Neurosurgical intraoperative ultrasonography using contrast enhanced superb microvascular imaging -vessel density and appearance time of the contrast agent.

BACKGROUND: Ultrasonography (US) provides real-time information on structures within the skull during neurosurgical operations. Superb microvascular imaging (SMI) is the latest imaging technique for detecting very low-velocity flow with minimal motion artifacts, and we have reported on this technique for intraoperative US monitoring. We combined SMI with administration of contrast agent to obtain detailed information during neurosurgical operations. MATERIALS AND METHODS: Twenty patients diagnosed with brain tumor (10 meningiomas, 5 glioblastomas, 2 hemangioblastomas, 1 schwannoma, 1 malignant lymphoma, 1 brain abscess) underwent neurosurgery under US with SMI and contrast agent techniques. Vessel density and appearance time following contrast administration were analyzed. RESULTS: Flow in numerous vessels was not visualized by SMI alone, but appeared following injection of contrast agent in all cases. Flow in tumors was drastically enhanced by contrast agent in schwannoma, hemangioblastoma and meningioma, compared to normal brain tissue. Flows in the dilated and bent vessels of glioblastoma were also enhanced, although flow in hypoechoic lymphoma remained inconspicuous. The characteristics of tumor vessels were clearly visualized and tumor borders were demonstrated by the difference between tumor flow and brain flow, by the increased tumor vessel density and decreased appearance time of contrast agent compared to normal brain vessels. CONCLUSIONS: The combination of SMI and contrast agent techniques for intraoperative US monitoring could provide innovative flow images of tumor and normal brain. The neurosurgeon obtains information about tumor flow and tumor borderline before tumor resection.

Mapping of flow velocity using spatiotemporal changes in time-intensity curves from indocyanine green videoangiography.

OBJECTIVE: The present study developed an image-based analysis method that uses indocyanine green videoangiography (ICG-VA) to measure flow velocity in the arteries and veins of the cortical surface in patients undergoing neurosurgery. METHODS: MATLAB-based code was used to correct motion artifacts in the ICG-VA and determine the time-intensity curve of the ICG. The slope of the initial increase in ICG intensity following the bolus injection was measured and normalized using the predicted input function in the imaging field. Flow velocity over a certain distance determined by the user was measured based on a time shift of the time-intensity curves along the centerline of the vessels. RESULTS: The normalized slope of ICG intensity represented the expected differences in the flow velocity among the artery (0.67 ± 0.05 s-1 ), parenchymal tissue (0.49 ± 0.10 s-1 ), and vein (0.44 ± 0.11 s-1 ). The flow velocities measured along the vessel centerline were 2.5 ± 1.1 cm/s and 1.1 ± 0.3 cm/s in the arteries (0.5 ± 0.2 mm in diameter) and veins (0.6 ± 0.2 mm in diameter), respectively. CONCLUSIONS: An image-based analysis method for ICG-VA was developed to map the expected differences in the flow velocity based on the rising slope of ICG intensity and to measure the absolute flow velocities using the flexible zone and cross-correlation methods.