Cone Beam Computed Tomography Slices Research Articles

Comparison of Quantitative Radiomorphometric Predictors of Healthy and MRONJ-Affected Bone Using Panoramic Radiography and Cone-Beam CT.

To determine the most distinctive quantitative radiomorphometric parameter(s) for the detection of MRONJ-affected bone changes in panoramic radiography (PR) and cone-beam computed tomography (CBCT). PR and sagittal CBCT slices of 24 MRONJ patients and 22 healthy controls were used for the measurements of mandibular cortical thickness (MCT), fractal dimension (FD), lacunarity, mean gray value (MGV), bone area fraction (BA/TA), trabecular thickness (Tb.Th), trabecular separation (Tb.Sp), trabecular number (Tb.N). MCT was measured in the mental foramen region. While FD and lacunarity were measured on mandibular trabecular and cortical regions of interest (ROIs), the remaining parameters were measured on trabecular ROIs. The independent samples t-test was used to compare the measurements between MRONJ and control group for both imaging modalities (p = 0.05). MCT was the only parameter that differentiated MRONJ-affected bone in both PR and CBCT (p < 0.05). None of the remaining parameters revealed any difference for MRONJ-affected bone in CBCT (p > 0.05). FD, lacunarity, MGV, BA/TA, and Tb.Sp could distinguish MRONJ-affected trabecular bone in PR (p < 0.05). The correspondent ROI for both imaging methods that was reliable for detecting MRONJ-affected bone was the trabecular bone distal to the mental foramen above the inferior alveolar canal (ROI-3). MCT is a reliable parameter for the discrimination of MRONJ-affected bone in both PR and CBCT images. PR may be used to detect MRONJ-affected trabecular bone using FD, lacunarity, MGV, BA/TA, and Tb.Sp measurements as well.

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.

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.

Detection of extracranial and intracranial calcified carotid artery atheromas in cone beam computed tomography using a deep learning convolutional neural network image segmentation approach

We leveraged an artificial intelligence deep-learning convolutional neural network (DL CNN) to detect calcified carotid artery atheromas (CCAAs) on cone beam computed tomography (CBCT) images. We obtained 137 full-volume CBCT scans with previously diagnosed CCAAs. The DL model was trained on 170 single axial CBCT slices, 90 with extracranial CCAAs and 80 with intracranial CCAAs. A board-certified oral and maxillofacial radiologist confirmed the presence of each CCAA. Transfer learning through a U-Net-based CNN architecture was utilized. Data allocation was 60% training, 10% validation, and 30% testing. We determined the accuracy of the DL model in detecting CCAA by calculating the mean training and validation accuracy and the area under the receiver operating characteristic curve (AUC). We reserved 5 randomly selected unseen full CBCT volumes for final testing. The mean training and validation accuracy of the model in detecting extracranial CCAAs was 92% and 82%, respectively, and the AUC was 0.84 with 1.0 sensitivity and 0.69 specificity. The mean training and validation accuracy in detecting intracranial CCAAs was 61% and 70%, respectively, and the AUC was 0.5 with 0.93 sensitivity and 0.08 specificity. Testing of full-volume scans yielded an AUC of 0.72 and 0.55 for extracranial and intracranial CCAAs, respectively. Our DL model showed excellent discrimination in detecting extracranial CCAAs on axial CBCT images and acceptable discrimination on full-volumes but poor discrimination in detecting intracranial CCAAs, for which further research is required.

Fan beam CT image synthesis from cone beam CT image using nested residual UNet based conditional generative adversarial network.

A radiotherapy technique called Image-Guided Radiation Therapy adopts frequent imaging throughout a treatment session. Fan Beam Computed Tomography (FBCT) based planning followed by Cone Beam Computed Tomography (CBCT) based radiation delivery drastically improved the treatment accuracy. Furtherance in terms of radiation exposure and cost can be achieved if FBCT could be replaced with CBCT. This paper proposes a Conditional Generative Adversarial Network (CGAN) for CBCT-to-FBCT synthesis. Specifically, a new architecture called Nested Residual UNet (NR-UNet) is introduced as the generator of the CGAN. A composite loss function, which comprises adversarial loss, Mean Squared Error (MSE), and Gradient Difference Loss (GDL), is used with the generator. The CGAN utilises the inter-slice dependency in the input by taking three consecutive CBCT slices to generate an FBCT slice. The model is trained using Head-and-Neck(H&N) FBCT-CBCT images of 53 cancer patients. The synthetic images exhibited a Peak Signal-to-Noise Ratio of 34.04±0.93 dB, Structural Similarity Index Measure of 0.9751±0.001 and a Mean Absolute Error of 14.81±4.70 HU. On average, the proposed model guarantees an improvement in Contrast-to-Noise Ratio four times better than the input CBCT images. The model also minimised the MSE and alleviated blurriness. Compared to the CBCT-based plan, the synthetic image results in a treatment plan closer to the FBCT-based plan. The three-slice to single-slice translation captures the three-dimensional contextual information in the input. Besides, it withstands the computational complexity associated with a three-dimensional image synthesis model. Furthermore, the results demonstrate that the proposed model is superior to the state-of-the-art methods.

