Generating High Quality, High Resolution, Patient-Specific 4D Models of Cerebral Vasculature

NIH RePORTER · NIH · R01 · $394,695 · view on reporter.nih.gov ↗

Abstract

Abstract Neurovascular diseases, including stroke, aneurysms, and arteriovenous malformations, can cause devastating and life-threatening injury to the brain. Each year these diseases affect nearly 1 million people in the US. Stroke alone kills more than 130,000 Americans each year. Effective treatment of these diseases requires understanding the cerebrovascular architecture, which is complex and patient specific. Existing clinically available methods for imaging blood vessels in the brain are limited by several factors, including spatial and temporal resolution, the need for ionizing radiation or contrast agents, and the lack of availability of some types of imaging during surgical procedures. We propose to generate patient-specific 4D models of cerebral vasculature with unprecedented spatial and temporal resolution from a single pair of 2D Digital Subtraction Angiography (DSA) image sequences. Two important advantages of using DSA are: 1) it has high spatial and temporal resolution; and 2) it is readily available both pre-operatively, for planning surgery, and intra-operatively, for monitoring the surgical procedure. To pursue this goal, we will investigate novel approaches for contouring vessels in DSA images, extracting information about blood flow with high temporal resolution from DSA video sequences, and annotating the contoured vessels with this temporal data. We will expand our recent work on constrained 2D-to-3D reconstruction for generating patient-specific 4D cerebrovascular models that will exploit these annotated vessel contours. The resultant models will support vessels as small as 0.1 mm3 and flow rates up to 15 frames per second, a 10-fold improvement in spatial and/or temporal resolution over models generated from clinically available MRA, CTA and rotational DSA. Finally, we will develop new software for visualizing and interacting with these 4D models and give surgeons the ability to virtually inject a bolus of contrast at any point in the vascular network to observe downstream flow. This software will give neurosurgeons a better understanding of their patient’s cerebral vasculature, allowing them to plan and perform safer and more effective neurovascular surgery.

Key facts

NIH application ID
10810843
Project number
5R01EB034223-02
Recipient
BRIGHAM AND WOMEN'S HOSPITAL
Principal Investigator
SARAH FRISKEN
Activity code
R01
Funding institute
NIH
Fiscal year
2024
Award amount
$394,695
Award type
5
Project period
2023-04-01 → 2027-03-31