Is 3T MR nerve-bone fusion imaging a viable alternative to MRI-CBCT to identify the relationship between the inferior alveolar nerve and mandibular third molar.

OBJECTIVES: To investigate the feasibility of MRI nerve-bone fusion imaging in assessing the relationship between inferior alveolar nerve (IAN) / mandibular canal (MC) and mandibular third molar (MTM) compared with MRI-CBCT fusion. MATERIALS AND METHODS: The MRI nerve-bone fusion and MRI-CBCT fusion imaging were performed in 20 subjects with 37 MTMs. The Hausdorff distance (HD) value and dice similarity coefficient (DSC) was calculated. The relationship between IAN/MC and MTM roots, inflammatory, and fusion patterns were compared between these two fused images. The reliability was assessed using a weighted κ statistic. RESULTS: The mean HD and DSC ranged from 0.62 ~ 1.35 and 0.83 ~ 0.88 for MRI nerve-bone fusion, 0.98 ~ 1.50 and 0.76 ~ 0.83 for MRI-CBCT fusion. MR nerve-bone fusion had considerable reproducibility compared to MRI-CBCT fusion in relation classification (MR nerve-bone fusion κ = 0.694, MRI-CBCT fusion κ = 0.644), direct contact (MR nerve-bone fusion κ = 0.729, MRI-CBCT fusion κ = 0.720), and moderate to good agreement for inflammation detection (MR nerve-bone fusion κ = 0.603, MRI-CBCT fusion κ = 0.532, average). The MR nerve-bone fusion imaging showed a lower ratio of larger pattern compared to MR-CBCT fusion (16.2% VS 27.3% in the molar region, and 2.7% VS 5.4% in the retromolar region). And the average time spent on MR nerve-bone fusion and MRI-CBCT fusion was 1 min and 3 min, respectively. CONCLUSIONS: Both MR nerve-bone fusion and MRI-CBCT fusion exhibited good consistency in evaluating the spatial relationship between IAN/MC and MTM, fusion effect, and inflammation detection. CLINICAL RELEVANCE: MR nerve-bone fusion imaging can be a preoperative one-stop radiation-free examination for patients at high risk for MTM surgery.

Differential diagnosis of cemento-osseous dysplasia and periapical cyst using texture analysis of CBCT.

BACKGROUND: Radiolucencies found at the root apex in patients with cemento-osseous dysplasia (COD) may be mistaken for periapical cysts (PC) of endodontic origin. The purpose of this study was to examine the utility of quantitative texture analysis using cone-beam computed tomography (CBCT) to differentiate between COD and PC. METHODS: Patients who underwent CBCT at Wonkwang University Daejeon Dental Hospital between January 2019 and December 2022 and were diagnosed with COD and PC by clinical, radiologic, and, if necessary, histopathologic examination were included. Twenty-five patients each were retrospectively enrolled in the COD and PC group. All lesions observed on axial CBCT images were manually segmented using the open-access software MaZda version 4.6 to establish the regions of interest, which were then subjected to texture analysis. Among the 279 texture features obtained, 10 texture features with the highest Fisher coefficients were selected. Statistical analysis was performed using the Mann-Whitney U-test, Welch's t-test, or Student's t-test. Texture features that showed significant differences were subjected to receiver operating characteristics (ROC) curve analysis to evaluate the differential diagnostic ability of COD and PC. RESULTS: The COD group consisted of 22 men and 3 women, while the PC group consisted of 14 men and 11 women, showing a significant difference between the two groups in terms of sex (p=0.003). The 10 selected texture features belonged to the gray level co-occurrence matrix and included the sum of average, sum of entropy, entropy, and difference of entropy. All 10 selected texture features showed statistically significant differences (p<0.05) when comparing patients with COD (n=25) versus those with PC (n=25), osteolytic-stage COD (n=11) versus PC (n=25), and osteolytic-stage COD (n=11) versus cementoblastic-stage COD (n=14). ROC curve analysis to determine the ability to differentiate between COD and PC showed a high area under the curve ranging from 0.96 to 0.98. CONCLUSION: Texture analysis of CBCT images has shown good diagnostic value in the differential diagnosis of COD and PC, which can help prevent unnecessary endodontic treatment, invasive biopsy, or surgical intervention associated with increased risk of infection.

Evaluation of Radiation Exposure and Influential Factors in Cone-Beam Computed Tomography (CBCT) of the Head and Abdomen during Interventional Procedures.

