Training and clinical testing of artificial intelligence derived right atrial cardiovascular magnetic resonance measurements.

ABSTRACT:

Background

Right atrial (RA) area predicts mortality in patients with pulmonary hypertension, and is recommended by the European Society of Cardiology/European Respiratory Society pulmonary hypertension guidelines. The advent of deep learning may allow more reliable measurement of RA areas to improve clinical assessments. The aim of this study was to automate cardiovascular magnetic resonance (CMR) RA area measurements and evaluate the clinical utility by assessing repeatability, correlation with invasive haemodynamics and prognostic value.

Methods

A deep learning RA area CMR contouring model was trained in a multicentre cohort of 365 patients with pulmonary hypertension, left ventricular pathology and healthy subjects. Inter-study repeatability (intraclass correlation coeff

SUBMITTER: Alandejani F 

PROVIDER: S-EPMC8988415 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature