Cone-beam Computed Tomography Data Research Articles

Quantitative assessment of adaptive radiotherapy for prostate cancer using deep learning: Bladder dose as a decision criterion.

Adaptive radiotherapy (ART) can incorporate anatomical variations in a reoptimized treatment plan for fractionated radiotherapy. An automatic solution to objectively determine whether ART should be performed immediately after the daily image acquisition is highly desirable. We investigate a quantitative criterion for whether ART should be performed in prostate cancer radiotherapy by synthesizing pseudo-CT (sCT) images and evaluating dosimetric impact on treatment planning using deep learning approaches. Planning CT (pCT) and daily cone-beam CT (CBCT) data sets of 74 patients are used to train (60 patients) and evaluate (14 patients) a cycle adversarial generative network (CycleGAN) that performs the task of synthesizing high-quality sCT from daily CBCT. Automatic delineation (AD) of the bladder is performed on the sCT using the U-net. The combination of sCT and AD allows us to perform dose calculations based on the up-to-date bladder anatomy to determine whether the original treatment plan (ori-plan) is still applicable. For positive cases that the patients' anatomical changes and the associated dose calculations warrant re-planning, we made rapid plan revisions (re-plan) based on the ori-plan. The mean absolute error within the region-of-interests (i.e., body, bladder, fat, muscle) between the sCT and pCT are 41.2, 25.1, 26.5, and 29.0HU, respectively. Taking the calculated results of pCT doses as the standard, for PTV, the gamma passing rates of sCT doses at 1mm/1%, 2mm/2% are 87.92%, 98.78%, respectively. The Dice coefficients of the AD-contours are 0.93 on pCT and 0.91 on sCT. According to the result of dose calculation, we found when the bladder volume underwent a substantial change (79.7%), the bladder dose is still within the safe limit, suggesting it is insufficient to solely use the bladder volume change as a criterion to determine whether adaptive treatment needs to be done. After AD-contours of the bladder using sCT, there are two cases whose bladder dose . For the two cases, we perform re-planning to reduce the bladder dose to , under the condition that the PTV meets the prescribed dose. We provide a dose accurate adaptive workflow for prostate cancer patients by using deep learning approaches, and implement ART that adapts to bladder dose. Of note, the specific replanning criterion for whether ART needs to be performed can adapt to different centers' choices based on their experience and daily observations.

The impact of teeth and dental restorations on gray value distribution in cone-beam computer tomography: a pilot study

PurposeTo investigate the influence of teeth and dental restorations on the facial skeleton's gray value distributions in cone-beam computed tomography (CBCT).MethodsGray value selection for the upper and lower jaw segmentation was performed in 40 patients. In total, CBCT data of 20 maxillae and 20 mandibles, ten partial edentulous and ten fully edentulous in each jaw, respectively, were evaluated using two different gray value selection procedures: manual lower threshold selection and automated lower threshold selection. Two sample t tests, linear regression models, linear mixed models, and Pearson's correlation coefficients were computed to evaluate the influence of teeth, dental restorations, and threshold selection procedures on gray value distributions.ResultsManual threshold selection resulted in significantly different gray values in the fully and partially edentulous mandible. (p = 0.015, difference 123). In automated threshold selection, only tendencies to different gray values in fully edentulous compared to partially edentulous jaws were observed (difference: 58–75). Significantly different gray values were evaluated for threshold selection approaches, independent of the dental situation of the analyzed jaw. No significant correlation between the number of teeth and gray values was assessed, but a trend towards higher gray values in patients with more teeth was noted.ConclusionsStandard gray values derived from CT imaging do not apply for threshold-based bone segmentation in CBCT. Teeth influence gray values and segmentation results. Inaccurate bone segmentation may result in ill-fitting surgical guides produced on CBCT data and misinterpreting bone density, which is crucial for selecting surgical protocols.Graphical Created with BioRender.com

Pattern of microimplant displacement during maxillary skeletal expander treatment: A cone-beam computed tomography study.

