Fetal critical aortic stenosis with evolving hypoplastic left heart syndrome (CAS-eHLHS) causes biomechanical and functional aberrations, leading to a high risk of progression to hypoplastic left heart syndrome (HLHS) at birth. Fetal aortic valvuloplasty (FAV) can resolve outflow obstruction and may reduce progression risk. However, it is currently difficult to accurately predict which patients will respond to the intervention and become functionally biventricular (BV) at birth, as opposed to becoming functionally univentricular (UV). This prediction is important for patient selection, parental counselling, and surgical planning. Therefore, we investigated whether biomechanics parameters from pre-FAV image-based computations could robustly distinguish between CAS-eHLHS cases with BV or UV outcomes in a retrospective cohort. To do so we performed image-based finite element biomechanics modelling of nine CAS-eHLHS cases undergoing intervention and six healthy fetal control hearts, and found that a biomechanical parameter, peak systolic myofibre stress, showed a uniquely large difference between BV and UV cases, which had a larger magnitude effect than echocardiography parameters. A simplified equation was derived for quick and easy estimation of myofibre stress from echo measurements via principal component analysis. When tested on a retrospective cohort of 37 CAS-eHLHS cases, the parameter outperformed other parameters in predicting UV versus BV outcomes, and thus has a high potential of improving outcome predictions, if incorporated into patient selection procedures. Physiologically, high myocardial stresses likely indicate a healthier myocardium that can withstand high stresses and resist pathological remodelling, which can explain why it is a good predictor of BV outcomes. KEY POINTS: Predicting the morphological birth outcomes (univentricular versus biventricular) of fetal aortic valvuloplasty for fetal aortic stenosis with evolving HLHS is important for accurate patient selection, parental counselling and management decisions. Computational simulations show that a biomechanics parameter, pre-intervention peak systolic myofibre stress, is uniquely robust in distinguishing between such outcomes, outperforming all echo parameters. An empirical equation was developed to quickly compute peak systolic myofibre stress from routine echo measurements and was the best predictor of outcomes among a wide range of parameters tested.
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http://dx.doi.org/10.1113/JP285475 | DOI Listing |
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