<b>Accuracy and Clinical Pitfalls of Cone-Beam CT for Planning Zygomatic Implant Placement: A Systematic Review</b>

This study was carried out to assess whether the spatial resolution has an impact on the detection accuracy of proximal caries in flat panel CBCT (cone beam computerized tomography) images and if the detection accuracy can be improved by flat panel CBCT images scanned with high spatial resolution when compared to digital intraoral images. The CBCT test images of 45 non-restored human permanent teeth were respectively scanned with the ProMax 3D and the DCT Pro scanners at different resolutions. Digital images were obtained with a phosphor plate imaging system Digora Optime. Eight observers evaluated all the test images for carious lesion within the 90 proximal surfaces. With the histological examination serving as the reference standard, observer performances were evaluated by receiver operating characteristic (ROC) curves. The areas under the ROC curves were analyzed with two-way analysis of variance. No significant differences were found among the CBCT images and between CBCT and digital images when only proximal enamel caries was detected (p = 0.989). With respect to the detection of proximal dentinal caries, significant difference was found between CBCT and digital images (p < 0.001) but not among CBCT images. The spatial resolution did not have an impact on the detection accuracy of proximal caries in flat panel CBCT images. The flat panel CBCT images scanned with high spatial resolution did not improve the detection accuracy of proximal enamel caries compared to digital intraoral images. CBCT images scanned with high spatial resolutions could not be used for proximal caries detection.

Purpose: Optical flow‐based deformable registration algorithm, which assumes that the image intensity does not change during the deformation, is not suitable for cone beam CT (CBCT) and Helical CT (HCT) image registration because CBCT image possesses a intensity inhomogeneity due to Compton scatter effect. The objective of this study is to develop a new deformable registration algorithm for CBCT and HCT image registration. Method and Materials: The proposed deformable registration algorithm for CBCT and HCT image registration is divided into two steps. First, a maximum a posteriori probability (MAP) based adaptive segmentation method is utilized to accurately segment the voxels of CBCT images and HCT images into four tissue types: air, fat, muscle and bone, even in the presence of severe image intensity inhomogeneity due to Compton scatter. The intensities of the segmented images represent the probability of each voxel belonging to different tissue types and are globally uniform. Thus, the image intensity inhomogeneity effect can be eliminated. Second, an optical flow based deformable registration algorithm is applied to the segmented images, instead of original CBCT and HCT image, to determine the deformation between CBCT and HCT images. Thus, the CBCT image can be deformed to match the HCT images. Results: The performance of the proposed deformable registration algorithm was tested using both digital phantoms and clinical CBCT images. Our studies showed that the conventional optical flow‐based method failed to converge to expected solution due to intensity inhomogeneity effect, and its registration results showed a severe mismatch on many detailed structures between CBCT and HCT images. In contrary, the proposed method matched CBCT and HCT image very well. Conclusion: The proposed segmentation‐based deformable registration algorithm is capable of CBCT and HCT image registration.

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Three-dimensional C-arm Cone-beam CT: Applications in the Interventional Suite

Does Changing Image Guidance Processes Impact Patient Setup Practice?

To investigate the accuracy and reliability of cone beam computed tomography (CBCT) measurements of buccal alveolar bone height (BBH) and thickness (BBT) using custom acquisition settings. School of Dentistry, Oregon Health & Science University. Twelve embalmed cadavers. Cadaver heads were imaged by CBCT (i-CAT® 17-19, Imaging Sciences International, Hatfield, PA) using a 'long scan' (LS) setting with 619 projection images, 360° revolution, 26.9 s duration, and 0.2 mm voxel size, and using a 'short scan' (SS) setting with 169 projection images, 180° rotation, 4.8 s duration, and 0.3 mm voxel size. BBH and BBT were measured with 65 teeth, indirectly from CBCT images and directly through dissection. Comparisons were assessed using paired t-tests (p≤0.05). Level of agreement was assessed by concordance correlation coefficients, Pearson's correlation coefficients, and Bland-Altman plots. Mean differences in measurements compared to direct measurements were as follows, LS 0.17±0.12 (BBH) and 0.10±0.07 mm (BBT), and SS 0.41±0.32 (BBH) and 0.12±0.11 mm (BBT). No statistical differences were found with any of BBH or BBT measurements. Correlation coefficients and Bland-Altman plots showed agreement was high between direct and indirect measurement methods, although agreement was stronger for measurements of BBH than BBT. Compared to the LS, the similarity in results with the reduced scan times and hence reduced effective radiation dose, favors use of shorter scans, unless other purposes for higher resolution imaging can be defined.

