Spinal cord volume quantification and clinical application in multiple sclerosis

Tsagkas, Charidimos. Spinal cord volume quantification and clinical application in multiple sclerosis. 2019, Doctoral Thesis, University of Basel, Faculty of Medicine.


Official URL: http://edoc.unibas.ch/diss/DissB_13325

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Magnetic resonance imaging of the spinal cord is a valuable part of the diagnostic work-up in patients with multiple sclerosis and other neurological disorders. Currently, mainly signal intensity changes within the cord in MR-images are considered in the clinical management of disorders of the central nervous system. However, cross-sectional or longitudinal measurements of spinal cord volume may deliver additional valuable information. Hence, the overall goal of this doctoral thesis was twofold: i) to clinically validate methods for quantification of spinal cord volume and spinal cord compartments, which are suitable for longitudinal assessment of large patient cohorts and clinical practice and ii) to evaluate spinal cord volume as a potential valuable biomarker and provide new insights into the role of spinal cord damage in multiple sclerosis.
The first part focuses on the validation of quantification methods for spinal cord volume and includes two projects. While several MRI-based approaches of semi- and fully automatic techniques for volumetric spinal cord measurements have been proposed, up to now no gold standard exists and only a few methods have been validated and/or evaluated on patient follow-up scans to demonstrate their applicability in longitudinal settings. One of the latter segmentation methods was recently developed in-house and showed excellent reliability for cervical cord segmentation (Cordial, the cord image analyzer). In a first project, we extended its applicability to the lumbar cord, since no other software has been tested so far within this anatomical region of interest. On a well-selected dataset of 10 healthy controls (scanned in a scan-rescan fashion) we were able to show that - even within this technically challenging region - this segmentation algorithm provides excellent inter- and intra-session reproducibility showing high potential for application in longitudinal trials. In a second project, we aimed at obtaining volumetric information on particular compartments of the spinal cord such as the cord grey and white matter, since recent studies in multiple sclerosis provided evidence that measuring spinal cord grey matter volume changes may be a better biomarker for disease progression than quantifying cord white matter pathology or even volumetric brain measures. We therefore implemented a novel imaging approach, the averaged magnetization inversion recovery acquisitions sequence, for better grey and white matter visualization within the cord and scanned 24 healthy controls in a scan-rescan fashion. Further we applied an innovative fully automatic variational segmentation algorithm with a shape prior modified for 3D data with a slice similarity prior to segment the spinal cord grey and white matter. This pipeline allowed for highly accurate and reproducible grey and white matter segmentation within the cord. In view of its features, our automatic segmentation method seems promising for further application in both cross-sectional and longitudinal and in large multi-center studies.
The second goal of this thesis was the clinical application of the above-mentioned methods for the evaluation of spinal cord volume changes as a potential biomarker in multiple sclerosis patients. For this purpose, we quantified spinal cord volume change in a large cohort of 243 multiple sclerosis patients, followed over a period of 6 years with annual clinical and MRI examinations. Spinal cord volume proved to be a strong predictor of physical disability and disease progression, indicating that it may be a suitable marker for monitoring disease activity and severity in all disease types but especially in progressive multiple sclerosis. Spinal cord volume also proved to be the only MRI metric to strongly explain the clinical progression over time as opposed to brain atrophy and lesion measures.
Advisors:Kappos, Ludwig and Cattin, Philippe and Parmar, Katrin and Wattjes, Mike Peter
Faculties and Departments:03 Faculty of Medicine > Bereich Medizinische Fächer (Klinik) > Neurologie > Neuroimmunologie (Kappos)
03 Faculty of Medicine > Departement Klinische Forschung > Bereich Medizinische Fächer (Klinik) > Neurologie > Neuroimmunologie (Kappos)
UniBasel Contributors:Kappos, Ludwig
Item Type:Thesis
Thesis Subtype:Doctoral Thesis
Thesis no:13325
Thesis status:Complete
Number of Pages:1 Online-Ressource (125 Seiten)
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edoc DOI:
Last Modified:19 Nov 2019 05:30
Deposited On:18 Nov 2019 13:45

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