Download Quantitative STIR MRI as prognostic imaging biomarker for

Survey
yes no Was this document useful for you?
   Thank you for your participation!

* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project

Document related concepts

Medical imaging wikipedia , lookup

Transcript
University of Groningen
Quantitative STIR MRI as prognostic imaging biomarker for nerve regeneration
Viddeleer, Alain
IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to
cite from it. Please check the document version below.
Document Version
Publisher's PDF, also known as Version of record
Publication date:
2016
Link to publication in University of Groningen/UMCG research database
Citation for published version (APA):
Viddeleer, A. R. (2016). Quantitative STIR MRI as prognostic imaging biomarker for nerve regeneration
[Groningen]: Rijksuniversiteit Groningen
Copyright
Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the
author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons).
Take-down policy
If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately
and investigate your claim.
Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons the
number of authors shown on this cover page is limited to 10 maximum.
Download date: 12-08-2017
Summary
121
Chapter 7
Summary
Nerve transection induced by traumatic forearm injury, has tremendous impact on a patient’s daily life, due to paralyzed hand muscles and sensory loss.
Although surgical repair of the transected nerve is possible, more than half
of the patients have permanent nerve dysfunction. Numerous axons have to
sprout from the proximal nerve end and grow into the distal nerve stump.
This process can be hindered however, for instance if the nerve ends are not
exactly aligned, if scar tissue forms between the nerve ends or if vascularisation is suboptimal. If nerve regeneration fails, a reoperation may be attempted, in which scar tissue between the nerve ends is resected and the
nerve ends are re-attached by sutures. It is known that chances of success of
such a re-operation are best within the first six months after initial trauma, as
the distal nerve end slowly degenerates, making it increasingly difficult for
axons to grow into this nerve stump.
Therefore, after surgical nerve repair it is of utmost importance to monitor
whether axons grow towards the hand muscles, to be able to intervene if
necessary. The current method of choice for monitoring is electromyography
(EMG), in which electrode are attached over the nerves or needle-electrodes
are inserted in muscles. Such an EMG examination is often painful for the patient, is time-consuming and the results can be influenced by several factors,
for instance temperature. Therefore new, objective, and more patient-friendly
methods are needed to monitor nerve regeneration over time. The purpose of
the research described in this thesis is to investigate whether magnetic resonance imaging (MRI) scans of intrinsic hand muscles can be used for this purpose. It is known that denervated muscles display higher signal intensities.
By comparing these intensities over time, and relate them to healthy muscle,
it may become possible to determine whether muscles are re-connected to the
nerves or whether a permanent block persists.
In this thesis first the reproduciblity of MRI signal intensities measured over
122
Chapter 7. Summary
time is investigated, by comparing signal intensities of several calibration
tubes filled with different fluids over a period of several years. It was found
that MRI scans, after correction for a number of influences, are suitable for
comparing signal intensities over time (Chapter 2). Furthermore, it was examined if the signal intensity of non-denervated muscle is influenced by for
instance wound edema, as this may distort the comparison of denervated and
non-denervated muscle. No influence was found after six months (Chapter
3). Next, muscle signal intensity changes over time were investigated in patients with a nerve transection. It was found that in patients with poor recovery, signal intensity remains elevated for at least one year, while in patient
with good function recovery the muscle signal intensities returned to normal
(Chapters 4 and 5).
In conclusion, MRI scans can be used as a new, objective method for monitoring nerve regeneration and show differences between affected and healthy
muscle for at least one year.