On Augmented DVH Analysis
A Loveless1*, A Roy1, I Das2, O Nohadani1, (1) Purdue University, West Lafayette, IN, (2) Indiana University- School of Medicine, Indianapolis, INSU-E-T-246 Sunday 3:00PM - 6:00PM Room: Exhibit Hall
Purpose: The process of IMRT planning is an iterative inverse process, where a planner seeks to attain a desired dose distribution, specified for tumors and OARs, hence creating a plethora of competing objectives. However, the final product is rather the unpredictable outcome of a series of trial-and-error attempts at meeting these objectives. A key tool to inspect the quality of plans is the DVH. This inspection, however, is primarily conducted visually, hence, the chosen treatment plan is ultimately clinician dependent. In this study, we propose a quantitative method for DVH comparison based on historical data.
Methods: The treatment of one prostate case was planned by seven planners, while imposing the same clinical objectives for PTV and OARs. The resulting seven test DVHs were compared based on their deviation of from the ideal coverage, namely 100% of PTV receiving 100% of the dose. A deviation function L is proposed to measure the weighted area between the ideal and realized DVH. The weights are formed based on the distribution of past data of 100 comparable prostate cases. The frequencies were interpolated to form a continuous surface using tensor product piecewise cubic hermite interpolation. While only the dose distribution to PTV was subject to this study, the proposed method is universal and applies to other organs and/or combinations of criteria as well.
Result: Even though none of the seven test DVHs appeared visually preferable, we measured significantly different L values: Planner 2 exhibited the lowest deviation, while the deviations of Planners 1 and 7 were far higher.
Conclusion: The proposed method of quantitative DVH comparison can distinguish DVHs that might otherwise visually appear similar in a clinical setting. Furthermore, the outcomes from our method are independent of planning personnel biases, providing a quantitative way of evaluating DVHs and augmenting decisions in IMRT.
Funding Support, Disclosures, and Conflict of Interest: Joint Purdue-IU Seed Grant