A data-driven model of disability progression in progressive multiple sclerosis.

This study applies the Gaussian process progression model, a Bayesian data-driven disease progression model, to analyse the evolution of primary progressive multiple sclerosis. Utilizing data from 1521 primary progressive multiple sclerosis participants collected within the International Progressive Multiple Sclerosis Alliance Project, the analysis includes 18 581 longitudinal time-points (average follow-up time: 28.2 months) of disability assessments including the expanded disability status scale, symbol digit modalities, timed 25-foot-walk, 9-hole-peg test and of MRI metrics such as T1 and T2 lesion volume and normalized brain volume.

Localized FDG loss in lung cancer lesions.

Background: Analysis of [18F]-Fluorodeoxyglucose (FDG) kinetics in cancer has been most often limited to the evaluation of the average uptake over relatively large volumes. Nevertheless, tumor lesions also contain inflammatory infiltrates whose cells are characterized by a significant radioactivity washout due to the hydrolysis of FDG-6P catalyzed by glucose-6P phosphatase. The present study aimed to verify whether voxel-wise compartmental analysis of dynamic imaging can identify tumor regions characterized by tracer washout.

Radiomic and clinical model for predicting atypical ductal hyperplasia upgrades and potentially reduce unnecessary surgical treatments.

Objective: To identify patients with atypical ductal hyperplasia (ADH) at low risk of upgrading to carcinoma. This study aims to assess the performance of radiomics combined with clinical factors to predict occult breast cancer among women diagnosed with ADH.

Methods: This study retrospectively included microcalcification clusters of patients who underwent Mx and VABB with a diagnosis of ADH at a tertiary center from January 2015 to May 2023.

Three-dimensional numerical schemes for the segmentation of the psoas muscle in X-ray computed tomography images.

The analysis of the psoas muscle in morphological and functional imaging has proved to be an accurate approach to assess sarcopenia, i.e. a systemic loss of skeletal muscle mass and function that may be correlated to multifactorial etiological aspects.