Literature DB >> 1692759

Quantitative features of chromatin structure in the prognosis of breast cancer.

D Komitowski1, C Janson.   

Abstract

In prognosis of breast cancer different parameters are in current use. Along with clinical staging the most important parameter appears to be histologic grading. Features of the grading such as nuclear pleomorphism proved to correlate closely with the proliferative activity and aggressiveness of the tumors. Because of difficulties in assessing and classifying the degree of nuclear pleomorphism by usual microscopy, the authors applied methods of digital image analysis. The study is a retrospective analysis of paraffine slides from the primary lesions of 60 breast cancers with 10 to 16 years of follow-up evaluation. Using large sets of different parameters defining nuclear morphology and chromatin structure the authors extracted criteria with prognostic importance. These included nuclear area in micron 2, eccentricity, integral optical density per micron 2, average area of a chromatin region, integral optical density of a chromatin region per micron 2, and the number of central chromatin regions per micron 2. The results demonstrate that the criteria used enable prediction of prognosis with an accuracy of 92%.

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Year:  1990        PMID: 1692759     DOI: 10.1002/1097-0142(19900615)65:12<2725::aid-cncr2820651221>3.0.co;2-u

Source DB:  PubMed          Journal:  Cancer        ISSN: 0008-543X            Impact factor:   6.860


  5 in total

1.  A prospective analysis of immunohistochemically determined hormone receptors and nuclear features as predictors of early recurrence in primary breast cancer.

Authors:  M Stierer; H Rosen; R Weber; H Hanak; L Auerbach; J Spona; H Tüchler
Journal:  Breast Cancer Res Treat       Date:  1995       Impact factor: 4.872

2.  Early Prediction of Cancer Progression by Depth-Resolved Nanoscale Mapping of Nuclear Architecture from Unstained Tissue Specimens.

Authors:  Shikhar Uttam; Hoa V Pham; Justin LaFace; Brian Leibowitz; Jian Yu; Randall E Brand; Douglas J Hartman; Yang Liu
Journal:  Cancer Res       Date:  2015-09-17       Impact factor: 12.701

3.  Improved prognostication in small (pT1) breast cancers by image cytometry.

Authors:  M Aubele; G Auer; U Falkmer; A Voss; K Rodenacker; L E Rutquist; H Höfler
Journal:  Breast Cancer Res Treat       Date:  1995       Impact factor: 4.872

4.  Nuclear image analysis study of neuroendocrine tumors.

Authors:  Meeja Park; Taehwa Baek; Jongho Baek; Hyunjin Son; Dongwook Kang; Jooheon Kim; Hyekyung Lee
Journal:  Korean J Pathol       Date:  2012-02-23

5.  Spectral morphometric characterization of breast carcinoma cells.

Authors:  I Barshack; J Kopolovic; Z Malik; C Rothmann
Journal:  Br J Cancer       Date:  1999-03       Impact factor: 7.640

  5 in total

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