Source-detector trajectory optimization in cone-beam computed tomography: a comprehensive review on today’s state-of-the-art

An interactive task-based method for the avoidance of metal artifacts in CBCT

PURPOSE

Intraoperative cone-beam CT imaging enables 3D validation of implant positioning and fracture reduction for orthopedic and trauma surgeries. However, the emergence of metal artifacts, especially in the vicinity of metallic objects, severely degrades the clinical value of the imaging modality. In previous works, metal artifact avoidance (MAA) methods have been shown to reduce metal artifacts by adapting the scanning trajectory. Yet, these methods fail to translate to clinical practice due to remaining methodological constraints and missing workflow integration.

METHODS

In this work, we propose a method to compute the spatial distribution and calibrated strengths of expected artifacts for a given tilted circular trajectory. By visualizing this as an overlay changing with the C-Arm's tilt, we enable the clinician to interactively choose an optimal trajectory while factoring in the procedural context and clinical task. We then evaluate this method in a realistic human cadaver study and compare the achieved image quality to acquisitions optimized using global metrics.

RESULTS

We assess the effectiveness of the compared methods by evaluation of image quality gradings of depicted pedicle screws. We find that both global metrics as well as the proposed visualization of artifact distribution enable a drastic improvement compared to standard non-tilted scans. Furthermore, the novel interactive visualization yields a significant improvement in subjective image quality compared to the state-of-the-art global metrics. Additionally we show that by formulating an imaging task, the proposed method allows to selectively optimize image quality and avoid artifacts in the region of interest.

CONCLUSION

We propose a method to spatially resolve predicted artifacts and provide a calibrated measure for artifact strength grading. This interactive MAA method proved practical and effective in reducing metal artifacts in the conducted cadaver study. We believe this study serves as a crucial step toward clinical application of an MAA system to improve image quality and enhance the clinical validation of implant placement.

Simulation-driven training of vision transformers enables metal artifact reduction of highly truncated CBCT scans

BACKGROUND

Due to the high attenuation of metals, severe artifacts occur in cone beam computed tomography (CBCT). The metal segmentation in CBCT projections usually serves as a prerequisite for metal artifact reduction (MAR) algorithms.

PURPOSE

The occurrence of truncation caused by the limited detector size leads to the incomplete acquisition of metal masks from the threshold-based method in CBCT volume. Therefore, segmenting metal directly in CBCT projections is pursued in this work.

METHODS

Since the generation of high quality clinical training data is a constant challenge, this study proposes to generate simulated digital radiographs (data I) based on real CT data combined with self-designed computer aided design (CAD) implants. In addition to the simulated projections generated from 3D volumes, 2D x-ray images combined with projections of implants serve as the complementary data set (data II) to improve the network performance. In this work, SwinConvUNet consisting of shift window (Swin) vision transformers (ViTs) with patch merging as encoder is proposed for metal segmentation.

RESULTS

The model's performance is evaluated on accurately labeled test datasets obtained from cadaver scans as well as the unlabeled clinical projections. When trained on the data I only, the convolutional neural network (CNN) encoder-based networks UNet and TransUNet achieve only limited performance on the cadaver test data, with an average dice score of 0.821 and 0.850. After using both data II and data I during training, the average dice scores for the two models increase to 0.906 and 0.919, respectively. By replacing the CNN encoder with Swin transformer, the proposed SwinConvUNet reaches an average dice score of 0.933 for cadaver projections when only trained on the data I. Furthermore, SwinConvUNet has the largest average dice score of 0.953 for cadaver projections when trained on the combined data set.

CONCLUSIONS

Our experiments quantitatively demonstrate the effectiveness of the combination of the projections simulated under two pathways for network training. Besides, the proposed SwinConvUNet trained on the simulated projections performs state-of-the-art, robust metal segmentation as demonstrated on experiments on cadaver and clinical data sets. With the accurate segmentations from the proposed model, MAR can be conducted even for highly truncated CBCT scans.