To analyze the microimplant (MI) displacement pattern on treatment with a maxillary skeletal expander (MSE) using cone-beam computed tomography (CBCT). Thirty-nine participants (12 males and 27 females; mean age, 18.2 ± 4.2 years) were treated successfully with the MSE II appliance. Their pre- and post-expansion CBCT data were superimposed. The pre- and post-expansion anterior and posterior inter-MI angles, neck and apical inter-MI distance, plate angle, palatal bone thickness at the MI positions, and suture opening at the MI positions were measured and compared. The jackscrew plate was slightly bent in both anterior and posterior areas. There was no significant difference in the extent of suture opening between the anterior and posterior MIs (p > 0.05). The posterior MI to hemiplate line was greater than that anteriorly (p < 0.05). The apical distance between the posterior MIs was greater than that anteriorly (p < 0.05). The palatal thickness at the anterior MIs was significantly greater than that posteriorly (p > 0.01). In the coronal plane, the angulation between the anterior MIs in relation to the jackscrew plate was greater than that between the posterior MIs owing to the differential palatal bone thickness.

CTA-UNet: CNN-transformer architecture UNet for dental CBCT images segmentation

In view of the limitations of current deep learning models in segmenting dental cone-beam computed tomography (CBCT) images, specifically dealing with complex root morphological features, fuzzy boundaries between tooth roots and alveolar bone, and the need for costly annotation of dental CBCT images. We collected dental CBCT data from 200 patients and annotated 45 of them for network training, and proposed a CNN-Transformer Architecture UNet network, which combines the advantages of CNN and Transformer. The CNN component effectively extracts local features, while the Transformer captures long-range dependencies. Multiple spatial attention modules were included to enhance the network’s ability to extract and represent spatial information. Additionally, we introduced a novel Masked image modeling method to pre-train the CNN and Transformer modules simultaneously, mitigating limitations due to a smaller amount of labeled training data. Experimental results demonstrate that the proposed method achieved superior performance (DSC of 87.12%, IoU of 78.90%, HD95 of 0.525 mm, ASSD of 0.199 mm), and provides a more efficient and effective approach to automatically and accurately segment dental CBCT images, has real-world applicability in orthodontics and dental implants.

Clinical Outcome and Predictors of Endodontic Microsurgery Using Cone-beam Computed Tomography: A Retrospective Cohort Study

IntroductionThe aim of this retrospective cohort study was to evaluate the clinical outcomes and identify the prognostic factors of endodontic microsurgery based on cone-beam computed tomographic (CBCT) scans. MethodsPatients who underwent endodontic microsurgery in teeth with asymptomatic apical periodontitis were included. The clinical outcomes were determined based on clinical and radiographic examinations after surgery 12–48 months. Radiographic healing was assessed on CBCT images by using the modified PENN 3-dimensional criteria and classified into 4 categories: complete, limited, uncertain, and unsatisfactory healing. Multivariate logistic regression was performed to detect outcome risk factors. ResultsOf the 204 teeth in 173 invited patients, 148 teeth of 126 patients were examined at review. On CBCT images, 88 teeth (59.5%) showed complete healing, and 42 (28.4%) teeth showed limited healing. All these 130 teeth were asymptomatic and achieved a clinical success rate of 87.8%. Uncertain healing was observed in 9 teeth, one of which was symptomatic. The remaining 9 teeth were unsatisfactory healing on CBCT scans, including 6 teeth with clinical symptoms and 3 free. Lesion type and root-end filling quality were significant outcome predictors (P < .05). The risk of treatment failure for teeth with combined endodontic-periodontal lesions was 8.6 times higher than that for teeth with isolated endodontic lesions. Adequate root-end filling quality improved the probability of success by 5.3 times. ConclusionsBased on CBCT data, an adequate performed endodontic microsurgery could have predictable success in teeth without periodontal involvement.

