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 themodel
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.