Quantitative evaluation of malignant potential of early breast cancer using high resolution image cytometry.
We have been testing two independent hypotheses which postulate that the malignant potential of early breast cancer can be objectively assessed by measuring nuclear features of the diagnostic-malignant cells (hypothesis I) and/or normal-appearing epithelial cells found in the vicinity of the carcinoma (hypothesis II). In preliminary experiments, we tested some of these hypotheses using historical samples and a high resolution image cytometry apparatus. Tissue sections were stained with our stoichiometric stain and over 60 nuclear features, primarily texture features describing the DNA distribution in the nuclei, were employed in the multivariate analyses. Data derived from measurements of ductal carcinoma in situ (DCIS) with and without the invasive component indicated that the malignant potential of these lesions can be estimated with a sensitivity and specificity of at least 80%. The analysis of the tissue surrounding an invasive breast carcinoma showed that the existing malignancy can be predicted solely from the measurements of normal nuclei (normal-appearing breast lobules) in more than 85% of patients. This result indicates that the analysis of benign tissues also could give prognostically valid information. These results can be greatly improved using larger sample sizes and other improvements, including technical improvements of the cytometry device. We believe that this approach can be developed into a practical diagnostic and prognostic tool for better management of early breast cancer.
Palcic
B
B
British Columbia Cancer Agency, Cancer Imaging Department, Vancouver, Canada.
Susnik
B
B
Garner
D
D
Olivotto
I
I
D001941:Breast Diseases / Q000473:pathology; D001943:Breast Neoplasms / Q000473:pathology*; D002278:Carcinoma in Situ / Q000473:pathology*; D018270:Carcinoma, Ductal, Breast / Q000473:pathology*; D002467:Cell Nucleus / Q000473:pathology; D003937:Diagnosis, Differential; D006801:Humans; D007091:Image Processing, Computer-Assisted; D009361:Neoplasm Invasiveness