Anatomical Investigation of C-shaped Root Canal Systems of Mandibular Molars in a Middle Eastern Population: A CBCT Study

The aim of this study is to identify the prevalence of C-shaped root canal systems in mandibular first and second molars in a Lebanese population, and to determine the relationship between C-shaped root canal systems and different factors (age, gender, and tooth location) and to examine the root canal system's morphology along the root. The presence of C-shaped root canal systems in 648 mandibular molars from 257 patients was analyzed using cone-beam computed tomography (CBCT). The sample included 296 and 352 mandibular first and second molars, respectively. The frequency of C-shaped canals, their relationship to gender, age, and tooth location, and unilateral or bilateral occurrences were noted. A 3D Slicer 4.10.1 was then used to classify teeth with identified C-shaped anatomy according to Fan's configuration and to determine the distance between the orifice and the cementoenamel junction (CEJ). C-shaped root canal systems were detected in 1.01 and 9.09% of mandibular first and second molars, respectively. In mandibular second molars, the most prevalent configurations were as follows: C1 at the orifice level, C3 at orifice-2 mm, C2 and C3 in the middle third, and C3 at the apical level. There was no correlation with age, gender, and tooth position. The bilateral occurrence happened in 60% of cases. Orifices were at a mean distance of 3.32 mm below the CEJ. The deepest groove was mostly lingual. The prevalence of C-shaped root canal systems in the Lebanese population is 1.01 and 9.09% in the first and second mandibular molars, respectively. The CBCT slices showed that the configuration varies along the root and that the orifices are at various distances below the CEJ. Therefore, pre-operatory scans can be beneficial for better understanding and preparation of root canal treatment. In the Lebanese population, C-shaped mandibular molars are not a rare finding. Clinicians should consider the different configurations and the possible changes along the root.

Investigation of Frequency of Heterotopic Teeth: A Cone Beam CT Study

Aim: Teeth that occur in distant places from the alveolar arch (maxillary sinus, orbit, infratemporal fossa, condylar region, etc.) because of various local or systemic factors are named heterotopic teeth. The heterotopic tooth is a rare phenomenon. Although the etiology is still unknown, it is known that it may be seen due to pathologies caused by cystic lesions, cleft lip-palate, trauma history, and infectious conditions. They are usually asymptomatic, so they are detected by chance in routine clinical and radiological examinations. This study aims to determine the frequency of heterotopic permanent teeth and their anatomical localization with the help of cone-beam computed tomography (CBCT).&#x0D; Methods: This study was retrospectively performed with CBCT slices. CBCT sections of 2590 individuals (1432 females, 1158 males) between the ages of 10-89 (mean: 44 ± 17 years) were evaluated in the study. Heterotopic teeth were investigated using coronal, axial, sagittal CBCT sections in regions distant from the maxillary-mandibular arch. SPSS V.21 software (IBM Corp., Armonk, NY, USA) was used for data analysis. &#x0D; Results: Heterotopic teeth were found in 10 of 2590 individuals (0.4%). All of the heterotopic teeth detected are molar teeth; 4 are mandibular third molar teeth, 5 are maxillary third molar teeth and 1 is maxillary second molar tooth. The frequency of heterotopic teeth according to gender did not show a statistically significant difference (4 females, 6 males) p&gt; 0.05. The average age of individuals with heterotopic teeth is 35.3 (17-65 years). 4 of the heterotopic impacted teeth are located in the ramus and 6 in the maxillary sinus.&#x0D; Conclusions: The prevalence of heterotopic teeth is very rare (0.4%). The teeth with the highest frequency of heterotopia are the third molars. Heterotopic teeth do not have an anatomical location and gender that they prefer predominantly.

