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

Publication ,  Journal Article
Gauriau, R; Bizzo, BC; Comeau, DS; Hillis, JM; Bridge, CP; Chin, JK; Pawar, J; Pourvaziri, A; Sesic, I; Sharaf, E; Cao, J; Noro, FTC; Lev, MH ...
Published in: Sci Rep
January 5, 2023

Non-contrast head CT (NCCT) is extremely insensitive for early (< 3-6 h) acute infarct identification. We developed a deep learning model that detects and delineates suspected early acute infarcts on NCCT, using diffusion MRI as ground truth (3566 NCCT/MRI training patient pairs). The model substantially outperformed 3 expert neuroradiologists on a test set of 150 CT scans of patients who were potential candidates for thrombectomy (60 stroke-negative, 90 stroke-positive middle cerebral artery territory only infarcts), with sensitivity 96% (specificity 72%) for the model versus 61-66% (specificity 90-92%) for the experts; model infarct volume estimates also strongly correlated with those of diffusion MRI (r2 > 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.

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Published In

Sci Rep

DOI

EISSN

2045-2322

Publication Date

January 5, 2023

Volume

13

Issue

1

Start / End Page

189

Location

England

Related Subject Headings

  • Tomography, X-Ray Computed
  • Stroke
  • Magnetic Resonance Imaging
  • Infarction, Middle Cerebral Artery
  • Humans
  • Deep Learning
 

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Gauriau, R., Bizzo, B. C., Comeau, D. S., Hillis, J. M., Bridge, C. P., Chin, J. K., … Lev, M. H. (2023). Head CT deep learning model is highly accurate for early infarct estimation. Sci Rep, 13(1), 189. https://doi.org/10.1038/s41598-023-27496-5
Gauriau, Romane, Bernardo C. Bizzo, Donnella S. Comeau, James M. Hillis, Christopher P. Bridge, John K. Chin, Jayashri Pawar, et al. “Head CT deep learning model is highly accurate for early infarct estimation.Sci Rep 13, no. 1 (January 5, 2023): 189. https://doi.org/10.1038/s41598-023-27496-5.
Gauriau R, Bizzo BC, Comeau DS, Hillis JM, Bridge CP, Chin JK, et al. Head CT deep learning model is highly accurate for early infarct estimation. Sci Rep. 2023 Jan 5;13(1):189.
Gauriau, Romane, et al. “Head CT deep learning model is highly accurate for early infarct estimation.Sci Rep, vol. 13, no. 1, Jan. 2023, p. 189. Pubmed, doi:10.1038/s41598-023-27496-5.
Gauriau R, Bizzo BC, Comeau DS, Hillis JM, Bridge CP, Chin JK, Pawar J, Pourvaziri A, Sesic I, Sharaf E, Cao J, Noro FTC, Wiggins WF, Caton MT, Kitamura F, Dreyer KJ, Kalafut JF, Andriole KP, Pomerantz SR, Gonzalez RG, Lev MH. Head CT deep learning model is highly accurate for early infarct estimation. Sci Rep. 2023 Jan 5;13(1):189.

Published In

Sci Rep

DOI

EISSN

2045-2322

Publication Date

January 5, 2023

Volume

13

Issue

1

Start / End Page

189

Location

England

Related Subject Headings

  • Tomography, X-Ray Computed
  • Stroke
  • Magnetic Resonance Imaging
  • Infarction, Middle Cerebral Artery
  • Humans
  • Deep Learning