Considerations for using data envelopment analysis for the assessment of radiotherapy treatment plan quality.

Purpose The operations research method of data envelopment analysis (DEA) shows promise for assessing radiotherapy treatment plan quality. The purpose of this paper is to consider the technical requirements for using DEA for plan assessment. Design/methodology/approach In total, 41 prostate treatment plans were retrospectively analysed using the DEA method. The authors investigate the impact of DEA weight restrictions with reference to the ability to differentiate plan performance at a level of clinical significance. Patient geometry influences plan quality and the authors compare differing approaches for managing patient geometry within the DEA method. Findings The input-oriented DEA method is the method of choice when performing plan analysis using the key undesirable plan metrics as the DEA inputs. When considering multiple inputs, it is necessary to constrain the DEA input weights in order to identify potential plan improvements at a level of clinical significance. All tested approaches for the consideration of patient geometry yielded consistent results. Research limitations/implications This work is based on prostate plans and individual recommendations would therefore need to be validated for other treatment sites. Notwithstanding, the method that requires both optimised DEA weights according to clinical significance and appropriate accounting for patient geometric factors is universally applicable. Practical implications DEA can potentially be used during treatment plan development to guide the planning process or alternatively used retrospectively for treatment plan quality audit. Social implications DEA is independent of the planning system platform and therefore has the potential to be used for multi-institutional quality audit. Originality/value To the authors' knowledge, this is the first published examination of the optimal approach in the use of DEA for radiotherapy treatment plan assessment.

Quality assessment for VMAT prostate radiotherapy planning based on data envelopment analysis.

The majority of commercial radiotherapy treatment planning systems requires planners to iteratively adjust the plan parameters in order to find a satisfactory plan. This iterative trial-and-error nature of radiotherapy treatment planning results in an inefficient planning process and in order to reduce such inefficiency, plans can be accepted without achieving the best attainable quality. We propose a quality assessment method based on data envelopment analysis (DEA) to address this inefficiency. This method compares a plan of interest to a set of past delivered plans and searches for evidence of potential further improvement. With the assistance of DEA, planners will be able to make informed decisions on whether further planning is required and ensure that a plan is only accepted when the plan quality is close to the best attainable one. We apply the DEA method to 37 prostate plans using two assessment parameters: rectal generalized equivalent uniform dose (gEUD) as the input and D95 (the minimum dose that is received by 95% volume of a structure) of the planning target volume (PTV) as the output. The percentage volume of rectum overlapping PTV is used to account for anatomical variations between patients and is included in the model as a non-discretionary output variable. Five plans that are considered of lesser quality by DEA are re-optimized with the goal to further improve rectal sparing. After re-optimization, all five plans improve in rectal gEUD without clinically considerable deterioration of the PTV D95 value. For the five re-optimized plans, the rectal gEUD is reduced by an average of 1.84 Gray (Gy) with only an average reduction of 0.07 Gy in PTV D95. The results demonstrate that DEA can correctly identify plans with potential improvements in terms of the chosen input and outputs.