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Protocol and Preliminary Results of the Establishment of Intracranial Aneurysm Database for Artificial Intelligence Application Based on CTA Images

BACKGROUND AND PURPOSE: Unruptured intracranial aneurysms (UIAs) are increasingly being detected in clinical practice. Artificial intelligence (AI) has been increasingly used to assist diagnostic techniques and shows encouraging prospects. In this study, we reported the protocol and preliminary resu...

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Autores principales: You, Wei, Sun, Yong, Feng, Junqiang, Wang, Zhiliang, Li, Lin, Chen, Xiheng, Lv, Jian, Tang, Yudi, Deng, Dingwei, Wei, Dachao, Gui, Siming, Liu, Xinke, Liu, Peng, Jin, Hengwei, Ge, Huijian, Zhang, Yanling
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9343848/
https://www.ncbi.nlm.nih.gov/pubmed/35928124
http://dx.doi.org/10.3389/fneur.2022.932933
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author You, Wei
Sun, Yong
Feng, Junqiang
Wang, Zhiliang
Li, Lin
Chen, Xiheng
Lv, Jian
Tang, Yudi
Deng, Dingwei
Wei, Dachao
Gui, Siming
Liu, Xinke
Liu, Peng
Jin, Hengwei
Ge, Huijian
Zhang, Yanling
author_facet You, Wei
Sun, Yong
Feng, Junqiang
Wang, Zhiliang
Li, Lin
Chen, Xiheng
Lv, Jian
Tang, Yudi
Deng, Dingwei
Wei, Dachao
Gui, Siming
Liu, Xinke
Liu, Peng
Jin, Hengwei
Ge, Huijian
Zhang, Yanling
author_sort You, Wei
collection PubMed
description BACKGROUND AND PURPOSE: Unruptured intracranial aneurysms (UIAs) are increasingly being detected in clinical practice. Artificial intelligence (AI) has been increasingly used to assist diagnostic techniques and shows encouraging prospects. In this study, we reported the protocol and preliminary results of the establishment of an intracranial aneurysm database for AI application based on computed tomography angiography (CTA) images. METHODS: Through a review of picture archiving and communication systems, we collected CTA images of patients with aneurysms between January 2010 and March 2021. The radiologists performed manual segmentation of all diagnosed aneurysms on subtraction CTA as the basis for automatic aneurysm segmentation. Then, AI will be applied to two stages of aneurysm treatment, namely, automatic aneurysm detection and segmentation model based on the CTA image and the aneurysm risk prediction model. RESULTS: Three medical centers have been included in this study so far. A total of 3,190 cases of CTA examinations with 4,124 aneurysms were included in the database. All identified aneurysms from CTA images that enrolled in this study were manually segmented on subtraction CTA by six readers. We developed a structure of 3D-Unet for aneurysm detection and segmentation in CTA images. The algorithm was developed and tested using a total of 2,272 head CTAs with 2,938 intracranial aneurysms. The recall and false positives per case (FP/case) of this model for detecting aneurysms were 0.964 and 2.01, and the Dice values for aneurysm segmentation were 0.783. CONCLUSION: This study introduces the protocol and preliminary results of the establishment of the intracranial aneurysm database for AI applications based on CTA images. The establishment of a multicenter database based on CTA images of intracranial aneurysms is the basis for the application of AI in the diagnosis and treatment of aneurysms. In addition to segmentation, AI should have great potential for aneurysm treatment and management in the future.
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spelling pubmed-93438482022-08-03 Protocol and Preliminary Results of the Establishment of Intracranial Aneurysm Database for Artificial Intelligence Application Based on CTA Images You, Wei Sun, Yong Feng, Junqiang Wang, Zhiliang Li, Lin Chen, Xiheng Lv, Jian Tang, Yudi Deng, Dingwei Wei, Dachao Gui, Siming Liu, Xinke Liu, Peng Jin, Hengwei Ge, Huijian Zhang, Yanling Front Neurol Neurology BACKGROUND AND PURPOSE: Unruptured intracranial aneurysms (UIAs) are increasingly being detected in clinical practice. Artificial intelligence (AI) has been increasingly used to assist diagnostic techniques and shows encouraging prospects. In this study, we reported the protocol and preliminary results of the establishment of an intracranial aneurysm database for AI application based on computed tomography angiography (CTA) images. METHODS: Through a review of picture archiving and communication systems, we collected CTA images of patients with aneurysms between January 2010 and March 2021. The radiologists performed manual segmentation of all diagnosed aneurysms on subtraction CTA as the basis for automatic aneurysm segmentation. Then, AI will be applied to two stages of aneurysm treatment, namely, automatic aneurysm detection and segmentation model based on the CTA image and the aneurysm risk prediction model. RESULTS: Three medical centers have been included in this study so far. A total of 3,190 cases of CTA examinations with 4,124 aneurysms were included in the database. All identified aneurysms from CTA images that enrolled in this study were manually segmented on subtraction CTA by six readers. We developed a structure of 3D-Unet for aneurysm detection and segmentation in CTA images. The algorithm was developed and tested using a total of 2,272 head CTAs with 2,938 intracranial aneurysms. The recall and false positives per case (FP/case) of this model for detecting aneurysms were 0.964 and 2.01, and the Dice values for aneurysm segmentation were 0.783. CONCLUSION: This study introduces the protocol and preliminary results of the establishment of the intracranial aneurysm database for AI applications based on CTA images. The establishment of a multicenter database based on CTA images of intracranial aneurysms is the basis for the application of AI in the diagnosis and treatment of aneurysms. In addition to segmentation, AI should have great potential for aneurysm treatment and management in the future. Frontiers Media S.A. 2022-07-19 /pmc/articles/PMC9343848/ /pubmed/35928124 http://dx.doi.org/10.3389/fneur.2022.932933 Text en Copyright © 2022 You, Sun, Feng, Wang, Li, Chen, Lv, Tang, Deng, Wei, Gui, Liu, Liu, Jin, Ge and Zhang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neurology
You, Wei
Sun, Yong
Feng, Junqiang
Wang, Zhiliang
Li, Lin
Chen, Xiheng
Lv, Jian
Tang, Yudi
Deng, Dingwei
Wei, Dachao
Gui, Siming
Liu, Xinke
Liu, Peng
Jin, Hengwei
Ge, Huijian
Zhang, Yanling
Protocol and Preliminary Results of the Establishment of Intracranial Aneurysm Database for Artificial Intelligence Application Based on CTA Images
title Protocol and Preliminary Results of the Establishment of Intracranial Aneurysm Database for Artificial Intelligence Application Based on CTA Images
title_full Protocol and Preliminary Results of the Establishment of Intracranial Aneurysm Database for Artificial Intelligence Application Based on CTA Images
title_fullStr Protocol and Preliminary Results of the Establishment of Intracranial Aneurysm Database for Artificial Intelligence Application Based on CTA Images
title_full_unstemmed Protocol and Preliminary Results of the Establishment of Intracranial Aneurysm Database for Artificial Intelligence Application Based on CTA Images
title_short Protocol and Preliminary Results of the Establishment of Intracranial Aneurysm Database for Artificial Intelligence Application Based on CTA Images
title_sort protocol and preliminary results of the establishment of intracranial aneurysm database for artificial intelligence application based on cta images
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9343848/
https://www.ncbi.nlm.nih.gov/pubmed/35928124
http://dx.doi.org/10.3389/fneur.2022.932933
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