Analytical cellular pathology : the journal of the European Society for Analytical Cellular Pathology最新文献

Background: Tissue counter analysis is an image analysis tool designed for the detection of structures in complex images at the macroscopic or microscopic scale. As a basic principle, small square or circular measuring masks are randomly placed across the image and image analysis parameters are obtained for each mask. Based on learning sets, statistical classification procedures are generated which facilitate an automated classification of new data sets.

Objective: To evaluate the influence of the size and shape of the measuring masks as well as the importance of feature selection, statistical procedures and technical preparation of slides on the performance of tissue counter analysis in microscopic images. As main quality measure of the final classification procedure, the percentage of elements that were correctly classified was used.

Study design: HE-stained slides of 25 primary cutaneous melanomas were evaluated by tissue counter analysis for the recognition of melanoma elements (section area occupied by tumour cells) in contrast to other tissue elements and background elements. Circular and square measuring masks, various subsets of image analysis features and classification and regression trees compared with linear discriminant analysis as statistical alternatives were used. The percentage of elements that were correctly classified by the various classification procedures was assessed. In order to evaluate the applicability to slides obtained from different laboratories, the best procedure was automatically applied in a test set of another 50 cases of primary melanoma derived from the same laboratory as the learning set and two test sets of 20 cases each derived from two different laboratories, and the measurements of melanoma area in these cases were compared with conventional assessment of vertical tumour thickness.

Results: Square measuring masks were slightly superior to circular masks, and larger masks (64 or 128 pixels in diameter) were superior to smaller masks (8 to 32 pixels in diameter). As far as the subsets of image analysis features were concerned, colour features were superior to densitometric and Haralick texture features. Statistical moments of the grey level distribution were of least significance. CART (classification and regression tree) analysis turned out to be superior to linear discriminant analysis. In the best setting, 95% of melanoma tissue elements were correctly recognized. Automated measurement of melanoma area in the independent test sets yielded a correlation of r=0.846 with vertical tumour thickness (p<0.001), similar to the relationship reported for manual measurements. The test sets obtained from different laboratories yielded comparable results.

Conclusions: Large, square measuring masks, colour features and CART analysis provide a useful setting for the automated measurement of melanoma tissue in

Multiple chromosomal imbalances have been identified in breast cancer using comparative genomic hybridization (CGH). Their association with the primary tumors' potential for building distant metastases is unknown. In this study we have investigated 39 invasive breast carcinomas with a mean follow-up period of 99 months (max. 193 months) by CGH to determine the prognostic value of chromosomal gains and losses. The mean number of chromosomal imbalances per tumor was 6.5+/-0.7 (range 2 to 18). The most frequent alterations identified in more than 1/3 of cases were gains on chromosomes 11q13, 12q24, 16, 17, and 20q, and losses on 2q and 13q. A significantly different frequency of chromosomal aberrations (p

In gynecologic oncology valid prognostic factors are necessary to define biologically similar subgroups for analysis of therapeutic efficacy. This study is the first published prospective study concerning prognostic significance of DNA ploidy and S-phase fraction in cervical and endometrial cancer following enrichment of tumor cells by cytokeratin labelling. Epithelial cells were labeled by FITC-conjugated cytokeratin antibody (CK 5, 6, 8, and CK 17) prior to flow cytometric cell cycle analysis in 91 specimens of cervical cancer and 73 samples of endometrial cancer. In cervical cancer neither DNA-ploidy nor S-phase fraction were relevant prognostic parameters. But CV of the G(0)G(1)-peak showed prognostic relevance in cervical cancer cells, even in multivariate analysis. This interesting observation, however, seems to have no therapeutic consequence due to the small discrimination capacity of CV. In endometrial carcinoma, gross DNA-aneuploidy (DNA-index > 1.3) and a high percentage of proliferating cells (>75th percentile) were univariate and multivariate highly significant prognostic factors for recurrence-free survival. Especially DNA-aneuploidy (DI>1.3) is one of the most important independent molecular biological prognostic factors. While diagnostic curettage we could identify risk patients even preoperatively by determination of the prognostic factors like histologic tumor type, grading, cervical involvement and DNA-ploidy. Thereby these patients could be treated primarily in an oncologic center. In conclusion, our investigations showed that the determination of DNA-ploidy should be done in endometrial carcinoma. In cervical cancer no clinical significance for determination of DNA-parameters was found.