Computational Model for Predicting Optimal Clinical Intervention in Pre-Operative Neonates with Transposition of the...

Transposition of the Great Arteries (TGA) is a congenital heart defect characterized by the abnormal positioning of the pulmonary artery over the left ventricle and aorta over the right ventricle. Systemic oxygen delivery, therefore, is dependent on the ability for blood to flow (shunt) between the "parallel" (systemic and pulmonary) circulations. Prior to the standard procedure for treatment of TGA (the arterial switch operation (ASO)), shunting is commonly inadequate, resulting in systemic hypoxemia and hypoxia. In this case the standard intervention is the balloon atrial septostomy, but it may not be sufficient and has a certain complication rate. Other adjustable anatomical and physiological factors may influence shunting but have not been adequately studied.

In this investigation, we develop a lumped parameter model (LPM) of TGA to explore the influence of several adjustable factors that can be altered by catheter or pharmacological interventions aimed at improving systemic arterial oxygen delivery to clinically acceptable levels in the preoperative period for newborns with TGA. This model is used to ascertain the sensitivity of oxygen saturation to these parameters and to propose optimal treatment scenarios using formal optimization techniques. Sensitivity in this study is determined using finite difference methods, and a Nelder Mead (NM) algorithm is used for optimization.

Out of 729 tested cases in the sensitivity study, percentage systemic arterial oxygen saturation (Ssa) was most sensitive to systemic vascular resistance (SVR) in 32.77% of cases and was the most sensitive to PDA diameter in 32.46% of cases. Increasing patent ductus arteriosus (PDA) diameter and SVR both yield an increase in Ssa in nearly all cases, while decreasing pulmonary vascular resistance (PVR) yields an increase in Ssa in nearly all cases. Notably, atrial septal defect (ASD) enlargement was not always most sensitive parameter for increasing Ssa. Best results were obtained with an objective function with a weight on pulmonary-to-systemic flow ratio of 0.1 compared to the weight of unity on Ssa. Lastly, while it does not significantly impact the results of optimization, compliance ratio does have the potential to influence optimal pre-operative strategy.

This study illuminates the influence of SVR and PVR in oxygen delivery to the systemic circulation through extensive sensitivity testing. These results hold promise for applying other interventions aside from atrial septostomy for improving systemic arterial oxygen saturation. Using our methodology in conjunction with machine learning (ML) using clinical data, an optimization-based tool will be developed to guide pre-operative decision-making in TGA management.