Clinical correlations of brain lesion distribution in multiple sclerosis

Abstract

Purpose: To explore relations between spatial distribution of multiple sclerosis (MS) lesions, and disability. In MS, the presence of asymptomatic brain lesions challenges the prediction of disability based on conventional brain MRI. Hypothesizing that symptomatology may partly be determined by lesion location, this retrospective study explored relations between lesion location and disability using voxelwise analyses in standard space. Materials and Methods:Using nonparametric permutation-based statistics, voxelwise lesion probability on T2 lesion masks was related to expanded disability status scale (EDSS) and MS functional composite (MSFC) subdomain scores and demographic characteristics of 325 MS patients. To identify statistically significant locations, a cluster-forming threshold of 3.1 was used. Results:In clusters in the periventricular region, lesion probability correlated significantly (P Ͻ 0.001) with disability and disease duration, and was higher in progressive than in relapsing disease. When controlled for lesion load (LL), no significant clusters survived. Presence and number of spinal cord lesions did not correlate with lesion probability in any location, and did not influence correlations with disability when included in its analyses.Conclusion: Periventricular lesions were related to disability. LL influenced relations between disability and lesion probability throughout the brain, suggesting interplay between lesional burden and its location in determining disability in MS.

Use of Magnetic Resonance Imaging as Well as Clinical Disease Activity in the Clinical Classification of Multiple Sclerosis and Assessment of Its Course

“…[25][26][27][28] This may be explained at least in part by several factors: lesions in "eloquent" brain areas such as the optic nerves are more likely to be clinically expressed than lesions in less eloquent pathways; the degree of matrix and axonal destruction may vary; and the potential exists for rapid symptom recovery. [29][30][31][32][33][34][35][36][37][38] Even patients with progressive forms of MS, particularly those with Gd+ lesions indicating a subclinical relapse, may respond clinically to disease-modifying therapies (DMTs). For example, in a post hoc analysis of the Olympus trial of rituximab in PPMS, patients with Gd+ lesions had a significantly better response to treatment than those without Gd+ lesions.…”

Genetic Correlations of Brain Lesion Distribution in Multiple Sclerosis: An Exploratory Study

“…Total brain lesion volume seems to be an important covariate in LPM analyses. 7 Apart from the left frontal horn cluster in rs2227139, no clusters retained significance when the model was controlled for lesion volume. Thus, the influence of genetic background on spatial lesion distribution, as assessed in the current study, may partly act through total brain lesion volume and come to expression in voxelwise analyses, especially in regions with relatively high frequencies of MS lesions, where differences among groups can become statistically significant (ie, the periventricular white matter).…”

“…Because total brain lesion volume has been found to influence lesion distribution, 7 we took the following 2 steps: First, for genotypes showing significant clusters in the LPM analyses, these LPM analyses were repeated while statistically controlling for total brain lesion volume. Second, we investigated the effect of genotype on the total brain lesion volume at a patient level by directly comparing the total brain lesion volume among genotypes, while statistically controlling for disease duration (without taking anatomic distribution into account).…”

“…The selected patients are a subgroup of those in whom the clinical correlates of brain lesion distribution were studied previously. 7 All had a diagnosis of MS according to the Poser criteria, 24 McDonald criteria, 25 or revised McDonald criteria, 26 depending on the date of data acquisition. EDSS 27 scores were obtained within a median interval of 0.0 (IQR, 0.0 -4.8) months from MR imaging.…”

“…This voxelwise method does not require a priori assumptions. Previous studies have shown differences in lesion distribution across disease subtypes and disability status, [5][6][7] as well as among different lesion subtypes: T1 gadolinium-enhancing lesions showed a spatial distribution differing from nonenhancing T2 lesions and from T1 hypointense lesions (black holes). 8,9 We hypothesized that spatial lesion distribution might depend on individual immunogenetic background.…”