A New Method of Grading Malignancy of Prostate Carcinoma Using Quantitative Microscopic Nuclear Features
A morphometrical assessment of nuclear features and a DNA study were performed on prostate tissue specimens from 33 patients with prostate carcinoma using an image analysing computer. Six nuclear geometric variables were measured and their mean, standard deviation (SD) and standard error (SE) were c...
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Veröffentlicht in: | Pathology, research and practice research and practice, 1989-11, Vol.185 (5), p.701-703 |
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description | A morphometrical assessment of nuclear features and a DNA study were performed on prostate tissue specimens from 33 patients with prostate carcinoma using an image analysing computer. Six nuclear geometric variables were measured and their mean, standard deviation (SD) and standard error (SE) were calculated for each case. The data on nuclear DNA content obtained by static cytometry were processed using an algorithm which provided a DNA grade of malignancy (DNA MG). Using the stepwise multiple regression, we found a significant correlation (p < 0.01) between the DNA MG, chosen as the dependent variable in the statistical model, and the following nuclear features in decreasing order ofimportance: area SD, convex perimeter SE, and the mean of maximum diameter. From the correlation coefficients of the variables an equation was built up which provided a geometric nuclear grade of malignancy (GNMG) on a morphometrical basis more closely related to the clinical stage ofthe tumour (r = 0.75) than the visually assessed histological grade (r = 0.68) based on the Gleason score. This new method of grading malignancy allows an objective and quantitative evaluation to be made of the biological behaviour of the tumour, as measured by the patient's clinical stage. |
doi_str_mv | 10.1016/S0344-0338(89)80221-3 |
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Six nuclear geometric variables were measured and their mean, standard deviation (SD) and standard error (SE) were calculated for each case. The data on nuclear DNA content obtained by static cytometry were processed using an algorithm which provided a DNA grade of malignancy (DNA MG). Using the stepwise multiple regression, we found a significant correlation (p < 0.01) between the DNA MG, chosen as the dependent variable in the statistical model, and the following nuclear features in decreasing order ofimportance: area SD, convex perimeter SE, and the mean of maximum diameter. From the correlation coefficients of the variables an equation was built up which provided a geometric nuclear grade of malignancy (GNMG) on a morphometrical basis more closely related to the clinical stage ofthe tumour (r = 0.75) than the visually assessed histological grade (r = 0.68) based on the Gleason score. This new method of grading malignancy allows an objective and quantitative evaluation to be made of the biological behaviour of the tumour, as measured by the patient's clinical stage.</description><identifier>ISSN: 0344-0338</identifier><identifier>EISSN: 1618-0631</identifier><identifier>DOI: 10.1016/S0344-0338(89)80221-3</identifier><identifier>PMID: 2626378</identifier><language>eng</language><publisher>Germany: Elsevier GmbH</publisher><subject>Cell Nucleus - pathology ; Computer assisted morphometry ; DNA, Neoplasm - analysis ; Humans ; Image Processing, Computer-Assisted - methods ; Male ; Malignancy grade ; Prostate carcinoma ; Prostatic Neoplasms - pathology ; Prostatic Neoplasms - ultrastructure ; Regression Analysis</subject><ispartof>Pathology, research and practice, 1989-11, Vol.185 (5), p.701-703</ispartof><rights>1989 Gustav Fischer Verlag · Stuttgart · New York</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c360t-6a82feb023fe2f3bd9be1b55c8f7039d969cda392e0f890ba6cfb35c0f8cbcd53</citedby><cites>FETCH-LOGICAL-c360t-6a82feb023fe2f3bd9be1b55c8f7039d969cda392e0f890ba6cfb35c0f8cbcd53</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/S0344-0338(89)80221-3$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>315,781,785,3551,27926,27927,45997</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/2626378$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Robutti, F.</creatorcontrib><creatorcontrib>Pilato, F.P.</creatorcontrib><creatorcontrib>Betta, P.-G.</creatorcontrib><title>A New Method of Grading Malignancy of Prostate Carcinoma Using Quantitative Microscopic Nuclear Features</title><title>Pathology, research and practice</title><addtitle>Pathol Res Pract</addtitle><description>A morphometrical assessment of nuclear features and a DNA study were performed on prostate tissue specimens from 33 patients with prostate carcinoma using an image analysing computer. Six nuclear geometric variables were measured and their mean, standard deviation (SD) and standard error (SE) were calculated for each case. The data on nuclear DNA content obtained by static cytometry were processed using an algorithm which provided a DNA grade of malignancy (DNA MG). Using the stepwise multiple regression, we found a significant correlation (p < 0.01) between the DNA MG, chosen as the dependent variable in the statistical model, and the following nuclear features in decreasing order ofimportance: area SD, convex perimeter SE, and the mean of maximum diameter. From the correlation coefficients of the variables an equation was built up which provided a geometric nuclear grade of malignancy (GNMG) on a morphometrical basis more closely related to the clinical stage ofthe tumour (r = 0.75) than the visually assessed histological grade (r = 0.68) based on the Gleason score. This new method of grading malignancy allows an objective and quantitative evaluation to be made of the biological behaviour of the tumour, as measured by the patient's clinical stage.