3D Cone-beam Computed Tomography Research Articles

Quantification of facial symmetry in orthognathic surgery: A novel approach integrating 3D contour maps and hyper-dimensional computing

This study aimed to enhance the evaluation of facial symmetry crucial for planning and assessing outcomes of orthognathic surgery (OGS). An innovative approach combining three-dimensional (3D) facial contour lines with hyperdimensional (HD) computing was developed for this purpose. Data were collected using 3D cone beam computed tomography (CBCT) at Chang Gung Memorial Hospital from 2016 to 2021. A comprehensive dataset was compiled, including images from 150 normal individuals and 2500 patients, totaling 5150 preoperative and postoperative facial images. A machine learning model was trained to analyze these images, and 3D contour data were used to create a facial symmetry quantification system with HD computing. Additionally, 3D CBCT data from 200 patients before and after OGS were retrospectively reviewed for clinical application. The developed facial symmetry algorithm demonstrated an overall accuracy of 84.1 %. Postoperative facial symmetry scores improved significantly, with a mean score increase of 53 %, from 2.40 to 3.63. The study culminated in the creation of a web-based system that leverages HD computing and 3D contour mapping to automate facial symmetry assessment. This system offers a user-friendly interface for rapid and accurate evaluations, facilitating better communication between clinicians and patients.

Geometry-Aware Attenuation Learning for Sparse-View CBCT Reconstruction.

Cone Beam Computed Tomography (CBCT) plays a vital role in clinical imaging. Traditional methods typically require hundreds of 2D X-ray projections to reconstruct a high-quality 3D CBCT image, leading to considerable radiation exposure. This has led to a growing interest in sparse-view CBCT reconstruction to reduce radiation doses. While recent advances, including deep learning and neural rendering algorithms, have made strides in this area, these methods either produce unsatisfactory results or suffer from time inefficiency of individual optimization. In this paper, we introduce a novel geometry-aware encoder-decoder framework to solve this problem. Our framework starts by encoding multi-view 2D features from various 2D X-ray projections with a 2D CNN encoder. Leveraging the geometry of CBCT scanning, it then back-projects the multi-view 2D features into the 3D space to formulate a comprehensive volumetric feature map, followed by a 3D CNN decoder to recover 3D CBCT image. Importantly, our approach respects the geometric relationship between 3D CBCT image and its 2D X-ray projections during feature back projection stage, and enjoys the prior knowledge learned from the data population. This ensures its adaptability in dealing with extremely sparse view inputs without individual training, such as scenarios with only 5 or 10 X-ray projections. Extensive evaluations on two simulated datasets and one real-world dataset demonstrate exceptional reconstruction quality and time efficiency of our method.

A Study on the Nasal Index of Malocclusion Patients Using Cone-Beam Computed Tomography 3D Program

A Study on the Nasal Index of Malocclusion Patients Using Cone-Beam Computed Tomography 3D Program

Effective and efficient coded aperture cone-beam computed tomography via generative adversarial U-Net

Coded aperture cone-beam computed tomography (CBCT) represents a crucial method for acquiring high-fidelity three-dimensional (3D) tomographic images while reducing radiation exposure. However, projections are non-uniformly and discontinuously sampled with the coded apertures placed in front of the x-ray source, leading to very small reconstruction scale and time-intensive iterations. In this study, an alternative approach to reconstruct coded aperture CBCT based on generative adversarial U-net is proposed to effectively and efficiently reconstruct large scale 3D CBCT images. Our method entails predicting complete and uniform projections from incomplete and non-uniform coded projections, enabling the requirement of continuity for the use of analytical algorithms in 3D image reconstruction. This novel technique effectively mitigates the traditional trade-off between image fidelity and computational complexity inherent in conventional coded aperture CBCT reconstruction methods. Our experimental results, conducted using clinical datasets comprising CBCT images from 102 patients at Nanjing Medical University, demonstrate that high-quality CBCT images with voxel dimensions of 400 × 400 × 400 can be reconstructed within 35 s, even when 95% of projections are blocked, yielding images with PSNR values exceeding 25dB and SSIM values surpassing 0.85.

