On the implementation of the plan-class specific reference field using multidimensional clustering of plan features and alternative strategies for improved dosimetry in modulated clinical linear accelerator treatments.

Abstract

The plan-class specific reference field concept could theoretically improve the calibration of radiation detectors in a beam environment much closer to clinical deliveries than existing broad beam dosimetry protocols. Due to a lack of quantitative guidelines and representative data, however, the pcsr field concept has not yet been widely implemented. This work utilizes quantitative plan complexity metrics from modulated clinical treatments in order to investigate the establishment of potential plan classes using two different clustering methodologies. The utility of these potential plan clusters is then further explored by analyzing their relevance to actual dosimetric correction factors. Two clinical databases containing several hundred modulated plans originally delivered on two Varian linear accelerators were analyzed using 21 plan complexity metrics. In the first approach, each database's plans were further subdivided into groups based on the anatomic site of treatment and then compared to one another using a series of nonparametric statistical tests. In the second approach, objective clustering algorithms were used to seek potential plan clusters in the multidimensional complexity-metric space. Concurrently, beam- and detector-specific dosimetric corrections for a subset of the modulated clinical plans were determined using Monte Carlo for three different ionization chambers. The distributions of the dosimetric correction factors were compared to the derived plan clusters to see which plan clusters, if any, could help predict the correction factor magnitudes. Ultimately, a simplified volume averaging metric (SVAM) is shown to be much more relevant to the total dosimetric correction factor than the established plan clusters. Plan groups based on the site of treatment did not show noticeable distinction from one another in the context of the metrics investigated. An objective clustering algorithm was able to discriminate volumetric modulated arc therapy (VMAT) plans from step-and-shoot intensity-modulated radiation therapy plans with an accuracy of 90.8%, but no clusters were found to exist at any level more specific than delivery modality. Monte Carlo determined correction factors for the modulated plans ranged from 0.970 to 1.104, 0.983 to 1.027, and 0.986 to 1.009 for the A12, A1SL, and A26 chambers, respectively, and were highly variable even within the treatment modality plan clusters. The magnitudes of these correction factors were explained almost entirely by volume averaging with SVAM demonstrating positive correlation with all Monte Carlo established total correction factors. Plan complexity metrics do provide some quantitative basis for the investigation of plan clusters, but an objective clustering algorithm demonstrated that quantifiable differences could only be found between VMAT and step-and-shoot beams delivered on the same treatment machine. The inherent variability of the Monte Carlo determined correction factors could not be explained solely by the modality of the treatment but were instead almost entirely dependent upon the volume averaging correction, which itself depends on the detector position within the dose distribution, dose gradients, and other factors. Considering the continued difficulty of determining a relevant plan metric to base plan clusters on, case-by-case corrections may instead obviate the need for the pcsr field concept in the future.