Abstract

Although septal myectomy is the preferred treatment for medication-refractory hypertrophic obstructive cardiomyopathy (HOCM), the procedure remains subjective. A preoperative planning procedure is proposed using computational fluid dynamics simulations and shape optimization to assist in the objective assessment of the adequacy of the resection. 3 patients with HOCM were chosen for the application of the proposed procedure. The geometries of the preoperative left ventricular outflow tract (LVOT) of patients in the systolic phase were reconstructed from medical images. Computaional fluid dynamics (CFD) simulations were performed to assess hemodynamics within LVOT. Sensitivity analysis was performed to determine the resection extent on the septal wall, and the depth of the resection was optimized to relieve LVOT obstruction while minimizing damage to the septum. The optimized resection was then transferred from systole to diastole to provide surgeons with instructive guidance for septal myectomy. Comparison between preoperative and postoperative hemodynamics showed an evident improvement with respect to the pressure gradient throughout the LVOT. The resected myocardium in the diastolic phase is more extended and thinner than its state in the systolic phase. The proposed preoperative planning procedure may be a viable addition to the current preoperative assessment of patients with HOCM.

Details

Title
A preoperative planning procedure of septal myectomy for hypertrophic obstructive cardiomyopathy using image-based computational fluid dynamics simulations and shape optimization
Author
Ding, Zhihao 1 ; Liu, Qianwen 2 ; Luo, Huan 2 ; Yang, Ming 3 ; Zhang, Yining 4 ; Wang, Shilin 4 ; Luo, Yuanming 5 ; Chen, Shu 4 

 Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Department of Cardiovascular Surgery, Wuhan, China (GRID:grid.33199.31) (ISNI:0000 0004 0368 7223); Boea Wisdom (Hangzhou) Network Technology Co., Ltd., Department of Technology, Hangzhou, China (GRID:grid.33199.31) 
 Boea Wisdom (Hangzhou) Network Technology Co., Ltd., Department of Technology, Hangzhou, China (GRID:grid.33199.31) 
 Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Department of Radiology, Wuhan, China (GRID:grid.33199.31) (ISNI:0000 0004 0368 7223); Hubei Province Key Laboratory of Molecular Imaging, Wuhan, China (GRID:grid.412839.5) (ISNI:0000 0004 1771 3250) 
 Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Department of Cardiovascular Surgery, Wuhan, China (GRID:grid.33199.31) (ISNI:0000 0004 0368 7223) 
 The University of Iowa, Department of Mechanical Engineering, Iowa City, USA (GRID:grid.214572.7) (ISNI:0000 0004 1936 8294) 
Pages
24617
Publication year
2024
Publication date
2024
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
3118397501
Copyright
© The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.