Abstract

Cerebral vasospasm is a dreaded sequelae of aneurysmal subarachnoid hemorrhage (aSAH), requiring timely intervention with therapeutic goals of improving brain perfusion. There are currently no standardized real-time, objective assessments of the interventional procedures performed to treat vasospasm. Here we describe real-time techniques to quantify cerebral perfusion during interventional cerebral angiography. We retrospectively analyzed 39 consecutive cases performed to treat clinical vasospasm and quantified the changes in perfusion metrics between pre- and post- verapamil administrations. With Digital Subtraction Angiography (DSA) perfusion analysis, we are able to identify hypoperfused territories and quantify the exact changes in cerebral perfusion for each individual case and vascular territory. We demonstrate that perfusion analysis for DSA can be performed in real time. This provides clinicians with a colorized map which directly visualizes hypoperfused tissue, combined with associated perfusion statistics. Quantitative thresholds and analysis based on DSA perfusion may assist with real-time dosage estimation and help predict response to treatment, however future prospective analysis is required for validation.

Details

Title
Computational methods for visualizing and measuring verapamil efficacy for cerebral vasospasm
Author
Abumoussa, Andrew 1 ; Flores, Alex 2 ; Ho, James 3 ; Niethammer, Marc 4 ; Sasaki-Adams, Deanna 5 ; Lee, Yueh Z 6 

 University of North Carolina, Department of Neurosurgery, Chapel Hill, USA (GRID:grid.410711.2) (ISNI:0000 0001 1034 1720); University of North Carolina, Department of Computer Science, Chapel Hill, USA (GRID:grid.410711.2) (ISNI:0000 0001 1034 1720) 
 University of North Carolina, School of Medicine, Chapel Hill, USA (GRID:grid.410711.2) (ISNI:0000 0001 1034 1720) 
 University of North Carolina, Department of Radiology, Chapel Hill, USA (GRID:grid.410711.2) (ISNI:0000 0001 1034 1720) 
 University of North Carolina, Department of Computer Science, Chapel Hill, USA (GRID:grid.410711.2) (ISNI:0000 0001 1034 1720) 
 University of North Carolina, Department of Neurosurgery, Chapel Hill, USA (GRID:grid.410711.2) (ISNI:0000 0001 1034 1720) 
 University of North Carolina, School of Medicine, Chapel Hill, USA (GRID:grid.410711.2) (ISNI:0000 0001 1034 1720); University of North Carolina, Department of Radiology, Chapel Hill, USA (GRID:grid.410711.2) (ISNI:0000 0001 1034 1720) 
Publication year
2020
Publication date
2020
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2471530835
Copyright
© The Author(s) 2020. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.