Partial volume and aliasing artefacts in helical cone-beam CT

Synthetic CT generation based on CBCT using improved vision transformer CycleGAN

Cone-beam computed tomography (CBCT) is a crucial component of adaptive radiation therapy; however, it frequently encounters challenges such as artifacts and noise, significantly constraining its clinical utility. While CycleGAN is a widely employed method for CT image synthesis, it has notable limitations regarding the inadequate capture of global features. To tackle these challenges, we introduce a refined unsupervised learning model called improved vision transformer CycleGAN (IViT-CycleGAN). Firstly, we integrate a U-net framework that builds upon ViT. Next, we augment the feed-forward neural network by incorporating deep convolutional networks. Lastly, we enhance the stability of the model training process by introducing gradient penalty and integrating an additional loss term into the generator loss. The experiment demonstrates from multiple perspectives that our model-generated synthesizing CT(sCT) has significant advantages compared to other unsupervised learning models, thereby validating the clinical applicability and robustness of our model. In future clinical practice, our model has the potential to assist clinical practitioners in formulating precise radiotherapy plans.

Accuracy and Feasibility of Synthetic CT for Lung Adaptive Radiotherapy: A Phantom Study

OBJECTIVES

The respiratory variations will lead to inconsistency between the actual delivery dose and the planning dose. How the minor interfractional amplitude changes affect the geometry and dose delivery accuracy remains to be investigated in the context of lung adaptive radiotherapy.

METHODS

Planning 4-dimensional-computed tomography and kV-cone beam computed tomography were scanned based on the Computerized Imaging Reference Systems phantom, which was employed to simulate the minor interfractional amplitude variations. The corresponding synthetic computed tomography for a particular motion pattern can be generated from Velocity program. Then a clinically meaningful synthetic computed tomography was analyzed through the geometrical and dosimetric assessment.

RESULTS

The image quality of synthetic computed tomography was improved obviously compared with cone beam computed tomography. Mean absolute error was minimized when no significant interfractional motion occurs and Velocity can be qualified for dealing with the regular breathing motion patterns. The mean percent hounsfield unit difference of the synthetic hounsfield unit values per organ relative to the planning 4-dimensional-computed tomography image was 22.3%. Under the same conditions, the mean percent hounsfield unit difference of the cone beam computed tomography hounsfield unit values per organ, relative to the planning 4-dimensional-computed tomography image was 83.9%. Overall, the accuracy of hounsfield unit in synthetic computed tomography was improved obviously and the variability of the synthetic image correlates with the planning 4-dimensional-computed tomography image variability. Meanwhile, the dose-volume histograms between planning 4-dimensional-computed tomography and synthetic computed tomography almost coincided each other, which indicates that Velocity program can qualify lung adaptive radiotherapy well when there were no interfractional respiratory variations. However, for cases with obvious interfractional amplitude change, the volume covered at least by 100% of the prescription dose was only 59.6% for that synthetic image.

CONCLUSION

The synthetic computed tomography images generated from Velocity were close to the real images in anatomy and dosimetry, which can make clinical lung adaptive radiotherapy possible based on the actual patient anatomy during treatment.

Synthetic CT generation based on CBCT using respath-cycleGAN

PURPOSE

Cone-beam computed tomography (CBCT) plays an important role in radiotherapy, but the presence of a large number of artifacts limits its application. The purpose of this study was to use respath-cycleGAN to synthesize CT (sCT) similar to planning CT (pCT) from CBCT for future clinical practice.

METHODS

The method integrates the respath concept into the original cycleGAN, called respath-cycleGAN, to map CBCT to pCT. Thirty patients were used for training, and 15 for testing.

RESULTS

The mean absolute error (MAE), root mean square error (RMSE), peak signal to noise ratio (PSNR), structural similarity index (SSIM), and spatial non-uniformity (SNU) were calculated to assess the quality of sCT generated from CBCT. Compared with CBCT images, the MAE improved from 197.72 to 140.7, RMSE from 339.17 to 266.51, and PSNR from 22.07 to 24.44, while SSIM increased from 0.948 to 0.964. Both visually and quantitatively, sCT with respath is superior to sCT without respath. We also performed a generalization test of the head-and-neck (H&N) model on a pelvic dataset. The results again showed that our model was superior.

CONCLUSION

We developed a respath-cycleGAN method to synthesize CT with good quality from CBCT. In future clinical practice, this method may be used to develop radiotherapy plans. This article is protected by copyright. All rights reserved.