Assessing masseter muscle volume and activity in relation to craniofacial morphology: a 3D CBCT study.

Understanding the factors influencing craniofacial structure growth is crucial for addressing craniofacial deformities. This study evaluates masseter muscle volume, activity, and maximum bite force across different skeletal malocclusion groups and aims to evaluate the masseter muscle volume, activity, and maximum bite force (BF) according to different skeletal malocclusion groups. This study aimed to assess masseter muscle volume, activity, and maximum bite force (BF) across different skeletal malocclusion groups in 60 young adults (18-30 years) seeking treatment at Kirikkale University Faculty of Dentistry. Cone-Beam Computed Tomography (CBCT) imaging, radiological measurements, surface electromyography (sEMG), and force sensor measurements were employed. Results revealed significant differences in sEMG measurements based on sagittal classification. Vertical direction groups showed notable results in muscle volume and BF, though no significant differences were observed in sEMG values. A correlation was identified between BF and sEMG, but no correlation was found between muscle volume and other parameters. The findings obtained in this study suggest that the significant relationship between EMG and sagittal skeletal classification could be a valuable diagnostic tool. However, concerns about reliability were raised due to uneven distribution in muscle volume and BF among vertical direction groups. The lack of significant results in muscle volume, sEMG, and BF was attributed to CBCT limitations in soft tissue imaging and the small sample size, emphasizing caution in interpreting the findings.

A review on 4D cone-beam CT (4D-CBCT) in radiation therapy: Technical advances and clinical applications.

Cone-beam CT (CBCT) is the most commonly used onboard imaging technique for target localization in radiation therapy. Conventional 3D CBCT acquires x-ray cone-beam projections at multiple angles around the patient to reconstruct 3D images of the patient in the treatment room. However, despite its wide usage, 3D CBCT is limited in imaging disease sites affected by respiratory motions or other dynamic changes within the body, as it lacks time-resolved information. To overcome this limitation, 4D-CBCT was developed to incorporate a time dimension in the imaging to account for the patient's motion during the acquisitions. For example, respiration-correlated 4D-CBCT divides the breathing cycles into different phase bins and reconstructs 3D images for each phase bin, ultimately generating a complete set of 4D images. 4D-CBCT is valuable for localizing tumors in the thoracic and abdominal regions where the localization accuracy is affected by respiratory motions. This is especially important for hypofractionated stereotactic body radiation therapy (SBRT), which delivers much higher fractional doses in fewer fractions than conventional fractionated treatments. Nonetheless, 4D-CBCT does face certain limitations, including long scanning times, high imaging doses, and compromised image quality due to the necessity of acquiring sufficient x-ray projections for each respiratory phase. In order to address these challenges, numerous methods have been developed to achieve fast, low-dose, and high-quality 4D-CBCT. This paper aims to review the technical developments surrounding 4D-CBCT comprehensively. It will explore conventional algorithms and recent deep learning-based approaches, delving into their capabilities and limitations. Additionally, the paper will discuss the potential clinical applications of 4D-CBCT and outline a future roadmap, highlighting areas for further research and development. Through this exploration, the readers will better understand 4D-CBCT's capabilities and potential to enhance radiation therapy.

Dynamic CBCT imaging using prior model-free spatiotemporal implicit neural representation (PMF-STINR)