Cone-beam computed tomography (CBCT) is a widely used imaging technique in interventional radiology. Although CBCT offers great advantages in terms of improving comprehension of complex angioarchitectures and guiding therapeutic decisions, its additional degree of radiation exposure has also aroused considerable concern. In this study, we aimed to assess radiation exposure and its influential factors in patients undergoing CBCT scans of the head and abdomen during interventional procedures. A total of 752 patients were included in this retrospective study. Dose area product (DAP) and reference air kerma (RAK) were used as measures of patient dose. The results showed that the median values of DAP were 53.8 (50.5-64.4) Gy⋅cm2 for head CBCT and 47.4 (39.6-54.3) Gy⋅cm2 for that of the abdomen. Male gender and body mass index (BMI) were characterized by increased DAP and RAK values in both head and abdominal CBCT scans. Larger FOV size was associated with a higher DAP but a lower RAK value, especially in head CBCT scans. Exposure parameters under automatic exposure control (AEC) also varied according to patient BMI and gender. In conclusion, the patients received slightly higher radiation doses from head CBCT scans than from those applied to the abdomen. BMI, gender, and FOV size were the key factors that influenced the radiation dose administered to the patients during CBCT scans. Our results may help to define and minimize patients' exposure to radiation.

Evaluating the Internal Anatomy of Maxillary Premolars in an Adult Saudi Subpopulation Using 2 Classifications: A CBCT-Based Retrospective Study.

BACKGROUND Understanding the root canal morphology is important for successful endodontic treatment. This retrospective cone-beam computed tomography (CBCT) study aimed to compare the adult maxillary premolars (MP), root, and canal morphology among a Saudi Arabian subpopulation based on Vertucci and Ahmed classifications. MATERIAL AND METHODS Scans of 1336 MP - 656 first premolars (MFP) and 680 second premolars (MSP) - were analyzed for the number of roots, morphology of the canals, and symmetry among them. The data were grouped based on the traditional preestablished Vertucci system and newer instantaneous code-based Ahmed classification. Comparative analysis was done using the chi-square test. RESULTS Two roots were common in MFP with 84.4% of the population, followed by those with 1 root and those with 3 roots. In MSP, single roots were more common. The results were non-significant with P values of 0.859 and 0.471, respectively. Most of these MFP had Type IV Vertucci configuration/²TNB¹P¹ Ahmed et al code (TN-tooth number, B-buccal canal, P-palatal canal). In MSP, Type I Vertucci/¹TN¹ Ahmed et al code was most common. However, the results were not statistically significant for the PM with P values of 0.997 and 0.732, respectively. Sex-based difference among them for the roots and root canals was also non-significant. Symmetry among PM in opposite quadrants was 87.1% in MFP and 90% in MSP. CONCLUSIONS Two roots with Type IV (²TNB¹P¹) and 1 root with Type I (¹TN¹) were most common in MFP and MSP, respectively. Symmetry among opposing PM was high.

Pathogenic factors of maxillary sinus mucosal thickening observed by cone-beam computed tomography (CBCT).

OBJECTIVE: To explore the pathogenic factors associated with maxillary sinus mucosal thickening with Cone-beam computed Tomography (CBCT). METHODS: From 2016 through 2020, 93 patients with periapical periodontitis or periodontitis in the maxillary posterior dental region were selected. RESULTS: The preoperative thickness of the periodontitis group was significantly higher than that of the periapical periodontitis group (P < 0.05). The difference achieves statistical significance for the comparison of the thickness change with various severity of inflammation (F = 54.824, P = 0.000), the change with time (F = 312.741, P = 0.000). and the change with the interaction severity of inflammation and time（F = 86.132, P = 0.000). CONCLUSIONS: Patients with maxillary sinus mucosa thickening caused by periodontitis and periapical periodontitis should be extracted their infectious teeth and get thoroughly debridement. Maxillary sinus augmentation can perform favorable efforts 3-6 months after extracting teeth.

A novel difficult-to-segment samples focusing network for oral CBCT image segmentation.

Using deep learning technology to segment oral CBCT images for clinical diagnosis and treatment is one of the important research directions in the field of clinical dentistry. However, the blurred contour and the scale difference limit the segmentation accuracy of the crown edge and the root part of the current methods, making these regions become difficult-to-segment samples in the oral CBCT segmentation task. Aiming at the above problems, this work proposed a Difficult-to-Segment Focus Network (DSFNet) for segmenting oral CBCT images. The network utilizes a Feature Capturing Module (FCM) to efficiently capture local and long-range features, enhancing the feature extraction performance. Additionally, a Multi-Scale Feature Fusion Module (MFFM) is employed to merge multiscale feature information. To further improve the loss ratio for difficult-to-segment samples, a hybrid loss function is proposed, combining Focal Loss and Dice Loss. By utilizing the hybrid loss function, DSFNet achieves 91.85% Dice Similarity Coefficient (DSC) and 0.216 mm Average Symmetric Surface Distance (ASSD) performance in oral CBCT segmentation tasks. Experimental results show that the proposed method is superior to current dental CBCT image segmentation techniques and has real-world applicability.

