Intraoperative Anatomical and Hemodynamic Analysis of Intracerebral Arteriovenous Malformations by Semi-quantitative Color-coded Indocyanine Green Videoangiography

Role of Indocyanine Green with FLOW 800 in Removal of Hidden Arteriovenous Malformations

OBJECTIVE

Indocyanine green videoangiography (ICG-VA) with FLOW 800 (Carl Zeiss AG) has been used as a visualization tool to guide arteriovenous malformation (AVM) surgery since 2011. We performed a systematic review and evaluated the quality of evidence available on this topic. In addition, we present a series of our own cases demonstrating the unique use of ICG-VA in the localization and removal of deeper seated AVMs.

METHODS

Using the PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analyses) guidelines for systematic reviews, we identified studies related to ICG-VA with FLOW 800 in AVM surgeries using search terms. The studies were screened and reviewed, and the quality of evidence was analyzed using the GRADE (Grading of Recommendations Assessment, Development, and Evaluation) criteria. We performed a retrospective review of our own cases of AVM removal with ICG-VA and FLOW 800.

RESULTS

Our search revealed 27 relevant studies, 17 of which met our inclusion criteria. The quality of the body of evidence was determined to be "very low" using the GRADE criteria. We used ICG-VA with FLOW 800 analysis for 14 cases of microsurgical AVM removal. This technique provided unique insights into the localization of deep seated AVMs in 8 cases (57%). No residual AVM was found when assessed by the 6-month follow-up angiogram.

CONCLUSIONS

We present cases highlighting the usefulness of this technique for the localization of certain AVMs. We believe the use of ICG-VA can guide the removal of deeper seated AVMs, because it can reveal surface feeders and draining veins that can be followed to a hidden nidus. Larger, registry-based studies are needed to confirm these findings and improve the overall quality of evidence.

Microsurgical Treatment of Deep and Eloquent AVMs

Over the past 30 years, the treatment of deep and eloquent arteriovenous malformations (AVMs) has moved away from microneurosurgical resection and towards medical management and the so-called minimally invasive techniques, such as endovascular embolization and radiosurgery. The Spetzler-Martin grading system (and subsequent modifications) has done much to aid in risk stratification for surgical intervention; however, the system does not predict the risk of hemorrhage nor risk from other interventions. In more recent years, the ARUBA trial has suggested that unruptured AVMs should be medically managed. In our experience, although these eloquent regions of the brain should be discussed with patients in assessing the risks and benefits of intervention, we believe each AVM should be assessed based on the characteristics of the patient and the angio-architecture of the AVM, in particular venous hypertension, which may guide us to treat even high-grade AVMs when we believe we can (and need to) to benefit the patient. Advances in imaging and intraoperative adjuncts have helped us in decision making, preoperative planning, and ensuring good outcomes for our patients. Here, we present several cases to illustrate our primary points that treating low-grade AVMs can be more difficult than treating high-grade ones, mismanagement of deep and eloquent AVMs at the behest of dogma can harm patients, and the treatment of any AVM should be tailored to the individual patient and that patient's lesion.

Automated Quantitative Analysis of Blood Flow in Extracranial-Intracranial Arterial Bypass Based on Indocyanine Green Angiography

Microvascular imaging based on indocyanine green is an important tool for surgeons who carry out extracranial–intracranial arterial bypass surgery. In terms of blood perfusion, indocyanine green images contain abundant information, which cannot be effectively interpreted by humans or currently available commercial software. In this paper, an automatic processing framework for perfusion assessments based on indocyanine green videos is proposed and consists of three stages, namely, vessel segmentation based on the UNet deep neural network, preoperative and postoperative image registrations based on scale-invariant transform features, and blood flow evaluation based on the Horn–Schunck optical flow method. This automatic processing flow can reveal the blood flow direction and intensity curve of any vessel, as well as the blood perfusion changes before and after an operation. Commercial software embedded in a microscope is used as a reference to evaluate the effectiveness of the algorithm in this study. A total of 120 patients from multiple centers were sampled for the study. For blood vessel segmentation, a Dice coefficient of 0.80 and a Jaccard coefficient of 0.73 were obtained. For image registration, the success rate was 81%. In preoperative and postoperative video processing, the coincidence rates between the automatic processing method and commercial software were 89 and 87%, respectively. The proposed framework not only achieves blood perfusion analysis similar to that of commercial software but also automatically detects and matches blood vessels before and after an operation, thus quantifying the flow direction and enabling surgeons to intuitively evaluate the perfusion changes caused by bypass surgery.