Prostate-cancer diagnosis by non-invasive prostatic Zinc mapping using X-Ray Fluorescence (XRF)

At present, the major screening tools (PSA, DRE, TRUS) for prostate cancer lack sensitivity and specificity, and none can distinguish between low-grade indolent cancer and high-grade lethal one. The situation calls for the promotion of alternative approaches, with better detection sensitivity and specificity, to provide more efficient selection of patients to biopsy and with possible guidance of the biopsy needles.;The prime objective of the present work was the development of a novel non-invasive method and tool for promoting detection, localization, diagnosis and follow-up of PCa. The method is based on in-vivo imaging of Zn distribution in the peripheral zone of the prostate, by a transrectal X-ray fluorescence (XRF) probe.;Local Zn levels, measured in 1--4 mm3 fresh tissue biopsy segments from an extensive clinical study involving several hundred patients, showed an unambiguous correlation with the histological classification of the tissue (Non-Cancer or PCa), and a systematic positive correlation of its depletion level with the cancer-aggressiveness grade (Gleason classification). A detailed analysis of computer-simulated Zn-concentration images (with input parameters from clinical data) disclosed the potential of the method to provide sensitive and specific detection and localization of the lesion, its grade and extension. Furthermore, it also yielded invaluable data on some requirements, such as the image resolution and counting-statistics, requested from a trans-rectal XRF probe for in-vivo recording of prostatic-Zn maps in patients. By means of systematic table-top experiments on prostate-phantoms comprising tumor-like inclusions, followed by dedicated Monte Carlo simulations, the XRF-probe and its components have been designed and optimized. Multiparameter analysis of the experimental data confirmed the simulation estimations of the XRF detection system in terms of: delivered dose, counting statistics, scanning resolution, target-volume size and the accuracy of locating at various depths of small-volume tumor-like inclusions in tissue-phantoms.;The clinical study, the Monte Carlo simulations and the analysis of Zn-map images provided essential information and promising vision on the potential performance of the Zn-based PCa detection concept. Simulations focusing on medical-probe design and its performance at permissible radiation doses yielded positive results --- confirmed by a series of systematic laboratory experiments with a table-top XRF system.