Cone-beam computed tomography (CBCT) dose optimization technique and image quality assessment scoring.

INTRODUCTION: Linear accelerator (LINAC) embedded with kV source-imager system is capable to do image-guided radiotherapy. The only disadvantage of cone-beam computed tomography image acquisition during treatment is the extra radiation dose to the patient. The aim of this study is to optimize the CBCT imaging doses likely to be received by the patient undergoing radiotherapy without affecting image quality. MATERIAL AND METHODS: The imaging dose to the patient was estimated on CTDI phantoms. The effect of additional filters of different materials (copper, brass, aluminum of thickness 0.1 mm each) was evaluated to find the optimized dose imaging technique. For the pelvis, a single imaging protocol available on the machine was used, whereas for the head and neck region, two protocols, high-quality head and standard-dose head were used. The image quality was assessed on CATPHAN-504 phantom using Owl CATPHAN® QA online tool. A new term "Image Assessment score" (IAS) was introduced to evaluate the image quality. RESULT: In the pelvis protocol, CBCT imaging doses with an additional 0.1-mm brass, copper, and aluminum filter were measured to be reduced by 7.1%, 4.7%, and 2.5%, respectively, whereas for high-quality head protocol, the dose reduction was 25.4% (with brass filter), 22% (with copper filter), and 3.1% (with aluminum filter). For the standard-dose head protocol, doses were reduced by 7.5%, 2.8%, and 2.1% with additional 0.1-mm brass copper and aluminum filters, respectively. Acceptable image quality was observed with all the filters. CONCLUSION: Although the reconstructed images were found somewhat noisier, they did not affect the purpose of imaging, that is, treatment position verification. It was observed that these extra filters further reduce the imaging dose without much affecting the image quality.

Multi-energy blended CBCT spectral imaging and scatter-decoupled material decomposition using a spectral modulator with flying focal spot (SMFFS).

BACKGROUND: Cone-beam CT (CBCT) has been extensively employed in industrial and medical applications, such as image-guided radiotherapy and diagnostic imaging, with a growing demand for quantitative imaging using CBCT. However, conventional CBCT can be easily compromised by scatter and beam hardening artifacts, and the entanglement of scatter and spectral effects introduces additional complexity. PURPOSE: The intertwined scatter and spectral effects within CBCT pose significant challenges to the quantitative performance of spectral imaging. In this work, we present the first attempt to develop a stationary spectral modulator with flying focal spot (SMFFS) technology as a promising, low-cost approach to accurately solving the x-ray scattering problem and physically enabling spectral imaging in a unified framework, and with no significant misalignment in data sampling of spectral projections. METHODS: To deal with the intertwined scatter-spectral challenge, we propose a novel scatter-decoupled material decomposition (SDMD) method for SMFFS, which consists of four steps in total, including (1) spatial resolution-preserved and noise-suppressed multi-energy "residual" projection generation free from scatter, based on a hypothesis of scatter similarity; (2) first-pass material decomposition from the generated multi-energy residual projections in non-penumbra regions, with a structure similarity constraint to overcome the increased noise and penumbra effect; (3) scatter estimation for complete data; and (4) second-pass material decomposition for complete data by using a multi-material spectral correction method. Monte Carlo simulations of a pure-water cylinder phantom with different focal spot deflections are conducted to validate the scatter similarity hypothesis. Both numerical simulations using a clinical abdominal CT dataset, and physics experiments on a tabletop CBCT system using a Gammex multi-energy CT phantom and an anthropomorphic chest phantom, are carried out to demonstrate the feasibility of CBCT spectral imaging with SMFFS and our proposed SDMD method. RESULTS: Monte Carlo simulations show that focal spot deflections within a range of 2 mm share quite similar scatter distributions overall. Numerical simulations demonstrate that SMFFS with SDMD method can achieve better material decomposition and CT number accuracy with fewer artifacts. In physics experiments, for the Gammex phantom, the average error of the mean values ( E RMSE ROI $E^{\text{ROI}}_{\text{RMSE}}$ ) in selected regions of interest (ROIs) of virtual monochromatic image (VMI) at 70 keV is 8 HU in SMFFS cone-beam (CB) scan, and 19 and 210 HU in sequential 80/120 kVp (dual kVp, DKV) CB scan with and without scatter correction, respectively. For the chest phantom, the E RMSE ROI $E^{\text{ROI}}_{\text{RMSE}}$ in selected ROIs of VMIs is 12 HU for SMFFS CB scan, and 15 and 438 HU for sequential 80/140 kVp CB scan with and without scatter correction, respectively. Also, the non-uniformity among selected regions of the chest phantom is 14 HU for SMFFS CB scan, and 59 and 184 HU for the DKV CB scan with and without a traditional scatter correction method, respectively. CONCLUSIONS: We propose a SDMD method for CBCT with SMFFS. Our preliminary results show that SMFFS can enable spectral imaging with simultaneous scatter correction for CBCT and effectively improve its quantitative imaging performance.

