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Children's Hospital of Philadelphia Uses Open Source NVIDIA AI for Cardiac Modeling
Key points
- CHOP uses open-source AI, including MONAI, for cardiac modeling.
- The AI creates precise heart models from medical images in seconds.
- This reduces a four-hour manual process to seconds for clinical use.
- Over 20 U.S. children's hospitals now use similar cardiac modeling programs.
AI-Powered Cardiac Modeling at CHOP
Children’s Hospital of Philadelphia (CHOP) has implemented open-source AI tools to generate detailed 3D models of children’s hearts. This initiative aims to enhance the safety and precision of care for pediatric patients diagnosed with congenital heart disease. The AI system processes existing medical images, such as CT scans, MRI, and 3D ultrasound, to produce anatomically accurate heart models.
Efficiency and Precision in Pre-Surgical Planning
The cardiac modeling service at CHOP, built on MONAI (an open-source medical imaging framework co-founded by NVIDIA), significantly accelerates the modeling process. What previously required a skilled researcher four hours to complete can now be done in seconds, making it feasible for routine clinical application. This speed allows medical teams to evaluate device fit and surgical approaches before procedures, which is critical given that congenital heart defects vary widely among patients.
Wider Adoption and Future Applications
The use of cardiac modeling is expanding, with more than 20 children’s hospitals across the U.S. now operating similar programs. For instance, Boston Children’s Hospital uses modeling to support over half of its cardiac surgeries, totaling approximately 500 cases annually. CHOP anticipates modeling around 200 cases this year. The hospital's IDEA Lab, part of the Morgan Center for Research and Innovation, plans to extend the application of these AI tools to other medical disciplines beyond cardiac care.
Development and Technological Foundation
The foundation for this work began with Dr. Matthew Jolley at CHOP, who, in 2015, worked with the open-source community to develop SlicerHeart. This extension of 3D Slicer software enabled the visualization, segmentation, and analysis of 3D medical images for pediatric hearts. The integration of machine learning, specifically using MONAI Label and NVIDIA’s Auto3DSeg, allowed Jolley’s team to train segmentation networks, automating and speeding up the model creation process from hours to seconds.
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Reporting from
Children’s Hospital of Philadelphia (CHOP) is utilizing open-source AI tools, including NVIDIA's MONAI, to create precise 3D models of children's hearts in seconds. This technology reduces a four-hour manual process to mere seconds, enabling more accurate and safer pre-surgical planning for congenital heart disease patients. The approach is being adopted by over 20 children's hospitals in the U.S., improving care for a significant number of pediatric cardiac cases.