Literature DB >> 2206192

Tissue architectural features for the grading of prostatic carcinoma.

M Bibbo1, D H Kim, C di Loreto, H E Dytch, H Galera-Davidson, D Thompson, D L Richards, H G Bartels, P H Bartels.   

Abstract

In research for the development of a computer-aided workstation for the objective grading of prostatic carcinoma, tissue architectural (histometric) features were analyzed in ten cases each of well-differentiated, moderately differentiated and poorly differentiated carcinoma (as subjectively graded by the consensus of a panel of experts). Sections were cut at 4 microns, stained by the Feulgen reaction and digitized by two different video-based photometric systems. Some images were interactively segmented, considering the histometric clues to be studied; others were automatically segmented by an expert system-guided technique. The latter procedure produced good results, with over 90% of the nuclei judged to be correctly segmented in 64% of the fields studied and over 80% in another 24% of the fields. While the number of nuclei per field provided some separation of well-differentiated from other lesions, the number of nuclei per gland distinguished between well-differentiated and moderately differentiated lesions. Simplicial decomposition of the images also provided a measure of the degree of differentiation, as did the "texture" of the nuclear placement, based on two run-length statistics. Combination of the run-length features distinguished the three categories of lesions with statistical significance. The results of this study provided insights into the problems (such as the effect of field boundaries) faced in the design of an computer-aided grading system. They also showed the value of expert system-guided scene segmentation and of such histometric features as the field cellularity and the number of nuclei per gland for the discrimination between lesions of different grades of differentiation.

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Year:  1990        PMID: 2206192

Source DB:  PubMed          Journal:  Anal Quant Cytol Histol        ISSN: 0884-6812            Impact factor:   0.302


  3 in total

1.  Automated quantification of nuclear immunohistochemical markers with different complexity.

Authors:  Carlos López; Marylène Lejeune; María Teresa Salvadó; Patricia Escrivà; Ramón Bosch; Lluis E Pons; Tomás Alvaro; Jordi Roig; Xavier Cugat; Jordi Baucells; Joaquín Jaén
Journal:  Histochem Cell Biol       Date:  2008-01-03       Impact factor: 4.304

2.  Quantitative assessment of gastric atrophy using the syntactic structure analysis.

Authors:  A M Zaitoun; H al Mardini; C O Record
Journal:  J Clin Pathol       Date:  1998-12       Impact factor: 3.411

3.  Syntactic structure analysis in uveal melanomas.

Authors:  K Coleman; P J van Diest; J P Baak; J Mullaney
Journal:  Br J Ophthalmol       Date:  1994-11       Impact factor: 4.638

  3 in total

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