Holistic AI analysis of hybrid cardiac perfusion images for mortality prediction.

ABSTRACT:

Background

While low-dose computed tomography scans are traditionally used for attenuation correction in hybrid myocardial perfusion imaging (MPI), they also contain additional anatomic and pathologic information not utilized in clinical assessment. We seek to uncover the full potential of these scans utilizing a holistic artificial intelligence (AI)-driven image framework for image assessment.

Methods

Patients with SPECT/CT MPI from 4 REFINE SPECT registry sites were studied. A multi-structure model segmented 33 structures and quantified 15 radiomics features for each on CT attenuation correction (CTAC) scans. Coronary artery calcium and epicardial adipose tissue scores were obtained from separate deep-learning models. Normal standard quantitative MPI features were derived

SUBMITTER: Michalowska AM 

PROVIDER: S-EPMC11071553 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature