Background and Purpose-The quantification of spinal cord (SC) atrophy by MRI has assumed an important role in assessment of neuroinflammatory/neurodegenerative diseases and traumatic SC injury. Recent technical advances make possible the quantification of gray matter (GM) and white matter tissues in clinical settings. However, the goal of a reliable diagnostic, prognostic or predictive marker is still elusive, in part due to large inter-subject variability of SC areas. Here, we investigated the sources of this variability and explored effective strategies to reduce it.Methods-129 healthy subjects (mean age: 41.0±15.9) underwent MRI on a Siemens 3T Skyra scanner. 2D PSIR at the C2-C3 vertebral level and a sagittal 1mm 3 3D T1-weighted brain acquisition extended to the upper cervical cord were acquired. Total cross-sectional area and GM area were measured at C2-C3, as well as measures of the vertebra, spinal canal and the skull. Correlations between the different metrics were explored using Pearson product-moment coefficients. The most promising metrics were used to normalize cord areas using multiple regression analyses.Results-The most effective normalization metrics were the V-scale (from SienaX) and the product of the C2-C3 spinal canal diameters. Normalization methods based on these metrics reduced the inter-subject variability of cord areas of up to 17.74%. The measured cord areas had a statistically significant sex difference, while the effect of age was moderate.Conclusions-The present work explored in a large cohort of healthy subjects the source of inter-subject variability of SC areas and proposes effective normalization methods for its reduction.
Objective A major challenge in multiple sclerosis (MS) research is the understanding of silent progression and Progressive MS. Using a novel method to accurately capture upper cervical cord area from legacy brain MRI scans we aimed to study the role of spinal cord and brain atrophy for silent progression and conversion to secondary progressive disease (SPMS). Methods From a single‐center observational study, all RRMS (n = 360) and SPMS (n = 47) patients and 80 matched controls were evaluated. RRMS patient subsets who converted to SPMS (n = 54) or silently progressed (n = 159), respectively, during the 12‐year observation period were compared to clinically matched RRMS patients remaining RRMS (n = 54) or stable (n = 147), respectively. From brain MRI, we assessed the value of brain and spinal cord measures to predict silent progression and SPMS conversion. Results Patients who developed SPMS showed faster cord atrophy rates (−2.19%/yr) at least 4 years before conversion compared to their RRMS matches (−0.88%/yr, p < 0.001). Spinal cord atrophy rates decelerated after conversion (−1.63%/yr, p = 0.010) towards those of SPMS patients from study entry (−1.04%). Each 1% faster spinal cord atrophy rate was associated with 69% (p < 0.0001) and 53% (p < 0.0001) shorter time to silent progression and SPMS conversion, respectively. Interpretation Silent progression and conversion to secondary progressive disease are predominantly related to cervical cord atrophy. This atrophy is often present from the earliest disease stages and predicts the speed of silent progression and conversion to Progressive MS. Diagnosis of SPMS is rather a late recognition of this neurodegenerative process than a distinct disease phase. ANN NEUROL 2022;91:268–281
BACKGROUND AND PURPOSE: MR imaging is essential for MS diagnosis and management, yet it has limitations in assessing axonal damage and remyelination. Gadolinium-based contrast agents add value by pinpointing acute inflammation and blood-brain barrier leakage, but with drawbacks in safety and cost. Neurite orientation dispersion and density imaging (NODDI) assesses microstructural features of neurites contributing to diffusion imaging signals. This approach may resolve the components of MS pathology, overcoming conventional MR imaging limitations. MATERIALS AND METHODS: Twenty-one subjects with MS underwent serial enhanced MRIs (12.6 6 9 months apart) including NODDI, whose key metrics are the neurite density and orientation dispersion index. Twenty-one age-and sex-matched healthy controls underwent unenhanced MR imaging with the same protocol. Fifty-eight gadolinium-enhancing and non-gadolinium-enhancing lesions were semiautomatically segmented at baseline and follow-up. Normal-appearing WM masks were generated by subtracting lesions and dirty-appearing WM from the whole WM. RESULTS: The orientation dispersion index was higher in gadolinium-enhancing compared with non-gadolinium-enhancing lesions; logistic regression indicated discrimination, with an area under the curve of 0.73. At follow-up, in the 58 previously enhancing lesions, we identified 2 subgroups based on the neurite density index change across time: Type 1 lesions showed increased neurite density values, whereas type 2 lesions showed decreased values. Type 1 lesions showed greater reduction in size with time compared with type 2 lesions. CONCLUSIONS: NODDI is a promising tool with the potential to detect acute MS inflammation. The observed heterogeneity among lesions may correspond to gradients in severity and clinical recovery after the acute phase. ABBREVIATIONS: AD ¼ axial diffusivity; DAWM ¼ dirty-appearing white matter; FA ¼ fractional anisotropy; FU ¼ follow-up; GEL ¼ gadolinium-enhancing lesion; HC ¼ healthy control; MD ¼ mean diffusivity; NAWM ¼ normal-appearing white matter; NDI ¼ neurite density index; NGEL ¼ non-gadolinium-enhancing lesion; NODDI ¼ neurite orientation dispersion and density Imaging; nODI ¼ normalized orientation dispersion index; ODI ¼ orientation dispersion index; RD ¼ radial diffusivity; VEC ¼ extra-neurite compartment C onventional MR imaging is essential for MS diagnosis and management, specifically for demonstrating WM lesion dissemination in space (involvement of .1 CNS region) and time (across time accumulation). 1 Conventional MR imaging, however, lacks specificity in characterizing MS WM lesions after the acute phase; all lesions show a similar radiologic appearance on T2WI, irrespective of the degree of inflammation, axonal loss, gliosis,
Scientific debate over chronic cerebrospinal venous insufficiency (CCSVI) has drawn attention to venous system involvement in a series of pathologic brain conditions. In the last few decades, the MRI venography (MRV) field has developed a number of valuable sequences to better investigate structural anatomy, vessel patency, and flow characteristics of venous drainage in the intra- and extracranial systems. A brief two-tier protocol is proposed to encompass the study of intra- and extracranial venous drainage with and without contrast administration, respectively. Contrast-enhanced protocol is based on time-resolved contrast-enhanced MRV of the whole region plus extracranial flow quantification through 2D Cine phase contrast (PC); non-contrast-enhanced protocol includes intracranial 3D PC, extracranial 2D time of flight (TOF), and 2D Cine PC flow quantification. Total scanning time is reasonable for clinical applications: approximately seven minutes is allocated for the contrast protocol (most of which is due to 2D Cine PC), while the noncontrast protocol accounts for around twenty minutes. We believe that a short though exhaustive MRI scan of the whole intra- and extracranial venous drainage system can be valuable for a variety of pathologic conditions, given the possible venous implication in several neurological conditions.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.