MultiD4CAD: Multimodal Dataset composed of CT and Clinical Features for Coronary Artery Disease Analysis

This is an old version of the Dataset. Please use the latest one here. MultiD4CAD is a multimodal dataset of suspected Coronary Artery Disease (CAD) patients, comprising both imaging and clinical data. The imaging data obtained from cardiac CT includes epicardial (EAT) and pericoronary (PAT) adipose tissue segmentations. These metabolically active fat tissues play a key role in diagnosing various cardiovascular diseases. In addition, clinical data includes a set of biomarkers recognized as CAD risk factors. Specifically, the dataset includes 118 samples, divided into those without CAD patients (40) and those with CAD patients (78). The validated EAT and PAT segmentations make the dataset suitable for training predictive models based on radiomics and deep learning architectures. Moreover, challenges such as classification, segmentation, radiomic, and deep training tasks can be investigated and validated using the MultiD4CAD dataset. Here you can find the Data Use Agreement (DUA) to sign before using the dataset, together with the instructions to have access.本数据集为旧版，请使用此处的最新版本。 MultiD4CAD是针对疑似冠状动脉疾病（Coronary Artery Disease, CAD）患者的多模态数据集，涵盖影像与临床两类数据。其中影像数据源自心脏CT，包含心外膜脂肪组织（epicardial adipose tissue, EAT）与冠状动脉周围脂肪组织（pericoronary adipose tissue, PAT）的分割结果。此类具有代谢活性的脂肪组织在多种心血管疾病的诊断中发挥关键作用。临床数据则包含一组被认定为CAD危险因素的生物标志物。 具体而言，本数据集共包含118例样本，分为无CAD患者组（40例）与CAD患者组（78例）。经验证的心外膜脂肪组织与冠状动脉周围脂肪组织分割结果，使得本数据集适用于基于放射组学与深度学习架构的预测模型训练。此外，借助MultiD4CAD数据集，可开展并验证分类、分割、放射组学分析以及深度学习训练等多项任务。 您可在此处获取使用本数据集前需签署的数据使用协议（Data Use Agreement, DUA）以及数据集获取指南。