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Oral Presentation

Cerebrovascular

Mummaneni Award: Intraoperative Microscope-Integrated ICG- FLOW 800 Data Analysis to Predict Surgical Outcomes in patients with Moyamoya Disease

Saturday, May 4, 2024
2:23 PM – 2:29 PM CT
Location:  S403ab
Disclosure(s):
Nadia Atai: No financial relationships to disclose
Jonathan Russin, MD: No financial relationships to disclose
Gary K. Steinberg, MD, PhD: Carl Zeiss Meditech AG: Consultant (Ongoing); Peter Lazic, US: Royalty Recipient (Ongoing); SanBio: Consultant (Ongoing); Surgical Theater: Consultant (Ongoing)
Introduction: Bypass surgery is an effective strategy for stroke prevention in Moyamoya disease (MMD). The ability to anticipate suboptimal clinical outcomes based on preoperative blood flow patterns would invaluably inform revascularization strategies. Microscope-integrated Flow800-based software uses indocyanine green (ICG) to non-invasively measure changes in cortical perfusion during bypass. Previous studies have validated the use of this software to predict post-operative events, but sample sizes have been limited to date. Here we are investigating the utility of ICG-FLOW 800 data for predicting surgical outcomes in MMD using a large cohort of patients.

Methods: A prospective database was reviewed to identify all patients who received cerebral bypass for MMD between 2018-2023. Demographic, clinical, and perioperative information were recorded. Intraoperative flow assessment using ICG-based software (Flow800) was performed immediately prior to initiation of and after the completion of the anastomosis. T-tests and non-parametric equivalents were performed to assess the relationship between recorded flow metrics and clinical outcomes. Regression models were developed in RStudio using the pre- and post-bypass Flow800 data.

Results: One hundred twenty-five patients were studied. One hundred twenty-three patients (98%) received extracranial-intracranial constructs and two received intracranial-intracranial constructs. Forty-six patients (36.8%) experienced new neurologic changes in the immediate postoperative period. None of the recorded clinical or demographic data correlated significantly with the occurrence of these events. Of the Flow800 metrics, only the pre-anastomosis arterial flow speed was significantly associated with the development of postoperative neurologic events (p = 0.024). Multivariate logistic regression revealed an association between post-bypass reductions in venous flow speed (p= 0.079), arterial flow delay (0.091), and cortical rise time (0.079) with the development of postoperative neurologic events. The regression analysis was used to develop a model that predicted the occurrence of these postoperative neurologic changes with an accuracy of 67%.

Conclusion : Here we report first large-scale cohort study on intraoperative ICG-Flow800 which is an effective method for assessing cerebral blood flow and has the potential to predict postoperative outcomes in those undergoing revascularization.