We propose to develop a machine-vision system for the diagnostic interpretation of histopathologic sections and cytologic preparations. in continuation of an ongoing research project grant. The system will have """"""""image understanding capability."""""""" that is, it will follow in its reasoning a model of the histology of a given application. The interpretive expert-system module will integrate concepts from human diagnostic knowledge with machine-computable histometric features. Systems of this kind can provide objective. quantitative, consistent evaluation of lesions, yielding more reliable interpretation and diagnostic, as well as prognostic, assessment. Using a combination of large data bases of digitized imagery for given diagnostic situations. and relational data bases (including patient history. treatment, and outcome), it is hoped that the objective assessment eventually will be related reliably to truth in diagnosis. The requirements for representative sampling are in the multimegapixel range, and require fully automatic scene segmentation and histometric feature extraction. This difficult problem has been largely resolved through ongoing support, employing an AI-based, adaptive segmentation approach. The major challenges for the proposed research are: 1) to gain an understanding of the necessary and sufficient human diagnostic clues and corresponding histometric analogs, that is, to determine the library of transforms to be used by the interpretive expert-system module; 2) to develop learning capability of the system for conceptual data; and 3) to gain an understanding of the functional requirements. dependence structure, and decision control capabilities of such a system.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Unknown (R35)
Project #
5R35CA053877-05
Application #
2095545
Study Section
Special Emphasis Panel (SRC (88))
Project Start
1991-03-01
Project End
1997-12-31
Budget Start
1995-01-01
Budget End
1995-12-31
Support Year
5
Fiscal Year
1995
Total Cost
Indirect Cost
Name
University of Arizona
Department
Type
Organized Research Units
DUNS #
City
Tucson
State
AZ
Country
United States
Zip Code
85721
Montironi, Rodolfo; Scarpelli, Marina; Mazzucchelli, Roberta et al. (2003) Subvisual changes in chromatin organization state are detected by karyometry in the histologically normal urothelium in patients with synchronous papillary carcinoma. Hum Pathol 34:893-901
Montironi, R; Thompson, D; Scarpelli, M et al. (2002) Transcontinental communication and quantitative digital histopathology via the Internet; with special reference to prostate neoplasia. J Clin Pathol 55:452-60
Montironi, Rodolfo; Mazzucchelli, Roberta; Colanzi, Paola et al. (2002) Improving inter-observer agreement and certainty level in diagnosing and grading papillary urothelial neoplasms: usefulness of a Bayesian belief network. Eur Urol 41:449-57
Scarpelli, M; Baccarini, M G; Colanzi, P et al. (2000) Chromatin texture analysis of cortical adrenal gland adenomas, including incidentalomas, and adjacent normal-appearing cortical tissue. Anal Quant Cytol Histol 22:235-43
Montironi, R; Mazzucchelli, R; Stramazzotti, D et al. (2000) Expression of pi-class glutathione S-transferase: two populations of high grade prostatic intraepithelial neoplasia with different relations to carcinoma. Mol Pathol 53:122-8
Scarpelli, M; Montironi, R; Mazzucchelli, R et al. (1999) Distinguishing cortical adrenal gland adenomas from carcinomas by their quantitative nuclear features. Anal Quant Cytol Histol 21:131-8
Montironi, R; Mazzucchelli, R; Pomante, R et al. (1999) Immunohistochemical expression of pi class glutathione S-transferase in the basal cell layer of benign prostate tissue following chronic treatment with finasteride. J Clin Pathol 52:350-4
Montironi, R; Hamilton, P W; Scarpelli, M et al. (1999) Subtle morphological and molecular changes in normal-looking epithelium in prostates with prostatic intraepithelial neoplasia or cancer. Eur Urol 35:468-73
Bartels, P H; Montironi, R; Duval da Silva, V et al. (1999) Tissue architecture analysis in prostate cancer and its precursors: An innovative approach to computerized histometry. Eur Urol 35:484-91
Hamilton, P W; Bartels, P H; Anderson, N et al. (1999) Case-based prediction of survival in colorectal cancer patients. Anal Quant Cytol Histol 21:283-91

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