Deep gray matter changes in relapsing-remitting multiple sclerosis detected by multi-parametric, high-resolution magnetic resonance imaging (MRI).

OBJECTIVES: To investigate a variety of magnetic resonance imaging (MRI) quantitative metrics, which reflect different aspects of microstructural damage in deep gray matter (dGM) regions and white matter T2 lesions in patients with relapsing-remitting multiple sclerosis (RRMS), and to determine the level of pathological interconnection between these two entities as well as their association with clinical disability. METHODS: We recruited thirty RRMS patients along with thirty age-matched healthy controls (HCs). Both groups were scanned at 3 T MRI using 3D high-resolution T1-, T2-, and T2*-weighted, magnetization transfer (MT)-prepared gradient echo for MT ratio (MTR) mapping, and eight repeats of T1-weighted images acquired at different inversion times to create T1 maps. dGM structures were segmented from T1-weighted images using FreeSurfer, WM-T2 lesions were extracted from T2-weighted images, and iron maps were calculated from the phase part of the T2*-weighted sequence. Extracted dGM MRI indices were compared between both groups. In the RRMS group, dGM MRI indices were correlated with those of WM-T2 lesions, expanded disability status scale, and disease duration. RESULTS: dGM volumetric metrics of RRMS patients were significantly (p < 0.01) smaller than those of HCs and showed a significant moderate association with lesions' load (p < 0.05) and lesions' iron concentration (p < 0.01). dGM MTRs of RRMS patients were significantly (p < 0.01) smaller than those of HCs and showed a significant (p < 0.01) moderate correlation with lesion T1 times. While T1 changes in some dGM regions of RRMS patients associated weakly with those of T2 lesions, dGM iron concentration did not show any association with any of lesions' metrics. Furthermore, lesions' MTR changes did not show any association with any dGM metrics. Most dGM metrics did not show any correlation with disease severity. Contrarily, most lesions' metrics showed weak association with disease severity. CONCLUSIONS: dGM changes occur in a non-uniform pattern and, almost, do not link directly to MS disease severity. Contrarily, most WM-T2 lesions' metrics tend to correlate with MS disease severity better than those of dGM. KEY POINTS: • Deep gray matter (dGM) structures are very much involved in the MS disease process and quite substantial neurodegeneration is undergone during the relapsing-remitting phase of the MS disease. • Deep gray matter (dGM) quantitative changes occur in a non-uniform and non-linked pattern and, except for CN's iron deposition, do not directly associate with the MS disease severity. • Most white matter T2 lesions' metrics tend to correlate with MS disease severity better than those of dGM structures.

Cortical and Subcortical Morphometric and Iron Changes in Relapsing-Remitting Multiple Sclerosis and Their Association with White Matter T2 Lesion Load : A 3-Tesla Magnetic Resonance Imaging Study.

INTRODUCTION: This study was carried out to investigate the global and regional morphometric and iron changes in grey matter (GM) of multiple sclerosis (MS) patients and link them to the white matter (WM) lesions in a multimodal magnetic resonance imaging approach. MATERIAL AND METHODS: The study involved 30 relapsing-remitting MS (RRMS) patients along with 30 age-matched healthy controls (HC) who were scanned on a 3T Siemens Trio system. The scanning protocol included a 3D, high resolution T1, T2, and T2*-weighted sequences. The T1-w images were used in FreeSurfer for cortical reconstruction and volumetric segmentation, while T2-w images were used to extract the WM T2 lesions; however, iron and magnetic susceptibility were calculated from the phase data of the T2*-w sequence. Surface-based analyses were performed in FreeSurfer to investigate the regional cortical morphometric changes and their correlations with the expanded disability status scale (EDSS), WM T2 lesions load, cortical iron deposition and magnetic susceptibility. RESULTS: Significant differences were detected between the RRMS patients and HC for all cortical and subcortical morphometric changes. The EDSS and T2 lesion load showed weak to moderate correlation with the reduced cortical morphometric measurements, increased cortical magnetic susceptibility and iron concentration. All deep grey matter (dGM) volumes showed a significant strong positive correlation with the cortical surface area and volume in RRMS patients and HC. CONCLUSIONS: Grey matter is very much involved in the RRMS and cortical morphometric changes occur in a non-uniform pattern and are very likely to be associated with cortical iron deposition and magnetic susceptibility, dGM atrophy, WM T2 lesion load, and disability.

Assessment of Abdominal Fat Using High-field Magnetic Resonance Imaging and Anthropometric and Biochemical Parameters.

BACKGROUND: To measure the abdominal subcutaneous fat (SF) and visceral fat (VF) volumes using high-field magnetic resonance imaging (MRI) and to investigate their association with selected anthropometric and biochemical parameters among obese and nonobese apparently healthy participants. METHODS: A cross-sectional study was conducted by recruiting 167 healthy participants. Abdominal scans were acquired at 3T MRI, and the SF and VF were segmented and their volumes were calculated. Selected anthropometric and biochemical measurements were also determined. RESULTS: A significant difference (P < 0.05) was observed between normal body weight and overweight and obese participants for SF and VF, total abdominal fat volumes, leptin, resistin, adiponectin and waist circumference. Waist circumferences were measured by tape and MRI. Findings revealed that MRI-measured fat volumes were different between males and females and had a significant (P < 0.01) strong positive correlation with body mass index, leptin, resistin and WC and had a negative correlation with adiponectin level. MRI-measured fat volumes were found to correlate moderately with interleukin-6 and weakly with cholesterol, serum triglyceride and low-density lipoprotein. Except for cholesterol, all measured biochemical variables and abdominal fat volumes in the current study were significantly associated with body mass index. CONCLUSIONS: All anthropometric and biochemical parameters showed weak-to-strong associations with the MRI-measured fat volumes. Abdominal fat distribution was different between males and females and their correlations with some lipid profiles were found to be sex dependent. These findings revealed that MRI can be used as an alternative tool for obesity assessment.