Fully automatic online geometric calibration for non-circular cone-beam CT orbits using fiducials with unknown placement

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.

A carbon nanotube x-ray source array designed for a new multisource cone beam computed tomography scanner

Cone beam computed tomography (CBCT) is known to suffer from strong scatter and cone beam artifacts. The purpose of this study is to develop and characterize a rapidly scanning carbon nanotube (CNT) field emission x-ray source array to enable a multisource CBCT (ms-CBCT) image acquisition scheme which has been demonstrated to overcome these limitations. A CNT x-ray source array with eight evenly spaced focal spots was designed and fabricated for a medium field of view ms-CBCT for maxillofacial imaging. An external multisource collimator was used to confine the radiation from each focal spot to a narrow cone angle. For ms-CBCT imaging, the array was placed in the axial direction and rapidly scanned while rotating continuously around the object with a flat panel detector. The x-ray beam profile, temporal and spatial resolutions, energy and dose rate were characterized and evaluated for maxillofacial imaging. The CNT x-ray source array achieved a consistent focal spot size of 1.10 ± 0.04 mm × 0.84 ± 0.03 mm and individual beam cone angle of 2.4°±0.08 after collimation. The x-ray beams were rapidly switched with a rising and damping times of 0.21 ms and 0.19 ms, respectively. Under the designed operating condition of 110 kVp and 15 mA, a dose rate of 8245μGy s-1was obtained at the detector surface with the inherent Al filtration and 2312μGy s-1with an additional 0.3 mm Cu filter. There was negligible change of the x-ray dose rate over many operating cycles. A ms-CBCT scan of an adult head phantom was completed in 14.4 s total exposure time for the imaging dose in the range of that of a clinical CBCT scanner. A spatially distributed CNT x-ray source array was designed and fabricated. It has enabled a new multisource CBCT to overcome some of the main inherent limitations of the conventional CBCT.

Source-detector trajectory optimization for CBCT metal artifact reduction based on PICCS reconstruction

Precise instrument placement plays a critical role in all interventional procedures, especially percutaneous procedures such as needle biopsies, to achieve successful tumor targeting and increased diagnostic accuracy. C-arm cone beam computed tomography (CBCT) has the potential to precisely visualize the anatomy in direct vicinity of the needle and evaluate the adequacy of needle placement during the intervention, allowing for instantaneous adjustment in case of misplacement. However, even with the most advanced C-arm CBCT devices, it can be difficult to identify the exact needle position on CBCT images due to the strong metal artifacts around the needle. In this study, we proposed a framework for customized trajectory design in CBCT imaging based on Prior Image Constrained Compressed Sensing (PICCS) reconstruction with the goal of reducing metal artifacts in needle-based procedures. We proposed to optimize out-of-plane rotations in three-dimensional (3D) space and minimize projection views while reducing metal artifacts at specific volume of interests (VOIs). An anthropomorphic thorax phantom with a needle inserted inside and two tumor models as the imaging targets were used to validate the proposed approach. The performance of the proposed approach was also evaluated for CBCT imaging under kinematic constraints by simulating some collision areas on the geometry of the C-arm. We compared the result of optimized 3D trajectories using the PICCS algorithm and 20 projections with the result of a circular trajectory with sparse view using PICCS and Feldkamp, Davis, and Kress (FDK), both using 20 projections, and the circular FDK method with 313 projections. For imaging targets 1 and 2, the highest values of structural similarity index measure (SSIM) and universal quality index (UQI) between the reconstructed image from the optimized trajectories and the initial CBCT image at the VOI was calculated 0.7521, 0.7308 and 0.7308, 0.7248 respectively. These results significantly outperformed the FDK method (with 20 and 313 projections) and the PICCS method (20 projections) both using the circular trajectory. Our results showed that the proposed optimized trajectories not only significantly reduce metal artifacts but also suggest a dose reduction for needle-based CBCT interventions, considering the small number of projections used. Furthermore, our results showed that the optimized trajectories are compatible with spatially constrained situations and enable CBCT imaging under kinematic constraints when the standard circular trajectory is not feasible.