Objective. Dynamic cone-beam computed tomography (CBCT) can capture high-spatial-resolution, time-varying images for motion monitoring, patient setup, and adaptive planning of radiotherapy. However, dynamic CBCT reconstruction is an extremely ill-posed spatiotemporal inverse problem, as each CBCT volume in the dynamic sequence is only captured by one or a few x-ray projections, due to the slow gantry rotation speed and the fast anatomical motion (e.g. breathing). Approach. We developed a machine learning-based technique, prior-model-free spatiotemporal implicit neural representation (PMF-STINR), to reconstruct dynamic CBCTs from sequentially acquired x-ray projections. PMF-STINR employs a joint image reconstruction and registration approach to address the under-sampling challenge, enabling dynamic CBCT reconstruction from singular x-ray projections. Specifically, PMF-STINR uses spatial implicit neural representations to reconstruct a reference CBCT volume, and it applies temporal INR to represent the intra-scan dynamic motion of the reference CBCT to yield dynamic CBCTs. PMF-STINR couples the temporal INR with a learning-based B-spline motion model to capture time-varying deformable motion during the reconstruction. Compared with the previous methods, the spatial INR, the temporal INR, and the B-spline model of PMF-STINR are all learned on the fly during reconstruction in a one-shot fashion, without using any patient-specific prior knowledge or motion sorting/binning. Main results. PMF-STINR was evaluated via digital phantom simulations, physical phantom measurements, and a multi-institutional patient dataset featuring various imaging protocols (half-fan/full-fan, full sampling/sparse sampling, different energy and mAs settings, etc). The results showed that the one-shot learning-based PMF-STINR can accurately and robustly reconstruct dynamic CBCTs and capture highly irregular motion with high temporal (∼ 0.1 s) resolution and sub-millimeter accuracy. Significance. PMF-STINR can reconstruct dynamic CBCTs and solve the intra-scan motion from conventional 3D CBCT scans without using any prior anatomical/motion model or motion sorting/binning. It can be a promising tool for motion management by offering richer motion information than traditional 4D-CBCTs.

Comparison of 3D Easy Box cone-beam computed tomography analysis with 2D Modified Easy Box on OPG as a prognostic tool for impacted maxillary canines: A pilot study.

To assess and compare the validity of 2D modified Easy Box and measurement of the Beta angle on standard conventional orthopantomogram (OPG) versus 3D cone-beam computed tomography (CBCT) OPG-constructed view. A retrospective agreement study. The aim of this study was to construct an Easy Box on a standard conventional OPG and to validate this novel method by comparing it with the Easy Box method on 3D CBCT. After approval from the Ethics Committee, OPG and CBCT radiographs were obtained for the study from departmental records and five private practices in the same location (Indore, India). The radiographs were selected based on record availability and with written consent from the participants before the commencement of the study. The records were analysed to enable a comparison and to assess the accuracy of Easy Box construction on both 3D CBCT and standard conventional OPG radiographs. The location of the impacted canine within the Easy Box boundaries and the measurement of the Beta angle were determined on both views. A perfect agreement was obtained for the comparison of 3D Easy Box CBCT analysis with 2D modified Easy Box on OPG for impacted maxillary canines (Kappa = 1.0). A Bland-Altman (LoA) analysis showed no proportional bias in the comparison of the Beta angle on 3D and 2D OPG radiographs. Beta angle and 2D modified Easy Box on a conventional OPG yield similar results when compared to Easy Box on 3D CBCT OPG-constructed view. The standard OPG was valuable and cost-effective, particularly in the early stages of diagnosis and treatment planning, either as a substitute or when CBCT was unavailable.

Assessing the Accuracy of Lateral Cephalogram in Quantifying Three-Dimensional Pharyngeal Airway Morphology Compared to Cone-Beam Computed Tomography.