Maksiller Sinüs ve Posterior Superior Alveolar Arterin Konik Işınlı Bilgisayarlı Tomografi Değerlendirmesi

Background The aim of this study was to investigate the diameter, location, and frequency of the appearance of posterior superior alveolar artery (PSAA), presence of septa and pathology in maxillary sinus on cone-beam computed tomography (CBCT) slices. Two hundred CBCT records were included in the study. The patients were divided into dentate, partially dentate and edentulous. Methods The diameter and type of the PSAA (intrasinus-intraosseous-superficial), the distance between the lower border of the PSAA and alveolar crest; the bone height measured from the floor of the sinus to the crest of the ridge; the distance from the lateral wall of the PSAA to the medial wall of the maxillary sinus, presence of septa and pathology were evaluated. Results On the right side, PSAA was detected in 86.5% and in the left, 84.5%. Intraosseous type of PSAA was most common type on right (50%) and left (51.5%). The average distances between the PSAA and the alveolar crest were 17.80±3.59 mm on the right and 17.83±3.61 mm on the left side. There was no significant correlation between age and the diameter of the PSAA (p&amp;gt;0.05). Conclusions The observation of PSAA on CBCT slices is high. Preoperatively CBCT imaging can prevent potential vascular damages around maxillary sinus.

Assessment of Maxillary Molars Interradicular Septum Morphological Characteristics as Criteria for Ideal Immediate Implant Placement-The Advantages of Cone Beam Computed Tomography Analysis.

The aim of this study was to evaluate the interradicular septum bone morphometric characteristics using cone beam computed tomography (CBCT) images, as well as to establish quantitative shortcuts to allow clinicians to make a faster and more reliable plan for immediate implant placement in the maxillary molars area. This retrospective quantitative study was conducted on CBCT images obtained from 100 patients. The morphometric analysis of the maxillary molars region was based on the parameters obtained on the sagittal and axial slices. The analysis performed on sagittal slices showed that the first maxillary molars had a wider interradicular septum when compared to the second molars, but the septum height in the first molars was significantly below the height in the second maxillary molars. The axial CBCT slices analysis showed that both interradicular septum perimeter and surface area were significantly more pronounced in the first than in the second maxillary molars. The interradicular furcation angle significantly correlated with the surface area (positively) and septum height (negatively) for both molars. The results of this study may recommend CBCT image analysis as a useful tool in predefining the circumstances that can allow for substantially better planning of immediate implant placement procedures in the region of maxillary molars.

Development and validation of a novel artificial intelligence driven tool for accurate mandibular canal segmentation on CBCT

ObjectivesThe objective of this study is the development and validation of a novel artificial intelligence driven tool for fast and accurate mandibular canal segmentation on cone beam computed tomography (CBCT). MethodsA total of 235 CBCT scans from dentate subjects needing oral surgery were used in this study, allowing for development, training and validation of a deep learning algorithm for automated mandibular canal (MC) segmentation on CBCT. Shape, diameter and direction of the MC were adjusted on all CBCT slices using a voxel-wise approach. Validation was then performed on a random set of 30 CBCTs - previously unseen by the algorithm - where voxel-level annotations allowed for assessment of all MC segmentations. ResultsPrimary results show successful implementation of the AI algorithm for segmentation of the MC with a mean IoU of 0.636 (± 0.081), a median IoU of 0.639 (± 0.081), a mean Dice Similarity Coefficient of 0.774 (± 0.062). Precision, recall and accuracy had mean values of 0.782 (± 0.121), 0.792 (± 0.108) and 0.99 (± 7.64×10−05) respectively. The total time for automated AI segmentation was 21.26 s (±2.79), which is 107 times faster than accurate manual segmentation. ConclusionsThis study demonstrates a novel, fast and accurate AI-driven module for MC segmentation on CBCT. Clinical SignificanceGiven the importance of adequate pre-operative mandibular canal assessment, Artificial Intelligence could help relieve practitioners from the delicate and time-consuming task of manually tracing and segmenting this structure, helping prevent per- and post-operative neurovascular complications.

Contextual loss based artifact removal method on CBCT image.

