AN ADAPTIVE-CONTROL ALGORITHM FOR OPTIMIZATION OF INTENSITY-MODULATEDRADIOTHERAPY CONSIDERING UNCERTAINTIES IN-BEAM PROFILES, PATIENT SET-UP AND INTERNAL ORGAN MOTION

A new general beam optimization algorithm for inverse treatment planni ng is presented. It utilizes a new formulation of the probability to a chieve complication-free tumour control. The new formulation explicitl y describes the dependence of the treatment outcome on the incident fl uence distribution, the patient geometry, the radiobiological properti es of the patient and the fractionation schedule. In order to account for both measured and non-measured positioning uncertainties, the algo rithm is based on a combination of dynamic and stochastic optimization techniques. Because of the difficulty in measuring all aspects of the intra-and interfractional variations in the patient geometry, such as internal organ displacements and deformations, these uncertainties ar e primarily accounted for in the treatment planning process by intensi ty modulation using stochastic optimization. The information about the deviations from the nominal fluence profiles and the nominal position of the patient relative to the beam that is obtained by portal imagin g during treatment delivery, is used in a feedback loop to automatical ly adjust the profiles and the location of the patient for all subsequ ent treatments. Based on the treatment delivered in previous fractions , the algorithm furnishes optimal corrections for the remaining dose d elivery both with regard to the fluence profile and its position relat ive to the patient. By dynamically refining the beam configuration fro m fraction to fraction, the algorithm generates an optimal sequence of treatments that very effectively reduces the influence of systematic and random set-up uncertainties to minimize and almost eliminate their overall effect on the treatment. Computer simulations have shown that the present algorithm leads to a significant increase in the probabil ity of uncomplicated tumour control compared with the simple classical approach of adding fixed set-up margins to the internal target volume .