Published February 9, 2024 | Version 1.1.0
Dataset Open

Cine and real-time free-breathing CMR at rest and under exercise stress of healthy volunteers

  • 1. ROR icon Universitätsmedizin Göttingen
  • 2. ROR icon Graz University of Technology

Description

The dataset consists of cine and real-time images from 15 healthy volunteers (7 males; 8 females). All images were acquired in supine position using a 32-channel cardiac surface receiver coil at 3 T (Skyra, Siemens Healthineers, Germany).

Conventional imaging at rest included a balanced steady-state free precession (bSSFP) ECG-gated cine sequence to create a short-axis stack covering the entire heart including both ventricles and atria. Real-time CMR data acquisition was performed during free-breathing and without ECG-synchronization at rest and under two different levels of exercise stress.

The dataset includes automatically created contours (comDL) using Medis (version 4.0.56.4, QMass® 8.1, Medical Imaging Systems, Leiden, Netherlands) for all images, as well as manually corrected (mc) contours based on the comDL contours for all cine and real-time measurements at rest and under exercise stress for end-diastolic (ED) and end-systolic phases (ES).

The dataset also includes segmentation masks in NIfTI format for cine and real-time CMR at rest and under exercise stress created with nnU-Net (DOI:10.1038/s41592-020-01008-z) with freely available weights based trained on the dataset of the cardiac segmentation challenge "Automated Cardiac Segmentation Challenge" (ACDC) (DOI:10.1109/TMI.2018.2837502).

To minimize the influence of respiratory motion on clinical measures, images in the ED and ES phase of the cardiac cycle during end-expiration were manually selected for each slice. The dataset includes indices for these images for real-time CMR measurements at rest and under exercise stress. For intra-observer variability, manually corrected contours for the derivation of the clinical measures were created three to six months after the initial segmentation. For inter-observer variability, manually corrected contours for the derivation of the clinical parameters were created for the first five volunteers by a second reader with experience in cardiac segmentation. Single images in the ED and ES phase during end-expiration were once again chosen from each slice.

Image data is provided in a file format used by the BART toolbox. 
DOI:10.5281/zenodo.7110562

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