When it comes to orthodontic diagnosis and treatment planning, the structures of the upper and lower airway spaceare crucial because of therole they play in craniofacial development. The major objective of this study was to evaluate the accuracy of lateral cephalogram in the evaluation of upper and lower pharyngeal space by comparing it to clinical usage of cone-beam computed tomography (CBCT) in quantifying the 3D morphology of the pharyngeal airway. In total, 70 patients were included in the study. They had both a CBCT scan and a lateral cephalogram performed within a week of each other. Different cephalometric landmarks have been utilized to estimate linear and area dimensions for use in lateral cephalogram airway investigations. By superimposing the lateral cephalogram measurement of the vertical height of the pharyngeal airwayover axial CBCT slices of 0.8 to 1 mm in thickness, airway volumes were calculated. For this study, we measured the pharyngeal airway space in each patient in two dimensions (2D) using the airway area from the lateral cephalogram and in three dimensions (3D) using the airway volume from the CBCT scan over the same region of interest, using a uniform scale and magnification throughout all split 3D volumes. The mean value of the area of pharyngeal space calculated by lateral cephalograph analysis (LCA) was 336.35 ± 86.49 mm2. The maximum value was 551.234 mm2. The minimum value was 206.32 mm2. The mean value of the volume of the same area calculated using CBCT was 3409.11 ± 1237.96 mm3. The maximum value was 5887.23 mm3. When the area calculated using LCA was compared with the volume calculated using CBCT, the correlation between them was significant statistically(r=0.831, p-value =0.000). The mean values of volume evaluated in 3D CBCT in males were 4198±1008 mm3 while for females it was 2980±1134.5 mm3. During the statistical analysis,these observations were found to have a positive correlation with increased volume of pharyngeal space in males as compared to that of females (p=0.006). The values of the area of pharyngeal space calculated using LCA in males was 370.1±60.9 mm2. while it was 301.9±88 mm2 in females. The area estimated for the pharyngeal airway on LCA correlates strongly with the volume determined by a CBCT scan. Since we have considered pharyngeal space analysis using CBCT to be a reliable and standard methodology, therefore a positive correlation of area calculated using LCA with volume calculated using CBCT shows that the analysis made by LCA can be reliable.

Biomedical Application of CT Assisted CBCT 3D Imaging Technology in Oral Implantation

In the field of oral implantology, our goals were to investigate the diagnostic utility of traditional CT imaging technology and 3D CBCT imaging technology based on the Internet of Things (IoT) dental Computed Tomography assisted CBCT, as well as to compare and contrast their respective advantages. 72 patients were split evenly between two groups: a control group with 35 participants and a study group with 37 participants. (1) Surgical indexes: The operation time of the control group was (27.96+4.64) minutes and (14.08+3.14) minutes, and the intraoperative blood loss was (16.36+2.95) ml and (5.85+0.64) ml, respectively. The time it took to do the procedure in the experimental group was (14.08+3.14) minutes. In the group that was under examination, both the total amount of time spent operating and the amount of blood lost during the procedure were significantly lower (P <0.05). (2) Dental function: There were no statistically significant variations in dental beauty, comfort, chewing, or retention between the two groups before surgery (P >0.05). This was determined by comparing the results of the dental examinations. After surgery, the dental function of the research group was significantly greater than that of the control group, and the difference between the two groups was statistically significant (P <0.05). (3) Theraputic effect: the effective rate of the treatment in the control group was 85.71 percent, while the effective rate in the study group was 94.59%. (4) Quality of life: when compared with the control group, the comprehensive quality of life of physiological, social, emotional, and cognitive functions in the research group was higher, and the difference was statistically significant (P < 0.05); (5) Satisfaction: the control group’s level of satisfaction was 80.00%, while the study group’s level of satisfaction was 94.59%. (6) Cost: the cost of the treatment in the research group was significantly lower than the cost of the treatment in the control group. As a result, the dental computed tomography assisted cone beam computed tomography (CBCT) 3D imaging technology based on the internet of things should be considered for implementation.

Mandibular canine development as an indicator of maxillary cleft site canine development

