TY - CHAP
T1 - Framework to Generate Perfusion Map from CT and CTA Images in Patients with Acute Ischemic Stroke
T2 - 9th International Workshop on Brain Lesion workshop, BrainLes 2023 and 3rd Stroke Workshop on Imaging and Treatment CHallenges, SWITCH 2023 Held in Conjunction with 26th Medical Image Computing and Computer Assisted Intervention, MICCAI 2023
AU - Tangwiriysakul, Chayanin
AU - Borges, Pedro
AU - Moriconi, Stefano
AU - Wright, Paul
AU - Mah, Yee Haur
AU - Teo, James
AU - Nachev, Parashkev
AU - Ourselin, Sebastien
AU - Cardoso, M. Jorge
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - Stroke is a leading cause of disability and death. Effective treatment decisions require early and informative vascular imaging. 4D perfusion imaging is ideal but rarely available within the first hour after stroke, whereas plain CT and CTA usually are. Hence, we propose a framework to extract a predicted perfusion map (PPM) derived from CT and CTA images. In all eighteen patients, we found significantly high spatial similarity (with average Spearman’s correlation = 0.7893) between our predicted perfusion map (PPM) and the T-max map derived from 4D-CTP. Voxelwise correlations between the PPM and National Institutes of Health Stroke Scale (NIHSS) subscores for L/R hand motor, gaze, and language on a large cohort of 2,110 subjects reliably mapped symptoms to expected infarct locations. Therefore our PPM could serve as an alternative for 4D perfusion imaging, if the latter is unavailable, to investigate blood perfusion in the first hours after hospital admission.
AB - Stroke is a leading cause of disability and death. Effective treatment decisions require early and informative vascular imaging. 4D perfusion imaging is ideal but rarely available within the first hour after stroke, whereas plain CT and CTA usually are. Hence, we propose a framework to extract a predicted perfusion map (PPM) derived from CT and CTA images. In all eighteen patients, we found significantly high spatial similarity (with average Spearman’s correlation = 0.7893) between our predicted perfusion map (PPM) and the T-max map derived from 4D-CTP. Voxelwise correlations between the PPM and National Institutes of Health Stroke Scale (NIHSS) subscores for L/R hand motor, gaze, and language on a large cohort of 2,110 subjects reliably mapped symptoms to expected infarct locations. Therefore our PPM could serve as an alternative for 4D perfusion imaging, if the latter is unavailable, to investigate blood perfusion in the first hours after hospital admission.
UR - http://www.scopus.com/inward/record.url?scp=85215785987&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-76160-7_15
DO - 10.1007/978-3-031-76160-7_15
M3 - Chapter
AN - SCOPUS:85215785987
SN - 9783031761591
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 154
EP - 162
BT - Brainlesion
A2 - Baid, Ujjwal
A2 - Dorent, Reuben
A2 - Malec, Sylwia
A2 - Pytlarz, Monika
A2 - Su, Ruisheng
A2 - Wijethilake, Navodini
A2 - Bakas, Spyridon
A2 - Crimi, Alessandro
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 8 October 2023 through 12 October 2023
ER -