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Clinical and pathological correlates of severity classifications in trigger fingers based on computer-aided image analysis

BACKGROUND: The treatment of trigger finger so far has heavily relied on clinicians’ evaluations for the severity of patients’ symptoms and the functionality of affected fingers. However, there is still a lack of pathological evidence supporting the criteria of clinical evaluations. This study’s aim...

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Autores principales: Yang, Tai-Hua, Chen, Hsin-Chen, Liu, Yung-Chun, Shih, Hui-Hsuan, Kuo, Li-Chieh, Cha, Stephen, Yang, Hsiao-Bai, Yang, Dee-Shan, Jou, I-Ming, Sun, Yung-Nien, Su, Fong-Chin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4118632/
https://www.ncbi.nlm.nih.gov/pubmed/25055721
http://dx.doi.org/10.1186/1475-925X-13-100
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author Yang, Tai-Hua
Chen, Hsin-Chen
Liu, Yung-Chun
Shih, Hui-Hsuan
Kuo, Li-Chieh
Cha, Stephen
Yang, Hsiao-Bai
Yang, Dee-Shan
Jou, I-Ming
Sun, Yung-Nien
Su, Fong-Chin
author_facet Yang, Tai-Hua
Chen, Hsin-Chen
Liu, Yung-Chun
Shih, Hui-Hsuan
Kuo, Li-Chieh
Cha, Stephen
Yang, Hsiao-Bai
Yang, Dee-Shan
Jou, I-Ming
Sun, Yung-Nien
Su, Fong-Chin
author_sort Yang, Tai-Hua
collection PubMed
description BACKGROUND: The treatment of trigger finger so far has heavily relied on clinicians’ evaluations for the severity of patients’ symptoms and the functionality of affected fingers. However, there is still a lack of pathological evidence supporting the criteria of clinical evaluations. This study’s aim was to correlate clinical classification and pathological changes for trigger finger based on the tissue abnormality observed from microscopic images. METHODS: Tissue samples were acquired, and microscopic images were randomly selected and then graded by three pathologists and two physicians, respectively. Moreover, the acquired images were automatically analyzed to derive two quantitative parameters, the size ratio of the abnormal tissue region and the number ratio of the abnormal nuclei, which can reflect tissue abnormality caused by trigger finger. A self-developed image analysis system was used to avoid human subjectivity during the quantification process. Finally, correlations between the quantitative image parameters, pathological grading, and clinical severity classification were assessed. RESULTS: One-way ANOVA tests revealed significant correlations between the image quantification and pathological grading as well as between the image quantification and clinical severity classification. The Cohen’s kappa coefficient test also depicted good consistency between pathological grading and clinical severity classification. CONCLUSIONS: The criteria of clinical classification were found to be highly associated with the pathological changes of affected tissues. The correlations serve as explicit evidence supporting clinicians in making a treatment strategy of trigger finger. In addition, our proposed computer-aided image analysis system was considered to be a promising and objective approach to determining trigger finger severity at the microscopic level.
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spelling pubmed-41186322014-08-02 Clinical and pathological correlates of severity classifications in trigger fingers based on computer-aided image analysis Yang, Tai-Hua Chen, Hsin-Chen Liu, Yung-Chun Shih, Hui-Hsuan Kuo, Li-Chieh Cha, Stephen Yang, Hsiao-Bai Yang, Dee-Shan Jou, I-Ming Sun, Yung-Nien Su, Fong-Chin Biomed Eng Online Research BACKGROUND: The treatment of trigger finger so far has heavily relied on clinicians’ evaluations for the severity of patients’ symptoms and the functionality of affected fingers. However, there is still a lack of pathological evidence supporting the criteria of clinical evaluations. This study’s aim was to correlate clinical classification and pathological changes for trigger finger based on the tissue abnormality observed from microscopic images. METHODS: Tissue samples were acquired, and microscopic images were randomly selected and then graded by three pathologists and two physicians, respectively. Moreover, the acquired images were automatically analyzed to derive two quantitative parameters, the size ratio of the abnormal tissue region and the number ratio of the abnormal nuclei, which can reflect tissue abnormality caused by trigger finger. A self-developed image analysis system was used to avoid human subjectivity during the quantification process. Finally, correlations between the quantitative image parameters, pathological grading, and clinical severity classification were assessed. RESULTS: One-way ANOVA tests revealed significant correlations between the image quantification and pathological grading as well as between the image quantification and clinical severity classification. The Cohen’s kappa coefficient test also depicted good consistency between pathological grading and clinical severity classification. CONCLUSIONS: The criteria of clinical classification were found to be highly associated with the pathological changes of affected tissues. The correlations serve as explicit evidence supporting clinicians in making a treatment strategy of trigger finger. In addition, our proposed computer-aided image analysis system was considered to be a promising and objective approach to determining trigger finger severity at the microscopic level. BioMed Central 2014-07-23 /pmc/articles/PMC4118632/ /pubmed/25055721 http://dx.doi.org/10.1186/1475-925X-13-100 Text en Copyright © 2014 Yang et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/4.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 Research
Yang, Tai-Hua
Chen, Hsin-Chen
Liu, Yung-Chun
Shih, Hui-Hsuan
Kuo, Li-Chieh
Cha, Stephen
Yang, Hsiao-Bai
Yang, Dee-Shan
Jou, I-Ming
Sun, Yung-Nien
Su, Fong-Chin
Clinical and pathological correlates of severity classifications in trigger fingers based on computer-aided image analysis
title Clinical and pathological correlates of severity classifications in trigger fingers based on computer-aided image analysis
title_full Clinical and pathological correlates of severity classifications in trigger fingers based on computer-aided image analysis
title_fullStr Clinical and pathological correlates of severity classifications in trigger fingers based on computer-aided image analysis
title_full_unstemmed Clinical and pathological correlates of severity classifications in trigger fingers based on computer-aided image analysis
title_short Clinical and pathological correlates of severity classifications in trigger fingers based on computer-aided image analysis
title_sort clinical and pathological correlates of severity classifications in trigger fingers based on computer-aided image analysis
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4118632/
https://www.ncbi.nlm.nih.gov/pubmed/25055721
http://dx.doi.org/10.1186/1475-925X-13-100
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