Multimodal Dataset for Coronary Artery Disease Analysis
Published April 4, 2025 | Version v2
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MultiD4CAD: Multimodal Dataset composed of CT and Clinical Features for Coronary Artery Disease Analysis

Authors/Creators

  • 1. Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University of Palermo, 90127, Palermo, Italy
  • 2. Institute for High-Performance Computing and Networking (ICAR-CNR), National Research Council, 90146, Palermo, Italy
  • 3. Radiology Unit, IRCCS ISMETT (Mediterranean Institute for Transplantation and Advanced Specialized Therapies), 90127, Palermo, Italy
  • 4. Department of Health Promotion Sciences Maternal and Infantile Care, Internal Medicine and Medical Specialities (ProMISE), University of Palermo, 90127, Palermo, Italy
  • 5. Department of Radiology, AOUP Paolo Giaccone, Via del Vespro 129, Palermo, 90127, Italy

Description

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.

 

 

 

 

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Additional details

Dates

Created
2025-03-21
Entry Dataset Creation on Zenodo