Clinical Cone Beam CT Research Articles

Universal non-circular cone beam CT orbits for metal artifact reduction imaging during image-guided procedures

Innovation in image-guided procedures has been driven by advances in robotic Cone Beam Computed Tomography (CBCT) systems. A fundamental challenge for CBCT imaging is metal artifacts arising from surgical tools and implanted hardware. Here, we outline how two universal non-circular imaging orbits, optimized for metal artifact reduction, can be implemented in real-time on clinical robotic CBCT systems. Demonstrating potential clinical utility, the universal orbits were implemented during a pedicle screw cervical spine fixation and hip arthroplasty performed on a porcine and ovine cadaver respectively. In both procedures, the universal non-circular orbits noticeably reduced the metal artifacts surrounding the implanted orthopedic hardware, revealing anatomy and soft tissue obscured in current conventional CBCT imaging. This work represents a key step in clinically translating universal orbits, unlocking high quality in-room procedural verification to increase broader use of robotic CBCT systems and reduce the occurrence of secondary corrective surgeries.

Deep learning architecture for scatter estimation in cone-beam computed tomography head imaging with varying field-of-measurement settings.

X-ray scatter causes considerable degradation in the cone-beam computed tomography (CBCT) image quality. To estimate the scatter, deep learning-based methods have been demonstrated to be effective. Modern CBCT systems can scan a wide range of field-of-measurement (FOM) sizes. Variations in the size of FOM can cause a major shift in the scatter-to-primary ratio in CBCT. However, the scatter estimation performance of deep learning networks has not been extensively evaluated under varying FOMs. Therefore, we train the state-of-the-art scatter estimation neural networks for varying FOMs and develop a method to utilize FOM size information to improve performance. We used FOM size information as additional features by converting it into two channels and then concatenating it to the encoder of the networks. We compared our approach for a U-Net, Spline-Net, and DSE-Net, by training them with and without the FOM information. We utilized a Monte Carlo-simulated dataset to train the networks on 18 FOM sizes and test on 30 unseen FOM sizes. In addition, we evaluated the models on the water phantoms and real clinical CBCT scans. The simulation study demonstrates that our method reduced average mean-absolute-percentage-error for U-Net by 38%, Spline-Net by 40%, and DSE-net by 33% for the scatter estimation in the 2D projection domain. Furthermore, the root-mean-square error on the 3D reconstructed volumes was improved for U-Net by 43%, Spline-Net by 30%, and DSE-Net by 23%. Furthermore, our method improved contrast and image quality on real datasets such as water phantom and clinical data. Providing additional information about FOM size improves the robustness of the neural networks for scatter estimation. Our approach is not limited to utilizing only FOM size information; more variables such as tube voltage, scanning geometry, and patient size can be added to improve the robustness of a single network.

Dosimetric impact of variable air cavity within PTV for rectum cancer.

The aim of this study is to determine the impact of rectal air volume changes on treatment plan quality, and subsequently inform daily cone-beam computed tomography (CBCT) evaluation constraints, in terms of acceptable rectal air volume during treatment. Twelve rectal cancer patients who exhibited rectal air within the PTV on their planning CT were selected. A study was conducted to evaluate the deterioration in plan quality due to expanding air volume. For each case, the air cavity volume was isotropically expanded in three dimensions using predefined margins of 3, 5, 7, and 10mm, while deforming bladder and rectum contours. A constraint was applied to the bony anatomy to restrict the deformation. Treatment plans were then generated for all twelve patients by recalculating the reference plan with the expanded air cavity volume. As the air cavity expanded, the maximum relative change in D98% coverage, compared to the reference plan, decreased by 10.8%±3.5%, while the D2% increased by 3.5%±0.9%. The positioning of the air cavity notably influenced the D98% variability with the 3mm expansion. D98% coverage falls below 95% when the air cavity volume exceeds 17 cm3. On average, D2% coverage increased by 0.5% with each expansion. At the largest expansion, extensive coverage of 102% and 105% isodoses was observed compared to the reference plan. Air cavity volumes above 17 cm3 can potentially degrade the high-dose PTV coverage while increasing the regions covered by the 102% and 105% isodoses. Clinical CBCT guidelines were deduced, recommending a maximum threshold of 3.2cm in diameter in any direction.