Accuracy of Intra-Oral Radiography and Cone Beam Computed Tomography in the Diagnosis of Buccal Bone Loss.

The use of cone beam computed tomography (CBCT) in dentistry started in the maxillofacial field, where it was used for complex and comprehensive treatment planning. Due to the use of reduced radiation dose compared to a computed tomography (CT) scan, CBCT has become a frequently used diagnostic tool in dental practice. However, published data on the accuracy of CBCT in the diagnosis of buccal bone level is lacking. The aim of this study was to compare the accuracy of intra-oral radiography (IOR) and CBCT in the diagnosis of the extent of buccal bone loss. A dry skull was used to create a buccal bone defect at the most coronal level of a first premolar; the defect was enlarged apically in steps of 1 mm. After each step, IOR and CBCT were taken. Based on the CBCT data, two observers jointly selected three axial slices at different levels of the buccal bone, as well as one transverse slice. Six dentists participated in the radiographic observations. First, all observers received the 10 intra-oral radiographs, and each observer was asked to rank the intra-oral radiographs on the extent of the buccal bone defect. Afterwards, the procedure was repeated with the CBCT scans based on a combination of axial and transverse information. For the second part of the study, each observer was asked to evaluate the axial and transverse CBCT slices on the presence or absence of a buccal bone defect. The percentage of buccal bone defect progression rankings that were within 1 of the true rank was 32% for IOR and 42% for CBCT. On average, kappa values increased by 0.384 for CBCT compared to intra-oral radiography. The overall sensitivity and specificity of CBCT in the diagnosis of the presence or absence of a buccal bone defect was 0.89 and 0.85, respectively. The average area under the curve (AUC) of the receiver operating curve (ROC) was 0.892 for all observers. When CBCT images are available for justified indications, other than bone level assessment, such 3D images are more accurate and thus preferred to 2D images to assess periodontal buccal bone. For other clinical applications, intra-oral radiography remains the standard method for radiographic evaluation.

CBCT Segmentation and Additive Manufacturing for the Management of Root Canals with Ledges: A Case Report and Technique

Cone-beam computed tomography (CBCT) assessment of a ledge could be useful to a clinician; however, using this information effectively during a treatment procedure can be challenging. Advanced additive manufacturing technologies combined with semi-automated segmentation of root canals can help simulate the ledge and help in management of these iatrogenic complications.A patient presented after unsuccessful root canal treatment with a ledge on the left mandibular first molar. A CBCT was taken, and the images imported into a segmentation software (Mimics, Materialise). The canal was isolated, and segmentation performed along with the other structures of the tooth. A 3-dimensional digital model of the internal structures of the canal were used to design a mock-up which was additively manufactured. This was used as a preclinical guide to simulate the procedure, precurve the file, and manage the canal. This novel technique using virtual modeling from CBCT data post ledge formation allowed for successful and quick management of a tooth with ledges.

Deep Learning Models for Automatic Upper Airway Segmentation and Minimum Cross-Sectional Area Localisation in Two-Dimensional Images.

To develop and validate convolutional neural network algorithms for automatic upper airway segmentation and minimum cross-sectional area (CSAmin) localisation in two-dimensional (2D) radiographic airway images. Two hundred and one 2D airway images acquired using cone-beam computed tomography (CBCT) scanning were randomly assigned to a test group (n = 161) to train artificial intelligence (AI) models and a validation group (n = 40) to evaluate the accuracy of AI processing. Four AI models, UNet18, UNet36, DeepLab50 and DeepLab101, were trained to automatically segment the upper airway 2D images in the test group. Precision, recall, Intersection over Union, the dice similarity coefficient and size difference were used to evaluate the performance of the AI-driven segmentation models. The CSAmin height in each image was manually determined using three-dimensional CBCT data. The nonlinear mathematical morphology technique was used to calculate the CSAmin level. Height errors were assessed to evaluate the CSAmin localisation accuracy in the validation group. The time consumed for airway segmentation and CSAmin localisation was compared between manual and AI processing methods. The precision of all four segmentation models exceeded 90.0%. No significant differences were found in the accuracy of any AI models. The consistency of CSAmin localisation in specific segments between manual and AI processing was 0.944. AI processing was much more efficient than manual processing in terms of airway segmentation and CSAmin localisation. We successfully developed and validated a fully automatic AI-driven system for upper airway segmentation and CSAmin localisation using 2D radiographic airway images.

