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Inter-rater reliability for assessing intracranial collaterals in patients with acute ischemic stroke: comparing 29 raters and an artificial intelligence-based software

Purpose Outcome of endovascular treatment in acute ischemic stroke patients is depending on the collateral circulation maintaining blood flow to the ischemic territory. We evaluated the inter-rater reliability and accuracy of raters and an automated algorithm for assessing the collateral score (CS,...

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Published in:Neuroradiology 2022-12, Vol.64 (12), p.2277-2284
Main Authors: Wolff, Lennard, Su, Jiahang, Van Loon, Derek, van Es, Adriaan, van Doormaal, Pieter Jan, Majoie, Charles, van Zwam, Wim, Dippel, Diederik, van der Lugt, Aad, van Walsum, Theo
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cited_by cdi_FETCH-LOGICAL-c474t-334948086d65d54e3b59362c7e8a5c5595d25bfd7a9bdc5a44c79025417989263
cites cdi_FETCH-LOGICAL-c474t-334948086d65d54e3b59362c7e8a5c5595d25bfd7a9bdc5a44c79025417989263
container_end_page 2284
container_issue 12
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container_title Neuroradiology
container_volume 64
creator Wolff, Lennard
Su, Jiahang
Van Loon, Derek
van Es, Adriaan
van Doormaal, Pieter Jan
Majoie, Charles
van Zwam, Wim
Dippel, Diederik
van der Lugt, Aad
van Walsum, Theo
description Purpose Outcome of endovascular treatment in acute ischemic stroke patients is depending on the collateral circulation maintaining blood flow to the ischemic territory. We evaluated the inter-rater reliability and accuracy of raters and an automated algorithm for assessing the collateral score (CS, range: 0–3) in acute ischemic stroke patients. Methods Baseline CTA scans with an intracranial anterior occlusion from the MR CLEAN study ( n =500) were used. For each core lab CS, ten CTA scans with sufficient quality were randomly selected. After a training session in collateral scoring, all selected CTA scans were individually evaluated for a visual CS by three groups: 7 radiologists, 13 junior and 9 senior radiology residents. Two additional radiologists scored CS to be used as reference, with a third providing a CS to produce a 2 out of 3 consensus CS in case of disagreement. An automated algorithm was also used to compute CS. Inter-rater agreement was reported with intraclass correlation coefficient (ICC). Accuracy of visual and automated CS were calculated. Results 39 CTA scans were assessed (1 corrupt CTA-scan excluded). All groups showed a moderate ICC (0.689-0.780) in comparison to the reference standard. Overall human accuracy was 65± 7% and increased to 88± 5% for dichotomized CS (0–1, 2–3). Automated CS accuracy was 62%, and 90% for dichotomized CS. No significant difference in accuracy was found between groups with different levels of expertise. Conclusion After training, inter-rater reliability in collateral scoring was not influenced by experience. Automated CS performs similar to residents and radiologists in determining a collateral score.
doi_str_mv 10.1007/s00234-022-02984-z
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We evaluated the inter-rater reliability and accuracy of raters and an automated algorithm for assessing the collateral score (CS, range: 0–3) in acute ischemic stroke patients. Methods Baseline CTA scans with an intracranial anterior occlusion from the MR CLEAN study ( n =500) were used. For each core lab CS, ten CTA scans with sufficient quality were randomly selected. After a training session in collateral scoring, all selected CTA scans were individually evaluated for a visual CS by three groups: 7 radiologists, 13 junior and 9 senior radiology residents. Two additional radiologists scored CS to be used as reference, with a third providing a CS to produce a 2 out of 3 consensus CS in case of disagreement. An automated algorithm was also used to compute CS. Inter-rater agreement was reported with intraclass correlation coefficient (ICC). Accuracy of visual and automated CS were calculated. Results 39 CTA scans were assessed (1 corrupt CTA-scan excluded). All groups showed a moderate ICC (0.689-0.780) in comparison to the reference standard. Overall human accuracy was 65± 7% and increased to 88± 5% for dichotomized CS (0–1, 2–3). Automated CS accuracy was 62%, and 90% for dichotomized CS. No significant difference in accuracy was found between groups with different levels of expertise. Conclusion After training, inter-rater reliability in collateral scoring was not influenced by experience. Automated CS performs similar to residents and radiologists in determining a collateral score.