Hung Chu, Rosaria J. Ferreira, Chantal Lokhorst, Johannes M. Douwes, Meindina G. Haarman, Tineke P. Willems, Rolf M.F. Berger, Mark-Jan Ploegstra
Beatrix Children’s Hospital, University Medical Center Groningen and University of Groningen. Frisius Medical Center Leeuwarden.
Netherlands
International Journal of Cardiovascular Imaging
Int J Cardiovasc Imaging 2025;
DOI: 10.1007/s10554-025-03434-6
Abstract
Purpose: Pulmonary arterial hypertension (PAH) significantly affects the pulmonary vasculature, requiring accurate estimation of mean pulmonary arterial pressure (mPAP) and pulmonary vascular resistance index (PVRi). Although cardiac catheterization is the gold standard for these measurements, it poses risks, especially in children. This pilot study explored how machine learning (ML) can predict pulmonary hemodynamics from non-invasive cardiac magnetic resonance (CMR) cine images in pediatric PAH patients.
Methods: A retrospective analysis of 40 CMR studies from children with PAH using a four-fold stratified group cross-validation was conducted. The endpoints were severity profiles of mPAP and PVRi, categorised as ‘low’, ‘high’, and ‘extreme’. Deep learning (DL) and traditional ML models were optimized through hyperparameter tuning. Receiver operating characteristic curves and area under the curve (AUC) were used as the primary evaluation metrics.
Results: DL models utilizing CMR cine imaging showed the best potential for predicting mPAP and PVRi severity profiles on test folds (AUCmPAP=0.82 and AUCPVRi=0.73). True positive rates (TPR) for predicting low, high, and extreme mPAP were 5/10, 11/16, and 11/14, respectively. TPR for predicting low, high, and extreme PVRi were 5/13, 14/15, and 7/12, respectively. Optimal DL models only used spatial patterns from consecutive CMR cine frames to maximize prediction performance.
Conclusion: This exploratory pilot study demonstrates the potential of DL leveraging CMR imaging for non-invasive prediction of mPAP and PVRi in pediatric PAH. While preliminary, these findings may lay the groundwork for future advancements in CMR imaging in pediatric PAH, offering a pathway to safer disease monitoring and reduced reliance on invasive cardiac catheterization.
Category
Diagnostic Testing for Pulmonary Vascular Disease. Non-invasive Testing
Diagnostic Testing for Pulmonary Vascular Disease. Invasive Testing
Age Focus: Pediatric Pulmonary Vascular Disease
Fresh or Filed Publication: Fresh (PHresh). Less than 1-2 years since publication
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Free PDF File or Full Text Article Available Through PubMed or DOI: Yes