ESTRO 2025 - Abstract Book

S3109

Physics - Inter-fraction motion management and offline adaptive radiotherapy

ESTRO 2025

6. Yang H, et al. Provision of Organ at Risk Contouring Guidance in UK Radiotherapy Clinical Trials

1657

Digital Poster A feasibility study of an automated offline workflow for CBCT-based adaptive radiotherapy for neoadjuvant treatment of locally advanced rectal cancer Martina Camilla Daniotti 1 , Sara Trivellato 2 , Gianluca Montanari 2 , Rita Marina Niespolo 3 , Lorenzo De Sanctis 4 , Giulia Rossano 4 , Valerio Pisoni 3,4 , Bianca Bordigoni 5 , Joseph Stancanello 6 , Jonathan Hugh Mason 6 , Roberto Pellegrini 7 , Elena De Ponti 2,4 , Stefano Arcangeli 3,4 1 Physics Department, University of Milan, Università degli Studi di Milano, Milan, Italy. 2 Medical Physics Department, Fondazione IRCCS San Gerardo dei Tintori, Monza, Italy. 3 Radiation Oncology Department, Fondazione IRCCS San Gerardo dei Tintori, Monza, Italy. 4 School of Medicine and Surgery, Università degli Studi di Milano-Bicocca, Milan, Italy. 5 Physics Department, University of Milan, Università degli Studi di Padova, Padua, Italy. 6 Clinical Application Development, Elekta AB, Stockholm, Sweden. 7 Global Medical Affairs, Elekta AB, Stockholm, Sweden Purpose/Objective: This study aimed to design and assess the feasibility of an automated workflow using a CBCT-based conventional LINAC for offline adaptive radiotherapy (ART) in locally advanced rectal cancer (LARC) patients. CBCT quality was enhanced using Elekta IRIS algorithm based on poli-energetic quantitative (Polyquant) method empowered with a convolutional neural network scatter correction. Automated contouring and TPS scripting were used to reduce time and staff workload. Material/Methods: Five LARC patients treated on an Elekta VersaHD with daily CBCT imaging were retrospectively selected for this study. Polyquant CBCTs (pCBCTs) were generated from the original CBCT raw data and were calibrated in relative electron density (RED) with a population-based curve. pCBCTs were contoured with the aid of the automated contouring by MIM-ProtégéAI generated via MIM-Assistant (MIM version 7.3.5) and by the anatomical contour adaptation provided by Elekta Monaco TPS (version 6.1.3.0). The original plans were recalculated on the pCBCTs, and the dose distributions were evaluated by the radiation oncologist. The TPS scripting module was exploited to automate the plan recalculation. If considered not acceptable, the treatment plan was adapted via a novel re-optimization on pCBCT, and a patient-specific pre treatment quality assurance (plan QA) was performed. MIM-Assistant was utilized to accumulate doses on CT. The required time was evaluated for each step of the workflow. Results: Plan recalculation showed significant discrepancies for both target and organs at risk and two over five patients would have benefited from offline ART. Also, four patients would have benefited from multiple online ART sessions. The overall time required for the daily recalculation was about 19min. Taking advantage of an ART-specific planning approach, the estimated time for the whole offline plan adaptation was 38min (Figure 1), including plan QA (Figure 2). The tests performed suggested that the ART workflow could be finalized to dose accumulation, exploiting a dedicated automated rule of MIM-Assistant. With some adjustments, an online ART workflow could be feasible for LARC patients in about 36min.