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Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
Non-lesional white matter changes depicted by q-space diffusional MRI correlate with clinical disabilities in
Haruhiko Motegi1, Kenji Kufukihara2, Satoshi Kitagawa3
1Department of Neurology, Keio University School of Medicine, Tokyo, Japan; Department of Neurology, The Jikei University School of Medicine, Tokyo, Japan.
Background:
We previously developed an optimized q-space diffusional MRI technique (normalized leptokurtic diffusion [NLD] map) to delineate the demyelinated lesions of multiple sclerosis (MS) patients. Herein, we evaluated the utility of NLD maps to discern the white matter abnormalities in normal-appearing white matter (NAWM) and the abnormalities' possible associations with physical and cognitive disabilities in MS.
Methods:
We conducted a retrospective observational study of MS patients treated at our hospital (Jan. 2012 to Dec. 2022). Clinical and MRI data were collected; Processing Speed Test (PST) data were obtained when possible. For a quantitative analysis of the NLD maps, we calculated the NLD index as GVROI/GVREF, where GV is a mean grayscale value in the regions of interest (ROIs) and the reference area (REF; cerebrospinal fluid).
Results:
One hundred-one individuals with MS were included. The lower corpus callosum and non-lesional WM NLD index were associated with worse Expanded Disability Status Scale (EDSS) and PST scores. The NLD indexes in the corpus callosum (p < 0.0001) and non-lesional white matter (p < 0.0001) were significantly reduced in progressive MS compared to relapsing-remitting MS. We categorized MS severity as moderate/severe (EDSS score ≥ 4 points) and mild (EDSS score < 4 points). The NLD indexes in the corpus callosum (p < 0.0001) and non-lesional white matter (p < 0.0001) were significantly lower in the moderate/severe MS group compared to the mild MS group.
Conclusion:
The NLD map revealed abnormalities in the non-lesional white matter, providing valuable insights for evaluating manifestations in MS patients.

