Share Email Print
cover

Proceedings Paper

Feasibility of locating infarct core with 2D angiographic parametric imaging (API) using computed tomography perfusion data
Author(s): Ryan A. Rava; Ariana B. Allman; Mohammad Mahdi Shiraz Bhurwani; Kenneth V. Snyder; Elad I. Levy; Adnan H. Siddiqui; Jason M. Davies; Ciprian N. Ionita
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Four-dimensional computed tomography perfusion (CTP) provides the capability to validate angiographic parametric imaging (API) when locating infarct core. Similar results between these two methods could indicate API can be used to determine whether infarct core has changed following reperfusion procedures. CTP data from 20 patients treated for ischemic strokes was retrospectively collected and loaded into a Vitrea software to locate cerebral infarct tissue. The CTP data was then used to simulate anteroposterior (AP), lateral, and planar digital subtraction angiograms (DSA) for each time period through the perfusion scan. These simulated DSA sequences were used to generate API maps related to mean transit time (MTT), bolus arrival time (BAT), time to peak (TTP), area under the curve (AUC), and peak height (PH) parameters throughout the brain. Contralateral hemisphere comparisons of these values were conducted to determine infarct regions. The infarct regions from the Vitrea and API software were compared using a region of interest overlay method. For all patients, contralateral hemisphere percent differences of 40% for MTT, 20% for BAT, 35% for TTP, 55% for AUC, and 50% for PH are consistent with infarct regions. Using these percentages, the accuracy of API in labeling infarct tissue for the AP, lateral, and planar views is 84%, 70%, and 78% respectively. API conducted on CTP data from stroke patients successfully identified infarct tissue using AP and planar DSA’s. Lateral DSA studies indicate future work is necessary for improved results. This validates API is a feasible method for locating infarct core after reperfusion procedures.

Paper Details

Date Published: 1 March 2019
PDF: 14 pages
Proc. SPIE 10948, Medical Imaging 2019: Physics of Medical Imaging, 109485T (1 March 2019); doi: 10.1117/12.2511980
Show Author Affiliations
Ryan A. Rava, Canon Stroke and Vascular Research Ctr., Univ. at Buffalo (United States)
Ariana B. Allman, Canon Stroke and Vascular Research Ctr., Univ. at Buffalo (United States)
Mohammad Mahdi Shiraz Bhurwani, Canon Stroke and Vascular Research Ctr., Univ. at Buffalo (United States)
Kenneth V. Snyder, Canon Stroke and Vascular Research Ctr., Univ. at Buffalo (United States)
Univ. at Buffalo Jacobs School of Medicine (United States)
Elad I. Levy, Canon Stroke and Vascular Research Ctr., Univ. at Buffalo (United States)
Univ. at Buffalo Jacobs School of Medicine (United States)
Adnan H. Siddiqui, Canon Stroke and Vascular Research Ctr., Univ. at Buffalo (United States)
Univ. at Buffalo Jacobs School of Medicine (United States)
Jason M. Davies, Canon Stroke and Vascular Research Ctr., Univ. at Buffalo (United States)
Univ. at Buffalo Jacobs School of Medicine (United States)
Ciprian N. Ionita, Canon Stroke and Vascular Research Ctr., Univ. at Buffalo (United States)
Univ. at Buffalo Jacobs School of Medicine (United States)


Published in SPIE Proceedings Vol. 10948:
Medical Imaging 2019: Physics of Medical Imaging
Taly Gilat Schmidt; Guang-Hong Chen; Hilde Bosmans, Editor(s)

© SPIE. Terms of Use
Back to Top