Evaluation of Software-Based Metal Artifact Reduction in Intraoperative 3D Imaging of the Spine Using a Mobile Cone Beam CT

The aim of our study was to evaluate whether software-based artifact reduction can achieve an improved image quality, using intraoperative 3D imaging in spinal surgery. A total of 49 intraoperative 3D image datasets of patients, who underwent surgery with pedicle screw placement, were retrospectively evaluated. The visibility of anatomical structures and the diameter of the pedicle screws were examined, with and without the application of the artifact reduction software. All software prototypes can improve the visibility of anatomical structures (P < 0.01), except MAR (metal artifact reduction) combined with IRIS (iterative reconstruction in image space) (P = 0.04). The algorithms MAR and MAR-2 can reduce the blooming artifacts significantly (P < 0.01), but SL (Shepp & Logan) cannot (P = 0.08-0.988). In summary, software-based artifact reduction for intraoperative 3D datasets can improve the current image quality. Additional information regarding the implant placement and the fracture reduction is therefore generated for the surgeon.

Optimization-based algorithm for solving the discrete x-ray transform with nonlinear partial volume effect

Purpose: Inverting the discrete x-ray transform (DXT) with the nonlinear partial volume (NLPV) effect, which we refer to as the NLPV DXT, remains of theoretical and practical interest. We propose an optimization-based algorithm for accurately and directly inverting the NLPV DXT. Methods: Formulating the inversion of the NLPV DXT as a nonconvex optimization program, we propose an iterative algorithm, referred to as the nonconvex primal-dual (NCPD) algorithm, to solve the problem. We obtain the NCPD algorithm by modifying a first-order primal-dual algorithm to address the nonconvex optimization. Subsequently, we perform quantitative studies to verify and characterize the NCPD algorithm. Results: In addition to proposing the NCPD algorithm, we perform numerical studies to verify that the NCPD algorithm can reach the devised numerically necessary convergence conditions and, under the study conditions considered, invert the NLPV DXT by yielding numerically accurate image reconstruction. Conclusion: We have developed and verified with numerical studies the NCPD algorithm for accurate inversion of the NLPV DXT. The study and results may yield insights into the effective compensation for the NLPV artifacts in CT imaging and into the algorithm development for nonconvex optimization programs in CT and other tomographic imaging technologies.

90,000 year-old specialised bone technology in the Aterian Middle Stone Age of North Africa

The question of cognitive complexity in early Homo sapiens in North Africa is intimately tied to the emergence of the Aterian culture (~145 ka). One of the diagnostic indicators of cognitive complexity is the presence of specialised bone tools, however significant uncertainty remains over the manufacture and use of these artefacts within the Aterian techno-complex. In this paper we report on a bone artefact from Aterian Middle Stone Age (MSA) deposits in Dar es-Soltan 1 cave on the Atlantic coast of Morocco. It comes from a layer that can be securely dated to ~90 ka. The typological characteristics of this tool, which suggest its manufacture and use as a bone knife, are comparatively similar to other bone artefacts from dated Aterian levels at the nearby site of El Mnasra and significantly different from any other African MSA bone technology. The new find from Dar es-Soltan 1 cave combined with those from El Mnasra suggest the development of a bone technology unique to the Aterian.

Comparison of panoramic radiography and cone beam CT in the assessment of juxta-apical radiolucency

OBJECTIVES

To compare the performance of panoramic radiography (PAN) and cone beam CT (CBCT) in the detection of juxta-apical radiolucency (JAR), as well as to investigate, in CBCT images, if there are factors associated with the detection of JAR on PAN.

METHODS

Two oral radiologists assessed the presence of JAR in PAN and CBCT images of 175 individuals (308 mandibular third molars). The cortical plates involvement and the JAR size and location were assessed on CBCT to evaluate if these factors were related to JAR detection on PAN. McNemar's test and multiple logistic regression were performed.

RESULTS

PAN and CBCT differed significantly in the detection of JAR (p = 0.001). On PAN, JAR was identified on 24% of the patients while on CBCT its detection increased to 32.6%. JAR was detected only on CBCT and only on PAN in 26 and 7 cases, respectively. Distal/mesial surfaces of dental roots were where JAR was mostly located (84.5%), cortical thinning was found in 59.2% of cases and the mean (SD) of JAR size was 5.03 (±1.8) mm. However, these factors were not associated with JAR detection on PAN (p > 0.05). On the other hand, the location of the cortical involvement (if buccal or lingual) was associated with JAR detection on PAN, which was more detectable when the thinning was on buccal cortical.