</description><subject>Cell Nucleus - pathology</subject><subject>Computer assisted morphometry</subject><subject>DNA, Neoplasm - analysis</subject><subject>Humans</subject><subject>Image Processing, Computer-Assisted - methods</subject><subject>Male</subject><subject>Malignancy grade</subject><subject>Prostate carcinoma</subject><subject>Prostatic Neoplasms - pathology</subject><subject>Prostatic Neoplasms - ultrastructure</subject><subject>Regression Analysis</subject><issn>0344-0338</issn><issn>1618-0631</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1989</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkE1v1DAQhi0EKtvCT6jkE6KHlHGceO0Tqlb9kroFBD1bznjcGmWTxU4W9d-TdFe9crLG7zMz9sPYqYBzAUJ9-QmyqgqQUn_W5kxDWYpCvmELoYQuQEnxli1ekffsOOffALCEShyxo1KVSi71gj1d8Hv6y9c0PPWe94FfJ-dj98jXro2Pnevweb79nvo8uIH4yiWMXb9x_CHP2I_RdUOcorgjvo44cdhvI_L7EVtyiV-RG8ZE-QN7F1yb6ePhPGEPV5e_VjfF3bfr29XFXYFSwVAop8tADZQyUBlk401Doqlr1GEJ0nijDHonTUkQtIHGKQyNrHGqsEFfyxP2aT93m_o_I-XBbmJGalvXUT9muzSVlrKCCaz34PzmnCjYbYobl56tADsbti-G7azPamNfDFs59Z0eFozNhvxr10HplH_d5zT9chcp2YyROiQfE-FgfR__s-EfzneMng</recordid><startdate>19891101</startdate><enddate>19891101</enddate><creator>Robutti, F.</creator><creator>Pilato, F.P.</creator><creator>Betta, P.-G.</creator><general>Elsevier GmbH</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope></search><sort><creationdate>19891101</creationdate><title>A New Method of Grading Malignancy of Prostate Carcinoma Using Quantitative Microscopic Nuclear Features</title><author>Robutti, F. ; Pilato, F.P. ; Betta, P.-G.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c360t-6a82feb023fe2f3bd9be1b55c8f7039d969cda392e0f890ba6cfb35c0f8cbcd53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1989</creationdate><topic>Cell Nucleus - pathology</topic><topic>Computer assisted morphometry</topic><topic>DNA, Neoplasm - analysis</topic><topic>Humans</topic><topic>Image Processing, Computer-Assisted - methods</topic><topic>Male</topic><topic>Malignancy grade</topic><topic>Prostate carcinoma</topic><topic>Prostatic Neoplasms - pathology</topic><topic>Prostatic Neoplasms - ultrastructure</topic><topic>Regression Analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Robutti, F.</creatorcontrib><creatorcontrib>Pilato, F.P.</creatorcontrib><creatorcontrib>Betta, P.-G.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><jtitle>Pathology, research and practice</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Robutti, F.</au><au>Pilato, F.P.</au><au>Betta, P.-G.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A New Method of Grading Malignancy of Prostate Carcinoma Using Quantitative Microscopic Nuclear Features</atitle><jtitle>Pathology, research and practice</jtitle><addtitle>Pathol Res Pract</addtitle><date>1989-11-01</date><risdate>1989</risdate><volume>185</volume><issue>5</issue><spage>701</spage><epage>703</epage><pages>701-703</pages><issn>0344-0338</issn><eissn>1618-0631</eissn><abstract>A morphometrical assessment of nuclear features and a DNA study were performed on prostate tissue specimens from 33 patients with prostate carcinoma using an image analysing computer. Six nuclear geometric variables were measured and their mean, standard deviation (SD) and standard error (SE) were calculated for each case. The data on nuclear DNA content obtained by static cytometry were processed using an algorithm which provided a DNA grade of malignancy (DNA MG). Using the stepwise multiple regression, we found a significant correlation (p < 0.01) between the DNA MG, chosen as the dependent variable in the statistical model, and the following nuclear features in decreasing order ofimportance: area SD, convex perimeter SE, and the mean of maximum diameter. From the correlation coefficients of the variables an equation was built up which provided a geometric nuclear grade of malignancy (GNMG) on a morphometrical basis more closely related to the clinical stage ofthe tumour (r = 0.75) than the visually assessed histological grade (r = 0.68) based on the Gleason score. This new method of grading malignancy allows an objective and quantitative evaluation to be made of the biological behaviour of the tumour, as measured by the patient's clinical stage.</abstract><cop>Germany</cop><pub>Elsevier GmbH</pub><pmid>2626378</pmid><doi>10.1016/S0344-0338(89)80221-3</doi><tpages>3</tpages></addata></record> |
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subjects | Cell Nucleus - pathology Computer assisted morphometry DNA, Neoplasm - analysis Humans Image Processing, Computer-Assisted - methods Male Malignancy grade Prostate carcinoma Prostatic Neoplasms - pathology Prostatic Neoplasms - ultrastructure Regression Analysis |
title | A New Method of Grading Malignancy of Prostate Carcinoma Using Quantitative Microscopic Nuclear Features |
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