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1 1999

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Predicting the Development of Pre-invasive Neoplastic Bronchial Epithelial Lesions from Biopsies

Barranco-Mendoza A., Clem C., Gupta A., Fizzano P., Guillaud M.

Archives of Control Sciences

1999

Vol. 9, no. 1/2

25-40

Lung cancer accounts for 28% of all cancer deaths in North America. However current treatment options lead to a cure in only 10% of these cases. It is well known that the survival rates can be improved by the early detection of pre-invasive lesions which are believed to be the possible precursors of malignant tumors. Although new technology is allowing numerous early lesions to be detected, it is becoming clear that only a small percentage of these will progress to cancer. A fundamental problem in the analysis of biopsies, i.e., longitudinal two-dimensional (2-D) sections of the central area of the lesions, is the quantification of tissue heterogeneity. One can distinguish abnormal cells from normal cells and analyse their spatial arrangement, but it is currently impossible in the case of pre-invasive lesions in the early stages, that is, when just a few abnormal cells are present in the biopsy, to tell if one observed pattern is more aggressive than another one. In this paper a stochastic model for the growth of pre-invasive neoplastic bronchial epithelial cells is presented. The results are analysed to differentiate progressive lesions from regressive ones given a particular biopsy. The problem is initially simplified to taking a one-dimensional (1-D) cross-section from a 2-D process and estimating the maximum likelihood rate of growth based on this limited information. We propose a number of extensions to eventually extend this approach to the higher dimension model by analysing 2-D sections and estimating their growth rates in a three-dimensional (3-D) process.