Avoidance of ischemic complications after resection of a brain lesion based on intraoperative real-time recognition of the vasculature using laser speckle flow imaging

Abstract

OBJECTIVE To avoid ischemic complications, it is important to consider the arteries in resection planning for lesions such as a vascular intraparenchymal tumor and arteriovenous malformation. Here, the clinical application of laser speckle flow imaging (LSFI) as a complementary method for the management of mass lesion–related arteries during surgery was evaluated. METHODS LSFI was performed in 12 patients with mass lesion–related arteries and brain tumor or arteriovenous malformation. The portable LSFI device was centered over the surgical field, and the relative cerebral blood flow (CBF) before and after the temporary interruption of the arteries was measured through continuous recording. CBF fluctuations permitted the classification of 3 kinds of artery—a feeding artery (FA), a “passing through” artery (PA), and a combined FA and PA (FA+PA)—based on decreased relative CBF in the inner resection area and unchanged CBF in the surrounding area (FA), unchanged CBF in the inner area and decreased CBF in the surrounding area (PA), or decreased CBF in both areas (FA+PA). This information allowed the appropriate management of these arteries and avoidance of postoperative ischemic complications. RESULTS Good visualization of CBF in the surgical field and relative CBF measurements in the regions of interest were achieved in real time with excellent spatiotemporal resolution. In 11 patients (92%) and 20 regions of interest, a decline in CBF was observed after temporary interruption of the FA (n = 8), PA (n = 2), and FA+PA (n = 2) types. There was a significant average reduction in CBF of 15.3% ± 29.0%. There were no ischemic complications, and only 1 patient had a postoperative ischemic lesion caused by resection through an artery that could not be viewed by LSFI due to a positional problem. CONCLUSIONS LSFI permits noninvasive and rapid intraoperative real-time recognition of mass lesion–related vasculature. This information can be used to avoid ischemic complications as a procedure complementary to neurophysiological monitoring.