Hybrid QUS Radiomics: A Multimodal-Integrated Quantitative Ultrasound Radiomics for Assessing Ambulatory Function in Duchenne Muscular Dystrophy

Background: Duchenne muscular dystrophy (DMD) is a neuromuscular disorder that affects ambulatory function. Quantitative ultrasound (QUS) imaging, utilizing envelope statistics, has proven effective in diagnosing DMD. Radiomics enables the extraction of detailed features from QUS images. This study...

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Veröffentlicht in:IEEE journal of biomedical and health informatics 2024-02, Vol.28 (2), p.835-845
Hauptverfasser: Yan, Dong, Li, Qiang, Lin, Chia-Wei, Shieh, Jeng-Yi, Weng, Wen-Chin, Tsui, Po-Hsiang
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container_title IEEE journal of biomedical and health informatics
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creator Yan, Dong
Li, Qiang
Lin, Chia-Wei
Shieh, Jeng-Yi
Weng, Wen-Chin
Tsui, Po-Hsiang
description Background: Duchenne muscular dystrophy (DMD) is a neuromuscular disorder that affects ambulatory function. Quantitative ultrasound (QUS) imaging, utilizing envelope statistics, has proven effective in diagnosing DMD. Radiomics enables the extraction of detailed features from QUS images. This study further proposes a hybrid QUS radiomics and explores its value in characterizing DMD. Methods: Patients (n = 85) underwent ultrasound examinations of gastrocnemius through Nakagami, homodyned K (HK), and information entropy imaging. The hybrid QUS radiomics extracted, selected, and integrated the retained features derived from each QUS image for classification of ambulatory function using support vector machine. Nested five fold cross-validation of the data was conducted, with the rotational process repeated 50 times. The performance was assessed by averaging the areas under the receiver operating characteristic curve (AUROC). Results: Radiomics enhanced the average AUROC of B-scan, Nakagami, HK, and entropy imaging to 0.790, 0.911, 0.869, and 0.890, respectively. By contrast, the hybrid QUS radiomics using HK and entropy images for diagnosing ambulatory function in DMD patients achieved a superior average AUROC of 0.971 ( p < 0.001 compared with conventional radiomics analysis). Conclusions: The proposed hybrid QUS radiomics incorporates microstructure-related backscattering information from various envelope statistics models to effectively enhance the performance of DMD assessment.
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Quantitative ultrasound (QUS) imaging, utilizing envelope statistics, has proven effective in diagnosing DMD. Radiomics enables the extraction of detailed features from QUS images. This study further proposes a hybrid QUS radiomics and explores its value in characterizing DMD. Methods: Patients (n = 85) underwent ultrasound examinations of gastrocnemius through Nakagami, homodyned K (HK), and information entropy imaging. The hybrid QUS radiomics extracted, selected, and integrated the retained features derived from each QUS image for classification of ambulatory function using support vector machine. Nested five fold cross-validation of the data was conducted, with the rotational process repeated 50 times. The performance was assessed by averaging the areas under the receiver operating characteristic curve (AUROC). Results: Radiomics enhanced the average AUROC of B-scan, Nakagami, HK, and entropy imaging to 0.790, 0.911, 0.869, and 0.890, respectively. By contrast, the hybrid QUS radiomics using HK and entropy images for diagnosing ambulatory function in DMD patients achieved a superior average AUROC of 0.971 ( p &lt; 0.001 compared with conventional radiomics analysis). Conclusions: The proposed hybrid QUS radiomics incorporates microstructure-related backscattering information from various envelope statistics models to effectively enhance the performance of DMD assessment.</description><identifier>ISSN: 2168-2194</identifier><identifier>ISSN: 2168-2208</identifier><identifier>EISSN: 2168-2208</identifier><identifier>DOI: 10.1109/JBHI.2023.3330578</identifier><identifier>PMID: 37930927</identifier><identifier>CODEN: IJBHA9</identifier><language>eng</language><publisher>United States: IEEE</publisher><subject>Duchenne muscular dystrophy ; Duchenne's muscular dystrophy ; Dystrophy ; Entropy ; Entropy (Information theory) ; envelope statistics ; Feature extraction ; Hospitals ; Humans ; Image classification ; Image contrast ; Imaging ; Medical imaging ; Muscle, Skeletal - diagnostic imaging ; Muscular dystrophy ; Muscular Dystrophy, Duchenne - diagnostic imaging ; Nakagami distribution ; parametric imaging ; Quantitative ultrasound ; Radiomics ; ROC Curve ; Statistical analysis ; Support vector machines ; Ultrasonic imaging ; Ultrasonography - methods ; Ultrasound</subject><ispartof>IEEE journal of biomedical and health informatics, 2024-02, Vol.28 (2), p.835-845</ispartof><rights>Copyright The Institute of Electrical and Electronics Engineers, Inc. 