Antidepressant-related microstructural changes in the external capsule.

Several magnetic resonance imaging (MRI) studies have reported that antidepressant medications are strongly linked to brain microstructural alterations. Notably, external capsule alterations have been reported to be a biological marker for therapeutic response. However, prior studies did not investigate whether a change in the neurite density or directional coherence of white matter (WM) fibers underlies the observed microstructural alterations.

Mapping brain volume change across time in primary-progressive multiple sclerosis.

Purpose: Detection and prediction of the rate of brain volume loss with age is a significant unmet need in patients with primary progressive multiple sclerosis (PPMS). In this study we construct detailed brain volume maps for PPMS patients. These maps compare age-related changes in both cortical and sub-cortical regions with those in healthy individuals.

MR Imaging Characteristics and ADC Histogram Metrics for Differentiating Molecular Subgroups of Pediatric Low-Grade Gliomas.

Background And Purpose: and type 1 neurofibromatosis status are distinctive features in pediatric low-grade gliomas with prognostic and therapeutic implications. We hypothesized that DWI metrics obtained through volumetric ADC histogram analyses of pediatric low-grade gliomas at baseline would enable early detection of and type 1 neurofibromatosis status.

Materials And Methods: We retrospectively evaluated 40 pediatric patients with histologically proved pilocytic astrocytoma ( = 33), ganglioglioma ( = 4), pleomorphic xanthoastrocytoma ( = 2), and diffuse astrocytoma grade 2 ( = 1).

A deep-learning method for the denoising of ultra-low dose chest CT in coronary artery calcium score evaluation.

Aim: To evaluate a novel deep-learning denoising method for ultra-low dose CT (ULDCT) in the assessment of coronary artery calcium score (CACS).

Materials And Methods: Sixty adult patients who underwent two unenhanced chest CT examinations, a normal dose CT (NDCT) and an ULDCT, were enrolled prospectively between September 2017 to December 201. A special training set was created to learn the characteristics of the real noise affecting the ULDCT implementing a fully convolutional neural network with batch normalisation.

Ultra-Low Dose Chest CT with Denoising for Lung Nodule Detection.

Background: Medical imaging and the resultant ionizing radiation exposure is a public concern due to the possible risk of cancer induction.

Objectives: To assess the accuracy of ultra-low-dose (ULD) chest computed tomography (CT) with denoising versus normal dose (ND) chest CT using the Lung CT Screening Reporting and Data System (Lung-RADS).

Methods: This prospective single-arm study comprised 52 patients who underwent both ND and ULD scans.