Objectives: The objective of this study was to determine if mandibular canine development is an indicator of maxillary cleft site canine development. Material and Methods: A cross-sectional chart review with analysis of cone-beam computed tomography (CBCT) imaging of patients aged 7–12 with a unilateral complete cleft lip and palate who received alveolar bone graft surgery from January 2009 to January 2019. Three-dimensional (3D) measurements of the cleft site canine and ipsilateral mandibular canine were taken. A two-dimensional image was created from the 3D CBCT to simulate a traditional panoramic radiograph. Descriptive statistics and multivariable linear regression analyses were conducted, adjusting for age and gender. Pearson and Spearman correlations were calculated. The main outcome measure was the mandibular canine crown-to-root ratio (C:RR) compared to that of the maxillary cleft site canine C:RR. Results: Five hundred and thirteen patients were reviewed, of which 78 met the inclusion criteria. Adjusting for age and gender, every unit change in mandibular canine C:RR corresponds to 0.69 (95% confidence interval [CI] = 0.42–0.95) change in maxillary canine C:RR, up to a mandibular canine C:RR of 3. Beyond a mandibular C:RR of 3, no change in the maxillary canine C:RR was observed (−0.02; 95%CI = −0.27–0.24). Pearson correlation coefficient was r = 0.65, and the Spearman correlation was P = 0.75. Conclusion: Mandibular canine C:RR is correlated to maxillary cleft site canine C:RR when the mandibular canine C:RR is ≤3.

DPI-MoCo: Deep Prior Image Constrained Motion Compensation Reconstruction for 4D CBCT.

4D cone-beam computed tomography (CBCT) plays a critical role in adaptive radiation therapy for lung cancer. However, extremely sparse sampling projection data will cause severe streak artifacts in 4D CBCT images. Existing deep learning (DL) methods heavily rely on large labeled training datasets which are difficult to obtain in practical scenarios. Restricted by this dilemma, DL models often struggle with simultaneously retaining dynamic motions, removing streak degradations, and recovering fine details. To address the above challenging problem, we introduce a Deep Prior Image Constrained Motion Compensation framework (DPI-MoCo) that decouples the 4D CBCT reconstruction into two sub-tasks including coarse image restoration and structural detail fine-tuning. In the first stage, the proposed DPI-MoCo combines the prior image guidance, generative adversarial network, and contrastive learning to globally suppress the artifacts while maintaining the respiratory movements. After that, to further enhance the local anatomical structures, the motion estimation and compensation technique is adopted. Notably, our framework is performed without the need for paired datasets, ensuring practicality in clinical cases. In the Monte Carlo simulation dataset, the DPI-MoCo achieves competitive quantitative performance compared to the state-of-the-art (SOTA) methods. Furthermore, we test DPI-MoCo in clinical lung cancer datasets, and experiments validate that DPI-MoCo not only restores small anatomical structures and lesions but also preserves motion information.

Morphometric Assessment of Condyle and Glenoid Fossa using Cone Beam Computed Tomography in Gujarati Population: A Cross-sectional Study

Introduction: Several morphological alterations and remodelling occur in the mandibular condyle and glenoid fossa to adapt to trauma, malocclusion and other developmental disorders. Understanding these changes will aid healthcare providers in comprehending the pathophysiology of various Temporomandibular Joint (TMJ) problems. Aim: To evaluate the morphometric attributes of the condyle and glenoid fossa in the Gujarati population using Cone Beam Computed Tomography (CBCT). Materials and Methods: This cross-sectional radiographic morphometric investigation was conducted at the Department of Oral Medicine and Radiology at the College of Dental Sciences and Research Centre in Bopal, Gujarat, India using departmental archives from September 2019 to September 2022. A total of 40 CBCT scans (80 TMJs) were performed and analysed using the Papaya 3D and Genoray CBCT machines, along with Triana imaging software. Measurements were taken for condylar length, width, height, joint space (anterior, superior, posterior, medial, lateral) and the thickness of the Roof of the Glenoid Fossa (RGF) (sagittal, coronal) on the CBCT images. The aforementioned parameters were compared between genders, age groups and sides using a paired t-test and statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS) software package (Chicago, IL, USA), version 21.0 for Microsoft (MS) Windows. Results: The mean age of the study participants was 34±9.6 years. The condylar width between males and females was the only condylar characteristic that differed significantly (p-value 0.001). Apart from the gender analysis, no statistically significant variations (p>0.05) were found in the thickness of the RGF when comparing age or side. However, in the genderwise examination of joint space, males had significantly higher measurements of Superior Joint Space (SJS), Medial Joint Space (MJS) and Lateral Joint Space (LJS) than females. Conclusion: Gujarati males had a significantly larger condylar width compared to females. When considering gender-specific data, males also exhibited greater SJSs, MJSs and LJSs, as well as increased thickness of the RGF. The results of the present study may provide a relevant and comparable reference for the clinical assessment of individuals with healthy, functional, or pathological TMJs.