PurposeCone beam computed tomography (CBCT) offers advantages such as high ray utilization rate, the same spatial resolution within and between slices, and high precision. It is one of the most actively studied topics in international computed tomography (CT) research. However, its application is hindered owing to scatter artifacts. This paper proposes a novel scatter artifact removal algorithm that is based on a convolutional neural network (CNN), where contextual loss is employed as the loss function.MethodsIn the proposed method, contextual loss is added to a simple CNN network to correct the CBCT artifacts in the pelvic region. The algorithm aims to learn the mapping from CBCT images to planning CT images. The 627 CBCT‐CT pairs of 11 patients were used to train the network, and the proposed algorithm was evaluated in terms of the mean absolute error (MAE), average peak signal‐to‐noise ratio (PSNR) and so on. The proposed method was compared with other methods to illustrate its effectiveness.ResultsThe proposed method can remove artifacts (including streaking, shadowing, and cupping) in the CBCT image. Furthermore, key details such as the internal contours and texture information of the pelvic region are well preserved. Analysis of the average CT number, average MAE, and average PSNR indicated that the proposed method improved the image quality. The test results obtained with the chest data also indicated that the proposed method could be applied to other anatomies.ConclusionsAlthough the CBCT‐CT image pairs are not completely matched at the pixel level, the method proposed in this paper can effectively correct the artifacts in the CBCT slices and improve the image quality. The average CT number of the regions of interest (including bones, skin) also exhibited a significant improvement. Furthermore, the proposed method can be applied to enhance the performance on such applications as dose estimation and segmentation.

Reliability of cephalograms derived of cone beam computed tomography versus lateral cephalograms to estimate cervical vertebrae maturity in a Peruvian population: A retrospective study

Cone beam computed tomography (CBCT) images can be useful for estimating cervical vertebrae maturity (CVM). The aim of this study was to evaluate the reliability of cephalograms derived from CBCT versus lateral cephalograms (LC) to estimate the CVM in a Peruvian population. The sample evaluated consisted of 40 cephalograms derived from CBCT and 40 LC images from individuals aged 10-19 years. One trained and calibrated observer (Kappa scores≥0.90) interpreted the CBCT and LC images twice. Intra-observer reliability of each maturation stage on CBCT sagittal slices and LC images were analysed using the weighted kappa statistics (α=0.05). Comparison of CVM stages between CBCT slices and LC images were analysed by the Spearman rank correlation coefficient, p<0.05. The weighted kappa test showed almost perfect intra-observer agreement for the CVM stages using the CBCT sagittal slices (0.873). Considering the LC images, the weighted kappa test showed almost perfect intra-observer agreement too (0.937). In both intra-observer agreement, the difference was limited to one maturation stage of the CVM method. The first and second intra-observer agreement for the CVM stages between the CBCT sagittal slices and LC images were almost perfect (0.937 and 0.874). High correlation values at the first (0.975) and second (0.976) intra-observer agreement for the CVM stages between CBCT sagittal slices and LC images were also found. CBCT is a reliable method for CVM assessment and can be used as an alternative method for this purpose. The orthodontists might use the CBCT scans as a valuable tool for CVM method estimation.

Comparing Unet training with three different datasets to correct CBCT images for prostate radiotherapy dose calculations

Image intensity correction is crucial to enable cone beam computed tomography (CBCT) based radiotherapy dose calculations. This study evaluated three different deep learning based correction methods using a U-shaped convolutional neural network architecture (Unet) in terms of their photon and proton dose calculation accuracy.CT and CBCT imaging data of 42 prostate cancer patients were included. For target ground truth data generation, a CBCT correction method based on CT to CBCT deformable image registration (DIR) was used. The method yields a deformed CT called (i) virtual CT (vCT) which is used to generate (ii) corrected CBCT projections allowing the reconstruction of (iii) a final corrected CBCT image.The single Unet architecture was trained using these three different datasets: (Unet1) raw and corrected CBCT projections, (Unet2) raw CBCT and vCT image slices and (Unet3) raw and reference corrected CBCT image slices. Volumetric arc therapy (VMAT) and proton pencil beam scanning (PBS) single field uniform dose (SFUD) plans were optimized on the reference corrected image and recalculated on the obtained Unet-corrected CBCT images.The mean error (ME) and mean absolute error (MAE) for Unet1/2/3 were Hounsfield units (HU) and HU. The 1% dose difference pass rates were better than 98.4% for VMAT for 8 test patients not seen during training, with little difference between Unets. Gamma evaluation results were even better. For protons a gamma evaluation was employed to account for small range shifts, and mm pass rates for Unet1/2/3 were better than and 91%. A 3 mm range difference threshold was established. Only for Unet3 the 5th and 95th percentiles of the range difference distributions over all fields, test patients and dose profiles were within this threshold.A single Unet architecture was successfully trained using both CBCT projections and CBCT image slices. Since the results of the other Unets were poorer than Unet3, we conclude that training using corrected CBCT image slices as target data is optimal for PBS SFUD proton dose calculations, while for VMAT all Unets provided sufficient accuracy.

