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Quality Control of Treatment Planning Using Knowledge-Based Planning Across a System of Radiation Oncology Practices

K Masi

K Masi1*, M Ditman1 , R Marsh1 , J Dai2 , M Huberts3 , M Khadija4 , D Tatro5 , P Archer1 , M Matuszak1 , (1) University of Michigan, Ann Arbor, MI, (2) Alpena Cancer Center, Alpena, MI, (3) McLaren Greater Lansing, Lansing, MI, (4) Metro Health, Wyoming, MI, (5) Allegiance Health, Jackson, MI


SU-G-TeP4-14 (Sunday, July 31, 2016) 5:30 PM - 6:00 PM Room: ePoster Theater

Purpose: There is potentially a wide variation in plan quality for a certain disease site, even for clinics located in the same system of hospitals. We have used a prostate-specific knowledge-based planning (KBP) model as a quality control tool to investigate the variation in prostate treatment planning across a network of affiliated radiation oncology departments.

Methods: A previously created KBP model was applied to 10 patients each from 4 community-based clinics (Clinics A, B, C, and D). The KBP model was developed using RapidPlan (Eclipse v13.5, Varian Medical Systems) from 60 prostate/prostate bed IMRT plans that were originally planned using an in-house treatment planning system at the central institution of the community-based clinics. The dosimetric plan quality (target coverage and normal-tissue sparing) of each model-generated plan was compared to the respective clinically-used plan. Each community-based clinic utilized the same planning goals to develop the clinically-used plans that were used at the main institution.

Results: Across all 4 clinics, the model-generated plans decreased the mean dose to the rectum by varying amounts (on average, 12.5, 2.6, 4.5, and 2.7 Gy for Clinics A, B, C, and D, respectively). The mean dose to the bladder also decreased with the model-generated plans (5.4, 2.3, 3.0, and 4.1 Gy, respectively). The KBP model also identified that target coverage (D95%) improvements were possible for for Clinics A, B, and D (0.12, 1.65, and 2.75%) while target coverage decreased by 0.72% for Clinic C, demonstrating potentially different trade-offs made in clinical plans at different institutions.

Conclusion: Quality control of dosimetric plan quality across a system of radiation oncology practices is possible with knowledge-based planning. By using a quality KBP model, smaller community-based clinics can potentially identify the areas of their treatment plans that may be improved, whether it be in normal-tissue sparing or improved target coverage.

Funding Support, Disclosures, and Conflict of Interest: M. Matuszak has research funding for KBP from Varian Medical Systems

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