Diagnostic Value of Artificial Intelligence—Based Software in Detection of Large Vessel Occlusion in Acute Ischemic Stroke

Background: Aim of the study was to test the accuracy of AI-based software for detection of large vessel occlusion (LVO) with computed tomography angiography (CTA) in stroke patients using an experienced neuroradiologist’s evaluation as the reference. Methods: Consecutive patients who underwent mult...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Marcin Sawicki, Krzysztof Safranow, Lidia Wiska, Igor Pasek, Aleksandra Gajdziel, Michał Gruszewski, Wojciech Poncyljusz
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	artificial intelligence cerebral angiography spiral computed tomography acute stroke cerebrovascular occlusion Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/36598c86816640139dc0318af5722f3f
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:36598c86816640139dc0318af5722f3f
record_format	dspace
spelling	oai:doaj.org-article:36598c86816640139dc0318af5722f3f2021-11-11T15:06:03ZDiagnostic Value of Artificial Intelligence—Based Software in Detection of Large Vessel Occlusion in Acute Ischemic Stroke10.3390/app1121100172076-3417https://doaj.org/article/36598c86816640139dc0318af5722f3f2021-10-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/10017https://doaj.org/toc/2076-3417Background: Aim of the study was to test the accuracy of AI-based software for detection of large vessel occlusion (LVO) with computed tomography angiography (CTA) in stroke patients using an experienced neuroradiologist’s evaluation as the reference. Methods: Consecutive patients who underwent multimodal brain CT for suspected acute ischemic stroke were retrospectively identified. The presence and site (classified as proximal and distal) of LVO were assessed in CTA by an experienced neuroradiologist as a reference and compared to readings of three medical students and AI-based software, the e-CTA. Results: One-hundred-eight participants with a mean age of 70 years (±12.6); 55 (50.9%) females were included. Neuroradiologist found LVO in 70 (64.8%) cases: 45 (41.7%) proximal, and 25 (23.1%) distal. The overall sensitivity for e-CTA was 0.67 (95%CI 0.55–0.78); 0.84 (95%CI 0.71–0.94) for proximal, and 0.36 (95%CI 0.18–0.57) for distal LVOs. Overall specificity and accuracy for e-CTA were 0.95 (95%CI 0.82–0.99) and 0.77 (95%CI 0.68–0.84), respectively. The student’s performance was similar to e-CTA. Conclusions: The tested software’s performance is acceptable for the detection of proximal LVOs, while it appears to be not accurate enough for distal LVOs.Marcin SawickiKrzysztof SafranowLidia WiskaIgor PasekAleksandra GajdzielMichał GruszewskiWojciech PoncyljuszMDPI AGarticleartificial intelligencecerebral angiographyspiral computed tomographyacute strokecerebrovascular occlusionTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10017, p 10017 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	artificial intelligence cerebral angiography spiral computed tomography acute stroke cerebrovascular occlusion Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	artificial intelligence cerebral angiography spiral computed tomography acute stroke cerebrovascular occlusion Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Marcin Sawicki Krzysztof Safranow Lidia Wiska Igor Pasek Aleksandra Gajdziel Michał Gruszewski Wojciech Poncyljusz Diagnostic Value of Artificial Intelligence—Based Software in Detection of Large Vessel Occlusion in Acute Ischemic Stroke
description	Background: Aim of the study was to test the accuracy of AI-based software for detection of large vessel occlusion (LVO) with computed tomography angiography (CTA) in stroke patients using an experienced neuroradiologist’s evaluation as the reference. Methods: Consecutive patients who underwent multimodal brain CT for suspected acute ischemic stroke were retrospectively identified. The presence and site (classified as proximal and distal) of LVO were assessed in CTA by an experienced neuroradiologist as a reference and compared to readings of three medical students and AI-based software, the e-CTA. Results: One-hundred-eight participants with a mean age of 70 years (±12.6); 55 (50.9%) females were included. Neuroradiologist found LVO in 70 (64.8%) cases: 45 (41.7%) proximal, and 25 (23.1%) distal. The overall sensitivity for e-CTA was 0.67 (95%CI 0.55–0.78); 0.84 (95%CI 0.71–0.94) for proximal, and 0.36 (95%CI 0.18–0.57) for distal LVOs. Overall specificity and accuracy for e-CTA were 0.95 (95%CI 0.82–0.99) and 0.77 (95%CI 0.68–0.84), respectively. The student’s performance was similar to e-CTA. Conclusions: The tested software’s performance is acceptable for the detection of proximal LVOs, while it appears to be not accurate enough for distal LVOs.
format	article
author	Marcin Sawicki Krzysztof Safranow Lidia Wiska Igor Pasek Aleksandra Gajdziel Michał Gruszewski Wojciech Poncyljusz
author_facet	Marcin Sawicki Krzysztof Safranow Lidia Wiska Igor Pasek Aleksandra Gajdziel Michał Gruszewski Wojciech Poncyljusz
author_sort	Marcin Sawicki
title	Diagnostic Value of Artificial Intelligence—Based Software in Detection of Large Vessel Occlusion in Acute Ischemic Stroke
title_short	Diagnostic Value of Artificial Intelligence—Based Software in Detection of Large Vessel Occlusion in Acute Ischemic Stroke
title_full	Diagnostic Value of Artificial Intelligence—Based Software in Detection of Large Vessel Occlusion in Acute Ischemic Stroke
title_fullStr	Diagnostic Value of Artificial Intelligence—Based Software in Detection of Large Vessel Occlusion in Acute Ischemic Stroke
title_full_unstemmed	Diagnostic Value of Artificial Intelligence—Based Software in Detection of Large Vessel Occlusion in Acute Ischemic Stroke
title_sort	diagnostic value of artificial intelligence—based software in detection of large vessel occlusion in acute ischemic stroke
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/36598c86816640139dc0318af5722f3f
work_keys_str_mv	AT marcinsawicki diagnosticvalueofartificialintelligencebasedsoftwareindetectionoflargevesselocclusioninacuteischemicstroke AT krzysztofsafranow diagnosticvalueofartificialintelligencebasedsoftwareindetectionoflargevesselocclusioninacuteischemicstroke AT lidiawiska diagnosticvalueofartificialintelligencebasedsoftwareindetectionoflargevesselocclusioninacuteischemicstroke AT igorpasek diagnosticvalueofartificialintelligencebasedsoftwareindetectionoflargevesselocclusioninacuteischemicstroke AT aleksandragajdziel diagnosticvalueofartificialintelligencebasedsoftwareindetectionoflargevesselocclusioninacuteischemicstroke AT michałgruszewski diagnosticvalueofartificialintelligencebasedsoftwareindetectionoflargevesselocclusioninacuteischemicstroke AT wojciechponcyljusz diagnosticvalueofartificialintelligencebasedsoftwareindetectionoflargevesselocclusioninacuteischemicstroke
_version_	1718437122638086144

Diagnostic Value of Artificial Intelligence—Based Software in Detection of Large Vessel Occlusion in Acute Ischemic Stroke

Ejemplares similares