PortalPublikationenEffect of CAD on performance in ASPECTS reading

Effect of CAD on performance in ASPECTS reading

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Effect of CAD on performance in ASPECTS reading. / Ernst, Marielle; Bernhardt, Martina; Bechstein, Matthias; Schön, Gerhard; Fiehler, Jens; Majoie, Charles B.L.M.; Marquering, Henk A.; van Zwam, Wim H.; Dippel, Diederik W.J.; van Oostenbrugge, Robert J.; Goebell, Einar.

in: Informatics in Medicine Unlocked, Jahrgang 18, 2020.

Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung

Harvard

Ernst, M, Bernhardt, M, Bechstein, M, Schön, G, Fiehler, J, Majoie, CBLM, Marquering, HA, van Zwam, WH, Dippel, DWJ, van Oostenbrugge, RJ & Goebell, E 2020, 'Effect of CAD on performance in ASPECTS reading', Informatics in Medicine Unlocked, Jg. 18. https://doi.org/10.1016/j.imu.2020.100295

APA

Ernst, M., Bernhardt, M., Bechstein, M., Schön, G., Fiehler, J., Majoie, C. B. L. M., Marquering, H. A., van Zwam, W. H., Dippel, D. W. J., van Oostenbrugge, R. J., & Goebell, E. (2020). Effect of CAD on performance in ASPECTS reading. Informatics in Medicine Unlocked, 18. https://doi.org/10.1016/j.imu.2020.100295

Vancouver

Ernst M, Bernhardt M, Bechstein M, Schön G, Fiehler J, Majoie CBLM et al. Effect of CAD on performance in ASPECTS reading. Informatics in Medicine Unlocked. 2020;18. https://doi.org/10.1016/j.imu.2020.100295

Bibtex

@article{a0fb1b67c3444a57ad89cc78acb8df02,
title = "Effect of CAD on performance in ASPECTS reading",
abstract = "Background and purpose While computer-aided diagnosis (CAD) tools are widely used in stroke imaging routines already, their influence on actual decision-making is still underexplored. We analyzed the effect of a simulated CAD tool on ASPECT-Scoring on acute-stroke CT-scans with respect to experience level. Materials and methods Baseline CT scans of 100 stroke patients from the MR CLEAN trial with consensus-ASPECTS as ground truth were independently ASPECTS graded by three readers with different levels of experience. Weeks later the same CTs were re-analyzed with additional displaying of simulated ASPECTS (s-ASPECTS, by adding or subtracting 2 points from the ground truth). Readers were told that the score was generated by an automatic ASPECT-Scoring algorithm. The influence of the displayed s-ASPECTS on the readers{\textquoteright} second ASPECT-Scoring was analyzed by using a linear mixed model and the reliability was assessed. Performance was measured as the absolute difference between readers ASPECTS and consensus-ASPECTS. Results The influence of the s-ASPECTS on the second ASPECT-Scoring was the lowest for the reader with the most experience in neuroradiology, while the other readers were significantly more influenced. All readers veered further away from the ground truth in their second ASPECT-Scoring with the s-ASPECTS, though not significantly. Overall interrater reliability was excellent (ICC = 0.94 [0.92–0.96]). Conclusions ASPECT-Scoring may be significantly influenced by simulated ASPECTS displayed by a suboptimal CAD tool, especially in readers with less experience, and performance tends to decrease.",
keywords = "Computed tomography, Ischemic stroke, Diagnostic method, Alberta stroke program early CT score, Machine learning",
author = "Marielle Ernst and Martina Bernhardt and Matthias Bechstein and Gerhard Sch{\"o}n and Jens Fiehler and Majoie, {Charles B.L.M.} and Marquering, {Henk A.} and {van Zwam}, {Wim H.} and Dippel, {Diederik W.J.} and {van Oostenbrugge}, {Robert J.} and Einar Goebell",
year = "2020",
doi = "10.1016/j.imu.2020.100295",
language = "Deutsch",
volume = "18",

}

RIS

TY - JOUR

T1 - Effect of CAD on performance in ASPECTS reading

AU - Ernst, Marielle

AU - Bernhardt, Martina

AU - Bechstein, Matthias

AU - Schön, Gerhard

AU - Fiehler, Jens

AU - Majoie, Charles B.L.M.

