Epicardial Adipose Tissue Radiomics for Predicting Cardiac Outcomes After AMI

206 acute myocardial infarction patients were enrolled in a single-center prospective cohort study between January 2022 and June 2023. The dataset likely contains radiomics features extracted from cardiac CT scans and clinical parameters used to predict ventricular remodeling and major adverse cardiovascular events. It was created by Zeyan Liu and is available under a CC-BY-4.0 license.

Use Cases

• Predict ventricular remodeling (VR) based on epicardial adipose tissue radiomics features.
• Predict major adverse cardiovascular events (MACE) based on epicardial adipose tissue radiomics features.
• Validate imaging-based biomarkers for adverse cardiac remodeling after acute myocardial infarction.
• Build machine learning models integrating radiomics features with clinical parameters.

Strengths

• 206 patient records from a prospective cohort study.
• Includes 12-month follow-up data with outcomes for VR (29.6%) and MACE (19.9%).
• Radiomics features were extracted using the Pyradiomics library.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data is from a single-center study, which may limit generalizability.

Provenance

Source

Second Affiliated Hospital of Anhui Medical University

Collection Method

A prospective cohort study enrolled patients; radiomics features were extracted from cardiac CT scans using Pyradiomics.

Time Range

January 2022 to June 2023 (enrollment), with 12-month follow-up.

Freshness

Last updated 2026-05-18 05:31:24; freshness should be verified.

Geography

Single-center study in China; specific location not detailed.