High-resolution diffusion tensor imaging of the fornix predicts memory function in multiple sclerosis

Katherine A Koenig; Ken E Sakaie; Daniel Ontaneda; Kedar R Mahajan; Se-Hong Oh; Kunio Nakamura; Stephen E Jones; Stephen M Rao; Mark J Lowe

doi:10.1177/20552173241240937

High-resolution diffusion tensor imaging of the fornix predicts memory function in multiple sclerosis

Mult Scler J Exp Transl Clin. 2024 May 6;10(2):20552173241240937. doi: 10.1177/20552173241240937. eCollection 2024 Apr-Jun.

Authors

Katherine A Koenig, Ken E Sakaie¹, Daniel Ontaneda, Kedar R Mahajan², Se-Hong Oh^{1

3}, Kunio Nakamura⁴, Stephen E Jones¹, Stephen M Rao⁵, Mark J Lowe¹

Affiliations

¹ Imaging Sciences, Imaging Institute, Cleveland Clinic, Cleveland, USA.
² Mellen Center, Neurological Institute, Cleveland Clinic, Cleveland, USA.
³ Department of Biomedical Engineering, Hankuk University of Foreign Studies, Yongin, Republic of Korea.
⁴ Department of Biomedical Engineering, Lerner Research Institute, Cleveland Clinic, Cleveland, USA.
⁵ Schey Center for Cognitive Neuroimaging, Neurological Institute, Cleveland Clinic, Cleveland, USA.

Abstract

Background: Cognitive dysfunction is a known symptom of multiple sclerosis (MS), with memory recognized as a frequently impacted domain. Here, we used high-resolution MRI at 7 tesla to build on cross-sectional work by evaluating the longitudinal relationship of diffusion tensor imaging (DTI) measures of the fornix to episodic memory performance.

Methods: A sample of 80 people with multiple sclerosis (mean age 51.9 ± 8.1 years; 24% male) underwent baseline clinical evaluation, neuropsychological assessment, and MRI. Sixty-four participants had follow-up neuropsychological testing after 1-2 years. Linear regression was used to assess the relationship of baseline imaging measures to follow-up episodic memory performance, measured using the Selective Reminding Test and Brief Visuospatial Memory Test. A reduced prediction model included cognitive function at baseline, age, sex, and disease course.

Results: Radial (β = -0.222, p < 0.026; likelihood ratio test (LRT) p < 0.018), axial (β = -0.270, p < 0.005; LRT p < 0.003), and mean (β = -0.242, p < 0.0139; LRT p < 0.009) diffusivity of the fornix significantly added to the model, with follow-up analysis indicating that a longer prediction interval may increase accuracy.

Conclusion: These results suggest that fornix DTI has predictive value specific to memory function in MS and warrants additional investigation in the drive to develop predictors of disease progression.

Keywords: Multiple sclerosis; biomarkers; cognitive dysfunction; diffusion tensor imaging; magnetic resonance imaging; memory.