Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2024
Challenges and opportunities in the development and clinical implementation of artificial intelligence based synthetic computed tomography for magnetic resonance only radiotherapy.
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Villegas Fernanda, Dal Bello Riccardo, Alvarez-Andres Emilie, Dhont Jennifer, Janssen Tomas, Milan Lisa, Robert Charlotte, Salagean Ghizela-Ana-Maria, Tejedor Natalia, Trnková Petra, Fusella Marco, Placidi Lorenzo, Cusumano Davide
Аннотация
Synthetic computed tomography (sCT) generated from magnetic resonance imaging (MRI) can serve as a substitute for planning CT in radiation therapy (RT), thereby removing registration uncertainties associated with multi-modality imaging pairing, reducing costs and patient radiation exposure. CE/FDA-approved sCT solutions are nowadays available for pelvis, brain, and head and neck, while more complex deep learning (DL) algorithms are under investigation for other anatomic sites. The main challenge in achieving a widespread clinical implementation of sCT lies in the absence of consensus on sCT commissioning and quality assurance (QA), resulting in variation of sCT approaches across different hospitals. To address this issue, a group of experts gathered at the ESTRO Physics Workshop 2022 to discuss the integration of sCT solutions into clinics and report the process and its outcomes. This position paper focuses on aspects of sCT development and commissioning, outlining key elements crucial for the safe implementation of an MRI-only RT workflow.