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Quantitative ultrasound (QUS) imaging, utilizing envelope statistics, has proven effective in diagnosing DMD. Radiomics enables the extraction of detailed features from QUS images. This study further proposes a hybrid QUS radiomics and explores its value in characterizing DMD. Methods: Patients (n = 85) underwent ultrasound examinations of gastrocnemius through Nakagami, homodyned K (HK), and information entropy imaging. The hybrid QUS radiomics extracted, selected, and integrated the retained features derived from each QUS image for classification of ambulatory function using support vector machine. Nested five fold cross-validation of the data was conducted, with the rotational process repeated 50 times. The performance was assessed by averaging the areas under the receiver operating characteristic curve (AUROC). Results: Radiomics enhanced the average AUROC of B-scan, Nakagami, HK, and entropy imaging to 0.790, 0.911, 0.869, and 0.890, respectively. By contrast, the hybrid QUS radiomics using HK and entropy images for diagnosing ambulatory function in DMD patients achieved a superior average AUROC of 0.971 ( p &lt; 0.001 compared with conventional radiomics analysis). 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Allied Health Premium</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>IEEE journal of biomedical and health informatics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Yan, Dong</au><au>Li, Qiang</au><au>Lin, Chia-Wei</au><au>Shieh, Jeng-Yi</au><au>Weng, Wen-Chin</au><au>Tsui, Po-Hsiang</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Hybrid QUS Radiomics: A Multimodal-Integrated Quantitative Ultrasound Radiomics for Assessing Ambulatory Function in Duchenne Muscular Dystrophy</atitle><jtitle>IEEE journal of biomedical and health informatics</jtitle><stitle>JBHI</stitle><addtitle>IEEE J Biomed Health Inform</addtitle><date>2024-02-01</date><risdate>2024</risdate><volume>28</volume><issue>2</issue><spage>835</spage><epage>845</epage><pages>835-845</pages><issn>2168-2194</issn><issn>2168-2208</issn><eissn>2168-2208</eissn><coden>IJBHA9</coden><abstract>Background: Duchenne muscular dystrophy (DMD) is a neuromuscular disorder that affects ambulatory function. Quantitative ultrasound (QUS) imaging, utilizing envelope statistics, has proven effective in diagnosing DMD. Radiomics enables the extraction of detailed features from QUS images. This study further proposes a hybrid QUS radiomics and explores its value in characterizing DMD. Methods: Patients (n = 85) underwent ultrasound examinations of gastrocnemius through Nakagami, homodyned K (HK), and information entropy imaging. The hybrid QUS radiomics extracted, selected, and integrated the retained features derived from each QUS image for classification of ambulatory function using support vector machine. Nested five fold cross-validation of the data was conducted, with the rotational process repeated 50 times. The performance was assessed by averaging the areas under the receiver operating characteristic curve (AUROC). Results: Radiomics enhanced the average AUROC of B-scan, Nakagami, HK, and entropy imaging to 0.790, 0.911, 0.869, and 0.890, respectively. By contrast, the hybrid QUS radiomics using HK and entropy images for diagnosing ambulatory function in DMD patients achieved a superior average AUROC of 0.971 ( p &lt; 0.001 compared with conventional radiomics analysis). Conclusions: The proposed hybrid QUS radiomics incorporates microstructure-related backscattering information from various envelope statistics models to effectively enhance the performance of DMD assessment.</abstract><cop>United States</cop><pub>IEEE</pub><pmid>37930927</pmid><doi>10.1109/JBHI.2023.3330578</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0001-7129-1456</orcidid><orcidid>https://orcid.org/0000-0002-6577-0116</orcidid><orcidid>https://orcid.org/0000-0002-3906-4269</orcidid><orcidid>https://orcid.org/0000-0002-6923-9138</orcidid><orcidid>https://orcid.org/0000-0002-5604-1800</orcidid><orcidid>https://orcid.org/0000-0002-2654-3324</orcidid></addata></record>
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subjects Duchenne muscular dystrophy
Duchenne's muscular dystrophy
Dystrophy
Entropy
Entropy (Information theory)
envelope statistics
Feature extraction
Hospitals
Humans
Image classification
Image contrast
Imaging
Medical imaging
Muscle, Skeletal - diagnostic imaging
Muscular dystrophy
Muscular Dystrophy, Duchenne - diagnostic imaging
Nakagami distribution
parametric imaging
Quantitative ultrasound
Radiomics
ROC Curve
Statistical analysis
Support vector machines
Ultrasonic imaging
Ultrasonography - methods
Ultrasound
title Hybrid QUS Radiomics: A Multimodal-Integrated Quantitative Ultrasound Radiomics for Assessing Ambulatory Function in Duchenne Muscular Dystrophy
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