Comparison of complexity metrics for multi-institutional evaluations of treatment plans in radiotherapy

Abstract

Background and purpose: It is known that intensity-modulated radiotherapy plans that are highly complex might be less accurate in dose calculation and treatment delivery. Multiple complexity metrics have been proposed, but the relationships between them have not been thoroughly investigated. This study investigated these relationships in multi-institutional comparisons of treatment plans, where plans from multiple treatment planning systems (TPSs) are typically evaluated. Materials and methods: A program was developed to compute several complexity indices and provide analysis of dynamic plan parameters. This in-house software was used to analyse plans from a recent multi-institutional audit. Additionally, 100 clinical volumetric modulated arc therapy (VMAT) plans from two institutions using different TPSs were analysed. Results: All plans produced satisfactory pre-treatment verification results and, hence, complexity metrics could not be used to predict plans failing QA. Regarding the relationship among complexity indices, some very strong correlations were found (r > 0.9 with p < 0.01). However, some relevant discrepancies between complexity indices were obtained, even with negative correlation coefficients (r ∼ −0.6) which were expected to be positive. These discrepancies could be explained because each complexity index focused on different features of the plan and different TPSs prioritised modulation of different plan parameters. Conclusions: Some complexity indices provided similar information and can be considered equivalent. However, indices that focused on different plan parameters yielded different results and it was unclear which complexity index should be used. Careful consideration should be given to the use of complexity metrics in multi-institutional studies.

On the need for tuning the dosimetric leaf gap for stereotactic treatment plans in the Eclipse treatment planning system

“…An in‐house software named “Plan‐Analyzer,” developed in MATLAB ® , was used to parse the MLC information from the DICOM files. In the present study, the meanGap and the mean TGi were investigated.…”

Evaluation of complexity and deliverability of prostate cancer treatment plans designed with a knowledge‐based VMAT planning technique

“…Investigators such as Younge et al have implemented aperture complexity penalties into the plan optimization stage to limit plan complexity without degrading plan quality . Others have examined how an array of metrics that quantify beam complexity (such as leaf travel in addition to plan irregularity and modulation) correlate with delivery accuracy and pretreatment verification results . Valdes et al .…”

“…It is possible that adjusting these specific optimization parameters may diminish KBP plan complexity and delivery accuracy deficiencies to an extent . Another potential limitation is that only a limited number of metrics were chosen to quantify plan complexity, though the chosen metrics are commonly used in the literature …”

“…This reduced treatment delivery accuracy can have clinical implications . These consequences have led investigators to explore strategies to quantify and reduce plan complexity without compromising plan quality …”

Complexity in Radiation Therapy: It's Complicated

“…Different TPSs prioritize the modulation of different plan parameters. 20 For instance, some may use relatively fixed gantry speeds and be more demanding on MLC; hence, their plans will be more susceptible to leaf position inaccuracies. 5 On the other hand, the relationship among complexity indices has been investigated, and many are strongly correlated with each other.…”