Stochastic optimization of intensity modulated radiotherapy to account foruncertainties in patient sensitivity

The aim of the present work is to better account for the known uncertaintie s in radiobiological response parameters when optimizing radiation therapy. The radiation sensitivity of a specific patient is usually unknown beyond the expectation value and possibly the standard deviation that may be deriv ed from studies on groups of patients. Instead of trying to find the treatm ent with the highest possible probability of a desirable outcome for a pati ent of average sensitivity, it is more desirable to maximize the expectatio n value of the probability for the desirable outcome over the possible rang e of variation of the radiation sensitivity of the patient. Such a stochast ic optimization will also have to consider the distribution function of the radiation sensitivity and the larger steepness of the response for the ind ividual patient. The results of stochastic optimization are also compared w ith simpler methods such as using biological response 'margins' to account for the range of sensitivity variation. By using stochastic optimization, t he absolute gain will typically be of the order of a few per cent and the r elative improvement compared with non-stochastic optimization is generally less than about 10 per cent. The extent of this gain varies with the level of interpatient variability as well as with the difficulty and complexity o f the case studied. Although the dose changes are rather small (<5 Gy) ther e is a strong desire to make treatment plans more robust, and tolerant of t he likely range of variation of the radiation sensitivity of each individua l patient. When more accurate predictive assays of the radiation sensitivit y for each patient become available, the need to consider the range of vari ations can be reduced considerably.