Predicting post-contrast information from contrast agent free cardiac MRI using machine learning: Challenges and methods.

ABSTRACT:

Objectives

Currently, administering contrast agents is necessary for accurately visualizing and quantifying presence, location, and extent of myocardial infarction (MI) with cardiac magnetic resonance (CMR). In this study, our objective is to investigate and analyze pre- and post-contrast CMR images with the goal of predicting post-contrast information using pre-contrast information only. We propose methods and identify challenges.

Methods

The study population consists of 272 retrospectively selected CMR studies with diagnoses of MI (n = 108) and healthy controls (n = 164). We describe a pipeline for pre-processing this dataset for analysis. After data feature engineering, 722 cine short-axis (SAX) images and segmentation mask pairs were used for experimentatio

SUBMITTER: Abdulkareem M 

PROVIDER: S-EPMC9426684 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature