Novel Software-Derived Workflow in Extracranial–Intracranial Bypass Surgery Validated by Transdural Indocyanine Green Videoangiography

Background The introduction of image-guided methods to bypass surgery has resulted in optimized preoperative identification of the recipients and excellent patency rates. However, the recently presented methods have also been resource-consuming. In the present study, we have reported a cost-efficient planning workflow for extracranial–intracranial (EC–IC) revascularization combined with transdural indocyanine green videoangiography (tICG-VA). Methods We performed a retrospective review at a single tertiary referral center from 2011 to 2018. A novel software-derived workflow was applied for 25 of 92 bypass procedures during the study period. The precision and accuracy were assessed using tICG-VA identification of the cortical recipients and a comparison of the virtual and actual data. The data from a control group of 25 traditionally planned procedures were also matched. Results The intraoperative transfer time of the calculated coordinates averaged 0.8 minute (range, 0.4–1.9 minutes). The definitive recipients matched the targeted branches in 80%, and a neighboring branch was used in 16%. Our workflow led to a significant craniotomy size reduction in the study group compared with that in the control group (P = 0.005). tICG-VA was successfully applied in 19 cases. An average of 2 potential recipient arteries were identified transdurally, resulting in tailored durotomy and 3 craniotomy adjustments. Follow-up patency results were available for 49 bypass surgeries, comprising 54 grafts. The overall patency rate was 91% at a median follow-up period of 26 months. No significant difference was found in the patency rate between the study and control groups (P = 0.317). Conclusions Our clinical results have validated the presented planning and surgical workflow and support the routine implementation of tICG-VA for recipient identification before durotomy.