Optimization of CBCT data with image processing methods and production with fused deposition modeling 3D printing.

The present study has investigated the effect of the removal of artifacts in cone beam computed tomography (CBCT) images with image processing techniques to dental implant planning. The aim of this study has been to benefit from the novel image processing techniques and additive manufacturing technologies in order to change the existing approach in the usage of the 3D model in the orthogonal surgery, traumatic cases, and tumor operations and to solve the restrictions in surgical operations. In the study, firstly, 3 × 3, 5 × 5, and 7 × 7 kernel values were determined on the CBCT image data of the patient. The determined kernel values were applied on CBCT images by choosing median, median-mean-Gaussian (MMG), and bilateral filters, which are quite successful in removing noise in medical images. A thresholding process to separate teeth and bones from soft tissue regions on CBCT images, histogram normalization for a balanced color distribution, morphology operations to reduce noise areas, and tooth and bone boundaries were determined as closely as possible to patient anatomy. The original image and the images obtained from image enhancement techniques were compared. Results showed that the 3 × 3 median filtering method from three different kernel values out of three different image processing methods used in the study greatly improved the artifacts. It has also been shown that the availability of image processing and additive manufacturing methods on CBCT images has been shown to be a highly important factor before dental surgery planning.

Generating missing patient anatomy from partially acquired cone-beam computed tomography images using deep learning: a proof of concept

The patient setup technique currently in practice in most radiotherapy departments utilises on-couch cone-beam computed tomography (CBCT) imaging. Patients are positioned on the treatment couch using visual markers, followed by fine adjustments to the treatment couch position depending on the shift observed between the computed tomography (CT) image acquired for treatment planning and the CBCT image acquired immediately before commencing treatment. The field of view of CBCT images is limited to the size of the kV imager which leads to the acquisition of partial CBCT scans for lateralised tumors. The cone-beam geometry results in high amounts of streaking artifacts and in conjunction with limited anatomical information reduces the registration accuracy between planning CT and the CBCT image. This study proposes a methodology that can improve radiotherapy patient setup CBCT images by removing streaking artifacts and generating the missing patient anatomy with patient-specific precision. This research was split into two separate studies. In Study A, synthetic CBCT (sCBCT) data was created and used to train two machine learning models, one for removing streaking artifacts and the other for generating the missing patient anatomy. In Study B, planning CT and on-couch CBCT data from several patients was used to train a base model, from which a transfer of learning was performed using imagery from a single patient, producing a patient-specific model. The models developed for Study A performed well at removing streaking artifacts and generating the missing anatomy. The outputs yielded in Study B show that the model understands the individual patient and can generate the missing anatomy from partial CBCT datasets. The outputs generated demonstrate that there is utility in the proposed methodology which could improve the patient setup and ultimately lead to improving overall treatment quality.

