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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 |
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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 |
format | article |
fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_9643213</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2733851956</sourcerecordid><originalsourceid>FETCH-LOGICAL-c474t-334948086d65d54e3b59362c7e8a5c5595d25bfd7a9bdc5a44c79025417989263</originalsourceid><addsrcrecordid>eNp9Ustu1TAQtRCI3hZ-gAWyxIZNwPEjiVkgoYpCpUpsYG1NnMm9LokdbF-q9ov4TJzeUh4LFmMv5sw5c2aGkGc1e1Uz1r5OjHEhK8Z5Cd3J6uYB2dRS8KrWnD0km5LvKqElOyLHKV0yxkQr2sfkSKiGdQ3XG_Lj3GeMVYTy0oiTg95NLl_TMUQKKWFKzm-p8zmCjeAdTNSGaVrxMKWSoAtkhz4neuXyjoLdZ6Qu2R3OztKUY_iKb0rNvEBcqbimt2qJgh9KUIjZjc6uzEUGp8lt0Vusekg40BTGfAURn5BHYxHEp3f_Cfly9v7z6cfq4tOH89N3F5WVrcyVEFLLrpgbGjUoiaJXWjTcttiBskppNXDVj0MLuh-sAiltqxlXsm51p3kjTsjbA--y72ccLK7OJ7NEN0O8NgGc-Tvj3c5sw3ejmzL5WhSCl3cEMXzbY8pmLtMotsBj2CfDm6bTNZOiK9AX_0Avwz76Ys_wVohO1VqtHfEDysaQUsTxvpmamfUQzOEQTDkEc3sI5qYUPf_Txn3Jr80XgDgA0rKuBeNv7f_Q_gSPdMMY</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2733851956</pqid></control><display><type>article</type><title>Inter-rater reliability for assessing intracranial collaterals in patients with acute ischemic stroke: comparing 29 raters and an artificial intelligence-based software</title><source>Springer Nature</source><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</creator><creatorcontrib>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 ; MR CLEAN investigators ; on behalf of the MR CLEAN investigators</creatorcontrib><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.</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 & 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. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c474t-334948086d65d54e3b59362c7e8a5c5595d25bfd7a9bdc5a44c79025417989263</citedby><cites>FETCH-LOGICAL-c474t-334948086d65d54e3b59362c7e8a5c5595d25bfd7a9bdc5a44c79025417989263</cites><orcidid>0000-0003-1631-7056 ; 0000-0002-6159-2228 ; 0000-0001-6119-7247 ; 0000-0002-9234-3515 ; 0000-0002-2212-6128 ; 0000-0002-7398-2864 ; 0000-0002-2448-122X ; 0000-0002-7600-9568 ; 0000-0001-8257-7759</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35608629$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wolff, Lennard</creatorcontrib><creatorcontrib>Su, Jiahang</creatorcontrib><creatorcontrib>Van Loon, Derek</creatorcontrib><creatorcontrib>van Es, Adriaan</creatorcontrib><creatorcontrib>van Doormaal, Pieter Jan</creatorcontrib><creatorcontrib>Majoie, Charles</creatorcontrib><creatorcontrib>van Zwam, Wim</creatorcontrib><creatorcontrib>Dippel, Diederik</creatorcontrib><creatorcontrib>van der Lugt, Aad</creatorcontrib><creatorcontrib>van Walsum, Theo</creatorcontrib><creatorcontrib>MR CLEAN investigators</creatorcontrib><creatorcontrib>on behalf of the MR CLEAN investigators</creatorcontrib><title>Inter-rater reliability for assessing intracranial collaterals in patients with acute ischemic stroke: comparing 29 raters and an artificial intelligence-based software</title><title>Neuroradiology</title><addtitle>Neuroradiology</addtitle><addtitle>Neuroradiology</addtitle><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.</description><subject>Accuracy</subject><subject>Algorithms</subject><subject>Artificial intelligence</subject><subject>Automation</subject><subject>Blood circulation</subject><subject>Blood flow</subject><subject>Cardiovascular system</subject><subject>Correlation coefficient</subject><subject>Correlation coefficients</subject><subject>Diagnostic Neuroradiology</subject><subject>Evaluation</subject><subject>Imaging</subject><subject>Ischemia</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Neurology</subject><subject>Neuroradiology</subject><subject>Neurosciences</subject><subject>Neurosurgery</subject><subject>Occlusion</subject><subject>Patients</subject><subject>Radiology</subject><subject>Reliability