43. CBCT dose calculation: accuracy assessment of four different methods

PurposeIn recent years, cone-beam computed tomography (CBCT) is increasingly used in adaptive radiation therapy (ART). However, compared with planning computed tomography (PCT), CBCT image has much more noise and imaging artifacts. Therefore, it is necessary to improve the image quality and HU accuracy of CBCT. In this study, we developed an unsupervised deep learning network (CycleGAN) model to calibrate CBCT images for the pelvis to extend potential clinical applications in CBCT-guided ART.MethodsTo train CycleGAN to generate synthetic PCT (sPCT), we used CBCT and PCT images as inputs from 49 patients with unpaired data. Additional deformed PCT (dPCT) images attained as CBCT after deformable registration are utilized as the ground truth before evaluation. The trained uncorrected CBCT images are converted into sPCT images, and the obtained sPCT images have the characteristics of PCT images while keeping the anatomical structure of CBCT images unchanged. To demonstrate the effectiveness of the proposed CycleGAN, we use additional nine independent patients for testing.ResultsWe compared the sPCT with dPCT images as the ground truth. The average mean absolute error (MAE) of the whole image on testing data decreased from 49.96 ± 7.21HU to 14.6 ± 2.39HU, the average MAE of fat and muscle ROIs decreased from 60.23 ± 7.3HU to 16.94 ± 7.5HU, and from 53.16 ± 9.1HU to 13.03 ± 2.63HU respectively.ConclusionWe developed an unsupervised learning method to generate high-quality corrected CBCT images (sPCT). Through further evaluation and clinical implementation, it can replace CBCT in ART.

Objective The objective of this study was to investigate maxillary sinus abnormalities in the patients who received orthodontic treatment by using cone-beam computed tomography (CBCT) and panoramic radiography. Methods The study sample comprised 480 consecutive patients who were candidates for orthodontic treatment and had taken CBCT and panoramic images at Peking University School and Hospital of Stomatology between August 2016 and December 2016. The 480 patients' radiographs were used for detection of abnormalities in maxillary sinuses. The sinus abnormalities include retention pseudocyst, thickened sinus mucosa and antrolith etc. Data were analyzed using descriptive statistics, chi-square tests and Kappa statistics. Results The occurrence of maxillary sinus abnormalities detected in CBCT images was significantly higher than that in panoramic radiographs (χ2=346.32, P=0.000). Abnormalities were diagnosed in 40.8% of CBCT cases. Retention pseudocyst was the most detectable abnormality (18.2%), followed by thickened sinus mucosa (15.1%). There was a significant difference between genders (χ2=14.98, P=0.000). However, no significant difference could be found between the age groups (χ2=0.26, P=0.621). Conclusions Abnormalities in maxillary sinus could be more accurately detected in CBCT images than in panoramic radiographs. Maxillary sinus abnormalities are common among patients who receive orthodontic treatment, and retention pseudocyst was the most detectable abnormality. The patients’ gender had an effect on the occurrence of maxillary sinus abnormalities, but age had no effect. Key words: Orthodontic treatment; Abnormality of maxillary sinus; Cone beam computed tomography; Panoramic radiography

How Long Does It Take? An Analysis Of Volumetric Image Assessment Time

Improvement of Dose Calculation with Scattered Photon-Corrected kV Cone-Beam CT Image Using the Kernel Deconvolution Method

