Neuroradiology · 2020
Validation of automated Alberta Stroke Program Early CT Score (ASPECTS) software for detection of early ischemic changes on non-contrast brain CT scans.
СтатьяМногоцентровое исследованиеРандомизированное исследованиеНазвание и аннотация: Перевод в очереди
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Wolff Lennard, Berkhemer Olvert A, van Es Adriaan C G M, van Zwam Wim H, Dippel Diederik W J, Majoie Charles B L M, van Walsum Theo, van der Lugt Aad, MR CLEAN Investigators
Аннотация
PURPOSE: In ASPECTS, 10 brain regions are scored visually for presence of acute ischemic stroke damage. We evaluated automated ASPECTS in comparison to expert readers.
METHODS: Consecutive, baseline non-contrast CT-scans (5-mm slice thickness) from the prospective MR CLEAN trial (n = 459, MR CLEAN Netherlands Trial Registry number: NTR1804) were evaluated. A two-observer consensus for ASPECTS regions (normal/abnormal) was used as reference standard for training and testing (0.2/0.8 division). Two other observers provided individual ASPECTS-region scores. The Automated ASPECTS software was applied. A region score specificity of ≥ 90% was used to determine the software threshold for detection of an affected region based on relative density difference between affected and contralateral region. Sensitivity, specificity, and receiver-operating characteristic curves were calculated. Additionally, we assessed intraclass correlation coefficients (ICCs) for automated ASPECTS and observers in comparison to the reference standard in the test set.
RESULTS: In the training set (n = 104), with software thresholds for a specificity of ≥ 90%, we found a sensitivity of 33-49% and an area under the curve (AUC) of 0.741-0.785 for detection of an affected ASPECTS region. In the test set (n = 355), the results for the found software thresholds were 89-89% (specificity), 41-57% (sensitivity), and 0.750-0.795 (AUC). Comparison of automated ASPECTS with the reference standard resulted in an ICC of 0.526. Comparison of observers with the reference standard resulted in an ICC of 0.383-0.464.
CONCLUSION: The performance of automated ASPECTS is comparable to expert readers and could support readers in the detection of early ischemic changes.
METHODS: Consecutive, baseline non-contrast CT-scans (5-mm slice thickness) from the prospective MR CLEAN trial (n = 459, MR CLEAN Netherlands Trial Registry number: NTR1804) were evaluated. A two-observer consensus for ASPECTS regions (normal/abnormal) was used as reference standard for training and testing (0.2/0.8 division). Two other observers provided individual ASPECTS-region scores. The Automated ASPECTS software was applied. A region score specificity of ≥ 90% was used to determine the software threshold for detection of an affected region based on relative density difference between affected and contralateral region. Sensitivity, specificity, and receiver-operating characteristic curves were calculated. Additionally, we assessed intraclass correlation coefficients (ICCs) for automated ASPECTS and observers in comparison to the reference standard in the test set.
RESULTS: In the training set (n = 104), with software thresholds for a specificity of ≥ 90%, we found a sensitivity of 33-49% and an area under the curve (AUC) of 0.741-0.785 for detection of an affected ASPECTS region. In the test set (n = 355), the results for the found software thresholds were 89-89% (specificity), 41-57% (sensitivity), and 0.750-0.795 (AUC). Comparison of automated ASPECTS with the reference standard resulted in an ICC of 0.526. Comparison of observers with the reference standard resulted in an ICC of 0.383-0.464.
CONCLUSION: The performance of automated ASPECTS is comparable to expert readers and could support readers in the detection of early ischemic changes.