Vessel-targeted compensation of deformable motion in interventional cone-beam CT

The present standard of care for unresectable liver cancer is transarterial chemoembolization (TACE), which involves using chemotherapeutic particles to selectively embolize the arteries supplying hepatic tumors. Accurate volumetric identification of intricate fine vascularity is crucial for selective embolization. Three-dimensional imaging, particularly cone-beam CT (CBCT), aids in visualization and targeting of small vessels in such highly variable anatomy, but long image acquisition time results in intra-scan patient motion, which distorts vascular structures and tissue boundaries. To improve clarity of vascular anatomy and intra-procedural utility, this work proposes a targeted motion estimation and compensation framework that removes the need for any prior information or external tracking and for user interaction. Motion estimation is performed in two stages: (i) a target identification stage that segments arteries and catheters in the projection domain using a multi-view convolutional neural network to construct a coarse 3D vascular mask; and (ii) a targeted motion estimation stage that iteratively solves for the time-varying motion field via optimization of a vessel-enhancing objective function computed over the target vascular mask. The vessel-enhancing objective is derived through eigenvalues of the local image Hessian to emphasize bright tubular structures. Motion compensation is achieved via spatial transformer operators that apply time-dependent deformations to partial angle reconstructions, allowing efficient minimization via gradient backpropagation. The framework was trained and evaluated in anatomically realistic simulated motion-corrupted CBCTs mimicking TACE of hepatic tumors, at intermediate (3.0 mm) and large (6.0 mm) motion magnitudes. Motion compensation substantially improved median vascular DICE score (from 0.30 to 0.59 for large motion), image SSIM (from 0.77 to 0.93 for large motion), and vessel sharpness (0.189 mm−1 to 0.233 mm−1 for large motion) in simulated cases. Motion compensation also demonstrated increased vessel sharpness (0.188 mm−1 before to 0.205 mm−1 after) and reconstructed vessel length (median increased from 37.37 to 41.00 mm) on a clinical interventional CBCT. The proposed anatomy-aware motion compensation framework presented a promising approach for improving the utility of CBCT for intra-procedural vascular imaging, facilitating selective embolization procedures.

Fine structural human phantom in dentistry and instance tooth segmentation

In this study, we present the development of a fine structural human phantom designed specifically for applications in dentistry. This research focused on assessing the viability of applying medical computer vision techniques to the task of segmenting individual teeth within a phantom. Using a virtual cone-beam computed tomography (CBCT) system, we generated over 170,000 training datasets. These datasets were produced by varying the elemental densities and tooth sizes within the human phantom, as well as varying the X-ray spectrum, noise intensity, and projection cutoff intensity in the virtual CBCT system. The deep-learning (DL) based tooth segmentation model was trained using the generated datasets. The results demonstrate an agreement with manual contouring when applied to clinical CBCT data. Specifically, the Dice similarity coefficient exceeded 0.87, indicating the robust performance of the developed segmentation model even when virtual imaging was used. The present results show the practical utility of virtual imaging techniques in dentistry and highlight the potential of medical computer vision for enhancing precision and efficiency in dental imaging processes.