CONCLUSIONS

Juxta-apical radiolucency is more often detected on CBCT than on PAN. JAR detection on PAN was improved when it was related to the buccal cortical plate of the mandible.

A constrained, total-variation minimization algorithm for low-intensity x-ray CT

PURPOSE

The authors developed an iterative image-reconstruction algorithm for application to low-intensity computed tomography projection data, which is based on constrained, total-variation (TV) minimization. The algorithm design focuses on recovering structure on length scales comparable to a detector bin width.

METHODS

Recovering the resolution on the scale of a detector bin requires that pixel size be much smaller than the bin width. The resulting image array contains many more pixels than data, and this undersampling is overcome with a combination of Fourier upsampling of each projection and the use of constrained, TV minimization, as suggested by compressive sensing. The presented pseudocode for solving constrained, TV minimization is designed to yield an accurate solution to this optimization problem within 100 iterations.

RESULTS

The proposed image-reconstruction algorithm is applied to a low-intensity scan of a rabbit with a thin wire to test the resolution. The proposed algorithm is compared to filtered backprojection (FBP).

CONCLUSIONS

The algorithm may have some advantage over FBP in that the resulting noise level is lowered at equivalent contrast levels of the wire.

Artefacts in CBCT: a review

Artefacts are common in today's cone beam CT (CBCT). They are induced by discrepancies between the mathematical modelling and the actual physical imaging process. Since artefacts may interfere with the diagnostic process performed on CBCT data sets, every user should be aware of their presence. This article aims to discuss the most prominent artefacts identified in the scientific literature and review the existing knowledge on these artefacts. We also briefly review the basic three-dimensional (3D) reconstruction concept applied by today's CBCT scanners, as all artefacts are more or less directly related to it.

Classifying CT image data into material fractions by a scale and rotation invariant edge model

A fully automated method is presented to classify 3-D CT data into material fractions. An analytical scale-invariant description relating the data value to derivatives around Gaussian blurred step edges--arch model--is applied to uniquely combine robustness to noise, global signal fluctuations, anisotropic scale, noncubic voxels, and ease of use via a straightforward segmentation of 3-D CT images through material fractions. Projection of noisy data value and derivatives onto the arch yields a robust alternative to the standard computed Gaussian derivatives. This results in a superior precision of the method. The arch-model parameters are derived from a small, but over-determined, set of measurements (data values and derivatives) along a path following the gradient uphill and downhill starting at an edge voxel. The model is first used to identify the expected values of the two pure materials (named L and H) and thereby classify the boundary. Second, the model is used to approximate the underlying noise-free material fractions for each noisy measurement. An iso-surface of constant material fraction accurately delineates the material boundary in the presence of noise and global signal fluctuations. This approach enables straightforward segmentation of 3-D CT images into objects of interest for computer-aided diagnosis and offers an easy tool for the design of otherwise complicated transfer functions in high-quality visualizations. The method is applied to segment a tooth volume for visualization and digital cleansing for virtual colonoscopy.

Optimizing 4D cone-beam CT acquisition protocol for external beam radiotherapy

PURPOSE

Four-dimensional cone-beam computed tomography (4D-CBCT) imaging is sensitive to parameters such as gantry rotation speed, number of gantry rotations, X-ray pulse rate, and tube current, as well as a patient's breathing pattern. The aim of this study is to optimize the image acquisition on a patient-specific basis while minimizing the scan time and the radiation dose.

METHODS AND MATERIALS

More than 60 sets of 4D-CBCT images, each with a temporal resolution of 10 phases, were acquired using multiple-gantry rotation and slow-gantry rotation techniques. The image quality was quantified with a relative root mean-square error (RE) and correlated with various acquisition settings; specifically, varying gantry rotation speed, varying both the rotation speed and the number of rotations, and varying both the rotation speed and tube current to keep the radiation exposure constant. These experiments were repeated for three different respiratory periods.

RESULTS

With similar radiation dose, 4D-CBCT images acquired with low current and low rotation speed have better quality over images obtained with high current and high rotation speed. In general, a one-rotation low-speed scan is superior to a two-rotation double-speed scan, even though they provide the same number of projections. Furthermore, it is found that the image quality behaves monotonically with the relative speed as defined by the gantry rotation speed and the patient respiratory period.

CONCLUSIONS

The RE curves established in this work can be used to predict the 4D-CBCT image quality before a scan. This allows the acquisition protocol to be optimized individually to balance the desired quality with the associated scanning time and patient radiation dose.