AU - Marquering, Henk A.

AU - van Zwam, Wim H.

AU - Dippel, Diederik W.J.

AU - van Oostenbrugge, Robert J.

AU - Goebell, Einar

PY - 2020

Y1 - 2020

N2 - Background and purpose While computer-aided diagnosis (CAD) tools are widely used in stroke imaging routines already, their influence on actual decision-making is still underexplored. We analyzed the effect of a simulated CAD tool on ASPECT-Scoring on acute-stroke CT-scans with respect to experience level. Materials and methods Baseline CT scans of 100 stroke patients from the MR CLEAN trial with consensus-ASPECTS as ground truth were independently ASPECTS graded by three readers with different levels of experience. Weeks later the same CTs were re-analyzed with additional displaying of simulated ASPECTS (s-ASPECTS, by adding or subtracting 2 points from the ground truth). Readers were told that the score was generated by an automatic ASPECT-Scoring algorithm. The influence of the displayed s-ASPECTS on the readers’ second ASPECT-Scoring was analyzed by using a linear mixed model and the reliability was assessed. Performance was measured as the absolute difference between readers ASPECTS and consensus-ASPECTS. Results The influence of the s-ASPECTS on the second ASPECT-Scoring was the lowest for the reader with the most experience in neuroradiology, while the other readers were significantly more influenced. All readers veered further away from the ground truth in their second ASPECT-Scoring with the s-ASPECTS, though not significantly. Overall interrater reliability was excellent (ICC = 0.94 [0.92–0.96]). Conclusions ASPECT-Scoring may be significantly influenced by simulated ASPECTS displayed by a suboptimal CAD tool, especially in readers with less experience, and performance tends to decrease.

AB - Background and purpose While computer-aided diagnosis (CAD) tools are widely used in stroke imaging routines already, their influence on actual decision-making is still underexplored. We analyzed the effect of a simulated CAD tool on ASPECT-Scoring on acute-stroke CT-scans with respect to experience level. Materials and methods Baseline CT scans of 100 stroke patients from the MR CLEAN trial with consensus-ASPECTS as ground truth were independently ASPECTS graded by three readers with different levels of experience. Weeks later the same CTs were re-analyzed with additional displaying of simulated ASPECTS (s-ASPECTS, by adding or subtracting 2 points from the ground truth). Readers were told that the score was generated by an automatic ASPECT-Scoring algorithm. The influence of the displayed s-ASPECTS on the readers’ second ASPECT-Scoring was analyzed by using a linear mixed model and the reliability was assessed. Performance was measured as the absolute difference between readers ASPECTS and consensus-ASPECTS. Results The influence of the s-ASPECTS on the second ASPECT-Scoring was the lowest for the reader with the most experience in neuroradiology, while the other readers were significantly more influenced. All readers veered further away from the ground truth in their second ASPECT-Scoring with the s-ASPECTS, though not significantly. Overall interrater reliability was excellent (ICC = 0.94 [0.92–0.96]). Conclusions ASPECT-Scoring may be significantly influenced by simulated ASPECTS displayed by a suboptimal CAD tool, especially in readers with less experience, and performance tends to decrease.

KW - Computed tomography

KW - Ischemic stroke

KW - Diagnostic method

KW - Alberta stroke program early CT score

KW - Machine learning

U2 - 10.1016/j.imu.2020.100295

DO - 10.1016/j.imu.2020.100295

M3 - SCORING: Zeitschriftenaufsatz

VL - 18

ER -