Towards virtual surgery planning: the modified Blalock-Taussig Shunt

Stephen Haller; Rabin Gerrah; Sandra Rugonyi; Stephen Haller; Rabin Gerrah; Sandra Rugonyi

doi:10.3934/biophy.2020014

AIMS Biophysics

2020, Volume 7, Issue 3: 169-188. doi: 10.3934/biophy.2020014

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Towards virtual surgery planning: the modified Blalock-Taussig Shunt

1.
Department of Biomedical Engineering, Oregon Health & Science University, 3303 SW Bond Ave., Portland, OR 97239, USA
2.
Samaritan Cardiovascular Surgery, Stanford University, 3640 NW Samaritan Dr., Suite 100B, Corvallis, OR 973301, USA

Received: 18 March 2020 Accepted: 03 June 2020 Published: 09 June 2020

A modified Blalock-Taussig shunt (MBTS) is an aortopulmonary shunt to establish or augment pulmonary perfusion in congenital cardiac defects with limited pulmonary blood flow. Proper function of this shunt is of utmost importance. In clinical practice, prediction of flow in an MBTS relies on previous experience. In the research field, computational modeling techniques have been developed to simulate flow in an MBTS and predict its performance. These techniques are promising but also time consuming and prone to uncertainties; therefore not yet suitable for clinical practice. Here we present a simplified, patient-based computational model to predict mean circulatory flow characteristics after MBTS insertion. Simulations performed over a range of pulmonary vascular resistances, were compared to data from: i) previous modeling studies; ii) data from the specific patient modeled, and iii) a cohort of patients with MBTS. Model predictions were within one standard deviation from cohort data; and within 1% from results of previous (more complex) computational models. In comparison to previous studies, our model is computationally stable with significantly shorter computational time to perform simulations. We envision that our approach could be used in the future to perform virtual surgeries, quickly testing different surgical scenarios using the patient own geometrical and physiological characteristics, to aid surgeons in decision making.
- multiscale computational model,
- cyanotic congenital heart disease,
- heart defects,
- pulmonary atresia,
- steady state flow
Citation: Stephen Haller, Rabin Gerrah, Sandra Rugonyi. Towards virtual surgery planning: the modified Blalock-Taussig Shunt[J]. AIMS Biophysics, 2020, 7(3): 169-188. doi: 10.3934/biophy.2020014

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Abstract

A modified Blalock-Taussig shunt (MBTS) is an aortopulmonary shunt to establish or augment pulmonary perfusion in congenital cardiac defects with limited pulmonary blood flow. Proper function of this shunt is of utmost importance. In clinical practice, prediction of flow in an MBTS relies on previous experience. In the research field, computational modeling techniques have been developed to simulate flow in an MBTS and predict its performance. These techniques are promising but also time consuming and prone to uncertainties; therefore not yet suitable for clinical practice. Here we present a simplified, patient-based computational model to predict mean circulatory flow characteristics after MBTS insertion. Simulations performed over a range of pulmonary vascular resistances, were compared to data from: i) previous modeling studies; ii) data from the specific patient modeled, and iii) a cohort of patients with MBTS. Model predictions were within one standard deviation from cohort data; and within 1% from results of previous (more complex) computational models. In comparison to previous studies, our model is computationally stable with significantly shorter computational time to perform simulations. We envision that our approach could be used in the future to perform virtual surgeries, quickly testing different surgical scenarios using the patient own geometrical and physiological characteristics, to aid surgeons in decision making.

Acknowledgments

The authors would like to thank Dr. Chivukula for advice during model implementation. This publication was made possible with support from the Oregon Clinical and Translational Research Institute (OCTRI), grant number UL1TR000128 from the National Center for Advancing Translational Sciences (NCATS), a component of the National Institutes of Health (NIH), and NIH Roadmap for Medical Research; and grant NIH R01 HL094570. The content is solely the responsibility of the authors and does not necessarily represent the official views of grant giving bodies.

Conflict of interest

The authors declare no conflicts of interest.

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