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Reduction of Hotspots in the Treatment Margin Between GTV and PTV in IMRT Plans

G Narayanasamy*, X Zhang , E Galhardo , S Morrill , T Kim , S Maraboyina , J Penagaricano , Department of Radiation Oncology, University of Arkansas for Medical Sciences, Little Rock, AR


(Sunday, 7/29/2018) 3:00 PM - 6:00 PM

Room: Exhibit Hall

Purpose: To reduce volume of hotspot region located in the treatment margin area outside of gross tumor volume (GTV) but inside planning target volume (PTV).

Methods: Ten IMRT or VMAT plans were selected such that the maximum dose to PTV were higher than GTV by atleast 1%. Plans included 4 lung, 2 pelvis, 2 spine, and 2 brain tumors. The volume of hotspot larger than 1 cc was recorded in a rind structure generated by subtracting GTV from PTV contour in Eclipse TPS ver 11. Rind structure density was overwritten by homogeneous tissue only for the plan optimization stage. Planning optimization was performed such that PTV meets the target objective (atleast 95% volume irradiated by Rx). Final dose calculation was performed on the original CT without density overwrite on the rind structure. Volume of the hotspots area was re-evaluated in rind structure and compared with the original treatment plan using Student’s T-test.

Results: Median ± standard deviation (SD) of GTV, PTV are 49.9±75.5 cc and 130.2±194.2 cc, respectively. Median ± SD of maximum doses in GTV, PTV are 107.1±2% and 108.8±2.4% in original clinical plans and 105.2±1.3%, 106.8±107.3% in revised plans. The hotspots considered in each case ranged between 101% and 105% such that the volumes were atleast 1 cc in the original plan. Median ± SD of hotspot volumes were 10.6±36.2 cc in the original plan and 3.7±21.7 cc in the revised plan. The hotspot volume reduction of 42.6±35.8% (range: 13.4–99.0%) was significant with a p-value < 0.05.

Conclusion: Overwriting density has a significant effect in reduction of hotspots in the rind structure between GTV and PTV.


Exposure Reduction, Intensity Modulation


TH- External beam- photons: IMRT dose optimization algorithms

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