Cargando…

Fully automatic framework for comprehensive coronary artery calcium scores analysis on non-contrast cardiac-gated CT scan: Total and vessel-specific quantifications

OBJECTIVES: To develop a fully automatic multiview shape constraint framework for comprehensive coronary artery calcium scores (CACS) quantification via deep learning on nonenhanced cardiac CT images. METHODS: In this retrospective single-centre study, a multi-task deep learning framework was propos...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Nan, Yang, Guang, Zhang, Weiwei, Wang, Wenjing, Zhou, Zhen, Zhang, Heye, Xu, Lei, Chen, Yundai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Science Ireland Ltd 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7814341/
https://www.ncbi.nlm.nih.gov/pubmed/33302029
http://dx.doi.org/10.1016/j.ejrad.2020.109420
_version_ 1783638039997710336
author Zhang, Nan
Yang, Guang
Zhang, Weiwei
Wang, Wenjing
Zhou, Zhen
Zhang, Heye
Xu, Lei
Chen, Yundai
author_facet Zhang, Nan
Yang, Guang
Zhang, Weiwei
Wang, Wenjing
Zhou, Zhen
Zhang, Heye
Xu, Lei
Chen, Yundai
author_sort Zhang, Nan
collection PubMed
description OBJECTIVES: To develop a fully automatic multiview shape constraint framework for comprehensive coronary artery calcium scores (CACS) quantification via deep learning on nonenhanced cardiac CT images. METHODS: In this retrospective single-centre study, a multi-task deep learning framework was proposed to detect and quantify coronary artery calcification from CT images collected between October 2018 and March 2019. A total of 232 non-contrast cardiac-gated CT scans were retrieved and studied (80 % for model training and 20 % for testing). CACS results of testing datasets (n = 46), including Agatston score, calcium volume score, calcium mass score, were calculated fully automatically and manually at total and vessel-specific levels, respectively. RESULTS: No significant differences were found in CACS quantification obtained using automatic or manual methods at total and vessel-specific levels (Agatston score: automatic 535.3 vs. manual 542.0, P = 0.993; calcium volume score: automatic 454.2 vs. manual 460.6, P = 0.990; calcium mass score: automatic 128.9 vs. manual 129.5, P = 0.992). Compared to the ground truth, the number of calcified vessels can be accurate recognized automatically (total: automatic 107 vs. manual 102, P = 0.125; left main artery: automatic 15 vs. manual 14, P = 1.000 ; left ascending artery: automatic 37 vs. manual 37, P = 1.000; left circumflex artery: automatic 22 vs. manual 20, P = 0.625; right coronary artery: automatic 33 vs. manual 31, P = 0.500). At the patient’s level, there was no statistic difference existed in the classification of Agatston scoring (P = 0.317) and the number of calcified vessels (P = 0.102) between the automatic and manual results. CONCLUSIONS: The proposed framework can achieve reliable and comprehensive quantification for the CACS, including the calcified extent and distribution indicators at both total and vessel-specific levels.
