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Background
• Trauma Patients undergo an initial, “on admission” CT scan
which includes:
– Non contrast brain
– Arterial phase full body scan
– Portal venous phase abdomen
• Many of these patients may be obese which in the past has
resulted in sub optimal imaging
• Trauma patients may have foreign objects (known or
unknown) at the time of scanning
• Trauma patients will often have metal fixation & or prostheses
• Seat belt injuries often result in damage to neck vessels
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Background
• Patients who remain in the hospital will have follow up
surgical & medical care which includes multiple follow up
CT scans depending on their diagnosis.
• The number of CT scans & the body region scanned will
depend on the type & severity of the injury
• Examples of follow up CT scans:
– Initial Brain scan showing hemorrhage will be rescanned 6 hrs
after initial scan
– Brain scans: approx 11 scans f/u within a one month period
– Abdomen & pelvis scans: approx 9 scans f/u over 3 month
period
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Background
Typical radiation dose for a trauma 64 MDCT at
University of Maryland R. Adams Cowley Shock
Trauma Centre:
kV
mAs
DLP (mGy*cm)
Effective
dose* (mSv)
Effective
dose (rem)++
Brain
120
350
968.9
2.03
0.20
Abdomen
120
200
354.8
5.19
0.52
Abdo/Pelvis
120
200
613.8
9.21
0.92
Full body scan
120
250 with dose
950.9
14.26**
1.42
modulation
(scan length
107mm)
*Conversion factors: Head: 0.0021 & Abd/Pel: 0.015
** used conversion factor of abdo/pelvis: 0.015
++ calculated from mSv dose: 1mSv= 0.1rem
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Consider
Using the UMMC example, the radiation dose of a patient
who undergoes
– 11 follow up brain CT scans result in a dose of 22.33mSv
(2.23rem) in one month
– 9 follow up abdomen/pelvis CT scans over 3 months result in
a dose of approx 27.63mSv (2.76rem) in one month
CONSIDER:
According to the US Environmental Protection Agency
• Exposure from external exposure combined with
internal exposure is limited to an effective dose of 0.5
rem in one calendar year
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Reconstruction Background
Filtered back projection (FBP)
o Industry standard for CT image reconstruction for decades
o Fast and fairly robust method
o Sub-optimal algorithm choice for poorly sampled data or for cases where
noise overwhelms the image signal
Iterative reconstruction :
o Reconstruction as an optimization problem
 Noisiest measurements given low weight in the iterative process.
o Provides overall improvement of image quality at any given dose.
o Improvements in spatial & low-contrast resolution
o Artifact reduction
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CT reconstruction:
from Projections
to Image
CT
Reconstruction:
FBP vs.
Iterative Reconstruction
Radon Transform
Attenuation projections
Projection
Attenuation for 1 angle
Image
Attenuation of each voxel
y
0°
u
θ x
rotation
θ
Iθ
180°
u
u
I




 I  exp     (u, )dl   r
 l

 

0
Filtered Back Projection reconstruction (FBP)
Analytical solution to the problem of finding the
attenuation from the logarithmized acquisition readings.
?
y
x
 ( x, y )
Iterative reconstruction (IR)
Iterative statistical solution to the problem of finding
the attenuation (image) that is the “best fit” to the
acquired data.
When the noise dominates signal (e.g. low dose):
- Logarithm function not defined, hence artificial
values used.
High
noise
/ dose
- All projections
treated
equally
(corrupted & noncorrupted)
in streaks
in the images.
Spatialresulting
OR Contrast
Resolution
- “logarithmizing” yields a bias in estimates of lineintegrals, hence CT number shift in the central
part of the image.
A scheme where the probability term in projection
space and regularity term in the image space are
optimized either simultaneously or separately.
Low noise / dose
High
AND Contrast
Resolution
When
the Spatial
noise dominates
signal (e.g.
low dose) :
- The most noisy measurements are weighted low
in the iterative updates and therefore contribute
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very little to the final image.
iDose4 iterative reconstruction
technique
How it works
iDose4 uses the raw data output from the detectors
to determine & remove noise resulting from low dose scanning,
while preserving morphological information
Statistical
Noise
Model
Anatomical
Structures
Model
iDose4
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iDose4: How it works
Projection space
Image space
Optimizing image quality &
artifact prevention
Model based noise removal &
resolution improvement
Data dependant noise and structural models
used iteratively to eliminate the quantum image
noise while preserving the underlying edges
associated with changes in the anatomic
structure.
Noise power spectrum maintained through
dynamic frequency noise removal.
Data
variation
analysis
Model
selection
Multifrequency
Model
Based
noise
removal
Structure
(Anatomy)
Model
Acquisition
Noise Model
Update
projections
n
Model y
Optimized
?
Noise
optimization
•
• Each projection examined for points likely to
result from noisy measurements
• Iterative diffusion process where noisy data and
edges are differentiated - noisy data is penalized
and edges are preserved
•
• Prevents low signal streaks and bias errors.
Images
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