Program Information
Quality Management of Accelerated Partial Breast Irradiation (APBI) Plans
H Ji1,2*, V Lorio1,2 , G Cernica1,2 , J Han2 , M Nurhussien2 , N Nasr2 , R Hong2 , (1) Associates In Medical Physics, Lanham, MD, (2) Virginia Hospital Center, Arlington, Virginia
Presentations
TU-FG-201-10 (Tuesday, August 2, 2016) 1:45 PM - 3:45 PM Room: 201
Purpose:
Since 2008, over 700 patients received high dose rate (HDR) APBI treatment at Virginia Hospital Center. The complexity involved in the planning process demonstrated a broad variation between patient geometry across all applicators, in relation to anatomical regions of interest. A quality management program instituting various metrics was implemented in March 2013 with the goal of ensuring an optimal plan is achieved for each patient.
Methods:
For each plan, an in-house complexity index, geometric conformity index, and plan quality index were defined. These indices were obtained for all patients treated. For patients treated after the implementation, the conformity index and quality index were maximized while other dosimetric limits, such as maximum skin and rib doses, were strictly kept. Subsequently, all evaluation parameters and applicator information were placed in a database for cross-evaluation with similar complexity.
Results:
Both the conformity and quality indices show good correlation with the complexity index. They decrease as complexity increases for all applicators. Multi lumen type balloon applicators demonstrate a minimal advantage over single lumen applicators in increasingly complex patient geometries, as compared to SAVI applicators which showed considerably greater advantage in these circumstances. After the implementation of the in-house planning protocol, there is a direct improvement of quality for SAVI plans.
Conclusion:
Due to their interstitial nature, SAVI devices show a better conformity in comparison to balloon-based devices regardless of the number of lumens, especially in complex cases. The quality management program focuses on optimizing indices by utilizing prior planning knowledge based on complexity levels. The database of indices assists in decision making and has subsequently aided in balancing the experience level among planners. This approach has made APBI planning more robust for patient care, with a measurable improvement in the plan quality.
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