Quantitative measurement of dural ectasia: associations with clinical and genetic characteristics in Marfan syndrome.

PURPOSE: Dural ectasia (DE) may significantly impact Marfan syndrome (MFS) patients' quality of life due to chronic lower back pain, postural headache and urinary disorders. We aimed to evaluate the association of quantitative measurements of DE, and their evolution over time, with demographic, clinical and genetic characteristics in a cohort of MFS patients. METHODS: We retrospectively included 88 consecutive patients (39% females, mean age 37.1 ± 14.2 years) with genetically confirmed MFS who underwent at least one MRI or CT examination of the lumbosacral spine. Vertebral scalloping (VS) and dural sac ratio (DSR) were calculated from L3 to S3. Likely pathogenic or pathogenic FBN1 variants were categorized as either protein-truncating or in-frame. The latter were further classified according to their impact on the cysteine content of fibrillin-1. RESULTS: Higher values of the systemic score (revised Ghent criteria) were associated with greater DSR at lumbar (p < 0.001) and sacral (p = 0.021) levels. Patients with protein-truncating variants exhibited a greater annual increase in lumbar (p = 0.039) and sacral (p = 0.048) DSR. Mutations affecting fibrillin-1 cysteine content were linked to higher VS (p = 0.009) and DSR (p = 0.038) at S1, along with a faster increase in VS (p = 0.032) and DSR (p = 0.001) in the lumbar region. CONCLUSION: Our study shed further light on the relationship between genotype, dural pathology, and the overall clinical spectrum of MFS. The identification of protein-truncating variants and those impacting cysteine content may therefore suggest closer patient monitoring, in order to address potential complications associated with DE.

Multiparametric MRI dataset for susceptibility-based radiomic feature extraction and analysis.

Multiple sclerosis (MS) is a progressive demyelinating disease impacting the central nervous system. Conventional Magnetic Resonance Imaging (MRI) techniques (e.g., T2w images) help diagnose MS, although they sometimes reveal non-specific lesions. Quantitative MRI techniques are capable of quantifying imaging biomarkers in vivo, offering the potential to identify specific signs related to pre-clinical inflammation. Among those techniques, Quantitative Susceptibility Mapping (QSM) is particularly useful for studying processes that influence the magnetic properties of brain tissue, such as alterations in myelin concentration. Because of its intrinsic quantitative nature, it is particularly well-suited to be analyzed through radiomics, including techniques that extract a high number of complex and multi-dimensional features from radiological images. The dataset presented in this work provides information about normal-appearing white matter (NAWM) in a cohort of MS patients and healthy controls. It includes QSM-based radiomic features from NAWM and its tracts, and MR sequences necessary to implement the pipeline: T1w, T2w, QSM, DWI. The workflow is outlined in this article, along with an application showing feature reliability assessment.

Sulcal Morphometry Predicts Mild Cognitive Impairment Conversion to Alzheimer's Disease.

Background: Being able to differentiate mild cognitive impairment (MCI) patients who would eventually convert (MCIc) to Alzheimer's disease (AD) from those who would not (MCInc) is a key challenge for prognosis. Objective: This study aimed to investigate the ability of sulcal morphometry to predict MCI progression to AD, dedicating special attention to an accurate identification of sulci. Methods: Twenty-five AD patients, thirty-seven MCI and twenty-five healthy controls (HC) underwent a brain-MR protocol (1.5T scanner) including a high-resolution T1-weighted sequence. MCI patients underwent a neuropsychological assessment at baseline and were clinically re-evaluated after a mean of 2.3 years. At follow-up, 12 MCI were classified as MCInc and 25 as MCIc. Sulcal morphometry was investigated using the BrainVISA framework. Consistency of sulci across subjects was ensured by visual inspection and manual correction of the automatic labelling in each subject. Sulcal surface, depth, length, and width were retrieved from 106 sulci. Features were compared across groups and their classification accuracy in predicting MCI conversion was tested. Potential relationships between sulcal features and cognitive scores were explored using Spearman's correlation. Results: The width of sulci in the temporo-occipital region strongly differentiated between each pair of groups. Comparing MCIc and MCInc, the width of several sulci in the bilateral temporo-occipital and left frontal areas was significantly altered. Higher width of frontal sulci was associated with worse performances in short-term verbal memory and phonemic fluency. Conclusions: Sulcal morphometry emerged as a strong tool for differentiating HC, MCI, and AD, demonstrating its potential prognostic value for the MCI population.