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Retrospective Clinical Evaluation of a Decision-Support Software for Adaptive Radiotherapy of Head & Neck Cancer Patients

S Gros1,2*, A Block1,2, B Lee1,2, B Emami1, A Santhanam3, (1) Loyola University Chicago, Stritch School of Medicine, Department of Radiation Oncology, Maywood, IL, (2) Loyola University Medical Center, Maywood, Illinois, (3) University of California, Los Angeles, Los Angeles, CA

Presentations

SU-H300-IePD-F6-3 (Sunday, 7/10/2022) 3:00 PM - 3:30 PM [Eastern Time (GMT-4)]

Exhibit Hall | Forum 6

Purpose: To evaluate the clinical need for an automated decision-support software platform for Adaptive Radiation Therapy (ART) of Head-and-Neck cancer (HNC) patients.

Methods: We tested RTapp (SegAna), a new ART software platform for deciding when a treatment replan is needed, to investigate a set of 27 HNC patients’ data retrospectively. For each fraction, RTapp estimated dose distributions and cumulative doses received by targets and OARs from daily CBCT in real-time. RTapp also included a prediction algorithm that analyzed dosimetric parameters (DP) trends against user-specified thresholds to proactively trigger adaptation up to 4 fractions ahead. The DPs evaluated for ART were based on treatment planning dose constraints. Warning (V95<95%) and adaptation (V95<93%) thresholds were set for PTVs, while OAR adaptation endpoints of +10% (DE10) were set for all Dmax and Dmean DPs. Any threshold violation at end-of-treatment (EOT) triggered a review of DP trends to determine the threshold-crossing fraction Fx. The prediction model accuracy was determined as the difference between calculated and predicted DP values with 95% confidence intervals (CI95).

Results: RTapp identified 17/27 studies (63%) for violating PTV coverage or parotids Dmean at EOT. Eleven PTVs had V95<95% (mean coverage decrease of -6.8 ±3.0%) including 5 flagged for adaptation at median Fx=8 (range: 1-18). Seventeen parotids exceeded their Dmean constraints with a median increase of +2.95 Gy (range: 0.99-6.31Gy) at EOT, including 9 with DP>DE10. The differences between predicted and calculated PTV V95 and parotids Dmean was up to 7.6% (mean±CI95: -2.9±4.6%) and 5Gy (mean±CI95: +0.3±1.6Gy), respectively. For parotids, a median Fx of 5 ranged between 1-23 with a lack of specific trend demonstrating that the need for treatment adaptation may be verified for every fraction.

Conclusion: Integrated in an ART clinical workflow, RTapp aids in predicting whether specific treatment would require adaptation up to four fractions ahead of time.

Keywords

Deformation, Image-guided Therapy, Software

Taxonomy

TH- External Beam- Photons: adaptive therapy

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