Abstract
AbstractPatients with congenital heart disease often have cardiac anatomy that deviates significantly from normal, frequently requiring multiple heart surgeries. Image segmentation from a preoperative cardiovascular magnetic resonance (CMR) scan would enable creation of patient-specific 3D surface models of the heart, which have potential to improve surgical planning, enable surgical simulation, and allow automatic computation of quantitative metrics of heart function. However, there is no publicly available CMR dataset for whole-heart segmentation in patients with congenital heart disease. Here, we release the HVSMR-2.0 dataset, comprising 60 CMR scans alongside manual segmentation masks of the 4 cardiac chambers and 4 great vessels. The images showcase a wide range of heart defects and prior surgical interventions. The dataset also includes masks of required and optional extents of the great vessels, enabling fairer comparisons across algorithms. Detailed diagnoses for each subject are also provided. By releasing HVSMR-2.0, we aim to encourage development of robust segmentation algorithms and clinically relevant tools for congenital heart disease.
Funder
U.S. Department of Health & Human Services | NIH | National Institute on Aging
U.S. Department of Health & Human Services | NIH | National Institute of Neurological Disorders and Stroke
Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada
Philips
Wistron Corporation
U.S. Department of Health & Human Services | NIH | National Institute of Biomedical Imaging and Bioengineering
U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute
Harvard Catalyst
Charles H. Hood Foundation
American Heart Association
Boston Children's Hospital Translational Research Program Boston Children's Hospital Office of Faculty Development
Publisher
Springer Science and Business Media LLC
Reference33 articles.
1. Frescura, C., Büchel, E. V., Ho, S. Y. & Thiene, G. Anatomical and pathophysiological classification of congenital heart disease. In Saremi, F., Achenbach, S., Arbustini, E. & Narula, J. (eds.) Revisiting Cardiac Anatomy: A Computed-Tomography-Based Atlas and Reference, chap. 2, 40–75 (Blackwell Publishing, Chichester, UK, 2010).
2. Centers for Disease Control and Prevention (CDC). Trends in infant mortality attributable to birth defects – United States, 1980–1995. Morbidity and Mortality Weekly Report (MMWR 47, 773–778 (1998).
3. Marelli, A. J., Mackie, A. S., Ionescu-Ittu, R., Rahme, E. & Pilote, L. Congenital heart disease in the general population: Changing prevalence and age distribution. Circulation 115, 163–172 (2007).
4. Pandya, B., Cullen, S. & Walker, F. Congenital heart disease in adults. BMJ 354, i3905 (2016).
5. Pace, D. F. Image Segmentation for Highly Variable Anatomy: Applications to Congenital Heart Disease. Ph.D. thesis, Massachusetts Institute of Technology (2020).