Working with DICOM craniofacial images

Three-dimensional surgical simulation

Purpose: Cone Beam CT (CBCT) kilovoltage imaging devices are increasingly available for daily imaging in radiotherapy departments. Flat‐panel based CBCT scanners present a distinctive set of artifacts due mostly to increased scatter, longer data acquisition time and reduced detector quantum efficiency as compared to helical Fan Beam CT (FBCT) systems. Our purpose is to characterize image quality from FBCT and CBCT scanners based on noise, contrast and dose, using FBCT as a benchmark. Method and Materials: we acquired phantom and clinical patient images with a CBCT Varian On‐Board Imager as well as with a FBCT Picker PQ5000 single‐row helical scanner. The CBCT scanner was equipped with antiscatter grid and bowtie filter. By comparing CBCT and FBCT images of a high contrast resolution insert, the CBCT reconstruction voxel size and filter were adjusted until the spatial resolution of the FBCT and CBCT images was approximately matched. Dose was measured with standard CTDI and Farmer chambers. Noise, contrast and SNR were evaluated and compared. Results: CBCT images of both phantom and patient were relatively free of streaking and cupping artifacts, indicating that the grid had successfully attenuated most of the scatter. Low contrast detectability threshold is similar for the two modalities, when CBCT dose is about twice as large as FBCT. Noise and non‐uniformities are more prevalent in patient CBCT images, but pelvic soft tissue structures are well discernible. For patient and phantom images Dose×SNR2 is about 4 times lower for FBCT than in CBCT, which is about 1.5–2 times larger than expected, given the measured grid transmission and detector quantum efficiency. Conclusion: In this study, resolution‐matched CBCT and FBCT images could exhibit similar SNRs and contrast‐to‐noise ratios through a combination of increased imaging dose and reduced spatial resolution.

Cone beam computed tomography (CBCT) images obtained from linac-based kV imagers are typically used for image-guided radiotherapy, in particular to perform three-dimensional image matching. CBCT image sets can also be used for adaptive radiotherapy where the treatment plan is modified on the basis of periodic imaging throughout the treatment course. CBCT images provide both anatomical information and Hounsfield unit (HU) values, which are required for dose calculations. This study evaluates treatment plans based on CBCT datasets calibrated using the Catphan 504 phantom to investigate the feasibility of using CBCT for adaptive replanning. The CBCT images were acquired from a Varian On-Board Imager system. Conventional planning CT (PCT) images obtained from a Philips Brilliance Big Bore CT scanner were used as reference images. The HU-density calibration curves of CBCT were obtained using a Catphan 504 phantom and a CIRS density phantom and compared with the clinical PCT calibration curve (obtained using the CIRS density phantom). Treatment plans created using the different calibration curves were compared. Identical targets were delineated on CBCT and PCT images on four different-sized phantoms and planar dose maps were generated. The dose-volume histograms of PCT-and CBCT-based plans were compared and evaluated by gamma analysis. To extend the study to a typical clinical situation, two prostate cases were included. The dose distribution comparison between PCT-and CBCT-based plans for patients yielded similar results to those obtained using phantoms. The study also analyzed the effect of phantom dimensions on HU values and its impact on dose calculations. The isodose distributions computed based on PCT and CBCT using the Catphan calibration curve agree to within ± 1% compared to that based on CBCT using the density phantom calibration curve. However, for phantoms of larger diameter, there is a pronounced discrepancy in the 50% and 60% isodose lines, with the dose difference being about ± 3%. For phantoms whose thickness is less than the cone beam scan length (16 cm) and for phantoms whose diameter is less than that of the calibration phantom, the variation in HU values is high. The effect of a change in radial diameter has a larger impact on dose calculations. This study shows that the CIRS density phantom is not suitable for CBCT calibration and that individual calibration curves obtained using phantoms of appropriate dimensions should be used for planning individual treatment sites.