Novel Detector Configurations in Cone-Beam CT Systems: A Simulation Study

Cone-beam computed tomography (CBCT) has emerged in recent years as an adequate alternative to mammography and tomosynthesis due to the several advantages over traditional mammography, including its ability to provide 3D images, its reduced radiation dose, and its ability to image dense breasts more effectively and conduct more effective breast compressions, etc. Furthermore, CBCT is capable of providing images with high sensitivity and specificity, allowing a more accurate evaluation, even of dense breasts, where mammography and tomosynthesis may lead to a false diagnosis. Clinical and experimental CBCT systems rely on cesium iodine (CsI:Tl) scintillators for X-ray energy conversion. This study comprises an investigation among different novel CBCT detector technologies, consisting either of scintillators (BGO, LSO:Ce, LYSO:Ce, LuAG:Ce, CaF2:Eu, LaBr3:Ce) or semiconductors (Silicon, CZT) in order to define the optimum detector design for a future experimental setup, dedicated to breast imaging. For this purpose, a micro-CBCT system was adapted, using GATE v9.2.1, consisting of the aforementioned various detection schemes. Two phantom configurations were selected: (a) an aluminum capillary positioned at the center of the field of view in order to calculate the system’s spatial resolution and (b) a breast phantom consisting of spheres of different materials, such that their characteristics are close to the breast composition. Breast phantom contrast-to-noise ratios (CNRs) were extracted from the phantom’s tomographic images. The images were reconstructed with filtered back projection (FBP) and ordered subsets expectation-maximization (OSEM) algorithms. The semiconductors acted satisfactorily in low-density matter, while LYSO:Ce, LaBr3:Ce, and LuAG:Ce presented adequate CNRs for all the different spheres’ densities. The energy converters that are presented in this study were evaluated for their performance against the standard CsI:Tl crystal.

Improving image segmentation with contextual and structural similarity

Deep learning models for medical image segmentation are usually trained with voxel-wise losses, e.g., cross-entropy loss, focusing on unary supervision without considering inter-voxel relationships. This oversight potentially leads to semantically inconsistent predictions. Here, we propose a contextual similarity loss (CSL) and a structural similarity loss (SSL) to explicitly and efficiently incorporate inter-voxel relationships for improved performance. The CSL promotes consistency in predicted object categories for each image sub-region compared to ground truth. The SSL enforces compatibility between the predictions of voxel pairs by computing pair-wise distances between them, ensuring that voxels of the same class are close together whereas those from different classes are separated by a wide margin in the distribution space. The effectiveness of the CSL and SSL is evaluated using a clinical cone-beam computed tomography (CBCT) dataset of patients with various craniomaxillofacial (CMF) deformities and a public pancreas dataset. Experimental results show that the CSL and SSL outperform state-of-the-art regional loss functions in preserving segmentation semantics.

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 8245 μGy s−1 was obtained at the detector surface with the inherent Al filtration and 2312 μGy s−1 with 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.

In silico evaluation and feasibility of near margin-less head and neck daily adaptive radiotherapy

ObjectiveWe explore the potential dosimetric benefits of reducing treatment volumes through daily adaptive radiation therapy for head and neck cancer (HNC) patients using the Ethos system/Intelligent Optimizer Engine (IOE). We hypothesize reducing treatment volumes afforded by daily adaption will significantly reduce the dose to adjacent organs at risk. We also explore the capability of the Ethos IOE to accommodate this highly conformal approach in HNC radiation therapy. MethodsTen HNC patients from a phase II trial were chosen, and their cone-beam CT (CBCT) scans were uploaded to the adaptive RT (ART) emulator. A new initial reference plan was generated using both a 1 mm and 5 mm planning target volume (PTV) expansion. Daily adaptive ART plans (1 mm) were simulated from the clinical CBCT taken every fifth fraction. Additionally, using physician-modified ART contours the larger 5 mm plan was recalculated on this recontoured on daily anatomy. Changes in target and OAR contours were measured using Dice coefficients as a surrogate of clinician effort. PTV coverage and organ-at-risk (OAR) doses were statistically compared, and the robustness of each ART plan was evaluated at fractions 5 and 35 to observe if OAR doses were within 3 Gy of pre-plan. ResultsThis study involved six patients with oropharynx and four with larynx cancer, totaling 70 adaptive fractions. The primary and nodal gross tumor volumes (GTV) required the most adjustments, with median Dice scores of 0.88 (range: 0.80–0.93) and 0.83 (range: 0.66–0.91), respectively. For the 5th and 35th fraction plans, 80 % of structures met robustness criteria (quartile 1–3: 67–100 % and 70–90 %). Adaptive planning improved median PTV V100% coverage for doses of 70 Gy (96 % vs. 95.6 %), 66.5 Gy (98.5 % vs. 76.5 %), and 63 Gy (98.9 % vs. 74.9 %) (p < 0.03). Implementing ART with total volume reduction yielded median dose reductions of 7–12 Gy to key organs-at-risk (OARs) like submandibular glands, parotids, oral cavity, and constrictors (p < 0.05). ConclusionsThe IOE enables feasible daily ART treatments with reduced margins while enhancing target coverage and reducing OAR doses for HNC patients. A phase II trial recently finished accrual and forthcoming analysis will determine if these dosimetric improvements correlate with improved patient-reported outcomes.

