Abstract
Purpose: This study measured to which extent RapidPlan can drive a reduction of the human-caused variability in prostate cancer treatment planning. Methods: Seventy clinical prostate plans were used to train a RapidPlan model. Seven planners, with different levels of planning experience, were asked to plan a VMAT treatment for fifteen prostate cancer patients with and without RapidPlan assistance. The plans were compared on the basis of target coverage, conformance and OAR sparing. Inter-planner and intra-planner variability were assessed on the basis of the Plan Quality Metric formalism. Differences in mean values and InterQuartile Ranges between patients and operators were assessed. Results: RapidPlan-assisted plans matched manual planning in terms of target coverage, homogeneity, conformance and bladder sparing but outperformed it for rectum and femoral heads sparing. 8 out of 15 patients showed a statistically significant increase in overall quality. Inter-planner variability is reduced in RapidPlan-assisted planning for rectum and femoral heads while bladder variability was constant. The inter-planner variability of the overall plan quality, IQR of PQM%, was approximately halved for all patients. RapidPlan assistance induced a larger increase in plan quality for less experienced planners. At the same time, a reduction in intra-planner variability is measured with a significant overall reduction. Conclusions: The assistance of RapidPlan during the optimization of treatments for prostate cancer induces a significant increase of plan quality and a contextual reduction of plan variability. RapidPlan is proven to be a valuable tool to leverage the planning skills of less experienced planners ensuring a better homogeneity of treatment plan quality.
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Scaggion, A., Fusella, M., Roggio, A., Bacco, S., Pivato, N., Rossato, M. A., … Paiusco, M. (2018). Reducing inter- and intra-planner variability in radiotherapy plan output with a commercial knowledge-based planning solution. Physica Medica, 53, 86–93. https://doi.org/10.1016/j.ejmp.2018.08.016
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