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Accuracy of An Automated Software for Adaptive Radiotherapy of Head and Neck Cancers

S Gros1,2*, A Block1,2, 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-F6-2 (Sunday, 7/10/2022) 3:00 PM - 3:30 PM [Eastern Time (GMT-4)]

Exhibit Hall | Forum 6

Purpose: To establish the accuracy of a new Adaptive Radiation Therapy (ART) decision-support software to limit parotids dose for Head-and-Neck cancer (HNC) patients.

Methods: 27 HNC patients data treated with external beam were analyzed retrospectively with RTapp®, an automated ART platform designed to provide real-time visualization of daily anatomical changes, while predicting adaptation needs from analyzing daily 3D imaging. RTapp estimates daily dose distributions within targets and OARs following the automatic deformable registration of the initial plan images to daily CBCTs anatomy. Structure specific dosimetric parameters (DPs) trends were tracked against user-defined thresholds for adaptation. For this work, parotid specific endpoints were defined as Dmean planning constraints (warning) and a +10% excess threshold (replanning). Deformed CTs and structures from fractions identified with threshold violations were exported to the Eclipse (Varian) TPS for dose recalculation with the original plan and identify true/false positives rates. A second dataset from fractions with estimated parotid Dmean within -10% of the planning constraint was exported for recalculation to establish true/false negatives rates. The software accuracy was determined by the difference between estimated and recalculated Dmean values, sensitivity, specificity, and predictive values of RTapp to identify adaptation needs for parotids Dmean on a fraction basis.

Results: 48% of patient studies were flagged for exceeding their respective parotids Dmean constraint or adaptation threshold. Mean absolute differences between estimated and recalculated Dmean for the adaptation (n=15) and non-flagged (n=12) groups were 1.52± 0.99 Gy and 1.03±0.83 Gy, respectively (p = 0.28). The sensitivity of RTapp to accurately identify a replanning need was 84.6% while the specificity to identify studies who did not need adaptation was 71.4%. Positive and negative predictive values for adaptation were 73.3% and 83.3%, respectively.

Conclusion: RTapp can predict the need to replan based on parotids mean dose thresholds with high accuracy.

Keywords

Image-guided Therapy, Treatment Planning, Deformation

Taxonomy

TH- External Beam- Photons: adaptive therapy

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