André Huisman, Lennert S Ploeger, Hub F J Dullens, Trudy N Jonges, Paul J van Diest
{"title":"用共聚焦激光扫描显微镜三维染色质织构分析前列腺活检良恶性鉴别。","authors":"André Huisman, Lennert S Ploeger, Hub F J Dullens, Trudy N Jonges, Paul J van Diest","doi":"","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>To evaluate the clinical usefulness of computing three-dimensional (3-D) nuclear texture features on prostate biopsy specimens to discriminate among benign, prostatic intraepithelial neoplasia (PIN), and malignant specimens.</p><p><strong>Study design: </strong>Twelve prostate cancer biopsy specimens were selected, diagnosed as either benign (N = 4), PIN (N = 4), or malignant (N = 4). Sections 14 microm thick were stained. 3-D image stacks of selected benign and malignant areas were obtained by confocal laser scanning microscopy (CLSM) and analyzed off-line using in-house-developed software for 3-D semiautomated segmentation and calculation of texture features. The power of the 3-D texture features to discriminate among the pooled benign (N = 1,507), PIN (N = 673), and malignant nuclei (N = 1,251) was established by multivariate linear discriminant analysis.</p><p><strong>Results: </strong>A total of 68.8% of the benign nuclei, 77.2% of the PIN nuclei, and 78.5% of the malignant nuclei could be classified correctly after cross validation.</p><p><strong>Conclusion: </strong>Quantification of changes in the distribution of nuclear chromatin by means of 3-D texture feature computation on CLSM images allows discriminating most benign and malignant prostate nuclei, which could be useful in cases that are difficult to diagnose morphologically.</p>","PeriodicalId":76995,"journal":{"name":"Analytical and quantitative cytology and histology","volume":"33 5","pages":"265-70"},"PeriodicalIF":0.0000,"publicationDate":"2011-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Discrimination between benign and malignant prostate biopsies using three-dimensional chromatin texture analysis by confocal laser scanning microscopy.\",\"authors\":\"André Huisman, Lennert S Ploeger, Hub F J Dullens, Trudy N Jonges, Paul J van Diest\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>To evaluate the clinical usefulness of computing three-dimensional (3-D) nuclear texture features on prostate biopsy specimens to discriminate among benign, prostatic intraepithelial neoplasia (PIN), and malignant specimens.</p><p><strong>Study design: </strong>Twelve prostate cancer biopsy specimens were selected, diagnosed as either benign (N = 4), PIN (N = 4), or malignant (N = 4). Sections 14 microm thick were stained. 3-D image stacks of selected benign and malignant areas were obtained by confocal laser scanning microscopy (CLSM) and analyzed off-line using in-house-developed software for 3-D semiautomated segmentation and calculation of texture features. The power of the 3-D texture features to discriminate among the pooled benign (N = 1,507), PIN (N = 673), and malignant nuclei (N = 1,251) was established by multivariate linear discriminant analysis.</p><p><strong>Results: </strong>A total of 68.8% of the benign nuclei, 77.2% of the PIN nuclei, and 78.5% of the malignant nuclei could be classified correctly after cross validation.</p><p><strong>Conclusion: </strong>Quantification of changes in the distribution of nuclear chromatin by means of 3-D texture feature computation on CLSM images allows discriminating most benign and malignant prostate nuclei, which could be useful in cases that are difficult to diagnose morphologically.</p>\",\"PeriodicalId\":76995,\"journal\":{\"name\":\"Analytical and quantitative cytology and histology\",\"volume\":\"33 5\",\"pages\":\"265-70\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Analytical and quantitative cytology and histology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytical and quantitative cytology and histology","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Discrimination between benign and malignant prostate biopsies using three-dimensional chromatin texture analysis by confocal laser scanning microscopy.
Objective: To evaluate the clinical usefulness of computing three-dimensional (3-D) nuclear texture features on prostate biopsy specimens to discriminate among benign, prostatic intraepithelial neoplasia (PIN), and malignant specimens.
Study design: Twelve prostate cancer biopsy specimens were selected, diagnosed as either benign (N = 4), PIN (N = 4), or malignant (N = 4). Sections 14 microm thick were stained. 3-D image stacks of selected benign and malignant areas were obtained by confocal laser scanning microscopy (CLSM) and analyzed off-line using in-house-developed software for 3-D semiautomated segmentation and calculation of texture features. The power of the 3-D texture features to discriminate among the pooled benign (N = 1,507), PIN (N = 673), and malignant nuclei (N = 1,251) was established by multivariate linear discriminant analysis.
Results: A total of 68.8% of the benign nuclei, 77.2% of the PIN nuclei, and 78.5% of the malignant nuclei could be classified correctly after cross validation.
Conclusion: Quantification of changes in the distribution of nuclear chromatin by means of 3-D texture feature computation on CLSM images allows discriminating most benign and malignant prostate nuclei, which could be useful in cases that are difficult to diagnose morphologically.