Relationship between Impacted Mandibular Third Molars and the Mandibular Canal on CBCT Scans.

This study aimed to assess the relationship of impacted mandibular third molars with the mandibular canal on cone beam computed tomography (CBCT) scans. This cross-sectional study was conducted on CBCT scans of 137 patients with 204 impacted mandibular third molars. The relation of age, gender, class of impaction, anatomical position of canal relative to tooth (buccal, lingual, inferior, inter-radicular), tooth angulation (mesioangular, vertical, distoangular, horizontal), relationship of tooth with the mandibular canal (no contact, in contact, relation), relationship of tooth with the mandibular cortex, anatomical site of contact of tooth with the mandibular cortex (buccal, lingual, inferior), and the impression of canal (grooving, no effect) on impacted teeth were evaluated. Data were analyzed using one-way ANOVA, Chi-square test and Fisher's exact test. Class B of impaction (78.9%), inferior position of canal relative to the impacted tooth (53.9%) and mesioangular angulation (53.4%) had the highest frequency, respectively. The relationship of tooth with the mandibular canal was "relation" in most cases (53.4%) followed by no contact (26.9%) and in contact (19.6%). Significant associations were noted between depth of impaction (P < 0.001), tooth angulation (P = 0.024), anatomical position of canal relative to tooth (P < 0.001), relationship of tooth with the mandibular cortex (P = 0.032) and anatomical site of contact of tooth with the mandibular cortex (P = 0.013) with the impacted tooth-mandibular canal relationship. CBCT provides accurate information about the relationship of impacted third molars with the mandibular canal and can decrease the risk of traumatization of inferior alveolar nerve (IAN) during their surgical extraction.

Performance of cone-beam computed tomography (CBCT) in comparison to conventional computed tomography (CT) and magnetic resonance imaging (MRI) for the detection of bone invasion in oral squamous cell cancer (OSCC): a prospective study.

BACKGROUND: Oral squamous carcinoma (OSCC) is often diagnosed at late stages and bone erosion or invasion of the jawbone is frequently present. Computed tomography (CT) and magnetic resonance imaging (MRI) are known to have high diagnostic sensitivities, specificities, and accuracies in detecting these bone affections in patients suffering from OSCC. To date, the existing data regarding the impact of cone-beam computed tomography (CBCT) have been weak. Therefore, this study aimed to investigate whether CBCT is a suitable tool to detect bone erosion or invasion in patients with OSCC. METHODS: We investigated in a prospective trial the impact of CBCT in the diagnosis of bone erosion or invasion in patients with OSCC who underwent surgery. Every participant received a CBCT, CT, and MRI scan during staging. Imaging modalities were evaluated by two specialists in oral and maxillofacial surgery (CBCT) and two specialists in radiology (CT and MRI) in a blinded way, to determine whether a bone affection was present or not. Reporting used the following 3-point system: no bony destruction ("0"), cortical bone erosion ("1"), or medullary bone invasion ("2"). Histological examination or a follow-up served to calculate the sensitivities, specificities, and accuracies of the imaging modalities. RESULTS: Our results revealed high diagnostic sensitivities (95.6%, 84.4%, and 88.9%), specificities (87.0%, 91.7%, and 91.7%), and accuracies (89.5%, 89.5%, and 90.8%) for CBCT, CT, and MRI. A pairwise comparison found no statistical difference between CBCT, CT, and MRI. CONCLUSION: Our data support the routine use of CBCT in the diagnosis of bone erosion and invasion in patients with OSCC as diagnostic accuracy is equal to CT and MRI, the procedure is cost-effective, and it can be performed during initial contact with the patient.

Feasibility of proton dosimetry overriding planning CT with daily CBCT elaborated through generative artificial intelligence tools.

