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Automated Dose Accumulation for Online Adaptive Radiotherapy of Head and Neck Cancers

S Gros1*, A Santhanam2, D Elliott3, J Roeske1, R Patel1, H Kang1, (1) Loyola Univ Medical Center, Maywood, IL, (2) University of California, Los Angeles, Los Angeles, CA, (3) SegAna Inc, Orlando

Presentations

(Sunday, 7/12/2020)   [Eastern Time (GMT-4)]

Room: AAPM ePoster Library

Purpose: study the performance of a commercial software dedicated to on-line Adaptive Radiation Therapy (ART) for Head and Neck cancer (HNC) patients.

Methods: set of 10 HNC patients treated with external beam radiotherapy were retrospectively analyzed for treatment adaptation. We employed RTappTM (SegAna, Orlando, FL)an ART platform that allows the automatic visualization of daily anatomical changes throughout an entire course of radiotherapy treatment and predict when treatment plans will exceed dose constraints. For each treatment fraction, the initial plan images and structure sets were registered and deformed according to daily CBCT images. The inverse transformation was applied to the initial plan dose, in order to estimate the daily fraction dose for each structure or interest. The daily fraction doses were then summed to estimate the cumulative dose received by each structure. A predictive algorithm analyzed the dose trend against pre-determined end points for each structure in order to estimate when each structure dose constraints would be violated.


Results: out of 10 studies were flagged for one or two violations of their initial planning dose constraints. Six structures exceeding their end point were parotids (mean dose > 20 Gy), two of which were flagged at the first treatment fraction. One flagged study showed a continuous decrease in the target coverage reaching below the required PTV dose constraints (V95%>95%) mid treatment (fraction 13) with a final estimated V95% = 85%. After review of individual 3D-3D daily set-up alignments, the deviation from planned dose constraints initially met could be explained by weight loss gradually occurring throughout treatment for all flagged cases.


Conclusion: RTappTM platform provided efficient tools to visualize and estimate the effects of anatomical changes on targets and OARS for H&N patients. It can potentially help to predict whether specific patients treatment would require adaptation.

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Keywords

Radiation Therapy, Computer Software

Taxonomy

TH- External Beam- Photons: adaptive therapy

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