</description><identifier>ISSN: 0028-3940</identifier><identifier>EISSN: 1432-1920</identifier><identifier>DOI: 10.1007/s00234-022-02984-z</identifier><identifier>PMID: 35608629</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Accuracy ; Algorithms ; Artificial intelligence ; Automation ; Blood circulation ; Blood flow ; Cardiovascular system ; Correlation coefficient ; Correlation coefficients ; Diagnostic Neuroradiology ; Evaluation ; Imaging ; Ischemia ; Medicine ; Medicine &amp; Public Health ; Neurology ; Neuroradiology ; Neurosciences ; Neurosurgery ; Occlusion ; Patients ; Radiology ; Reliability analysis ; Reproducibility ; Stroke ; Training</subject><ispartof>Neuroradiology, 2022-12, Vol.64 (12), p.2277-2284</ispartof><rights>The Author(s) 2022</rights><rights>2022. The Author(s).</rights><rights>The Author(s) 2022. 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We evaluated the inter-rater reliability and accuracy of raters and an automated algorithm for assessing the collateral score (CS, range: 0–3) in acute ischemic stroke patients. Methods Baseline CTA scans with an intracranial anterior occlusion from the MR CLEAN study ( n =500) were used. For each core lab CS, ten CTA scans with sufficient quality were randomly selected. After a training session in collateral scoring, all selected CTA scans were individually evaluated for a visual CS by three groups: 7 radiologists, 13 junior and 9 senior radiology residents. Two additional radiologists scored CS to be used as reference, with a third providing a CS to produce a 2 out of 3 consensus CS in case of disagreement. An automated algorithm was also used to compute CS. Inter-rater agreement was reported with intraclass correlation coefficient (ICC). Accuracy of visual and automated CS were calculated. Results 39 CTA scans were assessed (1 corrupt CTA-scan excluded). All groups showed a moderate ICC (0.689-0.780) in comparison to the reference standard. Overall human accuracy was 65± 7% and increased to 88± 5% for dichotomized CS (0–1, 2–3). Automated CS accuracy was 62%, and 90% for dichotomized CS. No significant difference in accuracy was found between groups with different levels of expertise. Conclusion After training, inter-rater reliability in collateral scoring was not influenced by experience. 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We evaluated the inter-rater reliability and accuracy of raters and an automated algorithm for assessing the collateral score (CS, range: 0–3) in acute ischemic stroke patients. Methods Baseline CTA scans with an intracranial anterior occlusion from the MR CLEAN study ( n =500) were used. For each core lab CS, ten CTA scans with sufficient quality were randomly selected. After a training session in collateral scoring, all selected CTA scans were individually evaluated for a visual CS by three groups: 7 radiologists, 13 junior and 9 senior radiology residents. Two additional radiologists scored CS to be used as reference, with a third providing a CS to produce a 2 out of 3 consensus CS in case of disagreement. An automated algorithm was also used to compute CS. Inter-rater agreement was reported with intraclass correlation coefficient (ICC). Accuracy of visual and automated CS were calculated. Results 39 CTA scans were assessed (1 corrupt CTA-scan excluded). All groups showed a moderate ICC (0.689-0.780) in comparison to the reference standard. Overall human accuracy was 65± 7% and increased to 88± 5% for dichotomized CS (0–1, 2–3). Automated CS accuracy was 62%, and 90% for dichotomized CS. No significant difference in accuracy was found between groups with different levels of expertise. Conclusion After training, inter-rater reliability in collateral scoring was not influenced by experience. 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subjects Accuracy
Algorithms
Artificial intelligence
Automation
Blood circulation
Blood flow
Cardiovascular system
Correlation coefficient
Correlation coefficients
Diagnostic Neuroradiology
Evaluation
Imaging
Ischemia
Medicine
Medicine & Public Health
Neurology
Neuroradiology
Neurosciences
Neurosurgery
Occlusion
Patients
Radiology
Reliability analysis
Reproducibility
Stroke
Training
title Inter-rater reliability for assessing intracranial collaterals in patients with acute ischemic stroke: comparing 29 raters and an artificial intelligence-based software
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