Radiotherapy commonly utilizes cone beam computed tomography (CBCT) for patient positioning and treatment monitoring. CBCT is deemed to be secure for patients, making it suitable for the delivery of fractional doses. However, limitations such as a narrow field of view, beam hardening, scattered radiation artifacts, and variability in pixel intensity hinder the direct use of raw CBCT for dose recalculation during treatment. To address this issue, reliable correction techniques are necessary to remove artifacts and remap pixel intensity into Hounsfield Units (HU) values. This study proposes a deep-learning framework for calibrating CBCT images acquired with narrow field of view (FOV) systems and demonstrates its potential use in proton treatment planning updates. Cycle-consistent generative adversarial networks (cGAN) processes raw CBCT to reduce scatter and remap HU. Monte Carlo simulation is used to generate CBCT scans, enabling the possibility to focus solely on the algorithm's ability to reduce artifacts and cupping effects without considering intra-patient longitudinal variability and producing a fair comparison between planning CT (pCT) and calibrated CBCT dosimetry. To showcase the viability of the approach using real-world data, experiments were also conducted using real CBCT. Tests were performed on a publicly available dataset of 40 patients who received ablative radiation therapy for pancreatic cancer. The simulated CBCT calibration led to a difference in proton dosimetry of less than 2%, compared to the planning CT. The potential toxicity effect on the organs at risk decreased from about 50% (uncalibrated) up the 2% (calibrated). The gamma pass rate at 3%/2 mm produced an improvement of about 37% in replicating the prescribed dose before and after calibration (53.78% vs 90.26%). Real data also confirmed this with slightly inferior performances for the same criteria (65.36% vs 87.20%). These results may confirm that generative artificial intelligence brings the use of narrow FOV CBCT scans incrementally closer to clinical translation in proton therapy planning updates.

Clinical relevance of distolingual roots and periodontal status in mandibular first molars: a cross-sectional study employing CBCT analysis. / ä¸‹é¢Œç¬¬ä¸€ç£¨ç‰™è¿œèˆŒæ ¹çš„å­˜åœ¨ä¸Žç‰™å‘¨çŠ¶æ€çš„ä¸´åºŠç›¸å ³æ€§åˆ†æžï¼šä¸€é¡¹é‡‡ç”¨é”¥å½¢å°„æŸç”µè„‘æ–­å±‚æ‰«æåˆ†æžçš„æ¨ªæ–­é¢ç ”ç©¶.

OBJECTIVES: Distolingual root of the permanent mandibular first molar (PMFM-DLR) has been frequently reported, which may complicate the treatment of periodontitis. This study aimed to assess the morphological features of PMFM-DLR and investigate the correlation between the morphological features of PMFM-DLR and periodontal status in patients with Eastern Chinese ethnic background. MATERIALS AND METHODS: A total of 836 cone beam computed tomography (CBCT) images with 1497 mandibular first molars were analyzed to observe the prevalence of PMFM-DLR at the patients and tooth levels in Eastern China. Among them, complete periodontal charts were available for 69 Chinese patients with 103 teeth. Correlation and regression analyses were used to evaluate the correlation between the morphological features of DLR, bone loss, and periodontal clinical parameters, including clinical attachment loss (CAL), probing pocket depth (PPD), gingival recession (GR), and furcation involvement (FI). RESULTS: The patient-level prevalence and tooth-level prevalence of DLR in mandibular first molars were 29.4% and 26.3%, respectively. Multiple linear regression analysis suggested that bone loss at the lingual site and CAL were negatively affected by the angle of separation between distolingual and mesial roots in the transverse section, while they were significantly influenced by age and the angle of separation between distobuccal and mesial roots in the coronal section. CONCLUSIONS: The prevalence of PMFM-DLR in Eastern China was relatively high in our cohort. The morphological features of DLR were correlated with the periodontal status of mandibular first molars. This study provides critical information on the morphological features of DLR for improved diagnosis and treatment options of mandibular molars with DLR.

A system for automatic classification of endodontic treatment quality in CBCT.

