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The relationship between HbA(1c) and ultrasound plaque textures in atherosclerotic patients

OBJECTIVE: Diabetes mellitus (DM) is associated to the morphological and componential characteristics of atheromatous plaques. It has proven that plaque textures are related to plaque components and beneficial for atherosclerotic risk stratification. The aim of this study is to compare plaque textur...

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Autores principales: Huang, Xiao-Wei, Zhang, Yan-Ling, Meng, Long, Qian, Ming, Zhou, Wei, Zheng, Rong-Qin, Zheng, Hai-Rong, Niu, Li–Li
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4949930/
https://www.ncbi.nlm.nih.gov/pubmed/27431674
http://dx.doi.org/10.1186/s12933-016-0422-5
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author Huang, Xiao-Wei
Zhang, Yan-Ling
Meng, Long
Qian, Ming
Zhou, Wei
Zheng, Rong-Qin
Zheng, Hai-Rong
Niu, Li–Li
author_facet Huang, Xiao-Wei
Zhang, Yan-Ling
Meng, Long
Qian, Ming
Zhou, Wei
Zheng, Rong-Qin
Zheng, Hai-Rong
Niu, Li–Li
author_sort Huang, Xiao-Wei
collection PubMed
description OBJECTIVE: Diabetes mellitus (DM) is associated to the morphological and componential characteristics of atheromatous plaques. It has proven that plaque textures are related to plaque components and beneficial for atherosclerotic risk stratification. The aim of this study is to compare plaque textures in patients with and without DM, and examine the relationship between HbA(1c) levels and the ultrasound plaque textures in atherosclerotic patients. METHODS: A total of 136 participants (among them 66 are diabetic and 70 are non-diabetic) suffering from carotid plaques were included. About 300 texture features were extracted from the ultrasound images of plaques using the algorithms of histogram, absolute gradient, run-length matrix, gray-level co-occurrence matrix, autoregressive model and wavelet transform, respectively. Thirty optimal features were selected by the Fisher coefficient and the mutual information measure. The most discriminating feature (MDF) was obtained from the linear discriminant analysis for the optimal features. Linear regression model was performed to investigate the relationship between HbA(1c) and MDF. The receiver operating characteristics (ROC) curve was further developed to validate the relation between the estimated HbA(1c) (models output) and diabetes status. RESULTS: A total of 12 texture features showed statistical difference between patients with and without DM. The MDF was significant higher in non-diabetic patients (0.326 ± 0.049) than diabetic patients (−0.346 ± 0.052) (p < 0.001). The optimal regression model (r = 0.348, p < 0.001) for HbA(1c) included a constant (p < 0.001) and the MDF (p < 0.001). The areas under ROC curve used to estimate HbA(1c) was 0.828. CONCLUSIONS: The results indicate that there is a quantitative relationship between the HbA(1c) levels and plaque textures in ultrasonic images of atherosclerotic patients, which may suggest that texture analysis of the ultrasonic image of plaque is a promising method for evaluating the cardiovascular risk caused by DM in patients with plaques.
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spelling pubmed-49499302016-07-20 The relationship between HbA(1c) and ultrasound plaque textures in atherosclerotic patients Huang, Xiao-Wei Zhang, Yan-Ling Meng, Long Qian, Ming Zhou, Wei Zheng, Rong-Qin Zheng, Hai-Rong Niu, Li–Li Cardiovasc Diabetol Original Investigation OBJECTIVE: Diabetes mellitus (DM) is associated to the morphological and componential characteristics of atheromatous plaques. It has proven that plaque textures are related to plaque components and beneficial for atherosclerotic risk stratification. The aim of this study is to compare plaque textures in patients with and without DM, and examine the relationship between HbA(1c) levels and the ultrasound plaque textures in atherosclerotic patients. METHODS: A total of 136 participants (among them 66 are diabetic and 70 are non-diabetic) suffering from carotid plaques were included. About 300 texture features were extracted from the ultrasound images of plaques using the algorithms of histogram, absolute gradient, run-length matrix, gray-level co-occurrence matrix, autoregressive model and wavelet transform, respectively. Thirty optimal features were selected by the Fisher coefficient and the mutual information measure. The most discriminating feature (MDF) was obtained from the linear discriminant analysis for the optimal features. Linear regression model was performed to investigate the relationship between HbA(1c) and MDF. The receiver operating characteristics (ROC) curve was further developed to validate the relation between the estimated HbA(1c) (models output) and diabetes status. RESULTS: A total of 12 texture features showed statistical difference between patients with and without DM. The MDF was significant higher in non-diabetic patients (0.326 ± 0.049) than diabetic patients (−0.346 ± 0.052) (p < 0.001). The optimal regression model (r = 0.348, p < 0.001) for HbA(1c) included a constant (p < 0.001) and the MDF (p < 0.001). The areas under ROC curve used to estimate HbA(1c) was 0.828. CONCLUSIONS: The results indicate that there is a quantitative relationship between the HbA(1c) levels and plaque textures in ultrasonic images of atherosclerotic patients, which may suggest that texture analysis of the ultrasonic image of plaque is a promising method for evaluating the cardiovascular risk caused by DM in patients with plaques. BioMed Central 2016-07-19 /pmc/articles/PMC4949930/ /pubmed/27431674 http://dx.doi.org/10.1186/s12933-016-0422-5 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Original Investigation
Huang, Xiao-Wei
Zhang, Yan-Ling
Meng, Long
Qian, Ming
Zhou, Wei
Zheng, Rong-Qin
Zheng, Hai-Rong
Niu, Li–Li
The relationship between HbA(1c) and ultrasound plaque textures in atherosclerotic patients
title The relationship between HbA(1c) and ultrasound plaque textures in atherosclerotic patients
title_full The relationship between HbA(1c) and ultrasound plaque textures in atherosclerotic patients
title_fullStr The relationship between HbA(1c) and ultrasound plaque textures in atherosclerotic patients
title_full_unstemmed The relationship between HbA(1c) and ultrasound plaque textures in atherosclerotic patients
title_short The relationship between HbA(1c) and ultrasound plaque textures in atherosclerotic patients
title_sort relationship between hba(1c) and ultrasound plaque textures in atherosclerotic patients
topic Original Investigation
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4949930/
https://www.ncbi.nlm.nih.gov/pubmed/27431674
http://dx.doi.org/10.1186/s12933-016-0422-5
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