Temporomandibular involvement in children and adolescents with juvenile idiopathic arthritis: a 2-year prospective cohort study

This study aimed to clinically evaluate temporomandibular joint (TMJ) involvement in juvenile idiopathic arthritis (JIA) and the ability to identify and/or predict development of TMJ-deformities over time using cone beam computed tomography (CBCT). The predictive value of self-reported TMJ pain was also assessed. A prospective longitudinal cohort study comprising 54 children with JIA, 39 girls and 15 boys, was performed. All children had active disease at baseline, 50% with the subtype oligoarthritis. Repeated clinical orofacial and CBCT examinations were performed over a two-year period. At baseline, 39% had radiographic TMJ deformities (24% unilateral, 15% bilateral), at 2-year follow-up, 42% (p > 0.05). Both progressing and improving TMJ deformities were observed. An association was found between TMJ-deformities and self-reported TMJ pain at baseline (p = 0.01). Maximum unassisted mouth opening (MUO) was smaller for children with TMJ-deformities (p < 0.05). The prevalence of palpatory muscle pain was high (48–59%) but not predictive of development of TMJ-deformities. TMJ noises increased over time and crepitations were associated with TMJ-deformities (p < 0.05). In conclusion, in children with JIA, self-reported TMJ pain and dysfunction were common and predictive of TMJ deformities. TMJ deformities were associated with smaller MUO and palpatory TMJ pain as well as crepitations. Trial registration. ClinicalTrials.gov Protocol id: 2010/2089-31/2.

Sex dependent differences of temporomandibular condylar bone mineral density distribution

ABSTRACT Objective The objective of this study was to examine whether bone mineral density (BMD) distribution in the mandibular condyle and facial morphology are associated with temporomandibular joint osteoarthritis (TMJ OA) using clinical cone beam computed tomography (CBCT) images. Methods CBCT images of 35 adults (16 male and 19 female) were examined to obtain TMJ OA counts, cephalometric analyses, and histograms of gray values that are proportional to BMD. Mean, standard deviation (SD), and low and high gray values at the 5th and 95th percentiles (Low5 and High5) of the histograms were measured. Results The female group had significantly higher values of TMJ OA counts, mean, and SD on the right mandibular condyle, High5 on both sides, and all gray value parameters for total (right + left) than the male group. Conclusion Comprehensive analysis of BMD distribution in the mandibular condyle can provide useful information for prognosis of TMJ OA.