Clinical validity and precision of deep learning-based cone-beam computed tomography automatic landmarking algorithm.

This study was performed to assess the clinical validity and accuracy of a deep learning-based automatic landmarking algorithm for cone-beam computed tomography (CBCT). Three-dimensional (3D) CBCT head measurements obtained through manual and automatic landmarking were compared. A total of 80 CBCT scans were divided into 3 groups: non-surgical (39 cases); surgical without hardware, namely surgical plates and mini-screws (9 cases); and surgical with hardware (32 cases). Each CBCT scan was analyzed to obtain 53 measurements, comprising 27 lengths, 21 angles, and 5 ratios, which were determined based on 65 landmarks identified using either a manual or a 3D automatic landmark detection method. In comparing measurement values derived from manual and artificial intelligence landmarking, 6 items displayed significant differences: R U6CP-L U6CP, R L3CP-L L3CP, S-N, Or_R-R U3CP, L1L to Me-GoL, and GoR-Gn/S-N (P<0.05). Of the 3 groups, the surgical scans without hardware exhibited the lowest error, reflecting the smallest difference in measurements between human- and artificial intelligence-based landmarking. The time required to identify 65 landmarks was approximately 40-60 minutes per CBCT volume when done manually, compared to 10.9 seconds for the artificial intelligence method (PC specifications: GeForce 2080Ti, 64GB RAM, and an Intel i7 CPU at 3.6 GHz). Measurements obtained with a deep learning-based CBCT automatic landmarking algorithm were similar in accuracy to values derived from manually determined points. By decreasing the time required to calculate these measurements, the efficiency of diagnosis and treatment may be improved.

3D wrist imaging - Is it time for superman to retire?

Computed tomography (CT) of the wrist may be challenged, due to patients' inability to extend the arm for a "Superman pose" resulting in increased radiation dose due to scatter. Alternative positions and less dose administering modalities such as 3D Cone-beam CT (CBCT) and single-shot CT could be considered. This phantom study aimed to estimate scatter radiation dose in different phantom positions using helical and single-shot CT and 3D CBCT. Wireless electronic dosimeters attached to the head and chest of an anthropomorphic phantom in various clinically relevant positions were used to measure scatter radiation. In helical CT, the following positions were used: Superman pose, semi-superman pose, wrist on the abdomen, and single-shot CT with the patient sitting in front of and behind the gantry. In 3D CBCT, the phantom was in a supine position with the arm extended laterally. Helical CT using the Superman pose resulted in a total scattered radiation dose of 64.8 µGy. The highest total dose (269.7 µGy) was obtained with the wrist positioned on the abdomen while the lowest total dose was achieved in single-shot CT with the phantom sitting behind the gantry with the forearm placed inside the gantry (3.2 µGy). The total dose in 3D CBCT was 171.1 µGy. The commonly used semi-superman and wrist-on-abdomen positions in CT administer the highest scattered doses and should be avoided when either single-shot CT or 3D CBCT is available. Radiographers should carefully consider alternatives when a patient referred for wrist CT cannot comply with the Superman position.