Image Quality Improvement in Sparse-View X-Ray Phase-Contrast Trimodal CBCT With Multifrequency Fringe Modulation and Iterative Methods

X-ray grating interferometer can simultaneously retrieve attenuation, refraction and scattering signals of the imaged sample, which shows its great potential in biomedical imaging. However, fast scan of gratings and high centrifugal forces during rotating in X-ray grating-based cone-beam computed tomography (CBCT) system may lead to phase-stepping errors and grating position fluctuations, which cause reconstruction failure with phase-stepping (PS) method. Whats more, the reconstructed slices usually suffer from severe artifacts under low dose conditions. Herein, we propose a multi-frequency model to simulate the mechanical instability of the system and put forward novel iterative image reconstruction methods named MFM-TLI and MLEM-FISTA-TV to improve image quality in sparse-view trimodal CBCT. Results reveal that the model and MFM-TLI is effective to retrieve high quality absorption, differential phase contrast (DPC) and dark-field (DF) signals under mechanical instability, significantly outperforming the PS method. Image quality reconstructed by MLEM-FISTA-TV is improved compared to other iterative and analytical algorithms with sparse-view data. To the best of our knowledge, this is the first time multi-frequency method is applied in X-ray grating interferometer and iterative MLEM-TV algorithm is evaluated on experimental sparse-view dark-field CBCT data. This work might provide support for future trimodal CBCT reconstruction.

Three-dimensional finite element study on the effects of maxillary anterior two-step retraction and en-masse retraction with clear aligners

Objective: To investigate the effects of two-step retraction and en-masse retraction on tooth movement pattern of anterior teeth and posterior anchorage with clear aligners using three-dimensional finite element analysis. Methods: A finite element model of maxillary first premolar extraction case undergoing clear aligner treatment was established based on maxillofacial cone-beam CT data of a 24-year-old adult male with individual normal occlusion, who visited Department of Oral Surgery, Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine for impacted mandibular third molar in June, 2022. The initial tooth displacement of five anterior retraction protocols (two-step with canine retraction, two-step with incisor bodily retraction, two-step with incisor retraction-overtreatment, en-masse bodily retraction, and en-masse retraction-overtreatment) were evaluated. Results: Two step with canine retraction caused distal tipping of the canine and labial tipping of the incisors (0.18° for central incisor and 0.13° for lateral incisor). Two step with incisor retraction caused mesial tipping of the canine. In two step with bodily retraction protocol, uncontrolled lingual tipping was found in central incisor (0.29°) and lateral incisor (0.32°). In two-step with incisor retraction-overtreatment protocol, the movement pattern of the incisors didn't change, but the inclinations reduced to 0.21° and 0.18°. En-masse retraction caused distal tipping of the canine. In en-masse bodily retraction protocol, uncontrolled lingual tipping was also found in central incisor (0.19°) and lateral incisor (0.27°). In en-masse retraction-overtreatment protocol, the central incisor showed controlled lingual tipping (0.02°) and the lateral incisor showed palatal root movement (0.03° labial inclination). Posterior teeth exhibited mesial tipping in all five protocols. Conclusion: En-masse retraction with incisor overtreatment was beneficial to incisor torque control in clear aligner treatment.

Immediate implant placement in single mandibular molar with chronic periapical periodontitis

IntroductionThe present study aims to assess and compare the clinical outcomes of immediate implant placement in the mandibular molar region with or without the presence of chronic periapical periodontitis. Materials and methodsEmploying a case-control design, this study encompassed a cohort of patients necessitating implant surgery to supplant a single, failed mandibular molar. Participants exhibiting periapical lesions measuring between > 4 mm and < 8 mm were assigned to the test group, while those without periapical lesions to the control group. Subsequent to flap surgery and tooth extraction, extraction sockets were debrided thoroughly, and implants were immediately implanted (baseline). Permanent restorative procedures were carried out three months post-operation, with follow-up conducted one year post-surgery. During the study period, parameters including implant survival rate, Cone Beam Computer Tomography (CBCT) data, implant stability quotient (ISQ), insertional torque values (ITV), and potential complications were closely monitored. ResultsThroughout the yearlong observation period subsequent to implant placement, both groups exhibited a 100% implant survival rate. None of the participants experienced any complications. Both groups demonstrated significant decreases in the height and width of the alveolar bone (P < 0.05). However, there were no statistically discernible differences between corresponding areas in the two groups (P > 0.05). The differences in ITV between the test group (37.94 ± 2.12 N•cm) and the control group (38.55 ± 2.71 N•cm) were not statistically significant at baseline (P > 0.05). A significant rise in ISQ was noted within the same group between baseline and three months post-operation (P < 0.05), while no significant variations in ISQ changes were noted between the two groups (P > 0.05). ConclusionGiven the constraints of this investigation, the preliminary clinical outcomes of immediate implant placement in the mandibular molar region with chronic periapical periodontitis do not significantly differ from those observed in instances devoid of chronic periapical periodontitis.

