Diffusion tensor imaging for characterizing white matter changes in multiple sclerosis

• Main Authors: Rasha Elshafey, Omar Hassanien, Mohamed Khalil
• Format: Article
• Language: English
• Published: SpringerOpen 2014-09-01
• Series: The Egyptian Journal of Radiology and Nuclear Medicine
• Subjects: Diffusion tensor imaging; Multiple sclerosis
• Online Access: http://www.sciencedirect.com/science/article/pii/S0378603X14000680

Purpose: To investigate the diagnostic values of quantitative diffusion tensor imaging parameters in detecting abnormalities in white matter of MS patients and correlate this with lesion load and clinical disability as prognostic factors. Patients and methods: Diffusion tensor imaging (DTI) was performed in 45 consecutive MS patients and 20 age-matched healthy control volunteers from March 2011 to November 2013. Mean diffusivity (MD), volume ratio (VR) and the fractional anisotropy (FA) were measured in normal appearing white matter (NAWM) and in different types of focal MS lesions during both activity and remission and compared with normal white matter (NWM) of the control group. Evaluation of lesion load was done by the semiautomated method. Clinical assessment of MS was established using the Kurtzke expanded disability status scale (EDSS) and the Kurtzke functional system score. Results: Significant increase of MD and decrease of FA and VR from normal appearing white matter of the patients to MRI detected active lesions and the least is inactive plaques comparing with NWM of the control group (P value 0.003 for MD, 0.013 for FA, and 0.014 for VR). Correlation and significant difference between {(increase in MD) and (decrease in FA and VR)} and lesion load (strongest in parietal lobes) and also Kurtzke expanded disability status scale (EDSS) and Kurtzke functional system score (KFS-p). Conclusion: DTI–MRI quantitative parameters are good predictors of tissue damage not only in MRI-defined lesions but also in NAWM as a result of Wallerian degeneration and are helpful as diagnostic and prognostic tools.