Intraoperative evaluation of local cerebral hemodynamic change by indocyanine green videoangiography: prediction of incidence and duration of postoperative transient neurological events in patients with moyamoya disease
Authors: Uda Kenji , Araki Yoshio , Muraoka Shinsuke , Ota Shinji , Wada Kentaro , Yokoyama Kinya , Nishihori Masahiro , Izumi Takashi , Okamoto Sho , Wakabayashi Toshihiko 
Published: April 2018

OBJECTIVE

Transient neurological events (TNEs) occur frequently in the acute phase after direct bypass surgery for moyamoya disease (MMD), but there is currently no way to predict them. FlowInsight is a specialized software for analyzing indocyanine green (ICG) videoangiography taken with a surgical microscope. The purpose of this study was to investigate whether intraoperative evaluation of local hemodynamic changes around anastomotic sites using FlowInsight could predict the incidence and duration of TNEs.

METHODS

From patients who were diagnosed with MMD in our hospital between August 2014 and March 2017 and who underwent superficial temporal artery–middle cerebral artery bypass surgery, we investigated 25 hemispheres (in 22 patients) in which intraoperative ICG analysis was performed using FlowInsight. To evaluate the local cerebral hemodynamics before and after anastomosis, regions of interest were set at 3 locations on the brain surface around the anastomotic site, and the mean cerebral blood flow (CBF), mean gradation (Grad), mean transit time (MTT), and mean time to peak (TTP) were calculated from the 3 regions of interest. Furthermore, the change rate in CBF (ΔCBF [%]) was calculated using the formula (postanastomosis mean CBF − preanastomosis mean CBF)/preanastomosis mean CBF. ΔGrad (%), ΔMTT (%), and ΔTTP (%) were similarly calculated.

RESULTS

Postoperative stroke without TNE occurred in 2 of the 25 hemispheres. These 2 hemispheres (in 2 patients) were excluded from the study, and data from the remaining 23 hemispheres (in 20 patients) were analyzed. For each parameter (ΔCBF, ΔGrad, ΔMTT, and ΔTTP) calculated by FlowInsight, the difference between the groups with and without TNEs was significant. The median values for ΔCBF and ΔGrad were significantly higher in the TNE group than in the no-TNE group (ΔCBF 30.13 vs 3.54, p = 0.0106; ΔGrad 62.05 vs 10.78, p = 0.00435), whereas the median values for ΔMTT and ΔTTP were significantly lower in the TNE group (ΔMTT −16.90 vs −7.393, p = 0.023; ΔTTP −29.07 vs −7.02, p = 0.00342). Comparison of the area under the curve (AUC) for each parameter showed that ΔTTP had the highest AUC and was the parameter with the highest diagnostic accuracy (AUC 0.857). The Youden index revealed that the optimal cutoff value of ΔTTP was −11.61 (sensitivity 77.8%, specificity 71.4%) as a predictor of TNEs. In addition, Spearman’s rank correlation coefficients were calculated, and ΔCBF, ΔGrad, ΔMTT, and ΔTTP each showed a strong correlation with the duration of TNEs. The larger the change in each parameter, the longer the TNEs persisted.

CONCLUSIONS

Intraoperative ICG videoangiography findings were correlated with the occurrence and duration of TNEs after direct bypass surgery for MMD. Screening for cases at high risk of TNEs can be achieved by ICG analysis using FlowInsight.