Methods for therapeutic optimization in radiation therapy: from dose measurement to NTCP modeling

The purpose of this thesis is to develop methods and materials for radiation therapy optimization from dose measurement to Normal Tissue Complication Probability (NTCP) modelling. The research activity focuses on two topics of the optimization problem: development of new optical fiber sensor dosimeters and investigation of standard dosimeters for small field and in vivo dosimetry and dose optimization to the organs at risk. The project aims to realize a passive detector for ionizing radiation based on optical fiber sensor technology suitable for radiation dosimetry in a dose range relevant to clinical practice. Optical fiber sensors have been characterized identifying the physical quantities involved in the interaction and modelling the interaction process between ionizing radiation and the fiber material. Dose response of fiber Bragg gratings, resonant cavities and thermoluminescent dosimeters (TLDs) have been investigated, under conventional photon beam and non-conventional accelerator beam, such as high dose-per-pulse electron beams. The results of the investigation has demonstrated the great potential of optical fiber sensors in radiation therapy procedures as well as in radiation monitoring and protection in medicine. The study also demonstrated that the TLD dose response in high dose-per-pulse electron beams has a parabolic behavior for doses under 10 Gy, assessing that TLD-100 may be useful detectors for intraoperative electron radiation therapy patient dosimetry if a proper calibration is provided. The accuracy of the verification of the delivered dose is strictly jointed with clinical efficacy of radiotherapy treatments. Radiotherapy optimization and many advances in technology and techniques are aimed at improving the balance between the tumor control probability (TCP) and the normal tissue complication probability, i.e. maximizing tumor control while maintaining tissue complications at an acceptable level. The steepness of the given TCP or NTCP curve versus dose defines the change in response expected for a given change in delivered dose. Thus, dosimetric uncertainties in the dose delivered will translate directly into changes in TCP and NTCP for the population of patients involved. Improving the predictive power of NTCP model itself, improve the accuracy in predicting clinical outcome and concurs to the optimization strategy. The present work provides multi-variables predictive models for several toxicity endpoint of organ at risks and different cancer patients treated with conformal radiation therapy. The potential role of data-driven multi-variable models respect to classical predictive risk models is the possibility to include in the analysis clinical patient-specific factors in addition to dosimetric variables of several radiation-involved organs. Multi-organs interaction in affecting diseases at a specific site have been evidenced suggesting the need to consider the normal tissue complication modelling a complex process involving multiple biological pathways and systems.