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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...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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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. |
format | Online Article Text |
id | pubmed-4118632 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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