Spinal cord imaging
Recent radiological advances in spinal cord imaging include: (1) Recommendations on standardised protocols for diagnosis, prognosis and monitoring of MS patients (2020 MAGNIMS-CMSC-NAIMS international consensus guidelines); (2) Recommendations on using spinal cord atrophy in clinical trials and clinical practice (2020 MAGNIMS consensus recommendations); (3) Development of registration-based methods, such as the generalized boundary shift integral (GBSI), to assess spinal cord atrophy, which show advantages when compared with segmentation-based methods; (4) Advanced, quantitative MRI and multi-modal imaging to assess spinal cord microstructural damage in MS; (5) Imaging assessment of the whole neuraxis (both spinal cord and brain) in order to understand the pathological changes that explain disability in MS.
In multiple sclerosis (MS), MRI measures at a whole and regional brain level have proven able to predict future disability, albeit to a limited degree. Their modest prognostic ability may reflect how cognitive and neurological functions are served by distributed networks rather than by single brain regions.
We aimed to identify data-driven MRI network-based measures of covarying gray matter (GM) volumes that can predict disability progression.
We used baseline MRI and longitudinal clinical data from 988 patients with secondary progressive MS (SPMS) from a randomized, double-blind, placebo-controlled, multicenter trial (ASCEND). We applied spatial-ICA to baseline structural GM probability maps to identify co-varying GM regions. We computed correlations between the loading of our ICA components and expanded disability status scale (EDSS), 9 hole peg test (9HPT), and symbol digit modalities test (SDMT) scores. We estimated the progression of the EDSS confirmed at 3 months, 6 months, and 1 year, and respectively the 20% and 10% worsening of 9HPT and SDMT. We used Cox proportional hazard models to determine the prognostic value of our ICA-components and conventional MRI measures (whole and deep GM volumes, and white matter lesion load).
We identified 15 networks of co-varying GM patterns that were clinically relevant. At baseline, SDMT and 9HPT scores correlated more strongly with ICA-components than the conventional MRI measures. The highest correlations were with a mainly basal ganglia component (encompassing the thalamus, caudate, putamen, frontal and temporal lobe). EDSS correlated more closely with an ICA-component involving cerebellum, brainstem, temporal and parietal lobes (r= -0.11, p<0.001). Prognostically, the baseline volume of caudate predicted EDSS progression confirmed at 3 months (HR= 0.81, 95%CI [0.68: 0.98], p<0.05), while some GM network-based measures outperformed conventional MRI measures in predicting SDMT and 9HPT worsening. SDMT progression was predicted by 6 ICA-components (component 8 (HR= 1.26, 95% CI [1.08-1.48], p< 0.005, and component 13 (HR= 1.25, 95% CI [1.07:1.46], p<0.005)). Two ICA-components were predictors of 9HPT worsening (HR=1.30, 95% CI [1.06:1.60], p<0.01; and HR= 1.21, 95%CI [1.01:1.45], p<0.05).
Data-driven MRI network-based measures of covarying GM volumes predict disability progression better than volumetric measures of GM and white matter lesion loads. ICA of MRI shows promise as a method that could enrich clinical MS studies with patients more likely to show a treatment response.
White matter (WM) microstructural changes occur in youth with multiple sclerosis (MS) and myelin oligodendrocyte glyoprotein (MOG)-associated disorders. While diffusion tensor imaging has been extensively used to characterize white matter, this method lacks microstructural and pathological specificity. ‘Fixel Based Analysis’ (FBA) statistically estimates changes in diffusion MRI connectivity that is specific to micro and macro-structure. WM damage that leads to less densely packed axons in a fiber bundle causes a decrease in fibre density (FD). If the number of axons is not reduced but occupies less area, then fibre cross-section (FC) will decrease. Last, if the density of axons within a fibre bundle and the area the bundle occupies are reduced, then fibre density and cross-section (FDC) will decrease.
To use whole-brain FBA to measure differences in FD, FC, FDC in youth with demyelinating syndromes compared to healthy controls.
We evaluated group differences in the FBA metrics between 28 typically developing children (17F; age 15.0±2.6y), 19 children with MS (13F; 16.9±1.1y; disease duration (DD)=0.1-11.7y; expanded disability status scale(EDSS):median=1.5,range=0-4.5), and 11 children with MOG (8F;12.1±2.8y; DD=0.5-6.4y;EDSS:m=1.0,r=0-3). Multi-shell diffusion-weighted imaging of the brain was acquired with echo planar imaging on a 3T MRI scanner and was pre-processed to correct for distortions and movement. Whole-brain group FBA was performed on FD, FC and FDC to test differences between groups adjusting for age, sex, total intracranial volume, EDSS and DD (p<0.05, family-wise error (FWE) corrected).
Participants with MS and MOG showed reduced FD, FC and FDC relative to typically developing children (FWE corrected p<0.05). Differences in FD were found within splenium, superior longitudinal fasciculus and optic radiations. MS patients had reduced FDC within the corticospinal tract and cerebellar peduncle compared to MOG patients. In participants with MS and MOG, decreased FD within the brain stem, cerebellar peduncles and corona radiata was associated with increased DD and EDSS.
Our preliminary findings showed that patients with demyelinating disorders display decreased axonal density and fibre bundle size in multiple WM tracts relative to typically developing children, which were related to clinical outcomes (EDSS, DD). These changes were more pronounced in MS compared to MOG participants in selected WM tracts.
Leptomeningeal inflammation (LMI) in multiple sclerosis (MS) can be putatively identified by leptomeningeal contrast enhancement (LMCE) on gadolinium-enhanced 3D T2-fluid attenuated inversion recovery (FLAIR) magnetic resonance (MR) images. Dura mater (DME), inclusive falx cerebri (FCE) enhancement and meningeal vessel wall enhancement (VWE) represent two other meningeal enhancement patterns in MS that have not been extensively studied.
To investigate the frequency of LMCE, DME/FCE and VWE in patients with MS and their associations with demographic, clinical and MRI characteristics in a longitudinal retrospective study.
217 MS patients (193 relapsing-remitting MS, 24 progressive MS) were assessed at baseline and over 18 months follow-up using 3T 3D FLAIR pre- and post-contrast and subtraction images. Lesion and brain volume outcomes were additionally calculated. Analysis of covariance (ANCOVA) and regression models were used to assess the relationship between MRI variables and clinical variables, controlling for age.
24% of MS patients revealed LMCE, and 47% and 24% revealed DME/FCE and VWE, respectively. LMCE presence correlated with age and higher ventricular cerebrospinal fluid (vCSF) volume. More LMCE positive subjects (38%) showed additional VWE, compared to LMCE negative subjects (20%, p=0.055). DME/FCE presence was associated with higher T1/T2 lesion load, higher vCSF volume and decreased total deep gray matter (GM) and hippocampus volumes. All three meningeal enhancement patterns showed a high persistence in shape and size at follow-up.
Different patterns of meningeal enhancement, i.e. LMCE, DME/FCE and VWE can be identified by gadolinium-enhanced 3D FLAIR MR imaging. LMCE positive patients show a trend for higher frequency of VWE than LMCE negative patients. DME/FCE is the most frequent meningeal enhancement pattern in MS, which correlates with imaging markers of lesion burden and brain atrophy and may indicate abnormal lymphatic drainage in these patients.