OBJECTIVES: An evaluation of the effectiveness of a new computational system proposed for automatic classification, developed based on a Siamese network combined with Convolutional Neural Networks (CNNs), is presented. It aims to identify endodontic technical errors using Cone Beam Computed Tomography (CBCT). The study also aims to compare the performance of the automatic classification system with that of dentists. METHODS: One thousand endodontically treated maxillary molars sagittal and coronal reconstructions were evaluated for the quality of the endodontic treatment and the presence of periapical hypodensities by three board-certified dentists and by an oral and maxillofacial radiologist. The proposed classification system was based on a Siamese network combined with EfficientNet B1 or EfficientNet B7 networks. Accuracy, sensivity, precision, specificity, and F1-score values were calculated for automated artificial systems and dentists. Chi-square tests were performed. RESULTS: The performances were obtained for EfficienteNet B1, EfficientNet B7 and dentists. Regarding accuracy, sensivity and specificity, the best results were obtained with EfficientNet B1. Concerning precision and F1-score, the best results were obtained with EfficientNet B7. The presence of periapical hypodensity lesions was associated with endodontic technical errors. In contrast, the absence of endodontic technical errors was associated with the absence of hypodensity. CONCLUSIONS: Quality evaluation of the endodontic treatment performed by dentists and by Siamese Network combined with EfficientNet B7 or EfficientNet B1 networks was comparable with a slight superiority for the Siamese Network. CLINICAL RELEVANCE: CNNs have the potential to be used as a support and standardization tool in assessing endodontic treatment quality in clinical practice.

Automatic image registration on intraoperative CBCT compared to Surface Matching registration on preoperative CT for spinal navigation: accuracy and workflow.

INTRODUCTION: Spinal navigation solutions have been slower to develop compared to cranial ones. To facilitate greater adoption and use of spinal navigation, the relatively cumbersome registration processes need to be improved upon. This study aims to validate a new solution for automatic image registration and compare it to a traditional Surface Matching method. METHOD: Adult patients undergoing spinal surgery requiring navigation were enrolled after providing consent. A registration matrix-Universal AIR (= Automatic Image Registration)-was placed in the surgical field and used for automatic registration based on intraoperative 3D imaging. A standard Surface Matching method was used for comparison. Accuracy measurements were obtained by comparing planned and acquired coordinates on the vertebrae. RESULTS: Thirty-nine patients with 42 datasets were included. The mean accuracy of Universal AIR registration was 1.20 ± 0.42 mm, while the mean accuracy of Surface Matching registration was 1.94 ± 0.64 mm. Universal AIR registration was non-inferior to Surface Matching registration. Post hoc analysis showed a significantly greater accuracy for Universal AIR registration. In Surface Matching, but not automatic registration, user-related errors such as incorrect identification of the vertebral level were seen. CONCLUSION: Automatic image registration for spinal navigation using Universal AIR and intraoperative 3D imaging provided improved accuracy compared to Surface Matching registration. In addition, it minimizes user errors and offers a standardized workflow, making it a reliable registration method for navigated spinal procedures.

Organ dose prediction for patients undergoing radiotherapy CBCT chest examinations using artificial intelligence.

PURPOSE: To propose an artificial intelligence (AI)-based method for personalized and real-time dosimetry for chest CBCT acquisitions. METHODS: CT images from 113 patients who underwent radiotherapy treatment were collected for simulating thorax examinations using cone-beam computed tomography (CBCT) with the Monte Carlo technique. These simulations yielded organ dose data, used to train and validate specific AI algorithms. The efficacy of these AI algorithms was evaluated by comparing dose predictions with the actual doses derived from Monte Carlo simulations, which are the ground truth, utilizing Bland-Altman plots for this comparative analysis. RESULTS: The absolute mean discrepancies between the predicted doses and the ground truth are (0.9 ± 1.3)% for bones, (1.2 ± 1.2)% for the esophagus, (0.5 ± 1.3)% for the breast, (2.5 ± 1.4)% for the heart, (2.4 ± 2.1)% for lungs, (0.8 ± 0.6)% for the skin, and (1.7 ± 0.7)% for integral. Meanwhile, the maximum discrepancies between the predicted doses and the ground truth are (14.4 ± 1.3)% for bones, (12.9 ± 1.2)% for the esophagus, (9.4 ± 1.3)% for the breast, (14.6 ± 1.4)% for the heart, (21.2 ± 2.1)% for lungs, (10.0 ± 0.6)% for the skin, and (10.5 ± 0.7)% for integral. CONCLUSIONS: AI models that can make real-time predictions of the organ doses for patients undergoing CBCT thorax examinations as part of radiotherapy pre-treatment positioning were developed. The results of this study clearly show that the doses predicted by analyzed AI models are in close agreement with those calculated using Monte Carlo simulations.

Do metal artifact reduction algorithms influence the detection of implant-related injuries to the inferior alveolar canal in CBCT images?