Clinical Super-Resolution Computed Tomography of Bone Microstructure: Application in Musculoskeletal and Dental Imaging

PurposeClinical cone-beam computed tomography (CBCT) devices are limited to imaging features of half a millimeter in size and cannot quantify the tissue microstructure. We demonstrate a robust deep-learning method for enhancing clinical CT images, only requiring a limited set of easy-to-acquire training data.MethodsKnee tissue from five cadavers and six total knee replacement patients, and 14 teeth from eight patients were scanned using laboratory CT as training data for the developed super-resolution (SR) technique. The method was benchmarked against ex vivo test set, 52 osteochondral samples are imaged with clinical and laboratory CT. A quality assurance phantom was imaged with clinical CT to quantify the technical image quality. To visually assess the clinical image quality, musculoskeletal and maxillofacial CBCT studies were enhanced with SR and contrasted to interpolated images. A dental radiologist and surgeon reviewed the maxillofacial images.ResultsThe SR models predicted the bone morphological parameters on the ex vivo test set more accurately than conventional image processing. The phantom analysis confirmed higher spatial resolution on the SR images than interpolation, but image grayscales were modified. Musculoskeletal and maxillofacial CBCT images showed more details on SR than interpolation; however, artifacts were observed near the crown of the teeth. The readers assessed mediocre overall scores for both SR and interpolation. The source code and pretrained networks are publicly available.ConclusionModel training with laboratory modalities could push the resolution limit beyond state-of-the-art clinical musculoskeletal and dental CBCT. A larger maxillofacial training dataset is recommended for dental applications.

Validation and comparison of 2D grading scales and 3D volumetric measurements for outcome assessment of bone-grafted alveolar clefts in children.

Several methods have been proposed to assess outcome of bone-grafted alveolar clefts on cone beam computed tomography (CBCT), but so far these methods have not been compared and clinically validated. To validate and compare methods for outcome assessment of bone-grafted clefts with CBCT and provide recommendations for follow-up. In this observational follow-up study, two grading scales (Suomalainen; Liu) and the volumetric bone fill (BF) were used to assess the outcome of 23 autogenous bone-grafted unilateral alveolar clefts. The mean age at bone grafting was 9 years. The volumetric BF was assessed in five vertical sections. The bone-grafted cleft outcome was based on a binary coding (success or regraft) on a clinical multidisciplinary expert consensus meeting. Grading scales and volumetric assessment were compared in relation to the bone-grafted cleft outcome (success or regraft). Reliability for the different outcome variables was analyzed with intra-class correlation and by calculating kappa values. The study had a limited sample size. Clinical CBCT acquisitions had a varying tube current and exposure time. Volumetric 3D measurements allowed for outcome assessment of bone-grafted alveolar clefts with high reliability and validity. The two grading scales showed highly reliable outcomes, yet the validity was high for the Suomalainen grading scale but low for the Liu grading scale. Volumetric 3D measurement as well as the Suomalainen grading can be recommended for outcome assessment of the bone-grafted cleft. Yet, one must always make a patient-specific assessment if there is a need to regraft.

Osseointegrability of 3D-printed porous titanium alloy implant on tibial shaft bone defect in rabbit model.

Previous studies have demonstrated the ability of osseointegration of porous titanium implants in cancellous bone. Our study was designed to (i) investigate the ability of bone ingrowth into 3D-printed porous titanium alloy implant on the cortical bone of rabbits using CT-scan and histology, and (ii) to identify the consistency of the radiology information between clinical Cone Beam Computed Tomography (CBCT) and Micro Computed Tomography (μCT) in the evaluation of bone ingrowth. The porous titanium alloy implants were 3D-printed employing the Electron Beam Melting (EBM) technology with an intended pore size of 600 μm and porosity of approximately 50 percent. Each implant was inserted into tibial diaphysis in one rabbit and its pores were classified as contacting bone or non-contacting bone. Depending on the time of explantation, the rabbits were divided into two groups: group 1 consisting of 6 rabbits between 13 and 20 weeks and group 2 consisting of 6 rabbits between 26 and 32 weeks. Tissue ingrowth into the non-bone contacting pores were evaluated by CBCT and histology. μCT was used to further investigate the bone ingrowth into four implants (two from each group were randomly chosen). The CBCT detected the present of tissue with bone-like density in both bone-contacting pores and non-bone-contacting pores of all implants. The μCT analysis also supported this result. All the bone-like tissues were then histologically confirmed to be mature bone. The analysis of CBCT data to assess bone ingrowth in porous implants had the sensitivity, specificity, positive and negative predictive values of 85, 84, 93 and 70 percent, respectively, when considering μCT assessment as the gold standard. Fully porous titanium alloy implant has great potential to reconstruct diaphyseal bone defect due to its good ability of osseointegration. CBCT is a promising method for evaluation of bone ingrowth into porous implants.

