Journal of Biomechanical Engineering
Background: Reduced exercise capacity is nearly universal among Fontan patients, though its etiology is not yet fully understood. While previous computational studies have attempted to model Fontan exercise, they did not fully account for global physiologic mechanisms nor directly compare results against clinical and physiologic data. Methods: In this study, we developed a protocol to simulate Fontan lower-body exercise using a closed-loop lumped-parameter model describing the entire circulation. We analyzed clinical exercise data from a cohort of Fontan patients, incorporated previous clinical findings from literature, quantified a comprehensive list of physiological changes during exercise, translated them into a computational model of the Fontan circulation, and designed a general protocol to model Fontan exercise behavior. Using inputs of patient weight, height, and if available, patient-specific reference heart rate (HR) and oxygen consumption, this protocol enables the derivation of a full set of parameters necessary to model a typical Fontan patient of a given body-size over a range of physiologic exercise levels. Results: In light of previous literature data and clinical knowledge, the model successfully produced realistic trends in physiological parameters with exercise level. Applying this method retrospectively to a set of clinical Fontan exercise data, direct comparison between simulation results and clinical data demonstrated that the model successfully reproduced the average exercise response of a cohort of typical Fontan patients. Conclusion: This work is intended to offer a foundation for future advances in modeling Fontan exercise, highlight the needs in clinical data collection, and provide clinicians with quantitative reference exercise physiologies for Fontan patients.
Kung E, Pennati G, Migliavacca F, Hsia TY, Marsden A, Giardini A, MOCHA Investigators, “A Simulation Protocol For Exercise Physiology In Fontan Patients Using A Closed-Loop Lumped- Parameter Model.” Journal of Biomechanical Engineering. 136(8):081007 (2014) doi: 10.1115/1.4027271