{"title":"染色质纹理和核分形尺寸分析能否作为有效手段,将具有乳头状核特征的非侵袭性甲状腺滤泡性肿瘤与其他具有甲状腺滤泡形态的恶性肿瘤区分开来?","authors":"Geet Bhuyan, Anjumoni Rabha","doi":"10.1080/01913123.2024.2362758","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>Thyroid carcinoma ranks as the 9th most prevalent global cancer, accounting for 586,202 cases and 43,636 deaths in 2020. Computerized image analysis, utilizing artificial intelligence algorithms, emerges as a potential tool for tumor evaluation.</p><p><strong>Aim: </strong>This study aims to assess and compare chromatin textural characteristics and nuclear dimensions in follicular neoplasms through gray-level co-occurrence matrix (GLCM), fractal, and morphometric analysis.</p><p><strong>Method: </strong>A retrospective cross-sectional study involving 115 thyroid malignancies, specifically 49 papillary thyroid carcinomas with follicular morphology, was conducted from July 2021 to July 2023. Ethical approval was obtained, and histopathological examination, along with image analysis, was performed using ImageJ software.</p><p><strong>Results: </strong>A statistically significant difference was observed in contrast (2.426 (1.774-3.412) vs 2.664 (1.963-3.610), <i>p</i> = .002), correlation (1.202 (1.071-1.298) vs 0.892 (0.833-0.946), <i>p</i> = .01), and ASM (0.071 (0.090-0.131) vs 0.044 (0.019-0.102), <i>p</i> = .036) between NIFTP and IFVPTC. However, morphometric parameters did not yield statistically significant differences among histological variants.</p><p><strong>Conclusion: </strong>Computerized image analysis, though promising in subtype discrimination, requires further refinement and integration with traditional diagnostic parameters. The study suggests potential applications in scenarios where conventional histopathological assessment faces limitations due to limited tissue availability. Despite limitations such as a small sample size and a retrospective design, the findings contribute to understanding thyroid carcinoma characteristics and underscore the need for comprehensive evaluations integrating various diagnostic modalities.</p>","PeriodicalId":23430,"journal":{"name":"Ultrastructural Pathology","volume":" ","pages":"310-316"},"PeriodicalIF":1.1000,"publicationDate":"2024-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Can the analysis of chromatin texture and nuclear fractal dimensions serve as effective means to distinguish non-invasive follicular thyroid neoplasm with papillary-like nuclear features from other malignancies with follicular pattern in the thyroid?: a study.\",\"authors\":\"Geet Bhuyan, Anjumoni Rabha\",\"doi\":\"10.1080/01913123.2024.2362758\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>Thyroid carcinoma ranks as the 9th most prevalent global cancer, accounting for 586,202 cases and 43,636 deaths in 2020. Computerized image analysis, utilizing artificial intelligence algorithms, emerges as a potential tool for tumor evaluation.</p><p><strong>Aim: </strong>This study aims to assess and compare chromatin textural characteristics and nuclear dimensions in follicular neoplasms through gray-level co-occurrence matrix (GLCM), fractal, and morphometric analysis.</p><p><strong>Method: </strong>A retrospective cross-sectional study involving 115 thyroid malignancies, specifically 49 papillary thyroid carcinomas with follicular morphology, was conducted from July 2021 to July 2023. Ethical approval was obtained, and histopathological examination, along with image analysis, was performed using ImageJ software.</p><p><strong>Results: </strong>A statistically significant difference was observed in contrast (2.426 (1.774-3.412) vs 2.664 (1.963-3.610), <i>p</i> = .002), correlation (1.202 (1.071-1.298) vs 0.892 (0.833-0.946), <i>p</i> = .01), and ASM (0.071 (0.090-0.131) vs 0.044 (0.019-0.102), <i>p</i> = .036) between NIFTP and IFVPTC. However, morphometric parameters did not yield statistically significant differences among histological variants.</p><p><strong>Conclusion: </strong>Computerized image analysis, though promising in subtype discrimination, requires further refinement and integration with traditional diagnostic parameters. The study suggests potential applications in scenarios where conventional histopathological assessment faces limitations due to limited tissue availability. Despite limitations such as a small sample size and a retrospective design, the findings contribute to understanding thyroid carcinoma characteristics and underscore the need for comprehensive evaluations integrating various diagnostic modalities.</p>\",\"PeriodicalId\":23430,\"journal\":{\"name\":\"Ultrastructural Pathology\",\"volume\":\" \",\"pages\":\"310-316\"},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2024-07-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ultrastructural Pathology\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1080/01913123.2024.2362758\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/6/3 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q4\",\"JCRName\":\"MICROSCOPY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ultrastructural Pathology","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1080/01913123.2024.2362758","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/6/3 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"MICROSCOPY","Score":null,"Total":0}
Can the analysis of chromatin texture and nuclear fractal dimensions serve as effective means to distinguish non-invasive follicular thyroid neoplasm with papillary-like nuclear features from other malignancies with follicular pattern in the thyroid?: a study.
Objective: Thyroid carcinoma ranks as the 9th most prevalent global cancer, accounting for 586,202 cases and 43,636 deaths in 2020. Computerized image analysis, utilizing artificial intelligence algorithms, emerges as a potential tool for tumor evaluation.
Aim: This study aims to assess and compare chromatin textural characteristics and nuclear dimensions in follicular neoplasms through gray-level co-occurrence matrix (GLCM), fractal, and morphometric analysis.
Method: A retrospective cross-sectional study involving 115 thyroid malignancies, specifically 49 papillary thyroid carcinomas with follicular morphology, was conducted from July 2021 to July 2023. Ethical approval was obtained, and histopathological examination, along with image analysis, was performed using ImageJ software.
Results: A statistically significant difference was observed in contrast (2.426 (1.774-3.412) vs 2.664 (1.963-3.610), p = .002), correlation (1.202 (1.071-1.298) vs 0.892 (0.833-0.946), p = .01), and ASM (0.071 (0.090-0.131) vs 0.044 (0.019-0.102), p = .036) between NIFTP and IFVPTC. However, morphometric parameters did not yield statistically significant differences among histological variants.
Conclusion: Computerized image analysis, though promising in subtype discrimination, requires further refinement and integration with traditional diagnostic parameters. The study suggests potential applications in scenarios where conventional histopathological assessment faces limitations due to limited tissue availability. Despite limitations such as a small sample size and a retrospective design, the findings contribute to understanding thyroid carcinoma characteristics and underscore the need for comprehensive evaluations integrating various diagnostic modalities.
期刊介绍:
Ultrastructural Pathology is the official journal of the Society for Ultrastructural Pathology. Published bimonthly, we are the only journal to be devoted entirely to diagnostic ultrastructural pathology.
Ultrastructural Pathology is the ideal journal to publish high-quality research on the following topics:
Advances in the uses of electron microscopic and immunohistochemical techniques
Correlations of ultrastructural data with light microscopy, histochemistry, immunohistochemistry, biochemistry, cell and tissue culturing, and electron probe analysis
Important new, investigative, clinical, and diagnostic EM methods.