Accuracy of Microimplant Placement Using a 3D Guide Plate for Orthodontic Anchorage.

This study aimed to design a three-dimensional (3D) guide plate using computer-aided design and a 3D printing system for precise implantation of microimplants for orthodontic treatment and investigate the accuracy and feasibility of a 3D guide plate in clinical practice. A total of 30 microimplants were placed in 15 patients in the Department of Stomatology, Affiliated Hospital of Jiangnan University. Before surgery, DICOM data from cone-beam computed tomography (CBCT) scans and STereoLithography data from the 3D model scan were imported to 3Shape Dental System. Data fitting and matching were performed, and 3D guide plates were designed primarily focusing on the thickness of guide plates, amount of concave compensation, and dimensions of the ring. Assist implantation method was used to place the microimplants, and postoperative CBCT images were used to evaluate the position and implantation angle. The feasibility of placing microimplants and precise implantation guided by the 3D guide plate. CBCT data before and after the placement of microimplants were compared. Regarding the secure positioning of microimplants based on CBCT data, 26 implants were categorized as Grade i, four as Grade ii, and none as Grade iii. No loosening of microimplants 1 and 3 months after surgery was reported. The implantation of microimplants is more accurate under the guidance of a 3D guide plate. This technology can achieve accurate implant positioning, thus ensuring safety, stability, and improved success rates after implantation.

Nonlinear ill-posed problem in low-dose dental cone-beam computed tomography

Abstract This paper describes the mathematical structure of the ill-posed nonlinear inverse problem of low-dose dental cone-beam computed tomography (CBCT) and explains the advantages of a deep learning-based approach to the reconstruction of computed tomography images over conventional regularization methods. This paper explains the underlying reasons why dental CBCT is more ill-posed than standard computed tomography. Despite this severe ill-posedness, the demand for dental CBCT systems is rapidly growing because of their cost competitiveness and low radiation dose. We then describe the limitations of existing methods in the accurate restoration of the morphological structures of teeth using dental CBCT data severely damaged by metal implants. We further discuss the usefulness of panoramic images generated from CBCT data for accurate tooth segmentation. We also discuss the possibility of utilizing radiation-free intra-oral scan data as prior information in CBCT image reconstruction to compensate for the damage to data caused by metal implants.

Differences in positions of cone-beam computed tomography landmarks in patients with skeletal Class III facial asymmetry according to midsagittal planes.

This study aimed to clarify differences in the positions of cone-beam computed tomography (CBCT) landmarks according to different midsagittal planes (MSPs) in patients with skeletal Class III facial asymmetry. Pre-treatment CBCT data from 60 patients with skeletal Class III were used. The patients were classified into symmetric (menton deviations of < 2 mm) or asymmetric (menton deviations of > 4 mm) groups. Six MSPs were established based on previous studies, and three-dimensional analyses were performed for the planes in both the groups. The measurement outcomes were compared statistically. A statistically significant interaction (p < 0.01) was observed between MSPs and facial asymmetry. No significant differences were observed among MSPs in the symmetric group. However, significant differences in linear measurements were identified among MSPs in the asymmetric group. Specifically, the upper facial MSP revealed both maxillary and mandibular transverse asymmetries. On the other hand, anterior nasal spine (ANS)-associated MSP could not identify maxillary asymmetry. Furthermore, the menton deviation was approximately 3 mm lower when estimated using the ANS-associated MSP than that using upper facial MSP. The choice of MSP can significantly affect treatment outcomes while diagnosing patients with asymmetry. Therefore, care should be taken when selecting MSP in clinical practice.

