Room: AAPM ePoster Library
Purpose: developed a target-based cone beam computed tomography (CBCT) imaging framework for optimizing a free three dimensional (3D) non-circular source–detector trajectory by incorporating prior image information. Our main aim is to enable a CBCT system to provide topical information about the target using a short-scan trajectory with a minimal number of projections.
Methods: patient specific model from a prior diagnostic computed tomography (CT) is used as a digital phantom for CBCT trajectory simulations. We propose a trajectory optimization scheme which aims to minimize the radiation dose by means of reducing projection views while keeping a sufficient imaging performance at region of interest (ROI). Selection of the best projections is accomplished through maximizing the Feature SIMilarity Index (FSIM) as the objective function fed by the imaging quality provided by different x-ray positions on digital phantom data. The final trajectory selected is applied to a clinical C-arm device. The image quality of the reconstructed image is evaluated by FSIM and Universal Quality Image (UQI) for an anatomical target using an Alderson-Rando head phantom. Adaptive steepest descent projection onto convex sets algorithm was selected as the reconstruction method. The dose delivered is measured using the computed tomography dose index (CTDI).
Results: optimized trajectory could achieve a comparable image quality compared to the circular trajectory while using approximately one quarter of projections. Relative deviation of FSIM and UQI between the reconstructed images related to non-circular and circular trajectories were achieved 9.96 % and 6.57% respectively. The CTDI measured for the circular and non-circular trajectories were 15.5 mGy and 3.38 mGy respectively . An angular range of 160° was used for the non-circular trajectory.
Conclusion: demonstrated that applying a short-scan trajectory with optimized 3D orientations can provide a suitable image quality in the ROI and has a potential for limited angle and low-dose CBCT-based interventions.
Funding Support, Disclosures, and Conflict of Interest: This work has been supported by ACMIT, Austrian Center for Medical Innovation and Technology. We also gratefully acknowledge the support of NVIDIA Corporation for the donation of Titan Xp GPU.