Three-dimensional assessment of periodontal support of lower incisors for skeletal Class II malocclusion undergoing presurgical orthodontic treatment with different vertical skeletal patterns

BackgroundThe aim of the present study was to compare periodontal support changes during retraction of mandibular anterior teeth for skeletal Class II malocclusion with different facial divergence and to analyze relevant factors influencing bone remodeling by applying three-dimensional (3D) cone-beam computed tomography (CBCT) reconstruction technology.MethodsForty-eight patients with Class II malocclusion requiring surgical orthodontic treatment enrolled in the study were divided into the hyperdivergent group (n = 16), normodivergent group (n = 16) and hypodivergent group (n = 16) according to their vertical skeletal patterns. Cone-beam computed tomography (CBCT) scans were obtained before treatment (T1) and after presurgical orthodontic treatment (T2). The two-dimensional (2D) alveolar bone morphology, movement of mandibular central incisors and volume of the alveolar bone around incisors were measured on the labial and lingual sides by 3D CBCT reconstruction technology. Statistical analyses were performed with one-way ANOVA, paired t tests and multiple linear regression.ResultsDuring presurgical orthodontic treatment, the alveolar bone height on the labial side of the hyperdivergent group decreased significantly (P ≤ 0.05), but was maintained in the normodivergent and hypodivergent groups (P > 0.05). However, the alveolar bone volume, alveolar bone thickness at each level and alveolar bone height on the lingual side decreased significantly for all the groups. Apart from the initial morphometric measurements at T1, the morphology of lingual alveolar bone at T2 was significantly influenced by the direction and amount of tooth movement. Horizontal retraction and vertical protrusion of the root apex were negatively related to the alveolar bone on the lingual side after presurgical orthodontic treatment.ConclusionFor Class II malocclusion patients undergoing presurgical orthodontic treatment, the changes in the periodontal support of the lower central incisors varied in different vertical skeletal patterns. There exists a great periodontal risk of alveolar bone resorption on the lingual side for various vertical types. To avoid alveolar bone deterioration, it is essential to investigate the bone remodeling of patients with different alveolar bone conditions and cautiously plan tooth movement prior to orthodontic treatment. Moreover, 3D measurements based on CBCT construction can provide complementary information to traditional 2D measurements.

Skeletal and Dentoalveolar Changes in Growing Patients Treated with Rapid Maxillary Expansion Measured in 3D Cone-Beam Computed Tomography.

The skeletal and dental effects of rapid maxillary expansion (RME) have been extensively studied, but high-quality research is still needed to determine the three-dimensional (3D) effects of RME. The aim of this study was to compare skeletal and dentoalveolar parameters through cone-beam computed tomography (CBCT) pre- (T1) and post-treatment (T2) with respect to RME. Twenty growing patients (mean age 10.7 years) were treated with a Hyrax-type expander. A 3D CBCT was performed at T1 and T2, measuring nasal width, maxillary width, palatal height, maxillary arch perimeter, angulation of the upper first molar, and intermolar width. The mean palatal suture opening was 2.85 ± 0.62 mm (p < 0.0001). Nasal width increased 1.28 ± 0.64 mm and maxillary width 2.79 ± 1.48 mm (p < 0.0001). In contrast, palatal height was reduced 0.65 ± 0.64 mm (p < 0.0001). Regarding arch perimeter, the radicular perimeter increased 2.89 ± 1.80 mm, while the coronal perimeter increased 3.42 ± 2.09 mm (p < 0.0001). Molar angulation increased 5.62 ± 3.20° for the right molar and 4.74 ± 2.22° for the left molar (p < 0.0001). Intermolar width increased 5.21 ± 1.55 mm (p < 0.0001). Treatment with Hyrax produced a significant opening in the mean palatal suture. Also, a significant increase in nasal width, maxillary width, arch perimeter, molar angulation, and intermolar width, and a decrease in palatal height, were observed.

Orthodontic Localization of Impacted Canines: Review of the Cutting-edge Evidence in Diagnosis and Treatment Planning Based on 3D CBCT Images.

A thorough clinical and radiographical assessment of an impacted maxillary canine's location forms the basis for proper diagnosis and successful treatment outcomes. Implementing a correct biomechanical approach for directing force application primarily relies on its precise localization. Poor biomechanical planning can resorb the roots of adjacent teeth and result in poor periodontal outcomes of the canine that has been disimpacted. Furthermore, treatment success and time strongly rely on an accurate assessment of the severity of impaction, which depends on its 3D spatial location. The evolution of cone-beam computed tomography (CBCT) radiographs provides more detailed information regarding the location of the impacted canines. In addition, the literature has shown that CBCT imaging has enhanced the quality of diagnosis and treatment planning by obtaining a more precise localization of impacted canines. This review article highlights current evidence regarding comprehensive evaluation of three-dimensional orientations of impacted canines on CBCT images for precise diagnosis and treatment planning.

