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Head CT deep learning model is highly accurate for early infarct estimation

Authors :
Romane Gauriau
Bernardo C. Bizzo
Donnella S. Comeau
James M. Hillis
Christopher P. Bridge
John K. Chin
Jayashri Pawar
Ali Pourvaziri
Ivana Sesic
Elshaimaa Sharaf
Jinjin Cao
Flavia T. C. Noro
Walter F. Wiggins
M. Travis Caton
Felipe Kitamura
Keith J. Dreyer
John F. Kalafut
Katherine P. Andriole
Stuart R. Pomerantz
Ramon G. Gonzalez
Michael H. Lev
Source :
Scientific reports. 13(1)
Publication Year :
2022

Abstract

Non-contrast head CT (NCCT) is extremely insensitive for early (2 > 0.98). When this 150 CT test set was expanded to include a total of 364 CT scans with a more heterogeneous distribution of infarct locations (94 stroke-negative, 270 stroke-positive mixed territory infarcts), model sensitivity was 97%, specificity 99%, for detection of infarcts larger than the 70 mL volume threshold used for patient selection in several major randomized controlled trials of thrombectomy treatment.

Subjects

Subjects :
Multidisciplinary

Details

ISSN :
20452322
Volume :
13
Issue :
1
Database :
OpenAIRE
Journal :
Scientific reports
Accession number :
edsair.doi.dedup.....1885ccb00088b6a641888d115188ee75