin(θ)
dt
(A.3)
fL = −γB0
(A.4)
ω0 = −fL ∗ 2π
(A.5)
ω0 =angular frequency
73
Figure A.3. Hydrogen nucleus in a static and homogenous magnetic field B̂0 . The
nucleus precesses around B̂0 with the Larmor frequency, fL .
B0 will not only cause the individual spins to precess around the ẑ-axis in
either one of the two spin directions. Additionally the application of B0 will result
in an implied energy difference, ∆E, between the spin states (Eq. A.6 & Eq. A.7)
[22].
EMI = E1/2 − E−1/2 = −µˆz B0 = −γB0 ~MI
(A.6)
|∆E| = γB0 h = fL h = ω0 ~
(A.7)
h = Planck’s Constant
In all nuclei with positive γ, such as hydrogen, the spin up state will achieve the
lower energy level. This will cause a displacement of the previous thermal spin state
equilibrium resulting in an excess of spins in the spin up state. The distribution
between the spin states can be estimated using the Boltzman distribution (Eq. A.8)
[22].
∆E
N↑
γ~B0
= e− kT ≈ 1 +
N↓
kB T
(A.8)
γ~B0 kB T
kB = Boltzman’s constant, T = absolute temperature, N↑ , N↓ = the number
of spins in the corresponding spin state.
Two Connected Magnetic Resonance Conditions
As already mentioned hydrogen nuclei exposed to a uniform B̂0 field will have the
same Larmor frequency and precess coherently around B̂0 . The nuclei are said
to be in magnetic resonance. A sample of nuclei in magnetic resonance is often
referred to as an isochromat whose macroscopic behaviour can be explained in
74
Magnetic Resonance
terms of classical mechanics through the Bloch equations (Section 2.1.4)[1]. An
additional resonance condition is implied through Newton’s second law. The law
states that a net absorption of energy by the isochromat will only appear when
the energy is quantified and corresponds to ∆E. From Eq A.7 it can be seen
that the energy can only be supplied by radiation of the same frequency fL as the
precessional frequency of the isochromat. The radiation will then cause coupling
between the two spin states resulting in spin transitions. So, an isochromat will
precess around B̂0 with fL and when exposed to radiation of fL a net absorption
of energy will appear until a saturation state is reached [22].
A.0.4
A Macroscopic Net Magnetization
(a) Zero Net Magnetization.
(b) Net Magnetization.
Figure A.4. In presence of a magnetic field B0 a resulting net magnetization will appear
due to an excess number of spins in the spin up state.
The disturbance of the natural equilibrium between the nuclear spins states
in presence of B0 will cause a macroscopic net magnetization, M0 (Eq. A.9), to
appear due to the excess number of magnetic moments induced in the ẑ-direction.
By introducing a frame of reference rotating with the isochromat’s Larmor frequency, the magnetization can be illustrated as a net vector M̂0 in the ẑ-direction
(Fig A.4). M̂0 form the basis of MRI since it supplies a magnetization originating
from magnetic nuclei in biological tissue.
p0 µ̂2 B0
(A.9)
3kT
In an MRI scanner with B0 = 1.5T there are approximately 4 ppm more atoms
in the lower energy state at body temperature giving M0 in orders of µT [1]. Due
to its small magnitude compared to B0 , M0 can not be measured in the ẑ-direction.
Neither does M0 contain any spatial information that can be used to derive from
where in the patient volume the signal originates. Additional magnetic fields and
radio frequency pulses (RF-pulses) are needed to get a spatial dependent signal
that can be used to retrieve a medical image of clinical importance.
M0 =
Appendix B
Abbreviations
ADC
B0
B1
GRASE
C
CMIV
Contrast Predictor
CSF
CT
DC
DICOM
EPI
FID
FLAIR
FOV
GE
Gpe
Gro
Gss
GUI
HUD
LIO
LUMC
M0
MR
MRI
MS
PACS
PD
PDw
Analog Digital Converter
The static magnetic field supplied by the MRI scanner.
The oscillationg magnetic field supplied by the RF-pulse
Gradient Spin Echo
Window Centre
Center for Medical Imaging and Visualization
In-house software used for syMRI visualizations at CMIV
CerebroSpinal Fluid
Computed Tomography
Device Context
Digital Imaging and Communications in Medicine
Echo Planar Imaging
Free Induction Decay
Fluid Attenuated Inversion Recovery
Field Of View
Gradient Echo
Phase Encoding Gradient
Read Out Gradient, Frequency Encoding Gradient
Slice Selecting Gradient
Graphical user interface
Head Up Display
Linköping Universoty Hospital
Leiden University Medical Center
Net Magnetization
Magnetic Resonance
Magnetic Resonance Imaging
Multiple Sclerosis
Picture Archiving and Communication System
Proton Density
PD weight
75
76
Abbreviations
qMRI
QRAPMASTER
R1
R2
RF-pulse
ROI
SE
SECTRA
SENSE
STIR
syMRI
T1
T1 -relaxation
T1 w
T2
T2 -relaxation
T2 w
TE
TI
TR
US
W
quantitative MRI
Quantification of Relaxation times And Proton
density by Multi-echo Acquisition of a Saturation
recovery using TSE Read-out
T1 Relaxation Rate
T2 Relaxation Rate
Radio Frequency Pulse
Region Of Interest
Spin Echo
SECure TRAnsmission
Sensitivity Encoding
Inversion Recovery
synthetic MRI
T1 value of the T1 -relaxation
Spin-Lattice Relaxation, Longitudinal Relaxation
T1 weighted contrast
T2 value of the T2 -relaxation
Spin-Spin Relaxation, Transverse Relaxation
T2 weighted contrast
Echo Time
Inversion Time
Repetition Time
The University Hospital of Linköping, Sweden
Window Width