A quantitative CBCT pipeline based on 2D antiscatter grid and grid-based scatter sampling for image-guided radiation therapy.

Quantitative accuracy is critical for expanding the role of cone beam CT (CBCT) imaging from target localization to quantitative treatment monitoring and plan adaptations in radiation therapy. Despite advances in CBCT image quality improvement methods, quantitative accuracy gap between CBCT and multi-detector CT (MDCT) remains. In this work, a physics-driven approach was investigated that combined robust scatter rejection, raw data correction and iterative image reconstruction to further improve CBCT image quality and quantitative accuracy, referred to as quantitative CBCT (qCBCT). QCBCT approach includes tungsten 2D antiscatter grid hardware, residual scatter correction with grid-based scatter sampling, image lag, and beam hardening correction for offset detector geometry linac-mounted CBCT. Images were reconstructed with iterative image reconstruction to reduce image noise. qCBCT was evaluated using a variety of phantoms to investigate the effect of object size and its composition on image quality, and image quality was benchmarked against clinical CBCT and gold standard MDCT images used for treatment planning. QCBCT provided statistically significant improvement in CT number accuracy and reduced image artifacts when compared to clinical CBCT images. When compared to gold standard MDCT, mean HU errors in qCBCT and clinical CBCT were 17±9 and 38±29 HU, respectively. Magnitude of phantom size dependent HU variations were comparable between MDCT and qCBCT images. With iterative reconstruction, contrast-to-noise ratio improved by 25% when compared to clinical CBCT protocols. Combination of novel scatter suppression techniques and other data correction methods in qCBCT provided CT number accuracy comparable to gold standard MDCT used for treatment planning. This approach may potentially improve CBCT's promise in fulfilling the tasks that demand high quantitative accuracy, such as online dose calculations and treatment response assessment, in image guided radiation therapy.

Cone-beam CT imaging features of common cystic lesions associated with the impacted mandibular third molar

Objective: To analyze the imaging features of cone-beam CT (CBCT) of ameloblastoma (AB), odontogenic keratocyst (OKC) and dentigerous cysts (DC) associated with the mandibular impacted third molars,so as to provide useful information for differential diagnosis of these lesions. Methods: The patients who were with complete clinical data, pathological diagnosis and CBCT images from AB, OKC and DC around the mandibular impacted third molars were collected in Peking University Hospital of Stomatology from August 2016 to December 2021. A total of 109 patients (14 were diagnosed as AB, 23 were diagnosed as OKC and the others were diagnosed as dental cysts) were collected, including 73 males and 36 females. The age ranged from 11 to 70. The analyzed imaging features included location and internal density of the lesions, bone expansion, root resorption of adjacent teeth and types of the impacted teeth. The Chi square test was used to compare the gender of different lesions, and the Fisher's exact test was used to compare imaging features of lesions. When P<0.05, there was a significant difference among the three. Logistic regression analysis was performed to determine the imaging features that significantly contribute to correct imaging diagnosis. Corresponding P-values were calculated for all factors from multivariate models. Results: In the 23 cases of OKC, no special location was observed for the center of the lesion, heterogeneous high-density were seen in 21.7% of the cases, 56.5% of the cases had no significant bone expansion and the impacted teeth were not specially oriented. Among the 14 AB, 7 cases (7/14) were mainly located in the ramus of the mandible, and all cases (14/14) had buccal/lingual expansion of the jaw, 8 cases (8/14) presented root resorption of the adjacent teeth, and mesial impacted mandibular third molar were seen in 6 cases (6/14). Among the 72 DC, 88.9% (64/72) of the cases were mainly limited to the crown of the impacted third molar, 72.2% (52/72) of the cases had no obvious bone expansion, inverted impacted teeth were shown in 56.9% (41/72) of the cases. There was a significant difference among the three groups (χ2=7.30, P=0.026) in gender. AB and odontogenic cyst were more common in men than in women, while the incidence of OKC was roughly equal between men and women.There were significant differences in the location (P<0.001), internal density (P=0.001) of the lesions, bone expansion (P<0.001) and types of the impacted teeth (P<0.001), while no statistical difference was found for root resorption of adjacent teeth (P=0.153). Logistics regression analysis showed that the location of the lesion, internal density, bone expansion, root resorption of adjacent teeth and the types of impacted teeth had significant effects on the accurate diagnosis of the three kinds of lesions. Conclusions: Location, internal density, bone expansion and types of the impacted teeth played an important role in the correct imaging diagnosis. Further analysis indicates that when the classification of impacted teeth and the location of lesions are considered synchronously, DC can be differentiated from AB and OKC.

