The chromatin pattern of cell nuclei is of prognostic value for renal cell carcinomas

Analytical Cellular Pathology

Volumn 16, Issue 3, 1998, Pages 161-175

  François, Christine ^a   Remmelink, Myriam ^b   Petein, Michel ^b   Van Velthoven, Roland ^c   Danguy, André ^a   Wespes, Eric ^b   Salmon, Isabelle ^b   Kiss, Robert ^a,d   Decaestecker, Christine ^a  

^a UNIVERSITÉ LIBRE DE BRUXELLES   (Belgium)

^b ERASME HOSPITAL   (Belgium)

^c JULES BORDET INSTITUTE   (Belgium)

^d FNRS   (Belgium)

Author keywords

Artificial intelligence; Chromatin pattern; DNA ploidy; Feulgen staining; Image cytometry; Prognosis; Renal cell carcinoma

Indexed keywords

ADULT; AGED; ARTICLE; CANCER SURVIVAL; CHROMATIN STRUCTURE; DIAGNOSTIC VALUE; FEMALE; HUMAN; HUMAN TISSUE; IMAGE CYTOMETRY; KIDNEY CARCINOMA; MALE; PRIORITY JOURNAL;

EID: 0031800414     PISSN: 09218912     EISSN: None     Source Type: Journal    
DOI: 10.1155/1998/485143     Document Type: Article

References (35)