analysis</subject><subject>Reproducibility</subject><subject>Stroke</subject><subject>Training</subject><issn>0028-3940</issn><issn>1432-1920</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp9Ustu1TAQtRCI3hZ-gAWyxIZNwPEjiVkgoYpCpUpsYG1NnMm9LokdbF-q9ov4TJzeUh4LFmMv5sw5c2aGkGc1e1Uz1r5OjHEhK8Z5Cd3J6uYB2dRS8KrWnD0km5LvKqElOyLHKV0yxkQr2sfkSKiGdQ3XG_Lj3GeMVYTy0oiTg95NLl_TMUQKKWFKzm-p8zmCjeAdTNSGaVrxMKWSoAtkhz4neuXyjoLdZ6Qu2R3OztKUY_iKb0rNvEBcqbimt2qJgh9KUIjZjc6uzEUGp8lt0Vusekg40BTGfAURn5BHYxHEp3f_Cfly9v7z6cfq4tOH89N3F5WVrcyVEFLLrpgbGjUoiaJXWjTcttiBskppNXDVj0MLuh-sAiltqxlXsm51p3kjTsjbA--y72ccLK7OJ7NEN0O8NgGc-Tvj3c5sw3ejmzL5WhSCl3cEMXzbY8pmLtMotsBj2CfDm6bTNZOiK9AX_0Avwz76Ys_wVohO1VqtHfEDysaQUsTxvpmamfUQzOEQTDkEc3sI5qYUPf_Txn3Jr80XgDgA0rKuBeNv7f_Q_gSPdMMY</recordid><startdate>20221201</startdate><enddate>20221201</enddate><creator>Wolff, Lennard</creator><creator>Su, Jiahang</creator><creator>Van Loon, 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reliability for assessing intracranial collaterals in patients with acute ischemic stroke: comparing 29 raters and an artificial intelligence-based software</title><author>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</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c474t-334948086d65d54e3b59362c7e8a5c5595d25bfd7a9bdc5a44c79025417989263</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Accuracy</topic><topic>Algorithms</topic><topic>Artificial intelligence</topic><topic>Automation</topic><topic>Blood circulation</topic><topic>Blood flow</topic><topic>Cardiovascular system</topic><topic>Correlation coefficient</topic><topic>Correlation coefficients</topic><topic>Diagnostic Neuroradiology</topic><topic>Evaluation</topic><topic>Imaging</topic><topic>Ischemia</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Neurology</topic><topic>Neuroradiology</topic><topic>Neurosciences</topic><topic>Neurosurgery</topic><topic>Occlusion</topic><topic>Patients</topic><topic>Radiology</topic><topic>Reliability analysis</topic><topic>Reproducibility</topic><topic>Stroke</topic><topic>Training</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wolff, Lennard</creatorcontrib><creatorcontrib>Su, Jiahang</creatorcontrib><creatorcontrib>Van Loon, Derek</creatorcontrib><creatorcontrib>van Es, Adriaan</creatorcontrib><creatorcontrib>van Doormaal, Pieter Jan</creatorcontrib><creatorcontrib>Majoie, Charles</creatorcontrib><creatorcontrib>van Zwam, Wim</creatorcontrib><creatorcontrib>Dippel, Diederik</creatorcontrib><creatorcontrib>van der Lugt, Aad</creatorcontrib><creatorcontrib>van Walsum, Theo</creatorcontrib><creatorcontrib>MR CLEAN investigators</creatorcontrib><creatorcontrib>on behalf of the MR CLEAN investigators</creatorcontrib><collection>Springer_OA刊</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database (ProQuest)</collection><collection>Neurosciences Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Health & Medical Collection (Proquest)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital 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29 raters and an artificial intelligence-based software</atitle><jtitle>Neuroradiology</jtitle><stitle>Neuroradiology</stitle><addtitle>Neuroradiology</addtitle><date>2022-12-01</date><risdate>2022</risdate><volume>64</volume><issue>12</issue><spage>2277</spage><epage>2284</epage><pages>2277-2284</pages><issn>0028-3940</issn><eissn>1432-1920</eissn><abstract>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.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>35608629</pmid><doi>10.1007/s00234-022-02984-z</doi><tpages>8</tpages><orcidid>https://orcid.org/0000-0003-1631-7056</orcidid><orcidid>https://orcid.org/0000-0002-6159-2228</orcidid><orcidid>https://orcid.org/0000-0001-6119-7247</orcidid><orcidid>https://orcid.org/0000-0002-9234-3515</orcidid><orcidid>https://orcid.org/0000-0002-2212-6128</orcidid><orcidid>https://orcid.org/0000-0002-7398-2864</orcidid><orcidid>https://orcid.org/0000-0002-2448-122X</orcidid><orcidid>https://orcid.org/0000-0002-7600-9568</orcidid><orcidid>https://orcid.org/0000-0001-8257-7759</orcidid><oa>free_for_read</oa></addata></record> |
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source | Springer Nature |
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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