Phillip A Williams, Bojana Djordjevic, Yasmine Ayroud, Shahidul Islam, Denis Gravel, Susan J Robertson, Carlos Parra-Herran
{"title":"乳腺扁平上皮异型性的核形态测定作为恶性肿瘤的预测因子:基于数字图像的组织病理学分析。","authors":"Phillip A Williams, Bojana Djordjevic, Yasmine Ayroud, Shahidul Islam, Denis Gravel, Susan J Robertson, Carlos Parra-Herran","doi":"","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To identify morphometric features unique to flat epithelial atypia associated with cancer using digital image analysis.</p><p><strong>Study design: </strong>Cases with diagnosis of flat epithelial atypia were retrieved and divided into 2 groups: flat epithelial atypia associated with invasive or in situ carcinoma (n = 31) and those without malignancy (n = 27). Slides were digitally scanned. Nuclear features were analyzed on representative images at 20x magnification using digital morphometric software.</p><p><strong>Results: </strong>Parameters related to nuclear shape and size (diameter, perimeter) were similar in both groups. However, cases with malignancy had significantly higher densitometric green (p = 0.02), red (p = 0.03), and grey (p = 0.02) scale levels as compared to cases without cancer. A mean grey densitometric level > 119.45 had 71% sensitivity and 70.4% specificity in detecting cases with concomitant carcinoma.</p><p><strong>Conclusion: </strong>Morphometry of features related to nuclear staining appears to be useful in predicting risk of concurrent malignancy in patients with flat epithelial atypia, when added to a comprehensive histopathologic evaluation.</p>","PeriodicalId":55517,"journal":{"name":"Analytical and Quantitative Cytopathology and Histopathology","volume":"36 6","pages":"305-13"},"PeriodicalIF":0.1000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Nuclear morphometry in flat epithelial atypia of the breast as a predictor of malignancy: a digital image-based histopathologic analysis.\",\"authors\":\"Phillip A Williams, Bojana Djordjevic, Yasmine Ayroud, Shahidul Islam, Denis Gravel, Susan J Robertson, Carlos Parra-Herran\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To identify morphometric features unique to flat epithelial atypia associated with cancer using digital image analysis.</p><p><strong>Study design: </strong>Cases with diagnosis of flat epithelial atypia were retrieved and divided into 2 groups: flat epithelial atypia associated with invasive or in situ carcinoma (n = 31) and those without malignancy (n = 27). Slides were digitally scanned. Nuclear features were analyzed on representative images at 20x magnification using digital morphometric software.</p><p><strong>Results: </strong>Parameters related to nuclear shape and size (diameter, perimeter) were similar in both groups. However, cases with malignancy had significantly higher densitometric green (p = 0.02), red (p = 0.03), and grey (p = 0.02) scale levels as compared to cases without cancer. A mean grey densitometric level > 119.45 had 71% sensitivity and 70.4% specificity in detecting cases with concomitant carcinoma.</p><p><strong>Conclusion: </strong>Morphometry of features related to nuclear staining appears to be useful in predicting risk of concurrent malignancy in patients with flat epithelial atypia, when added to a comprehensive histopathologic evaluation.</p>\",\"PeriodicalId\":55517,\"journal\":{\"name\":\"Analytical and Quantitative Cytopathology and Histopathology\",\"volume\":\"36 6\",\"pages\":\"305-13\"},\"PeriodicalIF\":0.1000,\"publicationDate\":\"2014-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Analytical and Quantitative Cytopathology and Histopathology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytical and Quantitative Cytopathology and Histopathology","FirstCategoryId":"3","ListUrlMain":"","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Medicine","Score":null,"Total":0}
Nuclear morphometry in flat epithelial atypia of the breast as a predictor of malignancy: a digital image-based histopathologic analysis.
Objective: To identify morphometric features unique to flat epithelial atypia associated with cancer using digital image analysis.
Study design: Cases with diagnosis of flat epithelial atypia were retrieved and divided into 2 groups: flat epithelial atypia associated with invasive or in situ carcinoma (n = 31) and those without malignancy (n = 27). Slides were digitally scanned. Nuclear features were analyzed on representative images at 20x magnification using digital morphometric software.
Results: Parameters related to nuclear shape and size (diameter, perimeter) were similar in both groups. However, cases with malignancy had significantly higher densitometric green (p = 0.02), red (p = 0.03), and grey (p = 0.02) scale levels as compared to cases without cancer. A mean grey densitometric level > 119.45 had 71% sensitivity and 70.4% specificity in detecting cases with concomitant carcinoma.
Conclusion: Morphometry of features related to nuclear staining appears to be useful in predicting risk of concurrent malignancy in patients with flat epithelial atypia, when added to a comprehensive histopathologic evaluation.
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