Influence of robust optimization in intensity‐modulated proton therapy with different dose delivery techniques

Abstract

IMPT's sensitivity to uncertainties can be improved by using robust optimization. They found two possible mechanisms that made improvements possible: (1) a localized single-field uniform dose distribution (LSFUD) mechanism, in which the optimization algorithm attempts to produce a single-field uniform dose distribution while minimizing the patching field as much as possible; and (2) perturbed dose distribution, which follows the change in anatomical geometry. Multiple-instance optimization has more knowledge of the influence matrices; this greater knowledge improves IMPT plans' ability to retain robustness despite the presence of uncertainties.

Effectiveness of robust optimization in intensity‐modulated proton therapy planning for head and neck cancers

“…The optimizer can find a desired beamlet weight solution from the degenerate solution space so that the dose distribution follows the changes in anatomical geometry and is minimally perturbed by uncertainties. 16,17 Either or both mechanisms are found in the H&N cases studied. Thus, robust optimization resulted in patient-specific, optimizer-determined, and effectively reduced margins compared with a predefined and fixed margin used in the PTV approach based on a patient population model.…”

“…6); and (2) perturbed dose distribution, which follows the change in anatomical geometry (Fig. 9 of Liu et al 16 ). This mechanism usually takes place at the edge of targets and intends to ensure the target coverage despite the presence of the uncertainties.…”

“…Two possible mechanisms were reported to improve plan robustness by robust optimization: (1) a localized single-field uniform dose distribution (LSFUD) mechanism, 16 which usually happens within the targets to render per beam dose distribution more homogeneous (Fig. 6); and (2) perturbed dose distribution, which follows the change in anatomical geometry (Fig.…”

“…7,8,[12][13][14][15][16][17][18][19] We have developed one such method that accounts for uncertainties during plan optimization via "worstcase" robust optimization. 17 The concept of representing plan robustness in terms of "worst-case" dose distribution was introduced by Lomax et al 20 and the first robust optimization scheme using the "worst-case" concept was reported by Pflugfelder et al 6 In our previous study, we showed that robust optimization can render IMPT plans less sensitive to uncertainties and by eliminating the needs to irradiate PTV, we were able to achieve better sparing of normal tissues than conventional plans optimized on the basis of margins.…”

“…17 The concept of representing plan robustness in terms of "worst-case" dose distribution was introduced by Lomax et al 20 and the first robust optimization scheme using the "worst-case" concept was reported by Pflugfelder et al 6 In our previous study, we showed that robust optimization can render IMPT plans less sensitive to uncertainties and by eliminating the needs to irradiate PTV, we were able to achieve better sparing of normal tissues than conventional plans optimized on the basis of margins. 16,17 The robust optimization method takes into account setup and range uncertainty directly during the spot-weight optimization, therefore it does not require extra volume to be irradiated. In other words, with robust-optimization technique, a robust plan is generated using CTV as a primary target to be irradiated and no longer requires geometrically expanded PTV.…”