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Exploratory analysis of quantitative histopathology of cervical intraepithelial neoplasia: objectivity,
Martial Guillaud1, Dennis Cox, Karen Adler-Storthz
1Department of Cancer Imaging, British Columbia Cancer Agency, Vancouver, British Columbia.
Background:
As part of a project to evaluate emerging optical technologies for cervical neoplasia, our group is performing quantitative histopathological analyses of biopsy specimens from 1,190 patients. Objectives in the interim analysis are (a) quantitatively assessing progression of the neoplastic process of cervical intraepithelial neoplasia (CIN)/squamous intraepithelial lesions (SIL), (b) detecting malignancy-associated changes (MACs), and (c) phenotypically measuring human papillomavirus (HPV) detected by DNA testing.
Methods:
The diagnostic region of interest (ROI) from immediately adjacent sections were imaged, and the basal lamina and surface of the superficial layer were delimited. Nonoverlapping quantitatively stained nuclei were selected from 1,190 samples with histopathological characteristics of normal (929), koilocytosis (130), CIN 1 (40), CIN 2 (23), and CIN 3/carcinoma in situ (CIS) (68). A fully automatic procedure located and recorded the center of every nucleus in the region of interest (ROI). We used linear discriminant analysis to assess the changes between normal and CIN 3/CIS.
Results:
Scores computed from the cell-by cell features and the clinical grade of CIN/SIL were highly correlated, as were those of the architectural features and the clinical grade of CIN/SIL. We found even higher correlations between a combination of cell-by-cell and architectural scores, and clinical grade. Using these scores, we found MACs in the normal biopsy specimens from patients with high-grade CIN/SIL. Furthermore, the same scores correlated with the molecular detection of HPV.
Conclusions:
Quantitative histopathology can be used in large clinical trials as an objective and reproducible measure of CIN/SIL. Detectable phenotypic changes correlate well with CIN/SIL neoplastic progression. It can also be used to infer the presence of CIN/SIL (MACs) and molecular changes associated with increased risk of cancer development (high-risk HPV).