Multiparametric MRI and artificial intelligence in predicting and monitoring treatment response in bladder cancer.

Bladder cancer is the 10th most common and 13th most deadly cancer worldwide, with urothelial carcinomas being the most common type. Distinguishing between non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC) is essential due to significant differences in management and prognosis. MRI may play an important diagnostic role in this setting.

Multiparametric MRI in Era of Artificial Intelligence for Bladder Cancer Therapies.

This review focuses on the principles, applications, and performance of mpMRI for bladder imaging. Quantitative imaging biomarkers (QIBs) derived from mpMRI are increasingly used in oncological applications, including tumor staging, prognosis, and assessment of treatment response. To standardize mpMRI acquisition and interpretation, an expert panel developed the Vesical Imaging-Reporting and Data System (VI-RADS).

Multi-layer analysis of quantitative 7 T magnetic resonance imaging in the cortex of multiple sclerosis patients reveals pathology associated with disability.

Background: Cortical demyelination is a relevant aspect of tissue damage in multiple sclerosis (MS). Microstructural changes may affect each layer in the cortex differently.

Objectives: To evaluate the sensitivity of quantitative magnetic resonance imaging (qMRI) measurements on cortical layers as clinically accessible biomarkers of grey matter (GM) pathology.

No association between cortical lesions and leptomeningeal enhancement on 7-Tesla MRI in multiple sclerosis.

Background: Autopsy data suggest a causative link between meningeal inflammation and cortical lesions (CLs) in multiple sclerosis (MS).

Objective: To use leptomeningeal enhancement (LME) and CLs on 7-Tesla (7T) magnetic resonance imaging (MRI) to investigate associations between meningeal inflammation and cortical pathology.

Methods: Forty-one participants with MS underwent 7T MRI of the brain.