The role of post-dilatation in carotid MicroNet-covered stent implantation, evaluated using 3D cone-beam CT angiography.

This study aims to assess the role and safety of post-dilatation in protected carotid artery stenting (PCAS) using the new MicroNet-covered 2nd-generation stent assessed by cone beam CT scans. From March 2020 to March 2022, patients were enrolled in the study according to CT angiography results based on the following criteria: Evidence of 70% to 99% carotid stenosis in asymptomatic patients and 50% to 99% in symptomatic patients, per the NASCET index. Using a FilterWire EZ™ (Boston Scientific, Natick, MA, USA) embolic protection system (EPS), MicroNet-covered stent PCAS was performed by two interventional radiologists with at least 8 years of experience in endovascular intervention. Each patient underwent post-dilatation following stent placement. Finally, a third radiologist (not participating in the interventional procedures) evaluated the cone beam CT scans and calculated residual stenosis. Major and minor complications were recorded in the 30 days following the procedure. A total of 192 patients (121 male, mean age 73±10 years) were included in the study, and all patients received post-dilatation following stent implantation. Technical successes were achieved in all procedures. Adverse events noted in this study were limited to periprocedural transient ischemic attacks that occurred in three out of 192 patients (1.6%) and showed a swift complete recovery. The post-dilatation balloon diameters used in the study were: 5.0 mm (30.3%), 5.5 mm (39.3%) and 6 mm (30.3%). Optimized postdilatation resulted in a significant increase in the final luminal area. Similar improvements were observed in all subtypes of plaque. Post-dilatation in protected CAS is safe and induces a significant improvement in the cross-sectional area regardless of the stenotic plaque.

The preliminary in vitro study and application of deep learning algorithm in cone beam computed tomography image implant recognition

To properly repair and maintain implants, which are bone tissue implants that replace natural tooth roots, it is crucial to accurately identify their brand and specification. Deep learning has demonstrated outstanding capabilities in analysis, such as image identification and classification, by learning the inherent rules and degrees of representation of data models. The purpose of this study is to evaluate deep learning algorithms and their supporting application software for their ability to recognize and categorize three dimensional (3D) Cone Beam Computed Tomography (CBCT) images of dental implants. By using CBCT technology, the 3D imaging data of 27 implants of various sizes and brands were obtained. Following manual processing, the data were transformed into a data set that had 13,500 two-dimensional data. Nine deep learning algorithms including GoogleNet, InceptionResNetV2, InceptionV3, ResNet50, ResNet50V2, ResNet101, ResNet101V2, ResNet152 and ResNet152V2 were used to perform the data. Accuracy rates, confusion matrix, ROC curve, AUC, number of model parameters and training times were used to assess the efficacy of these algorithms. These 9 deep learning algorithms achieved training accuracy rates of 100%, 99.3%, 89.3%, 99.2%, 99.1%, 99.5%, 99.4%, 99.5%, 98.9%, test accuracy rates of 98.3%, 97.5%, 94.8%, 85.4%, 92.5%, 80.7%, 93.6%, 93.2%, 99.3%, area under the curve (AUC) values of 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00, 1.00. When used to identify implants, all nine algorithms perform satisfactorily, with ResNet152V2 achieving the highest test accuracy, classification accuracy, confusion matrix area under the curve, and receiver operating characteristic curve area under the curve area. The results showed that the ResNet152V2 has the best classification effect on identifying implants. The artificial intelligence identification system and application software based on this algorithm can efficiently and accurately identify the brands and specifications of 27 classified implants through processed 3D CBCT images in vitro, with high stability and low recognition cost.