Dataset Information

Confounder-adjusted MRI-based predictors of multiple sclerosis disability.

ABSTRACT:

Introduction

Both aging and multiple sclerosis (MS) cause central nervous system (CNS) atrophy. Excess brain atrophy in MS has been interpreted as "accelerated aging." Current paper tests an alternative hypothesis: MS causes CNS atrophy by mechanism(s) different from physiological aging. Thus, subtracting effects of physiological confounders on CNS structures would isolate MS-specific effects.

Methods

Standardized brain MRI and neurological examination were acquired prospectively in 646 participants enrolled in ClinicalTrials.gov Identifier: NCT00794352 protocol. CNS volumes were measured retrospectively, by automated Lesion-TOADS algorithm and by Spinal Cord Toolbox, in a blinded fashion. Physiological confounders identified in 80 healthy volunteers were regressed out by stepwise multiple linear regression. MS specificity of confounder-adjusted MRI features was assessed in non-MS cohort (n = 158). MS patients were randomly split into training (n = 277) and validation (n = 131) cohorts. Gradient boosting machine (GBM) models were generated in MS training cohort from unadjusted and confounder-adjusted CNS volumes against four disability scales.

Results

Confounder adjustment highlighted MS-specific progressive loss of CNS white matter. GBM model performance decreased substantially from training to cross-validation, to independent validation cohorts, but all models predicted cognitive and physical disability with low p-values and effect sizes that outperform published literature based on recent meta-analysis. Models built from confounder-adjusted MRI predictors outperformed models from unadjusted predictors in the validation cohort.

Conclusion

GBM models from confounder-adjusted volumetric MRI features reflect MS-specific CNS injury, and due to stronger correlation with clinical outcomes compared to brain atrophy these models should be explored in future MS clinical trials.

SUBMITTER: Kim Y

PROVIDER: S-EPMC10365278 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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Publications

Confounder-adjusted MRI-based predictors of multiple sclerosis disability.

Kim Yujin Y Varosanec Mihael M Kosa Peter P Bielekova Bibiana B

Frontiers in radiology 20220913

<h4>Introduction</h4>Both aging and multiple sclerosis (MS) cause central nervous system (CNS) atrophy. Excess brain atrophy in MS has been interpreted as "accelerated aging." Current paper tests an alternative hypothesis: MS causes CNS atrophy by mechanism(s) different from physiological aging. Thus, subtracting effects of physiological confounders on CNS structures would isolate MS-specific effects.<h4>Methods</h4>Standardized brain MRI and neurological examination were acquired prospectively ...[more]

PMID: 37492673

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Project description:Next to the disseminated clinical symptoms, cognitive dysfunctions are common features of multiple sclerosis (MS). Over the recent years several different MRI measures became available representing the various features of the pathology, but the contribution to various clinical and cognitive functions is not yet fully understood. In this multiparametric MRI study we set out to identify the set of parameters that best predict the clinical and cognitive disability in MS. High resolution T1 weighted structural and high angular resolution diffusion MRI images were measured in 53 patients with relapsing remitting MS and 53 healthy controls. Clinical disability was inflicted by EDSS and cognitive functions were evaluated with the BICAMS tests. The contribution of lesion load, partial brain, white matter, gray matter and subcortical volumes as well as the diffusion parameters in the area of the lesions and the normal appearing white matter were examined by model free, partial least square (PLS) approach. Significance of the predictors was tested with Variable Importance in the Projection (VIP) score and 1 was used for threshold of significance. The PLS analysis indicated that the axial diffusivity of the NAWM contributed the most to the clinical disability (VIP score: 1.979). For the visuo-spatial working memory the most critical contributor was the size of the bilateral hippocampi (VIP scores: 1.183 and 1.2 left and right respectively). For the verbal memory the best predictors were the size of the right hippocampus (VIP score: 1.972), lesion load (VIP score: 1.274) and the partial brain volume (VIP score: 1.119). In case of the information processing speed the most significant contribution was from the diffusion parameters (fractional anisotropy, mean and radial diffusivity, VIP scores: 1.615, 1.321 respectively) of the normal appearing white matter. Our results indicate that various MRI measurable factors of MS pathology contribute differently to clinical and cognitive disability. These results point out the importance of the volumetry of the subcortical structures and the diffusion measures of the white matter in understanding the disability progression.

Dataset Information

Confounder-adjusted MRI-based predictors of multiple sclerosis disability.

Introduction

Methods

Results

Conclusion

Publications

Confounder-adjusted MRI-based predictors of multiple sclerosis disability.

Similar Datasets

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