Literature DB >> 8950575

Computerized nuclear morphometry of renal cell carcinomas.

E Paraskevakou1, N Kavantzas, P M Pavlopoulos, A Delibasis, D Yova, P Davaris.   

Abstract

The aim of this study was the evaluation of the usefulness of nuclear morphometry in the pathology of renal cell carcinoma by computer-aided image analysis and the statistical comparison of nuclear morphometric parameters with the histologic grade of the tumors. 44 cases of renal cell carcinoma, classified by two independent pathologists into 4 histologic grades (I-IV), were examined. The following 5 nuclear morphometric parameters were measured in a large number of randomly selected nuclei of each case: Major axis length, area, elongation, roundness and compactness. The statistical evaluation was performed using one-way analysis of variance between the four groups of the histologic grades (I-IV). Between them, there was a statistically very significant difference of the mean value of all the evaluated parameters. The values of the estimated parameters, with the exception of roundness and compactness, showed a strong tendency to increase in proportion to histologic grade. Our results suggest that image analysis is a reproducible and objective method for the grading of renal cell carcinoma, and it can be helpful in the unbiased evaluation of such tumors.

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Mesh:

Year:  1996        PMID: 8950575

Source DB:  PubMed          Journal:  Gen Diagn Pathol        ISSN: 0947-823X


  2 in total

1.  Association between microvessel density and histologic grade in renal cell carcinomas.

Authors:  Nikolaos Kavantzas; Helen Paraskevakou; Sofia Tseleni-Balafouta; Kyriaki Aroni; Pauline Athanassiades; George Agrogiannis; Efstratios Patsouris
Journal:  Pathol Oncol Res       Date:  2007-07-03       Impact factor: 3.201

2.  Computerized Cytological Features for Papillary Thyroid Cancer Diagnosis-Preliminary Report.

Authors:  Shyang-Rong Shih; I-Shiow Jan; Kuen-Yuan Chen; Wan-Yu Chuang; Chih-Yuan Wang; Yung-Lien Hsiao; Tien-Chun Chang; Argon Chen
Journal:  Cancers (Basel)       Date:  2019-10-25       Impact factor: 6.639

  2 in total

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