Abstract：
BACKGROUND: Coronary artery occlusion (CO) during transcatheter aortic valve replacement (TAVR) is a devastating complication. The objective is to assess the clinical impact of a novel computational predictive modeling algorithm for CO during TAVR planning.
METHODS: From January 2020 to December 2022, 116 patients (7.6%) undergoing TAVR evaluation were deemed at increased risk of CO based on traditional criteria. Patients underwent prospective computational modeling (DASI Simulations) to assess risk of CO during TAVR; procedural modifications and clinical results were reviewed retrospectively.
RESULTS: Of the 116 patients at risk for CO by traditional methodology, 53 had native aortic stenosis(45.7%), 47 a previous surgical AVR (40.5%), and 16 a prior TAVR (13.8%). Transcatheter valve choice, size, and/or implantation depth was modeled for all patients. Computational modeling predicted an increased risk of CO based in 39/116 (31.9%). Within this sub-cohort, 29 patients proceeded with TAVR. Procedural modifications to augment risk of CO included BASILICA (n=10), chimney coronary stents (n=8), coronary access without stent (n=3). There were no episodes of coronary compromise among patients following TAVR, either for those predicted to be at high risk of CO (with procedural modifications) or predicted low risk (standard TAVR).
CONCLUSIONS: Utilization of preoperative simulations for TAVR in patient-specific geometry through computational predictive modeling of CO was an effective enhancement to procedure planning.
METHODS: From January 2020 to December 2022, 116 patients (7.6%) undergoing TAVR evaluation were deemed at increased risk of CO based on traditional criteria. Patients underwent prospective computational modeling (DASI Simulations) to assess risk of CO during TAVR; procedural modifications and clinical results were reviewed retrospectively.
RESULTS: Of the 116 patients at risk for CO by traditional methodology, 53 had native aortic stenosis(45.7%), 47 a previous surgical AVR (40.5%), and 16 a prior TAVR (13.8%). Transcatheter valve choice, size, and/or implantation depth was modeled for all patients. Computational modeling predicted an increased risk of CO based in 39/116 (31.9%). Within this sub-cohort, 29 patients proceeded with TAVR. Procedural modifications to augment risk of CO included BASILICA (n=10), chimney coronary stents (n=8), coronary access without stent (n=3). There were no episodes of coronary compromise among patients following TAVR, either for those predicted to be at high risk of CO (with procedural modifications) or predicted low risk (standard TAVR).
CONCLUSIONS: Utilization of preoperative simulations for TAVR in patient-specific geometry through computational predictive modeling of CO was an effective enhancement to procedure planning.
摘要：
背景：经导管主动脉瓣置换术（TAVR）期间的冠状动脉闭塞（CO）是一种毁灭性的并发症。目的是评估TAVR计划期间CO的新型计算预测建模算法的临床影响。
方法：从2020年1月至2022年12月，根据传统标准，接受TAVR评估的116例患者（7.6%）被认为是CO风险增加。患者接受前瞻性计算模型（DASI模拟）以评估TAVR期间的CO风险；回顾性审查了程序修改和临床结果。
结果：在116例通过传统方法有CO风险的患者中，53例患者为固有主动脉瓣狭窄（45.7%），47以前的手术AVR（40.5%），和16个先前的TAVR（13.8%）。经导管瓣膜的选择,尺寸,和/或对所有患者的植入深度进行建模。计算模型预测39/116(31.9%)的CO风险增加。在这个子队列中，29例患者继续进行TAVR。增加CO风险的程序性修改包括BASILICA（n=10），烟囱冠状动脉支架（n=8），无支架冠状动脉通路（n=3）。TAVR后的患者中没有冠状动脉损害的发作，对于那些预测为CO高风险（通过程序修改）或预测为低风险（标准TAVR）的人。
结论：通过CO的计算预测建模，在患者特定的几何结构中对TAVR进行术前模拟是对手术计划的有效增强。
方法：从2020年1月至2022年12月，根据传统标准，接受TAVR评估的116例患者（7.6%）被认为是CO风险增加。患者接受前瞻性计算模型（DASI模拟）以评估TAVR期间的CO风险；回顾性审查了程序修改和临床结果。
结果：在116例通过传统方法有CO风险的患者中，53例患者为固有主动脉瓣狭窄（45.7%），47以前的手术AVR（40.5%），和16个先前的TAVR（13.8%）。经导管瓣膜的选择,尺寸,和/或对所有患者的植入深度进行建模。计算模型预测39/116(31.9%)的CO风险增加。在这个子队列中，29例患者继续进行TAVR。增加CO风险的程序性修改包括BASILICA（n=10），烟囱冠状动脉支架（n=8），无支架冠状动脉通路（n=3）。TAVR后的患者中没有冠状动脉损害的发作，对于那些预测为CO高风险（通过程序修改）或预测为低风险（标准TAVR）的人。
结论：通过CO的计算预测建模，在患者特定的几何结构中对TAVR进行术前模拟是对手术计划的有效增强。