format Online
Article
Text
id pubmed-7814341
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Elsevier Science Ireland Ltd
record_format MEDLINE/PubMed
spelling pubmed-78143412021-01-26 Fully automatic framework for comprehensive coronary artery calcium scores analysis on non-contrast cardiac-gated CT scan: Total and vessel-specific quantifications Zhang, Nan Yang, Guang Zhang, Weiwei Wang, Wenjing Zhou, Zhen Zhang, Heye Xu, Lei Chen, Yundai Eur J Radiol Research Article OBJECTIVES: To develop a fully automatic multiview shape constraint framework for comprehensive coronary artery calcium scores (CACS) quantification via deep learning on nonenhanced cardiac CT images. METHODS: In this retrospective single-centre study, a multi-task deep learning framework was proposed to detect and quantify coronary artery calcification from CT images collected between October 2018 and March 2019. A total of 232 non-contrast cardiac-gated CT scans were retrieved and studied (80 % for model training and 20 % for testing). CACS results of testing datasets (n = 46), including Agatston score, calcium volume score, calcium mass score, were calculated fully automatically and manually at total and vessel-specific levels, respectively. RESULTS: No significant differences were found in CACS quantification obtained using automatic or manual methods at total and vessel-specific levels (Agatston score: automatic 535.3 vs. manual 542.0, P = 0.993; calcium volume score: automatic 454.2 vs. manual 460.6, P = 0.990; calcium mass score: automatic 128.9 vs. manual 129.5, P = 0.992). Compared to the ground truth, the number of calcified vessels can be accurate recognized automatically (total: automatic 107 vs. manual 102, P = 0.125; left main artery: automatic 15 vs. manual 14, P = 1.000 ; left ascending artery: automatic 37 vs. manual 37, P = 1.000; left circumflex artery: automatic 22 vs. manual 20, P = 0.625; right coronary artery: automatic 33 vs. manual 31, P = 0.500). At the patient’s level, there was no statistic difference existed in the classification of Agatston scoring (P = 0.317) and the number of calcified vessels (P = 0.102) between the automatic and manual results. CONCLUSIONS: The proposed framework can achieve reliable and comprehensive quantification for the CACS, including the calcified extent and distribution indicators at both total and vessel-specific levels. Elsevier Science Ireland Ltd 2021-01 /pmc/articles/PMC7814341/ /pubmed/33302029 http://dx.doi.org/10.1016/j.ejrad.2020.109420 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Research Article
Zhang, Nan
Yang, Guang
Zhang, Weiwei
Wang, Wenjing
Zhou, Zhen
Zhang, Heye
Xu, Lei
Chen, Yundai
Fully automatic framework for comprehensive coronary artery calcium scores analysis on non-contrast cardiac-gated CT scan: Total and vessel-specific quantifications
title Fully automatic framework for comprehensive coronary artery calcium scores analysis on non-contrast cardiac-gated CT scan: Total and vessel-specific quantifications
title_full Fully automatic framework for comprehensive coronary artery calcium scores analysis on non-contrast cardiac-gated CT scan: Total and vessel-specific quantifications
title_fullStr Fully automatic framework for comprehensive coronary artery calcium scores analysis on non-contrast cardiac-gated CT scan: Total and vessel-specific quantifications
title_full_unstemmed Fully automatic framework for comprehensive coronary artery calcium scores analysis on non-contrast cardiac-gated CT scan: Total and vessel-specific quantifications
title_short Fully automatic framework for comprehensive coronary artery calcium scores analysis on non-contrast cardiac-gated CT scan: Total and vessel-specific quantifications
title_sort fully automatic framework for comprehensive coronary artery calcium scores analysis on non-contrast cardiac-gated ct scan: total and vessel-specific quantifications
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7814341/
https://www.ncbi.nlm.nih.gov/pubmed/33302029
http://dx.doi.org/10.1016/j.ejrad.2020.109420
work_keys_str_mv AT zhangnan fullyautomaticframeworkforcomprehensivecoronaryarterycalciumscoresanalysisonnoncontrastcardiacgatedctscantotalandvesselspecificquantifications
AT yangguang fullyautomaticframeworkforcomprehensivecoronaryarterycalciumscoresanalysisonnoncontrastcardiacgatedctscantotalandvesselspecificquantifications
AT zhangweiwei fullyautomaticframeworkforcomprehensivecoronaryarterycalciumscoresanalysisonnoncontrastcardiacgatedctscantotalandvesselspecificquantifications
AT wangwenjing fullyautomaticframeworkforcomprehensivecoronaryarterycalciumscoresanalysisonnoncontrastcardiacgatedctscantotalandvesselspecificquantifications
AT zhouzhen fullyautomaticframeworkforcomprehensivecoronaryarterycalciumscoresanalysisonnoncontrastcardiacgatedctscantotalandvesselspecificquantifications
AT zhangheye fullyautomaticframeworkforcomprehensivecoronaryarterycalciumscoresanalysisonnoncontrastcardiacgatedctscantotalandvesselspecificquantifications
AT xulei fullyautomaticframeworkforcomprehensivecoronaryarterycalciumscoresanalysisonnoncontrastcardiacgatedctscantotalandvesselspecificquantifications
AT chenyundai fullyautomaticframeworkforcomprehensivecoronaryarterycalciumscoresanalysisonnoncontrastcardiacgatedctscantotalandvesselspecificquantifications