Search

Background: Cone‐beam CT (CBCT) with non‐circular scanning orbits can improve image quality for 3D intraoperative image guidance. However, geometric calibration of such scans can be challenging. Existing methods typically require a prior image, specialized phantoms, presumed repeatable orbits, or long computation time. Purpose: We propose a novel fully automatic online geometric calibration algorithm that does not require prior knowledge of fiducial configuration. The algorithm is fast, accurate, and can accommodate arbitrary scanning orbits and fiducial configurations. Methods: The algorithm uses an automatic initialization process to eliminate human intervention in fiducial localization and an iterative refinement process to ensure robustness and accuracy. We provide a detailed explanation and implementation of the proposed algorithm. Physical experiments on a lab test bench and a clinical robotic C‐arm scanner were conducted to evaluate spatial resolution performance and robustness under realistic constraints. Results: Qualitative and quantitative results from the physical experiments demonstrate high accuracy, efficiency, and robustness of the proposed method. The spatial resolution performance matched that of our existing benchmark method, which used a 3D‐2D registration‐based geometric calibration algorithm. Conclusions: We have demonstrated an automatic online geometric calibration method that delivers high spatial resolution and robustness performance. This methodology enables arbitrary scan trajectories and should facilitate translation of such acquisition methods in a clinical setting. [ABSTRACT FROM AUTHOR]

Background: The adoption of four‐dimensional cone beam computed tomography (4DCBCT) for image‐guided lung cancer radiotherapy is increasing, especially for hypofractionated treatments. However, the drawbacks of 4DCBCT include long scan times (∼240 s), inconsistent image quality, higher imaging dose than necessary, and streaking artifacts. With the emergence of linear accelerators that can acquire 4DCBCT scans in a short period of time (9.2 s) there is a need to examine the impact that these very fast gantry rotations have on 4DCBCT image quality. Purpose: This study investigates the impact of gantry velocity and angular separation between x‐ray projections on image quality and its implication for fast low‐dose 4DCBCT with emerging systems, such as the Varian Halcyon that provide fast gantry rotation and imaging. Large and uneven angular separation between x‐ray projections is known to reduce 4DCBCT image quality through increased streaking artifacts. However, it is not known when angular separation starts degrading image quality. The study assesses the impact of constant and adaptive gantry velocity and determines the level when angular gaps impair image quality using state‐of‐the‐art reconstruction methods. Methods: This study considers fast low‐dose 4DCBCT acquisitions (60–80 s, 200‐projection scans). To assess the impact of adaptive gantry rotations, the angular position of x‐ray projections from adaptive 4DCBCT acquisitions from a 30‐patient clinical trial were analyzed (referred to as patient angular gaps). To assess the impact of angular gaps, variable and static angular gaps (20°, 30°, 40°) were introduced into evenly separated 200 projections (ideal angular separation). To simulate fast gantry rotations, which are on emerging linacs, constant gantry velocity acquisitions (9.2 s, 60 s, 120 s, 240 s) were simulated by sampling x‐ray projections at constant intervals using the patient breathing traces from the ADAPT clinical trial (ACTRN12618001440213). The 4D Extended Cardiac‐Torso (XCAT) digital phantom was used to simulate projections to remove patient‐specific image quality variables. Image reconstruction was performed using Feldkamp‐Davis‐Kress (FDK), McKinnon‐Bates (MKB), and Motion‐Compensated‐MKB (MCMKB) algorithms. Image quality was assessed using Structural Similarity‐Index‐Measure (SSIM), Contrast‐to‐Noise‐Ratio (CNR), Signal‐to‐Noise‐Ratio (SNR), Tissue‐Interface‐Width‐Diaphragm (TIW‐D), and Tissue‐Interface‐Width‐Tumor (TIW‐T). Results: Patient angular gaps and variable angular gap reconstructions produced similar results to ideal angular separation reconstructions, while static angular gap reconstructions produced lower image quality metrics. For MCMKB‐reconstructions, average patient angular gaps produced SSIM‐0.98, CNR‐13.6, SNR‐34.8, TIW‐D‐1.5 mm, and TIW‐T‐2.0 mm, static angular gap 40° produced SSIM‐0.92, CNR‐6.8, SNR‐6.7, TIW‐D‐5.7 mm, and TIW‐T‐5.9 mm and ideal produced SSIM‐1.00, CNR‐13.6, SNR‐34.8, TIW‐D‐1.5 mm, and TIW‐T‐2.0 mm. All constant gantry velocity reconstructions produced lower image quality metrics than ideal angular separation reconstructions regardless of the acquisition time. Motion compensated reconstruction (MCMKB) produced the highest contrast images with low streaking artifacts. Conclusion: Very fast 4DCBCT scans can be acquired provided that the entire scan range is adaptively sampled, and motion‐compensated reconstruction is performed. Importantly, the angular separation between x‐ray projections within each individual respiratory bin had minimal effect on the image quality of fast low‐dose 4DCBCT imaging. The results will assist the development of future 4DCBCT acquisition protocols that can now be achieved in very short time frames with emerging linear accelerators. [ABSTRACT FROM AUTHOR]