Revealing pelvic structures in the presence of metal hip prothesis via non-circular CBCT orbits

As the expansion of Cone Beam CT (CBCT) to new interventional procedures continues, the burdensome challenge of metal artifacts remains. Photon starvation and beam hardening from metallic implants and surgical tools in the field of view can result in the anatomy of interest being partially or fully obscured by imaging artifacts. Leveraging the flexibility of modern robotic CBCT imaging systems, implementing non-circular orbits designed for reducing metal artifacts by ensuring data-completeness during acquisition has become a reality. Here, we investigate using non-circular orbits to reduce metal artifacts arising from metallic hip prostheses when imaging pelvic anatomy. As a first proof-of-concept, we implement a sinusoidal and a double-circle-arc orbit on a CBCT test bench, imaging a physical pelvis phantom, with two metal hip prostheses, housing a 3D-printed iodine-filled radial line-pair target. A standard circular orbit implemented with the CBCT test bench acted as comparator. Imaging data collection and processing, geometric calibration and image reconstruction was completed using in-house developed software programs. Imaging with the standard circular orbit, image artifacts were observed in the pelvic bones and only 33 out of the possible 45 line-pairs of the radial line-pair target were partially resolvable in the reconstructed images. Comparatively, imaging with both the sinusoid and double-circle-arc orbits reduced artifacts in the surrounding anatomy and enabled all 45 line-pairs to be visibly resolved in the reconstructed images. These results indicate the potential of non-circular orbits to assist in revealing previously obstructed structures in the pelvic region in the presence of metal hip prosthesis.

A nonconvex model-based combined geometric calibration scheme for micro cone-beam CT with irregular trajectories

BACKGROUND

Many dedicated cone-beam CT (CBCT) systems have irregular scanning trajectories. Compared with the standard CBCT calibration, accurate calibration for CBCT systems with irregular trajectories is a more complex task, since the geometric parameters for each scanning view are variable. Most of the existing calibration methods assume that the intrinsic geometric relationship of the fiducials in the phantom is precisely known, and rarely delve deeper into the issue of whether the phantom accuracy is adapted to the calibration model.

PURPOSE

A high-precision phantom and a highly robust calibration model are interdependent and mutually supportive, and they are both important for calibration accuracy, especially for the high-resolution CBCT. Therefore, we propose a calibration scheme that considers both accurate phantom measurement and robust geometric calibration.

METHODS

Our proposed scheme consists of two parts: (1) introducing a measurement model to acquire the accurate intrinsic geometric relationship of the fiducials in the phantom; (2) developing a highly noise-robust nonconvex model-based calibration method. The measurement model in the first part is achieved by extending our previous high-precision geometric calibration model suitable for CBCT with circular trajectories. In the second part, a novel iterative method with optimization constraints based on a back-projection model is developed to solve the geometric parameters of each view.

RESULTS

The simulations and real experiments show that the measurement errors of the fiducial ball bearings (BBs) are within the subpixel level. With the help of the geometric relationship of the BBs obtained by our measurement method, the classic calibration method can achieve good calibration based on far fewer BBs. All metrics obtained in simulated experiments as well as in real experiments on Micro CT systems with resolutions of 9 and 4.5 μm show that the proposed calibration method has higher calibration accuracy than the competing classic method. It is particularly worth noting that although our measurement model proves to be very accurate, the classic calibration method based on this measurement model can only achieve good calibration results when the resolution of the measurement system is close to that of the system to be calibrated, but our calibration scheme enables high-accuracy calibration even when the resolution of the system to be calibrated is twice that of the measurement system.

CONCLUSIONS

The proposed combined geometrical calibration scheme does not rely on a phantom with an intricate pattern of fiducials, so it is applicable in Micro CT with high resolution. The two parts of the scheme, the "measurement model" and the "calibration model," prove to be of high accuracy. The combination of these two models can effectively improve the calibration accuracy, especially in some extreme cases.