title: Estimation of neoplasia-related biological parameters through modeling and sensitivity analysis of optical molecular imaging data.
abstract: We combine system's biology approaches with in vivo optical molecular imaging of epithelial neoplasia for estimating disease-specific biological parameters. Molecular imaging measures and maps the dynamic optical effects, generated by the topical application of acetic acid diluted solution. The dynamic characteristics of the in vivo measured optical signal are governed by the epithelial transport effects of the biomarker. Nine biological parameters, both structural and functional, have been identified to be potentially correlated with the neoplasia growth and to be manifested to the measured data in a convoluted manner. A compartmental model of the cervical neoplastic epithelium has been developed, which predicts the dynamic optical effects in all possible parameter value combinations. We have performed global sensitivity analysis for the purpose of identifying the subset of the input parameters that are the key determinants of the model's output. Finally, we have for the first time shown that it is possible to estimate, from in vivo measured dynamic optical data, the following neoplasia related parameters: number of neoplastic layers, intracellular and extracellular space dimensions, functionality of tight junctions, and extracellular pH. These findings have been (in part) validated with optical data and biopsies obtained from 30 women with cervical neoplasia.
authors.affiliation: Department of Electronic and Computer Engineering, Technical University of Crete, Chania 73100, Greece. gpap@electronics.tuc.gr
authors.forename: George S
authors.initials: GS
authors.lastname: Papoutsoglou
authors.forename: Costas
authors.initials: C
authors.lastname: Balas
mesh_terms: D000465:Algorithms; D015415:Biomarkers / Q000032:analysis / Q000737:chemistry; D003198:Computer Simulation; D004848:Epithelium / Q000737:chemistry; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008954:Models, Biological; D057054:Molecular Imaging / Q000379:methods*; D009010:Monte Carlo Method; D009369:Neoplasms / Q000737:chemistry / Q000145:classification; D061848:Optical Imaging / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D002583:Uterine Cervical Neoplasms
chemical_list: D015415:Biomarkers