Background And Purpose: The central vein sign (CVS) is a diagnostic imaging biomarker for multiple sclerosis (MS). FLAIR* is a combined MRI contrast that provides high conspicuity for CVS at 3 Tesla (3T), enabling its sensitive and accurate detection in clinical settings. This study evaluated whether CVS conspicuity of 3T FLAIR* is reliable across imaging sites and MRI vendors and whether gadolinium (Gd) contrast increases CVS conspicuity.
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November 2024
Background: Diagnosis of multiple sclerosis (MS) frequently relies on MRI dissemination in time (DIT) and space (DIS), as codified in 2017 McDonald criteria (McD 2017). The central vein sign (CVS) is a proposed MS diagnostic biomarker, but its optimal incorporation into McD 2017 has not been extensively studied.
Objective: Evaluate the diagnostic performance of several methods incorporating CVS into McD 2017 radiological DIS criteria.
Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While the technical advances spearheaded by the Human Connectome Project (HCP) led to significant improvements in dMRI data quality, it remains unclear how these data should be analyzed to maximize tractography accuracy. Over a period of two years, we have engaged the dMRI community in the IronTract Challenge, which aims to answer this question by leveraging a unique dataset.
View Article and Find Full Text PDFRepeated injections of linear gadolinium-based contrast agent (GBCA) have shown correlations with increased signal intensities (SI) on unenhanced T1-weighted (T1w) images. Assessment is usually performed manually on a single slice and the SI as an average of a freehand region-of-interest is reported. We aim to develop a fully automated software that segments and computes SI ratio of dentate nucleus (DN) to pons (DN/P) and globus pallidus (GP) to thalamus (GP/T) for the assessment of gadolinium presence in the brain after a serial GBCA administrations.
View Article and Find Full Text PDFAnalysis of the structural connectomes can lead to powerful insights about the brain's organization and damage. However, the accuracy and reproducibility of constructing the structural connectome done with different acquisition and reconstruction techniques is not well defined. In this work, we evaluated the reproducibility of the structural connectome techniques by performing test-retest (same day) and longitudinal studies (after 1 month) as well as analyzing graph-based measures on the data acquired from 22 healthy volunteers (6 subjects were used for the longitudinal study).
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