Utility of shape evolution and displacement in the classification of chronic multiple sclerosis lesions

Darin T. Okuda, Tatum M. Moog, Morgan McCreary, Jennifer N. Bachand, Andrew Wilson, Katy Wright, Mandy D. Winkler, Osniel Gonzalez Ramos, Aiden P. Blinn, Yeqi Wang, Thomas Stanley, Marco C. Pinho, Braeden D. Newton, Xiaohu Guo

Research output: Contribution to journalArticlepeer-review

6 Scopus citations


The accurate recognition of multiple sclerosis (MS) lesions is challenged by the high sensitivity and imperfect specificity of MRI. To examine whether longitudinal changes in volume, surface area, 3-dimensional (3D) displacement (i.e. change in lesion position), and 3D deformation (i.e. change in lesion shape) could inform on the origin of supratentorial brain lesions, we prospectively enrolled 23 patients with MS and 11 patients with small vessel disease (SVD) and performed standardized 3-T 3D brain MRI studies. Bayesian linear mixed effects regression models were constructed to evaluate associations between changes in lesion morphology and disease state. A total of 248 MS and 157 SVD lesions were studied. Individual MS lesions demonstrated significant decreases in volume < 3.75mm3 (p = 0.04), greater shifts in 3D displacement by 23.4% with increasing duration between MRI time points (p = 0.007), and greater transitions to a more non-spherical shape (p < 0.0001). If 62.2% of lesions within a given MRI study had a calculated theoretical radius > 2.49 based on deviation from a perfect 3D sphere, a 92.7% in-sample and 91.2% out-of-sample accuracy was identified for the diagnosis of MS. Longitudinal 3D shape evolution and displacement characteristics may improve lesion classification, adding to MRI techniques aimed at improving lesion specificity.

Original languageEnglish (US)
Article number19560
JournalScientific reports
Issue number1
StatePublished - Dec 2020

ASJC Scopus subject areas

  • General


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