SIS epidemiological model for adaptive RT: Forecasting the parotid glands shrinkage during tomotherapy treatment.

Purpose: A susceptible-infected-susceptible (SIS) epidemic model was applied to radiation therapy (RT) treatments to predict morphological variations in head and neck (H&N) anatomy.

Methods: 360 daily MVCT images of 12 H&N patients treated by tomotherapy were analyzed in this retrospective study. Deformable image registration (DIR) algorithms, mesh grids, and structure recontouring, implemented in the RayStation treatment planning system (TPS), were applied to assess the daily organ warping.

Semi-empirical model for fluorescence lines evaluation in diagnostic x-ray beams.

Diagnostic x-ray beams are composed of bremsstrahlung and discrete fluorescence lines. The aim of this study is the development of an efficient model for the evaluation of the fluorescence lines. The most important electron ionization models are analyzed and implemented.

A support vector machine tool for adaptive tomotherapy treatments: Prediction of head and neck patients criticalities.

Purpose: Adaptive radiation therapy (ART) is an advanced field of radiation oncology. Image-guided radiation therapy (IGRT) methods can support daily setup and assess anatomical variations during therapy, which could prevent incorrect dose distribution and unexpected toxicities. A re-planning to correct these anatomical variations should be done daily/weekly, but to be applicable to a large number of patients, still require time consumption and resources.