A study of transverse maxillomandibular discrepancy and dental compensation in early mixed dentition with skeletal Class III malocclusion without posterior crossbite.

To evaluate transverse maxillomandibular discrepancy and dental compensation in first molar areas in 7- to 9-year-old children with skeletal Class III malocclusion without posterior crossbite using cone-beam computed tomography (CBCT). The sample of this retrospective study consisted of 60 children (7 to 9 years old), who were divided into the skeletal Class III malocclusion group (study group, skeletal Class III malocclusion without posterior crossbite, N = 31) and the Class I occlusion group (control group, Class I occlusion with one or two impacted teeth, N = 30). CBCT data were obtained from the database of the Department of Radiology of Hospital of Stomatology, Shandong University. For three-dimensional reconstruction of the head, the dental arch width, basal bone width, and buccolingual inclination angle were measured using MIMICS 21.0 software. Independent-sample t tests were used to compare the two groups. The mean age of the children was 8.18±0.83years. The width of the maxillary basal bone was significantly smaller in the skeletal Class III malocclusion group (59.75 ± 3.14 mm) than in the Class I occlusion group (62.39 ± 3.01 mm) (P < 0.01). The mandibular basal bone width was significantly larger in the skeletal Class III malocclusion group (60.00 ± 2.56 mm) than in the Class I occlusion group (58.19 ± 2.42 mm) (P < 0.01). The difference in the width of the maxillary and mandibular bases in the skeletal Class III malocclusion group (-0.25 ± 1.73 mm) was significantly different from that in the Class I occlusion group (4.20 ± 1.25 mm) (P < 0.01). However, there was no significant difference in the upper or lower dental arch width between the two groups (P > 0.05). The buccal inclination of the maxillary molars in the skeletal Class III malocclusion group (31.4° ± 8.9°) was significantly higher than that in the Class I occlusion group (17.64° ± 7.3°) (P < 0.01), as was the lingual inclination angle of mandibular molars (45.24° ± 8.3° vs. 37.96° ± 10.18°; P < 0.01). Transverse maxillary and mandibular discrepancies in the posterior area and transverse dental compensation were found in the early mixed dentition of patients with skeletal Class III malocclusion without posterior crossbite. This suggests that even in the absence of posterior crossbite, maxillary expansion can be attempted to correct the maxillomandibular transverse discrepancy.

Feasibility of mini-implant insertion between mesial and distal buccal roots of a maxillary first molar: A cone-beam computed tomography imaging study

Mini-implant insertion in the maxillary posterior region can be influenced by anatomic limitations, thus increasing the failure rate. We explored the feasibility of a new implantation site: the region between the mesial and distal buccal roots of the maxillary first molar. Cone-beam computed tomography data from 177 patients were collected from a database. The maxillary first molars were morphologically classified by analyzing the angle and morphology of the mesial and distal buccal roots. Next, 77 subjects were randomly selected from the 177 patients to measure and analyze the hard-tissue morphology in the maxillary posterior region. We devised the Morphological Classification on the Mesial and Distal Buccal Roots of Maxillary First Molar (MCBRMM), divided into 3 types: MCBRMM-I, II, and III. In all subjects, MCBRMM-I, II, and III accounted for 43%, 25%, and 32%, respectively. At 8 mm from the mesial cementoenamel junction of maxillary first molars, the interradicular distance between the maxillary first molar's mesiodistal buccal roots of MCBRMM-I was 2.6 mm, showing an upward trend from the cementoenamel junction to the apex. The distance from the buccal bone cortex to the palatal root was>9 mm. The buccal cortical thickness was>1 mm. This study provided a potential site for mini-implant insertion in the maxillary posterior region: the alveolar bone of maxillary first molars in MCBRMM-I.

