Room: Exhibit Hall | Forum 6
Purpose: MRI-guided radiation therapy (RT) would allow to deliver a higher target dose for a fraction using online adaptation, taking advantage of the preferred anatomy change for the fraction. We introduce an avoidance planning strategy that maximizes target dose while maintaining the dose to organ at risk (OAR) at its constraint.
Methods: The idea is demonstrated on 17 daily CTs acquired using an in-room CT during RT for 3 pancreatic cancer patients. For each daily CT set, the target (pancreas head) and OAR (duodenum) were delineated, and three plans were generated: (1) iterative-avoidance: optimization with objective function (OF) iteratively adjusted to maximize target dose (2) avoidance plan using a reference OF (from other days) without adjusting, (3) repositioning plan (another dayâ€™s reference plan calculated directly). Outside the target doses were limited by conformity index (CI) criteria. The three plans were compared in terms of several dosimetric indicators. Anatomic indicators, e.g., target volume, distance between target and OAR (such as DIST-1cc: the distance resulting in 1cc OAR volume overlap, mean distance) were investigated as predictors for the necessity of avoidance planning.
Results: Average target mean and D99 were 68.8/57.6, 75.8/64, and 62.5/55.1 Gy for the three patient data studied. There was large daily variation, SD (D99) = 7.6, 6.0, and 1.7Gy for the three cases. Best predictor for avoidance planning was the DIST-1cc (R2= 0.66) and DIST-2cc (R2 = 0.64). The repositioning plans were generally inferior to the two types of avoidance plans. The iterative-avoidance planning decreased the variability in target doses by ~3% compared to those from the avoidance planning, but with cost of planning time.
Conclusion: The proposed avoidance planning can lead to higher target dose in online replanning, especially when a large separation exists between target and OAR.
Image-guided Therapy, MRI, Optimization
IM/TH- MRI in Radiation Therapy: MRI/Linear accelerator combined dose optimization