High-resolution micro-Doppler imaging during neurosurgical resection of an arteriovenous malformation: illustrative case

Abstract

OBJECTIVE Given the high-risk nature of arteriovenous malformation (AVM) resections, accurate pre- and intraoperative imaging of the vascular morphology is a crucial component that may contribute to successful surgical results. Surprisingly, current gold standard imaging techniques for surgical guidance of AVM resections are mostly preoperative, lacking the necessary flexibility to cater to intraoperative changes. Micro-Doppler imaging is a unique high-resolution technique relying on high frame rate ultrasound and subsequent Doppler processing of microvascular hemodynamics. In this paper the authors report the first application of intraoperative, coregistered magnetic resonance/computed tomograpy, micro-Doppler imaging during the neurosurgical resection of an AVM in the parietal lobe. OBSERVATIONS The authors applied intraoperative two-dimensional and three-dimensional (3D) micro-Doppler imaging during resection and were able to identify key anatomical features including draining veins, supplying arteries and microvasculature in the nidus itself. Compared to the corresponding preoperative 3D-digital subtraction angiography (DSA) image, the micro-Doppler images could delineate vascular structures and visualize hemodynamics with higher, submillimeter scale detail, even at significant depths (>5 cm). Additionally, micro-Doppler imaging revealed unique microvascular morphology of surrounding healthy vasculature. LESSONS The authors conclude that micro-Doppler imaging in its current form has clear potential as an intraoperative counterpart to preoperative contrast-dependent DSA, and the microvascular details it provides could build new ground to further study cerebrovascular pathophysiology.

Case report: High-resolution, intra-operative µDoppler-imaging of spinal cord hemangioblastoma

“…What is more, in line with our previous report on µDoppler-imaging in the context of cerebral AVMs ( 32 ), real-time imaging of spinal cord hemodynamics and morphology has many other benefits than improving surgical decision-making alone: increasing our understanding of neurovascular pathology. Up until now, there is only a handful of reports in literature showing images of the human spinal cord ( 37 – 39 ).…”

“…Previously, our team has demonstrated the potential of µDoppler-imaging and its functional counterpart called ‘functional Ultrasound (fUS)’ during awake brain tumor resections, where we showed highly detailed functional maps and vascular morphology of a range of low and high-grade gliomas ( 31 ). Additionally, our team has evaluated the potential of µDoppler-imaging in the context of a cerebral arteriovenous malformation (AVM) ( 32 ), where the technique was able to identify key anatomical features including draining veins, supplying arteries and microvasculature in the AVM-nidus intra-operatively.…”

“…Literature reports recommendations on improving surgical safety and efficacy during hemangioblastoma resection by focusing on vascular details specifically ( 12 ). Compared to currently available ultrasound-based techniques such as CEUS which aim to image these vascular details ( 20 , 21 , 26 ), µDoppler-imaging would be able to achieve the same if not better resolution images without the need for a contrast agent ( 32 ). This means that µDoppler-imaging is continuous in nature, whereas CEUS is contrast bolus-dependent ( 20 , 21 , 26 ).…”

A deep learning classification task for brain navigation during functional ultrasound imaging

“…Applied in both preclinical (e.g., rodents [13][14][15][16] and non-human primates 17,18 ) and clinical contexts (e.g., neonates 19,20 and adults [21][22][23] ), functional ultrasound (fUS) imaging is a recently established technology that combines large depth-of-field and high spatiotemporal resolution [24][25][26] . By repeating the acquisition of micro-Doppler images over time, fUS imaging tracks the hemodynamics of small vessels 13,24,27 , reflecting neuronal activity 15,[28][29][30][31] .…”