Abstract

To compare the signal alterations of amide proton transfer (APT), apparent diffusion coefficient (ADC), and fractional anisotropy (FA) in white matter (WM) lesions in multiple sclerosis (MS), compared with healthy controls (HCs), and to investigate the relationships between these changes and clinical measurements such as serum neurofilament light chain (sNfL). Twenty-nine patients with relapsing-remitting MS (21 females and 8 males) and 30 HCs (23 females and 7 males) were recruited. APT-weighted (APTw) and diffusion tensor imaging (DTI) data were acquired using a 3.0-T magnetic resonance system. APTw and DTI images were registered to FLAIR-SPIR images and assessed by two neuroradiologists. MTRasym (3.5 ppm), ADC, FA values for MS and HC are calculated using mean values from all regions of interest (ROI). The ROI criteria were: (1) for MS patients, ROI were defined as MS lesions, and each lesion was identified. (2) The WM around each HC's lateral ventricle (frontal lobe, parietal lobe, and centrum semiovale) was assessed bilaterally. The diagnostic efficacy of MTRasym (3.5 ppm), ADC, and FA in the lesions of MS patients was compared using receiver operating characteristic (ROC) curve analysis. The associations between MTRasym (3.5 ppm), ADC, and FA values and the clinical measurements were investigated further. The MTRasym (3.5 ppm) and ADC values of brain lesions were increased, while FA values were decreased in patients with MS. The diagnostic area under curve (AUC) of MTRasym (3.5 ppm), ADC, and FA value was 0.891 (95% CI: 0.813, 0.970), 0.761 (95% CI: 0.647, 0.875) and 0.970 (95% CI: 0.924, 1.0), respectively. sNfL was considerably positively correlated with MTRasym (3.5 ppm) (P = 0.043, R = 0.38) and disease durations were significantly negatively correlated with FA (P = 0.046, R = -0.37). Amide proton transfer-weighted (APTw) and DTI are potential imaging methods for assessing brain lesions in patients with MS at the molecular and microscopic levels, respectively. The association between APTw, DTI parameters and clinical factors implies that they may play a role in disease damage monitoring.

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