Exhibit Hall | Forum 2
Purpose: Various techniques have been proposed for online adaptive radiotherapy (ART), including CBCT or MR guided ART. CT has been widely used in radiotherapy and plays essential roles in organ delineation, motion management, and dose calculation. An integrated CT-guided Linear Accelerator (Linac) can offer robust and efficient solutions for the simulation and treatment in one setup and online ART. Here we present a full assessment of a CT-guided ART platform for the first time. The system integrates a 16-slice CT scanner and dual-energy (6X and 6XFFF) Linac with 120-leaf MLC. It has a fast Monte Carlo dose calculation algorithm and AI-powered organ segmentation and treatment planning. The CT and Linac are coaxial with a shared couch. In addition, the flat panel imager is designed with a fast image readout rate for MVCBCT acquisition and EPID based in vivo dosimetry.
Methods: A end to end test was repeated ten times using a MIMI phantom to evaluate the systematic accuracy. The precision of the movement of MLC leaves was evaluated using EPID at various gantry angles. The difference between measured and planned positions of each leaf was calculated. The image quality of CT and MVCBCT was assessed using a CATPHANTOM. Thirty-four cases were planned and measured for patient specific QA.
Results: The systematic error of the system was within 0.7mm. The MLC leaf positioning error was 0.3 ± 0.1 mm. The gamma passing rate using 3%/3mm criteria was 99.90% ± 0.15%. The high contrast spatial resolution was 15 line pairs (lp)/cm and 6 lp/cm for CT and MVCBCT, respectively, while the low contrast resolution was firstname.lastname@example.org%@40mGy and 9mm@1%@16mGy, respectively.
Conclusion: The accuracy and plan quality based on our initial assessment was demonstrated to be comparable to other platforms offering ART. The CT-guided ART system can become an important platform for radiotherapy.
Funding Support, Disclosures, and Conflict of Interest: Dr. Ning Wen has received funding and salary support from Shanghai United Imaging Healthcare Co., Ltd.