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Published on: February 1, 2020
TU-E-BRA-01: A Comparison of Various Online Strategies to Account for Interfractional Variations for Pancreatic
Purpose:
To indentify effective methods to address the large interfractional variations for pancreas irradiation, we compared various used/proposed online strategies.
Methods:
The daily CTs acquired using a respiration-gated in-room CT for 9 pancreatic cancer patients treated with IGRT (i.e., online repositioning based on rigid-body alignment) were analyzed. The contours of the pancreas and duodenum on each daily CT set were generated by populating those from the planning CT using a deformable registration tool (ABAS, Elekta) with manual editing. PTV was generated with 3 mm margin. Nine online strategies were considered: 1) IGRT with 0 mm additional margin (AM), 2) IGRT with 2mm AM, 3) IGRT with 5mm AM, 4) IGRT with plan renormalized to maintain 95% PTV coverage, 5) Full scale reoptimization, 6) Reoptimization starting from the original plan, 7) Segment Aperture Morphing (SAM) from the original plan based on PTV shape change 8) SAM plus Segment Weight Optimization (SWO), 9) Reoptimization starting from the SAM plan. One way ANOVA (analysis of variance) was applied to plan qualities for the 9 strategies to assess statistical significance in difference.
Results:
The standard IGRT strategies (1-3) resulted in either inadequate PTV coverage or higher duodenum doses. Margin expansion along is not efficient to account for the changes. Full-scale reoptimization resulted in the best plan but requiring delineation of several structures. Reoptimization on top of available plan (strategies 6 and 9) was considerably faster. SAM strategy (7) is the fastest online replanning, as it requires only one structure (target) delineation, and it's plan quality was comparable to that for the full-scale reoptimization.
Conclusion:
Online replanning strategies can lead to either reduced duodenum dose or improved target coverage as compared to the current practice of IGRT. The SAM-based online replanning is comparable to the full scale reoptimization and is efficient for practical use.
