Program Information
Assessment of Delivered Dose in Understanding HCC Tumor Progression Following SBRT
M McCulloch*, G Cazoulat , D Polan , M Schipper , T Lawrence , M Feng , K Brock , University of Michigan, Ann Arbor, MI
Presentations
SU-F-J-89 (Sunday, July 31, 2016) 3:00 PM - 6:00 PM Room: Exhibit Hall
Purpose: It is well documented that the delivered dose to patients undergoing radiotherapy (RT) is often different from the planned dose due to geometric variability and uncertainties in patient positioning. Recent work suggests that accumulated dose to the GTV is a better predictor of progression compared to the minimum planned dose to the PTV. The purpose of this study is to evaluate if deviations from the planned dose can contributed to tumor progression.
Methods: From 2010 to 2014 an in-house Phase II clinical trial of adaptive stereotactic body RT was completed. Of the 90 patients enrolled, 7 patients had a local recurrence defined on contrast enhanced CT or MR imaging 3 – 21 months after completion of RT. Retrospective dose accumulation was performed using a biomechanical model-based deformable image registration algorithm (DIR) to accumulate the dose based on the kV CBCT acquired prior to each fraction for soft tissue alignment of the patient. The DIR algorithm was previously validated for geometric accuracy in the liver (target registration error = 2.0 mm) and dose accumulation in a homogeneous image, similar to a liver CBCT (gamma index = 91%). Following dose accumulation, the minimum dose to 0.5 cc of the GTV was compared between the planned and accumulated dose. Work is ongoing to evaluate the tumor control probability based on the planned and accumulated dose.
Results: DIR and dose accumulation was performed on all fractions for 6 patients with local recurrence. The difference in minimum dose to 0.5 cc of the GTV ranged from -0.3 – 2.3 Gy over 3-5 fractions. One patient had a potentially significant difference in minimum dose of 2.3 Gy.
Conclusion:Dose accumulation can reveal tumor underdosage, improving our ability to understand recurrence and tumor progression patterns, and could aid in adaptive re-planning during therapy to correct for this.
Funding Support, Disclosures, and Conflict of Interest: This work was supported in part by NIH P01CA059827.
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