MCR toolkit: A GPU-based toolkit for multi-channel reconstruction of preclinical and clinical x-ray CT data.

The advancement of x-ray CT into the domains of photon counting spectral imaging and dynamic cardiac and perfusion imaging has created many new challenges and opportunities for clinicians and researchers. To address challenges such as dose constraints and scanning times while capitalizing on opportunities such as multi-contrast imaging and low-dose coronary angiography, these multi-channel imaging applications require a new generation of CT reconstruction tools. These new tools should exploit the relationships between imaging channels during reconstruction to set new image quality standards while serving as a platform for direct translation between the preclinical and clinical domains. We outline and demonstrate a new Multi-Channel Reconstruction (MCR) Toolkit for GPU-based analytical and iterative reconstruction of preclinical and clinical multi-energy and dynamic x-ray CT data. To promote open science, open-source distribution of the Toolkit will coincide with the release of this publication (GPL v3; gitlab.oit.duke.edu/dpc18/mcr-toolkit-public). The MCR Toolkit source code is implemented in C/C++ and NVIDIA's CUDA GPU programming interface, with scripting support from MATLAB and Python. The Toolkit implements matched, separable footprint CT reconstruction operators for projection and backprojection in two geometries: planar, cone-beam CT (CBCT) and 3rd generation, cylindrical multi-detector row CT (MDCT). Analytical reconstruction is performed using filtered backprojection (FBP) for circular CBCT, weighted FBP (WFBP) for helical CBCT, and cone-parallel projection rebinning followed by WFBP for MDCT. Arbitrary combinations of energy and temporal channels are iteratively reconstructed under a generalized multi-channel signal model for joint reconstruction. We solve this generalized model algebraically using the split Bregman optimization method and the BiCGSTAB(l) linear solver interchangeably for both CBCT and MDCT data. Rank-sparse kernel regression (RSKR) and patch-based singular value thresholding (pSVT) are used to regularize the energy and time dimensions, respectively. Under a Gaussian noise model, regularization parameters are estimated automatically from the input data, dramatically reducing algorithm complexity for end users. Multi-GPU parallelization of the reconstruction operators is supported to manage reconstruction times. Denoising with RSKR and pSVT and post-reconstruction material decomposition are illustrated with preclinical and clinical cardiac photon-counting (PC)CT data. A digital MOBY mouse phantom with cardiac motion is used to illustrate single energy (SE), multi-energy (ME), time resolved (TR), and combined multi-energy and time-resolved (METR) helical, CBCT reconstruction. A fixed set of projection data is used across all reconstruction cases to demonstrate the Toolkit's robustness to increasing data dimensionality. Identical reconstruction code is applied to in vivo cardiac PCCT data acquired in a mouse model of atherosclerosis (METR). Clinical cardiac CT reconstruction is illustrated using the XCAT phantom and the DukeSim CT simulator, while dual-source, dual-energy CT reconstruction is illustrated for data acquired with a Siemens Flash scanner. Benchmarking results with NVIDIA RTX 8000 GPU hardware demonstrate 61%-99% efficiency in scaling computation from one to four GPUs for these reconstruction problems. The MCR Toolkit provides a robust solution for temporal and spectral x-ray CT reconstruction problems and was built from the ground up to facilitate translation of CT research and development between preclinical and clinical applications.

Ectopic teeth in the maxillary sinus

Dental ectopia is a rare developing anomaly characterized by a change in the normal eruption pathway of a deciduous, permanent or supernumerary tooth. In some cases, ectopic teeth are present in the non-dentate area like maxillary sinus. The article presents cone beam computed tomography data of 7 asymptomatic patients with teeth totally or partially located inside the maxillary sinus. Dentigerous cysts and odontomas can cause displacement of impacted teeth into ectopic positions.