Implementation and Evaluation of Helical On-Board CBCT and Exact Image Reconstruction
J Tan*, H Li, P Parikh, E Izaguirre, H Li, D Yang, Washington University School of Medicine, St. Louis, MOWE-G-217BCD-7 Wednesday 4:30:00 PM - 6:00:00 PM Room: 217BCD
Purpose: Longitudinal coverage of CBCT, which is 17 cm for head scan and 15.5 cm for body scan, is not enough to cover the entire PTV for over 90% of head/neck and gastrointestinal/genitourinary/gynecologic patients if lymph nodes are involved. Helical CBCT, which was accomplished using external beam LINAC in its research mode, is one promising way to extend the CBCT longitudinal coverage. Aim of this study is to compare Katsevich's exact algorithm with traditional FDK algorithm for helical CBCT image reconstruction.
Methods: CBCT projection raw data were acquired on a TrueBeam LINAC machine (Varian Medical Systems) in the research mode in helical trajectories that encompass a 360 degree rotation, 25 cm pitch, 100 kVp, 80 mA, and 25 ms, with a Catphan 600. Reconstruction was done with Katsevich's exact and FDK approximate algorithms. Scatter correction, beam-hardening correction, and non-uniform gantry angle correction, are performed on projection data to reduce artifacts and noise. Image qualities (CT number accuracy, uniformity, SNR) were evaluated and compared between the reconstruction algorithms.
Results: Images reconstructed by Katsevich's algorithm show better qualities, compared to ones by FDK algorithm and HU numbers have higher uniformity and accuracy. The HU-density calibration curve closely conforms to the manufacturer recommended values. The level of noise computed as the standard deviation in the phantom uniform region is 28.07 for the Katsevich algorithm, compared to 44.64 for the FDK algorithm.
Conclusions: Katsevich's exact reconstruction algorithm provided better image qualities than FDK for helical CBCT scans. This result will very useful for our ongoing investigation of helical CBCT, which would lead to improvement of CBCT longitudinal coverage of PTV and would be essential for future image-guided adaptive radiation therapy applications.