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Matthias Bussas

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3 papers

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YNICL Journal 2023 Journal Article

Lesion location across diagnostic regions in multiple sclerosis

Viola Pongratz
Matthias Bussas
Paul Schmidt
Sophia Grahl
Christiane Gasperi
Malek El Husseini
Laura Harabacz
Viktor Pineker

BACKGROUND: Lesions in the periventricular, (juxta)cortical, and infratentorial region, as visible on brain MRI, are part of the diagnostic criteria for Multiple sclerosis (MS) whereas lesions in the subcortical region are currently only a marker of disease activity. It is unknown whether MS lesions follow individual spatial patterns or whether they occur in a random manner across diagnostic regions. AIM: First, to describe cross-sectionally the spatial lesion patterns in patients with MS. Second, to investigate the spatial association of new lesions and lesions at baseline across diagnostic regions. METHODS: Experienced neuroradiologists analyzed brain MRI (3D, 3T) in a cohort of 330 early MS patients. Lesions at baseline and new solitary lesions after two years were segmented (manually and by consensus) and classified as periventricular, (juxta)cortical, or infratentorial (diagnostic regions) or subcortical-with or without Gadolinium-enhancement. Gadolinium enhancement of lesions in the different regions was compared by Chi square test. New lesions in the four regions served as dependent variable in four zero-inflated Poisson models each with the six independent variables of lesions in the four regions at baseline, age and gender. RESULTS: At baseline, lesions were most often observed in the subcortical region (mean 13.0 lesions/patient), while lesion volume was highest in the periventricular region (mean 2287 µl/patient). Subcortical lesions were less likely to show gadolinium enhancement (3.1 %) than juxtacortical (4.3 %), periventricular (5.3 %) or infratentorial lesions (7.2 %). Age was inversely correlated with new periventricular, juxtacortical and subcortical lesions. New lesions in the periventricular, juxtacortical and infratentorial region showed a significant autocorrelative behavior being positively related to the number of lesions in the respective regions at baseline. New lesions in the subcortical region showed a different behavior with a positive association with baseline periventricular lesions and a negative association with baseline infratentorial lesions. CONCLUSION: Across regions, new lesions do not occur randomly; instead, new lesions in the periventricular, juxtacortical and infratentorial diagnostic region are associated with that at baseline. Lesions in the subcortical regions are more closely related to periventricular lesions. Moreover, subcortical lesions substantially contribute to lesion burden in MS but are less likely to show gadolinium enhancement (than lesions in the diagnostic regions).

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YNICL Journal 2022 Journal Article

Multiple sclerosis lesions and atrophy in the spinal cord: Distribution across vertebral levels and correlation with disability

Matthias Bussas
Malek El Husseini
Laura Harabacz
Viktor Pineker
Sophia Grahl
Viola Pongratz
Achim Berthele
Isabelle Riederer

BACKGROUND: The vast majority of magnetic resonance imaging (MRI) studies on multiple sclerosis (MS) covered the spinal cord (SC), if at all, incompletely. OBJECTIVE: To assess SC involvement in MS, as detectable by whole SC MRI, with regard to distribution across vertebral levels and relation to clinical phenotypes and disability. METHODS: We investigated SC MRI with sagittal and axial coverage. Analyzed were brain and SC MRI scans of 17 healthy controls (HC) and of 370 patients with either clinically isolated syndrome (CIS, 27), relapsing remitting MS (RRMS, 303) or progressive MS (PMS, 40). Across vertebral levels, cross-sectional areas were semiautomatically segmented, and lesions manually delineated. RESULTS: The frequency of SC lesions was highest at the level C3-4. The volume of SC lesions increased from CIS to RRMS, and from RRMS to PMS whereas lesion distribution across SC levels did not differ. SC atrophy was demonstrated in RRMS and, to a higher degree, in PMS; apart from an accentuation at the level C3-4, it was evenly distributed across SC levels. SC lesions and atrophy volume were not correlated with each other and were independently associated with disability. CONCLUSION: SC lesions and atrophy already exist at the stage of RRMS in the whole SC with an accentuation in the cervical enlargement; SC lesions and atrophy are more pronounced in the stage of PMS. Both contribute to the clinical picture but are largely independent.

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YNICL Journal 2019 Journal Article

Automated segmentation of changes in FLAIR-hyperintense white matter lesions in multiple sclerosis on serial magnetic resonance imaging

Paul Schmidt
Viola Pongratz
Pascal Küster
Dominik Meier
Jens Wuerfel
Carsten Lukas
Barbara Bellenberg
Frauke Zipp

Longitudinal analysis of white matter lesion changes on serial MRI has become an important parameter to study diseases with white-matter lesions. Here, we build on earlier work on cross-sectional lesion segmentation; we present a fully automatic pipeline for serial analysis of FLAIR-hyperintense white matter lesions. Our algorithm requires three-dimensional gradient echo T1- and FLAIR- weighted images at 3 Tesla as well as available cross-sectional lesion segmentations of both time points. Preprocessing steps include lesion filling and intrasubject registration. For segmentation of lesion changes, initial lesion maps of different time points are fused; herein changes in intensity are analyzed at the voxel level. Significance of lesion change is estimated by comparison with the difference distribution of FLAIR intensities within normal appearing white matter. The method is validated on MRI data of two time points from 40 subjects with multiple sclerosis derived from two different scanners (20 subjects per scanner). Manual segmentation of lesion increases served as gold standard. Across all lesion increases, voxel-wise Dice coefficient (0.7) as well as lesion-wise detection rate (0.8) and false-discovery rate (0.2) indicate good overall performance. Analysis of scans from a repositioning experiment in a single patient with multiple sclerosis did not yield a single false positive lesion. We also introduce the lesion change plot as a descriptive tool for the lesion change of individual patients with regard to both number and volume. An open source implementation of the algorithm is available at http://www.statistical-modeling.de/lst.html.

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