Validation of automated Alberta Stroke Program Early CT Score (ASPECTS) software for detection of early ischemic changes on non-contrast brain CT scans.
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 N...
| Publicado en: | Neuroradiology Vol. 63; no. 4; pp. 491 - 499 |
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| Autores principales: | , , , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Springer Nature
Apr2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=149311256&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 149311256 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 00283940 NYZ jtl: Neuroradiology issn: 00283940 maglogo: N pubinfo: dt: Apr2021 vid: 63 iid: 4 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 149311256 145357727 149311256 149311256 10.1007/s00234-020-02533-6 149311256 ppf: 491 ppct: 8 formats: fmt: @attributes: type: P tig: atl: Validation of automated Alberta Stroke Program Early CT Score (ASPECTS) software for detection of early ischemic changes on non-contrast brain CT scans. aug: au: 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 affil: Department of Radiology & Nuclear Medicine, Erasmus MC, P. van Andel & L. Wolff, room Ne-515, Postbus 2040, 3000, Rotterdam, CA, the Netherlands sug: subj: Software Design Evaluation Brain Radiography Cerebral Ischemia Physiopathology Tomography, X-Ray Computed Ischemic Stroke Instrument Validation Clinical Assessment Tools Human Female Male Validation Studies Consensus Sensitivity and Specificity ROC Curve Intraclass Correlation Coefficient Descriptive Statistics Image Processing, Computer Assisted Female Male ab: 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. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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