BACKGROUND: The routine application of dental implants for replacing missing teeth has revolutionized restorative and prosthetic dentistry. However, cone beam computed tomography (CBCT) evaluations of structures adjacent to the implants are limited by metal artifacts. There are several methods for reducing metal artifacts, but this remains a challenging task. This study aimed to examine the effectiveness of metal artifact reduction (MAR) algorithms in identifying injuries of implants to the inferior alveolar canal in CBCT images. METHOD: In this in vitro study, mono-cortical bone windows were created and the inferior alveolar canal was revealed. Using 36 implants, pilot drill and penetration damage of the implant tip into the canal was simulated and compared to the control implants with distance from the canal. CBCT images were evaluated by four experienced observers with and without the MAR algorithm and compared to direct vision as the gold standard. The values of accuracy, sensitivity, and specificity were obtained and compared by receiver operating characteristic (ROC) curve (α = 0.05). RESULT: The area under the ROC curve values for detection of pilot drill injuries varied between 0.840-0.917 and 0.639-0.854 in the active and inactive MAR conditions, respectively. The increase in ROC area was only significant for one of the observers (P = 0.010). For diagnosing penetrative injuries, the area under the ROC curve values was between 0.990-1.000 and 0.722-1.000 in the active and inactive MAR conditions, respectively. The improvement of ROC curve values in active MAR mode was only significant for one of the observers (P = 0.006). CONCLUSION: Activation of MAR improved the diagnostic values of CBCT images in detecting both types of implant-related injuries to the inferior alveolar canal. However, for most observers, this increase was not statistically significant.

Age and Gender-related Morphometric Assessment and Degenerative Changes of Temporomandibular Joint in Symptomatic Subjects and Controls using Cone Beam Computed Tomography (CBCT): A Comparative Analysis.

BACKGROUND: The temporomandibular joint diseases have been associated with various predisposing factors. Joint spaces, articular eminence height and inclination, and the shapes of the condylar and glenoid fossa have all been shown to vary in temporomandibular joint diseases (TMD) patients. Advanced imaging techniques like cone beam computed tomography (CBCT) have been employed to estimate these parameters. AIMS AND OBJECTIVES: The aim of the current study was to investigate the condylar morphology, condylar and glenoid fossa shapes, and assessment of joint spaces, such as anterior, posterior, superior, lateral, and medial spaces, through CBCT slices in coronal and sagittal planes and compare them between the control group and TMD group. MATERIALS AND METHODS: A cross-sectional study was planned where 80 joints in 40 patients were assessed for the above parameters; group I consisted of healthy patients, and group II included those with temporomandibular joint diseases (TMDs). The articular eminence height and inclination were assessed on the midsagittal section. The condylar changes and shapes of the glenoid fossa and condyles, as well as the joint spaces, were assessed on the selected coronal and sagittal sections. RESULTS: The condylar fossa had a triangular shape in the TMJ group and an oval shape in the control group. The results were highly significant (P = 0.000**). A highly significant difference in morphological parameters, such as AJS, PJS, SJS, MJS, LJS, articular eminence height, and inclination, was found between the two groups (P = 0.000**). The association of morphological parameters, such as AJS, PJS, SJS, MJS, LJS, and articular eminence height and inclination were compared with condylar and glenoid fossa shapes, where the association of superior joint space and articular eminence inclination was observed. A highly significant difference was noted between the two groups with regard to all the parameters with P=0.00*. CONCLUSION: The articular eminence inclination, as well as the superior joint space, were found to be associated with the glenoid and condyle fossa shapes in the TMJ group. These observations would, therefore, help in the early diagnosis of temporomandibular joint diseases.

Fully automatic integration of dental CBCT images and full-arch intraoral impressions with stitching error correction via individual tooth segmentation and identification.

We present a fully automated method of integrating intraoral scan (IOS) and dental cone-beam computerized tomography (CBCT) images into one image by complementing each image's weaknesses. Dental CBCT alone may not be able to delineate precise details of the tooth surface due to limited image resolution and various CBCT artifacts, including metal-induced artifacts. IOS is very accurate for the scanning of narrow areas, but it produces cumulative stitching errors during full-arch scanning. The proposed method is intended not only to compensate the low-quality of CBCT-derived tooth surfaces with IOS, but also to correct the cumulative stitching errors of IOS across the entire dental arch. Moreover, the integration provides both gingival structure of IOS and tooth roots of CBCT in one image. The proposed fully automated method consists of four parts; (i) individual tooth segmentation and identification module for IOS data (TSIM-IOS); (ii) individual tooth segmentation and identification module for CBCT data (TSIM-CBCT); (iii) global-to-local tooth registration between IOS and CBCT; and (iv) stitching error correction for full-arch IOS. The experimental results show that the proposed method achieved landmark and surface distance errors of 112.4µm and 301.7µm, respectively.

