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Radiomics assessment of carotid intraplaque hemorrhage: detecting the vulnerable patients

BACKGROUND: Intraplaque hemorrhage (IPH), one of the key features of vulnerable plaques, has been shown to be associated with increased risk of stroke. The aim is to develop and validate a CT-based radiomics nomogram incorporating clinical factors and radiomics signature for the detection of IPH in...

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Autores principales: Zhang, Shuai, Gao, Lin, Kang, Bing, Yu, Xinxin, Zhang, Ran, Wang, Ximing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Vienna 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9768061/
https://www.ncbi.nlm.nih.gov/pubmed/36538100
http://dx.doi.org/10.1186/s13244-022-01324-2
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author Zhang, Shuai
Gao, Lin
Kang, Bing
Yu, Xinxin
Zhang, Ran
Wang, Ximing
author_facet Zhang, Shuai
Gao, Lin
Kang, Bing
Yu, Xinxin
Zhang, Ran
Wang, Ximing
author_sort Zhang, Shuai
collection PubMed
description BACKGROUND: Intraplaque hemorrhage (IPH), one of the key features of vulnerable plaques, has been shown to be associated with increased risk of stroke. The aim is to develop and validate a CT-based radiomics nomogram incorporating clinical factors and radiomics signature for the detection of IPH in carotid arteries. METHODS: This retrospective study analyzed the patients with carotid plaques on CTA from January 2013 to January 2021 at two different institutions. Radiomics features were extracted from CTA images. Demographics and CT characteristics were evaluated to build a clinical factor model. A radiomics signature was constructed by the least absolute shrinkage and selection operator method. A radiomics nomogram combining the radiomics signature and independent clinical factors was constructed. The area under curves of three models were calculated by receiver operating characteristic analysis. RESULTS: A total of 46 patients (mean age, 60.7 years ± 10.4 [standard deviation]; 36 men) with 106 carotid plaques were in the training set, and 18 patients (mean age, 61.4 years ± 10.1; 13 men) with 38 carotid plaques were in the external test sets. Stenosis was the independent clinical factor. Eight features were used to build the radiomics signature. The area under the curve (AUC) of the radiomics nomogram was significantly higher than that of the clinical factor model in both the training (p = 0.032) and external test (p = 0.039) sets. CONCLUSIONS: A CT-based radiomics nomogram showed satisfactory performance in distinguishing carotid plaques with and without intraplaque hemorrhage. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13244-022-01324-2.
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spelling pubmed-97680612022-12-22 Radiomics assessment of carotid intraplaque hemorrhage: detecting the vulnerable patients Zhang, Shuai Gao, Lin Kang, Bing Yu, Xinxin Zhang, Ran Wang, Ximing Insights Imaging Original Article BACKGROUND: Intraplaque hemorrhage (IPH), one of the key features of vulnerable plaques, has been shown to be associated with increased risk of stroke. The aim is to develop and validate a CT-based radiomics nomogram incorporating clinical factors and radiomics signature for the detection of IPH in carotid arteries. METHODS: This retrospective study analyzed the patients with carotid plaques on CTA from January 2013 to January 2021 at two different institutions. Radiomics features were extracted from CTA images. Demographics and CT characteristics were evaluated to build a clinical factor model. A radiomics signature was constructed by the least absolute shrinkage and selection operator method. A radiomics nomogram combining the radiomics signature and independent clinical factors was constructed. The area under curves of three models were calculated by receiver operating characteristic analysis. RESULTS: A total of 46 patients (mean age, 60.7 years ± 10.4 [standard deviation]; 36 men) with 106 carotid plaques were in the training set, and 18 patients (mean age, 61.4 years ± 10.1; 13 men) with 38 carotid plaques were in the external test sets. Stenosis was the independent clinical factor. Eight features were used to build the radiomics signature. The area under the curve (AUC) of the radiomics nomogram was significantly higher than that of the clinical factor model in both the training (p = 0.032) and external test (p = 0.039) sets. CONCLUSIONS: A CT-based radiomics nomogram showed satisfactory performance in distinguishing carotid plaques with and without intraplaque hemorrhage. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13244-022-01324-2. Springer Vienna 2022-12-20 /pmc/articles/PMC9768061/ /pubmed/36538100 http://dx.doi.org/10.1186/s13244-022-01324-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Zhang, Shuai
Gao, Lin
Kang, Bing
Yu, Xinxin
Zhang, Ran
Wang, Ximing
Radiomics assessment of carotid intraplaque hemorrhage: detecting the vulnerable patients
title Radiomics assessment of carotid intraplaque hemorrhage: detecting the vulnerable patients
title_full Radiomics assessment of carotid intraplaque hemorrhage: detecting the vulnerable patients
title_fullStr Radiomics assessment of carotid intraplaque hemorrhage: detecting the vulnerable patients
title_full_unstemmed Radiomics assessment of carotid intraplaque hemorrhage: detecting the vulnerable patients
title_short Radiomics assessment of carotid intraplaque hemorrhage: detecting the vulnerable patients
title_sort radiomics assessment of carotid intraplaque hemorrhage: detecting the vulnerable patients
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9768061/
https://www.ncbi.nlm.nih.gov/pubmed/36538100
http://dx.doi.org/10.1186/s13244-022-01324-2
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