Quantifying disease pathology and predicting disease progression in multiple sclerosis with only clinical routine T2-FLAIR MRI

Tom A Fuchs; Michael G Dwyer; Dejan Jakimovski; Niels Bergsland; Deepa P Ramasamy; Bianca Weinstock-Guttman; Ralph Hb Benedict; Robert Zivadinov

doi:10.1016/j.nicl.2021.102705

Quantifying disease pathology and predicting disease progression in multiple sclerosis with only clinical routine T2-FLAIR MRI

Neuroimage Clin. 2021:31:102705. doi: 10.1016/j.nicl.2021.102705. Epub 2021 May 24.

Authors

Tom A Fuchs¹, Michael G Dwyer², Dejan Jakimovski³, Niels Bergsland⁴, Deepa P Ramasamy³, Bianca Weinstock-Guttman⁵, Ralph Hb Benedict⁵, Robert Zivadinov⁶

Affiliations

¹ Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA; Jacobs Multiple Sclerosis Center, Department of Neurology, School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.
² Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA; Center for Biomedical Imaging at Clinical Translational Science Institute, University at Buffalo, State University of New York, Buffalo, NY, USA.
³ Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.
⁴ Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA; IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy.
⁵ Jacobs Multiple Sclerosis Center, Department of Neurology, School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA.
⁶ Buffalo Neuroimaging Analysis Center, Department of Neurology, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, State University of New York, Buffalo, NY, USA; IRCCS, Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy. Electronic address: rzivadinov@bnac.net.

Abstract

Background: Although quantitative measures from research-quality MRI provide a means to study multiple sclerosis (MS) pathology in vivo, these metrics are often unavailable in legacy clinical datasets.

Objective: To determine how well an automatically-generated quantitative snapshot of brain pathology, measured only on clinical routine T2-FLAIR MRI, can substitute for more conventional measures on research MRI in terms of capturing multi-factorial disease pathology and providing similar clinical relevance.

Methods: MRI with both research-quality sequences and conventional clinical T2-FLAIR was acquired for 172 MS patients at baseline, and neurologic disability was assessed at baseline and five-years later. Five measures (thalamus volume, lateral ventricle volume, medulla oblongata volume, lesion volume, and network efficiency) for quantifying disparate aspects of neuropathology from low-resolution T2-FLAIR were applied to predict standard research-quality MRI measures. They were compared in regard to association with future neurologic disability and disease progression over five years.

Results: The combination of the five T2-FLAIR measures explained most of the variance in standard research-quality MRI. T2-FLAIR measures were associated with neurologic disability and cognitive function five-years later (R² = 0.279, p < 0.001; R² = 0.382, p < 0.001), similar to standard research-quality MRI (R² = 0.279, p < 0.001; R² = 0.366, p < 0.001). They also similarly predicted disability progression over five years (%-correctly-classified = 69.8, p = 0.034), compared to standard research-quality MRI (%-correctly-classified = 72.4%, p = 0.022) in relapsing-remitting MS.

Conclusion: A set of five T2-FLAIR-only measures can substitute for standard research-quality MRI, especially in relapsing-remitting MS. When only clinical T2-FLAIR is available, it can be used to obtain substantially more quantitative information about brain pathology and disability than is currently standard practice.

Keywords: Disability progression; MRI; Multiple sclerosis; Predictivity; Quantifying pathology; T2-FLAIR.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Atrophy / pathology
Brain / diagnostic imaging
Brain / pathology
Disease Progression
Humans
Magnetic Resonance Imaging
Multiple Sclerosis* / diagnostic imaging
Multiple Sclerosis* / pathology
Multiple Sclerosis, Relapsing-Remitting* / pathology

Grants and funding

UL1 TR001412/TR/NCATS NIH HHS/United States