A new dental CBCT metal artifact reduction method based on a dual-domain processing framework

Objective. Cone beam computed tomography (CBCT) has been wildly used in clinical treatment of dental diseases. However, patients often have metallic implants in mouth, which will lead to severe metal artifacts in the reconstructed images. To reduce metal artifacts in dental CBCT images, which have a larger amount of data and a limited field of view compared to computed tomography images, a new dental CBCT metal artifact reduction method based on a projection correction and a convolutional neural network (CNN) based image post-processing model is proposed in this paper. Approach. The proposed method consists of three stages: (1) volume reconstruction and metal segmentation in the image domain, using the forward projection to get the metal masks in the projection domain; (2) linear interpolation in the projection domain and reconstruction to build a linear interpolation (LI) corrected volume; (3) take the LI corrected volume as prior and perform the prior based beam hardening correction in the projection domain, and (4) combine the constructed projection corrected volume and LI-volume slice-by-slice in the image domain by two concatenated U-Net based models (CNN1 and CNN2). Simulated and clinical dental CBCT cases are used to evaluate the proposed method. The normalized root means square difference (NRMSD) and the structural similarity index (SSIM) are used for the quantitative evaluation of the method. Main results. The proposed method outperforms the frequency domain fusion method (FS-MAR) and a state-of-art CNN based method on the simulated dataset and yields the best NRMSD and SSIM of 4.0196 and 0.9924, respectively. Visual results on both simulated and clinical images also illustrate that the proposed method can effectively reduce metal artifacts. Significance. This study demonstrated that the proposed dual-domain processing framework is suitable for metal artifact reduction in dental CBCT images.

Evaluation of the feasibility of a multisource CBCT for maxillofacial imaging

Objective. The aim of this study was to investigate the feasibility of improving the image quality and accuracy of cone beam computed tomography (CBCT) by replacing the conventional wide cone angle x-ray tube with a distributed x-ray source array positioned in the axial direction. Approach. The multisource CBCT (ms-CBCT) design was experimentally simulated using a benchtop scanner with a carbon nanotube x-ray tube and a flat-panel detector. The source was collimated and translated in the axial direction to simulate a source array with a reduced cone angle for each beam. An adjacent scatter ratio subtraction (ASRS) method was implemented for residual scatter reduction. Several phantoms were imaged using the ms-CBCT and conventional CBCT configurations under otherwise similar conditions. The Requirements of the ms-CBCT design on the x-ray source and detector were evaluated. Main results. Compared to the conventional CBCT, the ms-CBCT design with 8 sources and ASRS significantly improved the image quality and accuracy, including: (1) reducing the cupping artifact from 15% to 3.5%; (2) reducing the spatial nonuniformity of the CT Hounsfield unit values from 38.0 to 9.2; (3) improving the contrast-to-noise ratio of the low contrast objects (acrylic and low density polyethylene inserts) against the water-equivalent background by ∼20% and (4) reducing the root-mean-square error of the HU values by 70%, from 420.1 to 124.4. The imaging dose and scanning time used by the current clinical CBCT for maxillofacial imaging can be achieved by current source and detector technologies. Significance. The ms-CBCT design significantly reduces the scatter and improves the image quality and accuracy compared to the conventional CBCT.

