Fluorescence and reflectance device variability throughout the progression of a phase II clinical trial to detect and screen for cervical neoplasia using a fiber optic probe

Abstract

Large phase II trials of fluorescence and reflectance spectroscopy using a fiber optic probe in the screening and diagnostic settings for detecting cervical neoplasia have been conducted. We present accrual and histopathology data, instrumentation, data processing, and the preliminary results of interdevice consistencies throughout the progression of a trial. Patients were recruited for either a screening trial (no history of abnormal Papanicolaou smears) or a diagnostic trial (a history of abnormal Papanicolaou smears). Colposcopy identified normal and abnormal squamous, columnar, and transformation zone areas that were subsequently measured with the fiber probe and biopsied. In the course of the clinical trial, two generations of spectrometers (FastEEM2 and FastEEM3) were designed and utilized as optical instrumentation for in vivo spectroscopic fluorescence and reflectance measurements. Data processing of fluorescence and reflectance data is explained in detail and a preliminary analysis of the variability across each device and probe combination is explored. One thousand patients were recruited in the screening trial and 850 patients were recruited in the diagnostic trial. Three clinical sites attracted a diverse range of patients of different ages, ethnicities, and menopausal status. The fully processed results clearly show that consistencies exist across all device and probe combinations throughout the diagnostic trial. Based on the stratification of the data, the results also show identifiable differences in mean intensity between normal and high-grade tissue diagnosis, pre- and postmenopausal status, and squamous and columnar tissue type. The mean intensity values of stratified data show consistent separation across each of the device and probe combinations. By analyzing trial spectra, we provide more evidence that biographical variables such as menopausal status as well as tissue type and diagnosis significantly affect the data. Understanding these effects will lead to better modeling parameters when analyzing the performance of fluorescence and reflectance spectroscopy.