1. O. Arner, C. Blanck and T. von Schreeb, Malignancy grading of renal adenocarcinoma, Acta Chir. Scand. 346(Suppl.) (1965), 1-50.
2. G. Brugal, C. Garbay, F. Giroud and D. Adhel, A double scanning microphotometer for image analysis: Hardware, software and biomedical applications, J. Histochem. Cytochem. 27 (1979), 144-152.
3. C. Decaestecker, R. van Velthoven, M. Petein, T. Janssen, I. Salmon, J.L. Pasteels, P. Van Ham, C. Schulman and R. Kiss, The use of the decision tree technique and image cytometry to characterize aggressiveness in World Health Organization (WHO) grade II superficial transitional cell carcinoma of the bladder, J. Pathol. 178 (1996), 274-283.
4. C. Decaestecker, I. Camby, N. Nagy, J. Brotchi, R. Kiss and I. Salmon, Improving morphology-based malignancy grading schemes in astrocytic tumors by means of computer-assisted techniques, Brain Pathol. 8 (1998), 29-38.
5. C. Decaestecker, M. Remmelink, I. Salmon, I. Camby, D. Goldshmidt, M. Petein, P. Van Ham, J.L. Pasteels and R. Kiss, Methodological aspects of using Decision Trees to characterize leiomyomatous tumors, Cytometry 24 (1996), 83-92.
6. C. DePrez, Y. de Launoit, R. Kiss, M. Petein, J.L. Pasteels, A. Verhest and R. van Velthoven, Computerized morphonuclear cell image analysis of malignant disease in bladder tissues, J. Urol. 143 (1990), 694-699.
7. C. François, C. Decaestecker, M. Petein, P. Van Ham, J.-L. Pasteels, A. Danguy, I. Salmon, R. van Velthoven and R. Kiss, Classification strategies for the grading of renal cell carcinomas, based on nuclear morphometry and densitometry, J. Pathol. 183 (1997), 141-150.
8. C. François, C. Decaestecker, I. Salmon, M. Petein, M. Remmelink, T. Janssen, A. Peltier, E. Wespes, C. Schulman, R. van Velthoven and R. Kiss, Stem cell line identification is of prognostic value for renal cell carcinomas, Anal. Quant. Cytol. Histol. (1998, in press).
9. S.A. Fuhrman, L.C. Lasky and C. Limas, Prognostic significance of morphologic parameters in renal cell carcinoma, Am. J. Surg. Pathol. 6 (1982), 655-663.
10. M.M. Galloway, Texture analysis using grayrun length, Comput. Graph Image Process. 4 (1975), 172-179.
11. F. Gao, U. Jutting, K. Rodenacker, P. Gais and P.Z. Lin, Relevance of chromatin features in the progression of esophageal epithelial sever dysplasia, Anal. Cell. Pathol. 13 (1997), 17-28.
12. D. Goldschmidt, C. Decaestecker, J.V. Berthe, L. Gordower, M. Remmelink, A. Danguy, J.L. Pasteels, I. Salmon and R. Kiss, The contribution of computer-assisted methods for histopathological classification of adipose tumors, Lab. Invest. 75 (1996), 295-306.
13. R.M. Haralick, T. Shanmugan and I. Dinstein, Textural features for image classification, IEE Trans. Syst. Man Cybern. 3 (1973), 610-621.
14. UICC (International Union Against Cancer), TNM Classification of Malignant Tumors, P. Hermanek and L.H. Sobin, eds, 4th edn, 2nd rev., Springer, Berlin, 1992, pp. 148-150.
15. T. Jorgensen, Y. Kanagasingam, O. Kaalhus, K.J. Tveter, M. Bryne, F. Skjorten, A. Berner and H.E. Danielsen, Prognostic factors in patients with metastatic (stage D2) prostate cancer: experience from Scandinavian Prostatic Cancer Group Study-2, J. Urol. 158 (1997), 164-170.
16. R. Kiss, I. Salmon, I. Camby, S. Gras and J.L. Pasteels, Characterization of factors in routine laboratory protocols that significantly influence the Feulgen reaction, J. Histochem. Cytochem. 41 (1993), 935-945.
17. D. Lanigan, R. Conroy, C. Barry-Walsh, B. Loftus, D. Royston and M.A. Leader, Comparative analysis of grading systems in renal adenocarcinoma, Histopathology 24 (1994), 473-476.
18. B. Ljungberg, P. Larsson and R. Stenling, Flow cytometric deoxyribonucleic acid analysis in stage I renal cell carcinoma, J. Urol. 146 (1991), 697-699.
19. G.J. McLachlan, Discriminant Analysis and Statistical Pattern Recognition, Wiley, New York, 1992.
20. L.J. Medeiros, S.A. Michie, D.E. Johnson, R.A. Waenke and L.M. Weiss, An immunoperoxidase study of renal cell carcinomas. Correlation with nuclear grade, cell type, and histologic pattern, Hum. Pathol. 19 (1988), 980-987.
21. W.M. Murphy, J.B. Beckwith and G.M. Farrow, Tumors of the kidney, in: Tumors of the Kidney, Bladder, and Related Urinary Structures, Atlas of Tumor Pathology, Armed Forces Institute of Pathology, Washington, 1994, pp. 92-178.
22. M. Petein, Y. de Launoit, R. Kiss, C. DePrez, K. Crols, J.L. Pasteels, A. Verhest and R. van Velthoven, Characterization of the morphonuclear features and DNA ploidy of prostatic disease, Prostate 16 (1990), 199-208.
23. M. Petein, P. Michel, R. van Velthoven, J.L. Pasteels, M. Brawer, J.R. Davis, R. Nagle and R. Kiss, Morphonuclear relationship between prostatic intraepithelial neoplasia and cancers as assessed by digital cell image analysis, Am. J. Clin. Pathol. 96 (1991), 628-634.
24. J.R. Quinlan, Induction of Decision Trees, Machine Learning 1 (1986), 81-106.
25. J.R. Quinlan, C4.5: Programs for Machine Learning, Morgan Kaufmann Publishers, San Mateo, CA, 1993.
26. G. Raviv, I. Leibovich, Y. Mor, D. Nass, O. Medalia, B. Goldwasser and O. Nativ, Localized renal cell carcinoma treated by radical nephrectomy. Influence of pathologic data and the importance of DNA ploidy pattern on disease outcome, Cancer 72 (1993), 2207-2212.
27. J.L. Ruiz-Cerda, M. Hernandez, F. Gomis, C.D. Vera, B.F. Kimler, J.E. O'Connor and F. Jimenez-Cruz, Value of deoxyribonucleic acid ploidy and nuclear morphometry for prediction of disease progression in renal cell carcinoma, J. Urol. 155 (1996), 459-465.
28. C.E. Shannon, A mathematical theory of communication, Bell Sys. Tech. J. 27 (1948), 379-423, 623-656.
29. D.G. Skinner, R.B. Colvin, C.D. Vermillion, R.C. Pfister and W.F. Leadbetter, Diagnosis and management of renal cell carcinoma, Cancer 28 (1971), 1165-1177.
30. K. Syrjänen and L. Hjelt, Grading of human renal adenocarcinoma, Scand. J. Urol. Nephrol. 12 (1978), 49-55.
31. P. Tosi, P. Luzi, J.P.A. Baak, C. Miracco, R. Santopietro, C. Vindgni, F.M. Mattei, A. Acconcia and M.R. Massai, Nuclear morphology as an important prognostic factor in stage I renal cell carcinoma, Cancer 58 (1986), 2512-2518.
32. H.G. van der Poel, P.F. Mulders, G.O. Oosterhof, H.E. Schaafsma, J.C. Hendriks, J.A. Schalken and F.M. Debruyne, Prognostic value of karyometric and clinical characteristics in renal cell carcinoma. Quantitative assessment of tumor heterogeneity, Cancer 72 (1993), 2667-2674.
33. R. van Velthoven, M. Petein, A. Zlotta, W.J. Oosterlinck, A. Vandermeijden, C. Zandona, H. Roels, J.L. Pasteels, C. Schulman and R. Kiss, Computer-assisted chromatin texture characterization of Feulgen-stained nuclei in a series of 331 transitional bladder cell carcinomas, J. Pathol. 173 (1994), 235-242.
34. L.L. Wheeless, R.A. Badalament, R.W. de Vere White, Y. Fradet and B. Tribukait, Consensus review of clinical utility of DNA cytometry in bladder cancer, Cytometry 14 (1993) 478-481.
35. K. Yogesan, T. Jorgensen, F. Albregtsen, K.J. Tveter and H.E. Danielsen, Entropy-based texture analysis of chromatin structure in advanced prostate cancer, Cytometry 24 (1996), 268-276.