S2186
Physics - Inter-fraction motion management and daily adaptive radiotherapy
ESTRO 2026
Results:
Digital Poster Highlight 4457 In-silico implementation of a data-driven trigger for online adaptive radiotherapy in locally advanced lung cancer Joel A Pogue 1 , Jingwei Duan 2 , Rex Cardan 1 , Courtney Stanley 1 , Natalie Viscariello 1 , Carlos Cardenas 1 , Dennis Stanley 1 , Drexel Boggs 1 , Adam Kole 1 , M. Chris Dobelbower 1 , Joseph Harms 3 1 Radiation Oncology, The University of Alabama at Birmingham, Birmingham, USA. 2 Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, USA. 3 Radiation Oncology, Washington University, Saint Louis, USA Purpose/Objective: Online adaptive radiotherapy (OART) may provide significant dosimetric advantages[1-2] for lung cancer patients by accounting for daily anatomic variation[3], yet its widespread clinical adoption is constrained by limited resources[4-5]. Research has shown that the OART’s dosimetric benefits are heterogeneous across patients and fractions[6-7], thus identifying those most likely to benefit from OART is critical for efficient resources allocation. This study aimed to develop and test a simple, data-driven planning target volume (PTV) shrinkage “trigger”[8] to guide selective implementation of OART for patients with locally advanced lung cancer in-silico. Material/Methods: Eleven patients (313 fractions) with locally advanced lung cancer treated using daily cone-beam CT (CBCT)– guided OART on the Varian Ethos platform were retrospectively analyzed. For each fraction, dose– volume histogram (DVH) metrics were compared between adaptive and non-adaptive recalculations on daily anatomy. Relative dosimetric improvement with adaptation was quantified ((adaptive - non- adaptive)/non-adaptive) for target metrics (CTV V100%, PTV D98%, and PTV D0.03cc) and for organs-at-risk (OARs), including lungs-ITV V20Gy, heart Dmean, esophagus Dmean, spinal cord D0.03cc, and the mean across all four OAR metrics. Percent improvement was correlated with daily PTV shrinkage to assess the predictive value of volumetric target change. A clinical workflow was simulated in which patients transitioned from standard image-guided radiotherapy (IGRT) to OART once a predefined PTV-shrinkage threshold (“trigger”) was reached (Figure 1), and dosimetric implications were evaluated across potential trigger levels.
Mean percent OAR improvement correlated strongly with PTV shrinkage (Figure2a, R=0.73), supporting the use of PTV reduction as a decision metric. Two practical trigger thresholds were identified. An “opportunity-driven” trigger of 20% volume reduction resulted in adaptation of 50% of fractions (7/11 patients) and an average 13.0% relative OAR dose improvement in the triggered cohort (15.8%) versus the untriggered cohort (2.8%). A more selective 30% “resource-conscious” trigger resulted in adaptation of 22% of fractions (4/11 patients) and an average 17.0% relative OAR improvement in the triggered cohort (Figure2b, 22.1%) versus the untriggered cohort (4.1%). Clinically insignificant target metric differences were observed (<2%) for both triggered scenarios. Conclusion: Simple, data-driven volumetric PTV triggers effectively identified patients and fractions most likely to benefit from OART. Implementation of 20% and 30% shrinkage thresholds enabled opportunity-driven and resource-conscious workflows, respectively, achieving 15.8%-22.1% mean OAR sparing while maintaining target coverage. This pragmatic framework supports judicious OART utilization, facilitating scalable integration of adaptive workflows for locally advanced
lung cancer. References:
[1] https://doi.org/10.1016/j.prro.2021.12.017; [2] https://doi.org/10.1016/j.adro.2023.101292; [3] https://doi.org/10.7759/cureus.66943; [4] https://doi.org/10.1016/j.prro.2024.08.007; [5] https://doi.org/10.1016/j.ijrobp.2025.03.013; [6] https://doi.org/10.1016/j.adro.2025.101740; [7] https://doi.org/10.1016/j.prro.2024.02.007;[8] https://doi.org/10.1002/acm2.14060 Keywords: lung cancer, trigger adaptive, resource allocation
Digital Poster 4480
Evaluation of a new Adaptive Radiation Therapy System based on synthetic CT generation from Cone Beam CT Marco D'Andrea 1 , Vicente Bruzzaniti 1 , Sara Ungania 1 , Francesca Marcelli 2 , Monica Montano 2 , Francesco Dionisi 2 , Giuseppe Sanguineti 2 , Antonella Soriani 1 1 Medical Physics Unit, IRCCS Regina Elena National Cancer Institute, Rome, Italy. 2 Radiation Oncology Unit,
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