Phillip M Trusty1, Zhenglun Alan Wei1, Timothy C Slesnick2, Kirk R Kanter3, Thomas L Spray4, Mark A Fogel5, Ajit P Yoganathan6. 1. Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Ga. 2. Division of Cardiology, Department of Pediatrics, Children's Healthcare of Atlanta, Emory University School of Medicine, Atlanta, Ga. 3. Division of Cardiothoracic Surgery, Children's Healthcare of Atlanta, Emory University School of Medicine, Atlanta, Ga. 4. Division of Pediatric Cardiothoracic Surgery, Children's Hospital of Philadelphia, Philadelphia, Pa. 5. Division of Cardiology, Children's Hospital of Philadelphia, Philadelphia, Pa. 6. Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, Atlanta, Ga. Electronic address: ajit.yoganathan@bme.gatech.edu.
Abstract
OBJECTIVE: Fontan surgical planning is an image-based, collaborative effort, which is hypothesized to result in improved patient outcomes. A common motivation for Fontan surgical planning is the progression (or concern for progression) of pulmonary arteriovenous malformations. The purpose of this study was to evaluate the accuracy of surgical planning predictions, specifically hepatic flow distribution (HFD), a known factor in pulmonary arteriovenous malformation progression, and identify methodological improvements needed to increase prediction accuracy. METHODS: Twelve single-ventricle patients who were enrolled in a surgical planning protocol for Fontan surgery with pre- and postoperative cardiac imaging were included in this study. Computational fluid dynamics were used to compare HFD in the surgical planning prediction and actual postoperative conditions. RESULTS: Overall, HFD prediction error was 17 ± 13%. This error was similar between surgery types (15 ± 18% and 18 ± 10% for revisions vs Fontan completions respectively; P = .73), but was significantly lower (6 ± 7%; P = .05) for hepatic to azygous shunts. Y-grafts and extracardiac conduits showed a strong correlation between prediction error and discrepancies in graft insertion points (r = 0.99; P < .001). Improving postoperative anatomy prediction significantly reduced overall HFD prediction error to 9 ± 6% (P = .03). CONCLUSIONS: Although Fontan surgical planning can offer accurate HFD predictions for specific graft types, methodological improvements are needed to increase overall accuracy. Specifically, improving postoperative anatomy prediction was shown to be an important target for future work. Future efforts and refinements to the surgical planning process will benefit from an improved understanding of the current state and will rely heavily on increased follow-up data.
OBJECTIVE: Fontan surgical planning is an image-based, collaborative effort, which is hypothesized to result in improved patient outcomes. A common motivation for Fontan surgical planning is the progression (or concern for progression) of pulmonary arteriovenous malformations. The purpose of this study was to evaluate the accuracy of surgical planning predictions, specifically hepatic flow distribution (HFD), a known factor in pulmonary arteriovenous malformation progression, and identify methodological improvements needed to increase prediction accuracy. METHODS: Twelve single-ventricle patients who were enrolled in a surgical planning protocol for Fontan surgery with pre- and postoperative cardiac imaging were included in this study. Computational fluid dynamics were used to compare HFD in the surgical planning prediction and actual postoperative conditions. RESULTS: Overall, HFD prediction error was 17 ± 13%. This error was similar between surgery types (15 ± 18% and 18 ± 10% for revisions vs Fontan completions respectively; P = .73), but was significantly lower (6 ± 7%; P = .05) for hepatic to azygous shunts. Y-grafts and extracardiac conduits showed a strong correlation between prediction error and discrepancies in graft insertion points (r = 0.99; P < .001). Improving postoperative anatomy prediction significantly reduced overall HFD prediction error to 9 ± 6% (P = .03). CONCLUSIONS: Although Fontan surgical planning can offer accurate HFD predictions for specific graft types, methodological improvements are needed to increase overall accuracy. Specifically, improving postoperative anatomy prediction was shown to be an important target for future work. Future efforts and refinements to the surgical planning process will benefit from an improved understanding of the current state and will rely heavily on increased follow-up data.
Authors: Keshav Kohli; Zhenglun Alan Wei; Vahid Sadri; Tiffany Netto; John C Lisko; Adam B Greenbaum; Vasilis Babaliaros; John N Oshinski; Ajit P Yoganathan Journal: Ann Biomed Eng Date: 2021-03-15 Impact factor: 3.934
Authors: Nicolas Tobin; Bryan C Good; Jonathan D Plasencia; Mark A Fogel; William J Weiss; Keefe B Manning Journal: Ann Biomed Eng Date: 2022-04-22 Impact factor: 3.934
Authors: Zhenglun Wei; Shelly Singh-Gryzbon; Phillip M Trusty; Connor Huddleston; Yingnan Zhang; Mark A Fogel; Alessandro Veneziani; Ajit P Yoganathan Journal: Ann Biomed Eng Date: 2020-05-05 Impact factor: 3.934
Authors: Zhenglun Alan Wei; Camille Johnson; Phillip Trusty; Morgan Stephens; Wenjun Wu; Ritchie Sharon; Balaji Srimurugan; Brijesh P Kottayil; G S Sunil; Mark A Fogel; Ajit P Yoganathan; Mahesh Kappanayil Journal: Pediatr Cardiol Date: 2020-05-06 Impact factor: 1.655