The expansion and severity of chronic MS lesions follows a periventricular gradient

Background and Objectives: Expansion of chronic lesions in MS patients and recently described CSF-related gradient of tissue damage are linked to microglial activation. The aim of the current study was to investigate whether lesion expansion is associated with proximity to ventricular CSF spaces. Methods: Pre- and post-gadolinium 3D-T1, 3D FLAIR and diffusion tensor images were acquired from 36 RRMS patients. Lesional activity was analysed between baseline and 48 months at different distances from the CSF using successive 1-mm thick concentric rings radiating from the ventricles. Results: Voxel-based analysis of the rate of lesion expansion demonstrated a clear periventricular gradient decreasing away from the ventricles. This was particularly apparent when lesions of equal diameter were analysed. Periventricular lesional tissue showed higher degree of tissue distraction at baseline that significantly increased during follow-up in rings close to CSF. This longitudinal change was proportional to degree of lesion expansion. Lesion-wise analysis revealed a gradual, centrifugal decrease in the proportion of expanding lesions from the immediate periventricular zone. Discussion: Our data suggest that chronic white matter lesions in close proximity to the ventricles are more destructive, show a higher degree of expansion at the lesion border and accelerated tissue loss in the lesion core.

FLAIR2 post-processing: improving MS lesion detection in standard MS imaging protocols

Background Technical improvements in magnetic resonance imaging (MRI) acquisition, such as higher field strength and optimized sequences, lead to better multiple sclerosis (MS) lesion detection and characterization. Multiplication of 3D-FLAIR with 3D-T2 sequences (FLAIR2) results in isovoxel images with increased contrast-to-noise ratio, increased white–gray-matter contrast, and improved MS lesion visualization without increasing MRI acquisition time. The current study aims to assess the potential of 3D-FLAIR2 in detecting cortical/leucocortical (LC), juxtacortical (JC), and white matter (WM) lesions. Objective To compare lesion detection of 3D-FLAIR2 with state-of-the-art 3D-T2-FLAIR and 3D-T2-weighted images. Methods We retrospectively analyzed MRI scans of thirteen MS patients, showing previously noted high cortical lesion load. Scans were acquired using a 3 T MRI scanner. WM, JC, and LC lesions were manually labeled and manually counted after randomization of 3D-T2, 3D-FLAIR, and 3D-FLAIR2 scans using the ITK-SNAP tool. Results LC lesion visibility was significantly improved by 3D-FLAIR2 in comparison to 3D-FLAIR (4 vs 1; p = 0.018) and 3D-T2 (4 vs 1; p = 0.007). Comparing LC lesion detection in 3D-FLAIR2 vs. 3D-FLAIR, 3D-FLAIR2 detected on average 3.2 more cortical lesions (95% CI − 9.1 to 2.8). Comparing against 3D-T2, 3D-FLAIR2 detected on average 3.7 more LC lesions (95% CI 3.3–10.7). Conclusions 3D-FLAIR2 is an easily applicable time-sparing MR post-processing method to improve cortical lesion detection. Larger sampled studies are warranted to validate the sensitivity and specificity of 3D-FLAIR2.

Three - dimensional fluid attenuated inversion recovery sequence on 3 tesla magnetic resonace imaging in cranial nerve pathologies: Two case reports

Three - dimensional fluid attenuated inversion recovery sequence (3D-FLAIR) was introduced as a practical sequence which helps to reduce the cerebrospinal fluid pulsation and flow artefacts of conventional 2D acquisition and brings contiguous slices, ability in reformatting in variable planes which are typical features of 3D acquisition. 3D - FLAIR has been applied on assessing several neurologic pathologies. In this article, we introduce the application of 3D - FLAIR sequence without contrast enhancement on detecting abnormalities of cranial nerve pathology by presenting two cases, acute vestibular neuritis and facial nerve palsy. We suggest that 3D - FLAIR is the relatively useful sequence in detecting cranial nerve pathologies.

The European Prevention of Alzheimer's Dementia (EPAD) MRI Dataset and Processing Workflow

The European Prevention of Alzheimer Dementia (EPAD) is a multi-center study that aims to characterize the preclinical and prodromal stages of Alzheimer's Disease. The EPAD imaging dataset includes core (3D T1w, 3D FLAIR) and advanced (ASL, diffusion MRI, and resting-state fMRI) MRI sequences. Here, we give an overview of the semi-automatic multimodal and multisite pipeline that we developed to curate, preprocess, quality control (QC), and compute image-derived phenotypes (IDPs) from the EPAD MRI dataset. This pipeline harmonizes DICOM data structure across sites and performs standardized MRI preprocessing steps. A semi-automated MRI QC procedure was implemented to visualize and flag MRI images next to site-specific distributions of QC features - i.e. metrics that represent image quality. The value of each of these QC features was evaluated through comparison with visual assessment and step-wise parameter selection based on logistic regression. IDPs were computed from 5 different MRI modalities and their sanity and potential clinical relevance were ascertained by assessing their relationship with biological markers of aging and dementia. The EPAD v1500.0 data release encompassed core structural scans from 1356 participants 842 fMRI, 831 dMRI, and 858 ASL scans. From 1356 3D T1w images, we identified 17 images with poor quality and 61 with moderate quality. Five QC features - Signal to Noise Ratio (SNR), Contrast to Noise Ratio (CNR), Coefficient of Joint Variation (CJV), Foreground-Background energy Ratio (FBER) , and Image Quality Rate (IQR) - were selected as the most informative on image quality by comparison with visual assessment. The multimodal IDPs showed greater impairment in associations with age and dementia biomarkers, demonstrating the potential of the dataset for future clinical analyses.