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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.

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BACKGROUND: The clinical benefits of intraoperative cone beam CT (CBCT) during orthopedic procedures include (1) improved accuracy for procedures involving the placement of hardware and (2) providing immediate surgical verification. PURPOSE: Orthopedic interventions often involve long and wide anatomical sites (e.g., lower extremities). Therefore, in order to ensure that the clinical benefits are available to all orthopedic procedures, we investigate the feasibility of a novel imaging trajectory to simultaneously expand the CBCT field-of-view longitudinally and laterally. METHODS: A continuous dual-isocenter imaging trajectory was implemented on a clinical robotic CBCT system using additional real-time control hardware. The trajectory consisted of 200° circular arcs separated by alternating lateral and longitudinal table translations. Due to hardware constraints, the direction of rotation (clockwise/anticlockwise) and lateral table translation (left/right) was reversed every 400°. X-ray projections were continuously acquired at 15 frames/s throughout all movements. A whole-body phantom was used to verify the trajectory. As comparator, a series of conventional large volume acquisitions were stitched together. Image quality was quantified using Root Mean Square Deviation (RMSD), Mean Absolute Percentage Deviation (MAPD), Structural Similarity Index Metric (SSIM) and Contrast-to-Noise Ratio (CNR). RESULTS: The imaging volume produced by the continuous dual-isocenter trajectory had dimensions of L = 95 cm × W = 45 cm × H = 45 cm. This enabled the hips to the feet of the whole-body phantom to be captured in approximately half the imaging dose and acquisition time of the 11 stitched conventional acquisitions required to match the longitudinal and lateral imaging dimensions. Compared to the stitched conventional images, the continuous dual-isocenter acquisition had RMSD of 4.84, MAPD of 6.58% and SSIM of 0.99. The CNR of the continuous dual-isocenter and stitched conventional acquisitions were 1.998 and 1.999, respectively. CONCLUSION: Extended longitudinal and lateral intraoperative volumetric imaging is feasible on clinical robotic CBCT systems.

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OBJECTIVES: Cone beam computed tomography (CBCT) imaging is becoming an indispensable intraoperative tool; however, the current field of view prevents visualization of long anatomical sites, limiting clinical utility. Here, we demonstrate the longitudinal extension of the intraoperative CBCT field of view using a multi-turn reverse helical scan and assess potential clinical utility in interventional procedures. MATERIALS AND METHODS: A fixed-room robotic CBCT imaging system, with additional real-time control, was used to implement a multi-turn reverse helical scan. The scan consists of C-arm rotation, through a series of clockwise and anticlockwise rotations, combined with simultaneous programmed table translation. The motion properties and geometric accuracy of the multi-turn reverse helical imaging trajectory were examined using a simple geometric phantom. To assess potential clinical utility, a pedicle screw posterior fixation procedure in the thoracic spine from T1 to T12 was performed on an ovine cadaver. The multi-turn reverse helical scan was used to provide postoperative assessment of the screw insertion via cortical breach grading and mean screw angle error measurements (axial and sagittal) from 2 observers. For all screw angle measurements, the intraclass correlation coefficient was calculated to determine observer reliability. RESULTS: The multi-turn reverse helical scans took 100 seconds to complete and increased the longitudinal coverage by 370% from 17 cm to 80 cm. Geometric accuracy was examined by comparing the measured to actual dimensions (0.2 ± 0.1 mm) and angles (0.2 ± 0.1 degrees) of a simple geometric phantom, indicating that the multi-turn reverse helical scan provided submillimeter and degree accuracy with no distortion. During the pedicle screw procedure in an ovine cadaver, the multi-turn reverse helical scan identified 4 cortical breaches, confirmed via the postoperative CT scan. Directly comparing the screw insertion angles (n = 22) measured in the postoperative multi-turn reverse helical and CT scans revealed an average difference of 3.3 ± 2.6 degrees in axial angle and 1.9 ± 1.5 degrees in the sagittal angle from 2 expert observers. The intraclass correlation coefficient was above 0.900 for all measurements (axial and sagittal) across all scan types (conventional CT, multi-turn reverse helical, and conventional CBCT), indicating excellent reliability between observers. CONCLUSIONS: Extended longitudinal field-of-view intraoperative 3-dimensional imaging with a multi-turn reverse helical scan is feasible on a clinical robotic CBCT imaging system, enabling long anatomical sites to be visualized in a single image, including in the presence of metal hardware.

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Cone-beam CT (CBCT) with non-circular acquisition orbits has the potential to improve image quality, increase the field-of view, and facilitate minimal interference within an interventional imaging setting. Because time is of the essence in interventional imaging scenarios, rapid reconstruction methods are advantageous. Model-Based Iterative Reconstruction (MBIR) techniques implicitly handle arbitrary geometries; however, the computational burden for these approaches is particularly high. The aim of this work is to extend a previously proposed framework for fast reconstruction of non-circular CBCT trajectories. The pipeline combines a deconvolution operation on the backprojected measurements using an approximate, shift-invariant system response prior to processing with a Convolutional Neural Network (CNN). We trained and evaluated the CNN for this approach using 1800 randomized arbitrary orbits. Noisy projection data were formed from 1000 procedurally generated tetrahedral phantoms as well as anthropomorphic data in the form of 800 CT and CBCT images from the Lung Image Database Consortium Image Collection (LIDC). Using this proposed reconstruction pipeline, computation time was reduced by 90% as compared to MBIR with only minor differences in performance. Quantitative comparisons of nRMSE, FSIM and SSIM are reported. Performance was consistent for projection data simulated with acquisition orbits the network has not previously been trained on. These results suggest the potential for fast processing of arbitrary CBCT trajectory data with reconstruction times that are clinically relevant and applicable - facilitating the application of non-circular orbits in CT image-guided interventions and intraoperative imaging.

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Non-circular orbits in cone-beam CT (CBCT) imaging are increasingly being studied for potential benefits in field-of-view, dose reduction, improved image quality, minimal interference in guided procedures, metal artifact reduction, and more. While modern imaging systems such as robotic C-arms are enabling more freedom in potential orbit designs, practical implementation on such clinical systems remains challenging due to obstacles in critical stages of the workflow, including orbit realization, geometric calibration, and reconstruction. In this work, we build upon previous successes in clinical implementation and address key challenges in the geometric calibration stage with a novel calibration method. The resulting workflow eliminates the need for prior patient scans or dedicated calibration phantoms, and can be conducted in clinically relevant processing times.

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In this work we compare a novel model-based material decomposition (MBMD) approach against a standard approach in high-resolution spectral CT using multi-layer flat-panel detectors. Physical experiments were conducted using a prototype dual-layer detector and a custom high-resolution iodine-enhanced line-pair phantom. Reconstructions were performed using three methods: traditional filtered back-projection (FBP) followed by image-domain decomposition, idealized MBMD with no blur modeling (iMBMD), and MBMD with system blur modeling (bMBMD). We find that both MBMD methods yielded higher resolution decompositions with lower noise than the FBP method, and that bMBMD further improves spatial resolution over iMBMD due to the additional blur modeling. These results demonstrate the advantages of MBMD in resolution performance and noise control over traditional methods for spectral CT. Model-based material decomposition hence has great potential in high-resolution spectral CT applications.