A structure-based gamma evaluation method for identifying clinically relevant dose differences in organs at risk.

Gamma evaluation is currently the most widely used dose comparison method for patient specific quality assurance (PSQA). However, existing methods for normalising the dose difference, using either the dose at the global maximum dose point or at each local point, can respectively lead to under- and over-sensitivity to dose differences in organ-at-risk structures. This may be of concern for plan evaluation from clinical perspectives.

Monte Carlo calculations of radiotherapy dose in "homogeneous" anatomy.

Given the substantial literature on the use of Monte Carlo (MC) simulations to verify treatment planning system (TPS) calculations of radiotherapy dose in heterogeneous regions, such as head and neck and lung, this study investigated the potential value of running MC simulations of radiotherapy treatments of nominally homogeneous pelvic anatomy. A pre-existing in-house MC job submission and analysis system, built around BEAMnrc and DOSXYZnrc, was used to evaluate the dosimetric accuracy of a sample of 12 pelvic volumetric arc therapy (VMAT) treatments, planned using the Varian Eclipse TPS, where dose was calculated with both the Analytical Anisotropic Algorithm (AAA) and the Acuros (AXB) algorithm. In-house TADA (Treatment And Dose Assessor) software was used to evaluate treatment plan complexity, in terms of the small aperture score (SAS), modulation index (MI) and a novel exposed leaf score (ELS/ELA).

Analysis of dose comparison techniques for patient-specific quality assurance in radiation therapy.

Purpose: Gamma evaluation is the most commonly used technique for comparison of dose distributions for patient-specific pretreatment quality assurance in radiation therapy. Alternative dose comparison techniques have been developed but not widely implemented. This study aimed to compare and evaluate the performance of several previously published alternatives to the gamma evaluation technique, by systematically evaluating a large number of patient-specific quality assurance results.