A Konstantinidou, E Patsouris, N Kavantzas, P M Pavlopoulos, V Bouropoulou, P Davaris
{"title":"脑膜瘤中增殖细胞核抗原表达的计算机测定。与非自动化方法的比较。","authors":"A Konstantinidou, E Patsouris, N Kavantzas, P M Pavlopoulos, V Bouropoulou, P Davaris","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>Proliferating cell nuclear antigen (PCNA) expression has been proven to be a significant marker of cell proliferation in meningiomas, which correlates with growth rate and, as shown by several authors, possibly provides prognostic information concerning biologic behavior. However, the current method for determining PCNA labeling index (LI) is tedious and time consuming like all the nonautomated methods for evaluating cell kinetics, presenting high interobserver and interlaboratory variability and low reproducibility. In the present study, we introduce a semi-automated computer-assisted image analysis method for determining PCNA LI in 38 meningiomas, in parallel with the current nonautomated method. Image analysis technique permits unbiased cell counting, standardizes the degree of staining intensity and provides instant results. By calculating coefficient of variability, the method proved to be highly reproducible. The correlation between the results provided by the nonautomated and the semiautomated image analysis method showed a high agreement between them, with a correlation coefficient, r, of 0.82. In conclusion, we consider that image analysis contributes to the accuracy, reproducibility, and practicality of PCNA LI determination so that along with other useful parameters this significant marker may serve to predict the clinical behavior in meningiomas.</p>","PeriodicalId":79430,"journal":{"name":"General & diagnostic pathology","volume":"142 5-6","pages":"311-6"},"PeriodicalIF":0.0000,"publicationDate":"1997-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Computerized determination of proliferating cell nuclear antigen expression in meningiomas. A comparison with non-automated method.\",\"authors\":\"A Konstantinidou, E Patsouris, N Kavantzas, P M Pavlopoulos, V Bouropoulou, P Davaris\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Proliferating cell nuclear antigen (PCNA) expression has been proven to be a significant marker of cell proliferation in meningiomas, which correlates with growth rate and, as shown by several authors, possibly provides prognostic information concerning biologic behavior. However, the current method for determining PCNA labeling index (LI) is tedious and time consuming like all the nonautomated methods for evaluating cell kinetics, presenting high interobserver and interlaboratory variability and low reproducibility. In the present study, we introduce a semi-automated computer-assisted image analysis method for determining PCNA LI in 38 meningiomas, in parallel with the current nonautomated method. Image analysis technique permits unbiased cell counting, standardizes the degree of staining intensity and provides instant results. By calculating coefficient of variability, the method proved to be highly reproducible. The correlation between the results provided by the nonautomated and the semiautomated image analysis method showed a high agreement between them, with a correlation coefficient, r, of 0.82. In conclusion, we consider that image analysis contributes to the accuracy, reproducibility, and practicality of PCNA LI determination so that along with other useful parameters this significant marker may serve to predict the clinical behavior in meningiomas.</p>\",\"PeriodicalId\":79430,\"journal\":{\"name\":\"General & diagnostic pathology\",\"volume\":\"142 5-6\",\"pages\":\"311-6\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1997-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"General & diagnostic pathology\",\"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":"General & diagnostic pathology","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Computerized determination of proliferating cell nuclear antigen expression in meningiomas. A comparison with non-automated method.
Proliferating cell nuclear antigen (PCNA) expression has been proven to be a significant marker of cell proliferation in meningiomas, which correlates with growth rate and, as shown by several authors, possibly provides prognostic information concerning biologic behavior. However, the current method for determining PCNA labeling index (LI) is tedious and time consuming like all the nonautomated methods for evaluating cell kinetics, presenting high interobserver and interlaboratory variability and low reproducibility. In the present study, we introduce a semi-automated computer-assisted image analysis method for determining PCNA LI in 38 meningiomas, in parallel with the current nonautomated method. Image analysis technique permits unbiased cell counting, standardizes the degree of staining intensity and provides instant results. By calculating coefficient of variability, the method proved to be highly reproducible. The correlation between the results provided by the nonautomated and the semiautomated image analysis method showed a high agreement between them, with a correlation coefficient, r, of 0.82. In conclusion, we consider that image analysis contributes to the accuracy, reproducibility, and practicality of PCNA LI determination so that along with other useful parameters this significant marker may serve to predict the clinical behavior in meningiomas.