The effect of tooth loss on the temporomandibular joint space: A CBCT study.

OBJECTIVE: The tooth loss has a significant impact on the positioning of the condyle in the glenoid fossa and joint spaces of the temporomandibular joint (TMJ). The aim of this study was to assess the association between tooth loss and TMJ spaces using cone beam computed tomography (CBCT) images. MATERIALS AND METHODS: This retrospective investigation involved the evaluation of CBCT images of the bilateral TMJs in a cohort of 111 individuals, comprising 68 males and 43 women. The dentition of the patients was categorized into three categories, including A (65.4%), B (19.1%), and C (16.4%), based on the Eichner index. Anterior, superior, and posterior joint spaces were then measured in sagittal views. The Kruskal-Wallis test and Mann-Whitney test were employed to identify significant differences among the three Eichner groups. RESULTS: The findings of the present study suggested that there was no statistically significant variation in the anterior joint space among different Eichner groups within the general population (p = .781). Nevertheless, the superior and posterior joint spaces exhibited statistically significant alterations, as indicated by p-values of .039 and .010, respectively. It was detected that condyles were positioned inferiorly and posteriorly in group C when compared to groups A and B. CONCLUSION: The present study indicated that greater loss of tooth-supporting zones is associated with posterior and inferior displacement of condyles. Understanding these relationships helps emphasize how crucial it is to replace missing teeth to enhance occlusion support and, in turn, stop the progression and further deterioration of temporomandibular disorders.

PET/SPECT/spectral-CT/CBCT imaging in a small-animal radiation therapy platform: A Monte Carlo study-Part I: Quad-modal imaging.

BACKGROUND: In spite of the tremendous potential of game-changing biological image- and/or biologically guided radiation therapy (RT) and adaptive radiation therapy for cancer treatment, existing limited strategies for integrating molecular imaging and/or biological information with RT have impeded the translation of preclinical research findings to clinical applications. Additionally, there is an urgent need for a highly integrated small-animal radiation therapy (SART) platform that can seamlessly combine therapeutic and diagnostic capabilities to comprehensively enhance RT for cancer treatment. PURPOSE: We investigated a highly integrated quad-modal on-board imaging configuration combining positron emission tomography (PET), single-photon emission computed tomography (SPECT), photon-counting spectral CT, and cone-beam computed tomography (CBCT) in a SART platform using a Monte Carlo model as a proof-of-concept. METHODS: The quad-modal on-board imaging configuration of the SART platform was designed and evaluated by using the GATE Monte Carlo code. A partial-ring on-board PET imaging subsystem, utilizing advanced semiconductor thallium bromide detector technology, was designed to achieve high sensitivity and spatial resolution. On-board SPECT, photon-counting spectral-CT, and CBCT imaging were performed using a single cadmium zinc telluride flat detector panel. The absolute peak sensitivity and scatter fraction of the PET subsystem were estimated by using simulated phantoms described in the NEMA NU-4 standard. The spatial resolution of the PET image of the platform was evaluated by imaging a simulated micro-Derenzo hot-rod phantom. To evaluate the quantitative imaging capability of the system's spectral CT, the Bayesian eigentissue decomposition (ETD) method was utilized to quantitatively decompose the virtual noncontrast (VNC) electron densities and iodine contrast agent fractions in the Kidney1 inserts mixed with the iodine contrast agent within the simulated phantoms. The performance of the proposed quad-model imaging in the platform was validated by imaging a simulated phantom with multiple imaging probes, including an iodine contrast agent and radioisotopes of 18F and 99mTc. RESULTS: The PET subsystem demonstrated an absolute peak sensitivity of 18.5% at the scanner center, with an energy window of 175-560 KeV, and a scatter fraction of only 3.5% for the mouse phantom, with a default energy window of 480-540 KeV. The spatial resolution of PET on-board imaging exceeded 1.2 mm. All imaging probes were identified clearly within the phantom. The PET and SPECT images agreed well with the actual spatial distributions of the tracers within the phantom. Average relative errors on electron density and iodine contrast agent fraction in the Kidney1 inserts were less than 3%. High-quality PET images, SPECT images, spectral-CT images (including iodine contrast agent fraction images and VNC electron density images), and CBCT images of the simulated phantom demonstrated the comprehensive multimodal imaging capability of the system. CONCLUSIONS: The results demonstrated the feasibility of the proposed quad-modal imaging configuration in a SART platform. The design incorporates anatomical, molecular, and functional information about tumors, thereby facilitating successful translation of preclinical studies into clinical practices.