Comparative Evaluation of the Horizontal Condylar Guidance Using Protrusive Interocclusal Records, OPG, and CBCT in Edentulous Patients: An In Vivo Study.

A clinical study to compare the horizontal condylar guidance using protrusive interocclusal records, orthopantomography (OPG), and cone-beam computed tomography (CBCT) in edentulous patients. Thirty-six edentulous subjects were selected as per predetermined criteria. Horizontal condylar guidance was recorded using protrusive interocclusal records (PIR), OPG, and CBCT for each patient. The PIR were obtained using extraoral Gothic arch tracers to program the Hanau articulator. The horizontal condylar guidance angles (HCGAs) were digitally constructed using appropriate software along the posterior slope of articular eminence for all radiographs. The collected data were recorded, tabulated, and statistically analyzed. The condylar guidance angle values were tested for significance to compare the different angles. The correlation of HCGA measurements on both sides between the three groups was analyzed. The PIR and OPG methods (p = 0.001), as well as the OPG and CBCT methods (p = 0.001), show substantial differences on both sides. On the contrary, the PIR and CBCT methods did not differ significantly (p = 0.11). Cone-beam computed tomography is as reliable and accurate as the clinical method. A significant correlation exists between the clinical method and CBCT. It can be used as a dependable adjunct to the clinical method of HCGA measurement. Cone-beam computed tomography can overcome the shortcomings of the conventional clinical methods to determine the accurate horizontal condylar guidance angulation measurement. It is safer with minimum discomfort and wastage of time for the patients.

Clinical feasibility of a commercially available MRI-only method for radiotherapy treatment planning of the brain.

Advancements in deep-learning based synthetic computed tomography (sCT) image conversion methods have enabled the development of magnetic resonance imaging (MRI)-only based radiotherapy treatment planning (RTP) of the brain. This study evaluates the clinical feasibility of a commercial, deep-learning based MRI-only RTP method with respect to dose calculation and patient positioning verification performance in RTP of the brain. Clinical validation of dose calculation accuracy was performed by a retrospective evaluation for 25 glioma and 25 brain metastasis patients. Dosimetric and image quality of the studied MRI-only RTP method was evaluated by a direct comparison of the sCT-based and computed tomography (CT)-based external beam radiation therapy (EBRT) images and treatment plans. Patient positioning verification accuracy of sCT images was evaluated retrospectively for 10 glioma and 10 brain metastasis patients based on clinical cone-beam computed tomography (CBCT) imaging. An average mean dose difference of Dmean = 0.1% for planning target volume (PTV) and 0.6% for normal tissue (NT) structures were obtained for glioma patients. Respective results for brain metastasis patients were Dmean = 0.5% for PTVs and Dmean =1.0% for NTs. Global three-dimensional (3D) gamma pass rates using 2%/2 mm dose difference and distance-to-agreement (DTA) criterion were 98.0% for the glioma subgroup, and 95.2% for the brain metastasis subgroup using 1%/1 mm criterion. Mean distance differences of <1.0 mm were observed in all Cartesian directions between CT-based and sCT-based CBCT patient positioning in both subgroups. In terms of dose calculation and patient positioning accuracy, the studied MRI-only method demonstrated its clinical feasibility for RTP of the brain. The results encourage the use of the studied method as part of a routine clinical workflow.