What Are the Risk Factors for External Root Resorption of Second Molars Associated With Impacted Third Molars? A Cone-Beam Computed Tomography Study

In relation to an impacted third molar, which is the most frequently impacted tooth, external root resorption (ERR) or dental caries can be seen on the distal surface of the adjacent secondmolar. The purpose of this study was to investigate the risk factors for ERR in secondmolars associated with impacted third molars using cone-beam computed tomography (CBCT). In this cross-sectional study, the presence of ERR on the adjacent secondmolar was investigated retrospectively on sagittal and axial CBCT slices of patients who underwent CBCT examination for diagnostic reasons (surgical removal of third molars, orthodontic assessments, and so on) between 2013 and 2017 at the Necmettin Erbakan University Faculty of Dentistry, Konya, Turkey. The primary outcome variable was ERR (yes or no). Predictor variables included demographic (age and gender) and radiographic (impacted tooth angulation and tooth type) parameters. Given that there are multiple observations per patient (1 to 4 impacted teeth), 1 third molar per patient was selected at random for study inclusion. Statistical analysis was performed using descriptive statistics, the Mann-Whitney U test, and the Pearson χ2 test. Logistic regression analysis was used to determine the risk factors for ERR in secondmolars. The Cohen κ test was used to test intraobserver agreement. The significance level was set at P<.05. Two hundred patients were analyzed, and of the 200 impacted third molars evaluated, 42 (21%) showed ERR. The severity of resorption increased with aging (P<.05). Logistic regression analysis indicated that tooth type and inclination of the third molars could predict the occurrence of ERR associated with an impacted third molar (P<.05). Mesioangular and horizontal inclinations and impacted mandibular third molars posed a greater risk of ERR lesions in adjacent secondmolars than other inclinations (distoangular and vertical) and maxillary third molars.

Lack of significant volumetric alteration after rapid maxillary expansion supports the use of frontal sinuses for human identification purposes

Abstract Aim The present study aimed to assess the volume of the frontal sinuses before and after rapid maxillary expansion (RME). Material and methods The sample consisted of 12 subjects (8 females and 4 males) with maxillary deficiency aged between 10 and 15 years old. In order to treat the skeletal deficiency, RME was performed using Hyrax system. Cone Beam Computed Tomography (CBCT) scans were obtained from each subject before (T1) and 120 days after (T2) the RME. A table digitizer G-Pen F350 (Genius, Taipei, Taiwan) was used to select the area of the frontal sinuses in CBCT slices. The volume of the sinuses was quantified in T1 and T2. T-test for paired samples was used to compare the differences between the volume of the frontal sinuses before and after RME Results The mean volume of the frontal sinuses before and after the RME was 3.03 mm3 (ranging from 2.20 mm3 to 4.40 mm3) and 3.21 mm3 (ranging from 2.55 mm3 to 4.52 mm3), respectively. Differences in volume between T1 and T2 were not statistically significant (p > .05). The present study indicates that the frontal sinuses do not modify considerably in volume after RME. Conclusion From the forensic scope, this outcome supports the usefulness of the frontal sinuses for ante-mortem and post-mortem comparisons in human identification cases.

Accuracy and Reliability of Cone-Beam Computed Tomography for Linear and Volumetric Mandibular Condyle Measurements. A Human Cadaver Study

The accuracy of Cone-Beam Computed Tomography (CBCT) on linear and volumetric measurements on condyles has only been assessed on dry skulls. The aim of this study was to evaluate the reliability and accuracy of linear and volumetric measurements of mandibular condyles in the presence of soft tissues using CBCT. Six embalmed cadaver heads were used. CBCT scans were taken, followed by the extraction of the condyles. The water displacement technique was used to calculate the volumes of the condyles and three linear measurements were made using a digital caliper, these measurements serving as the gold standard. Surface models of the condyles were obtained using a 3D scanner, and superimposed onto the CBCT images. Condyles were isolated on the CBCT render volume using the surface models as reference and volumes were measured. Linear measurements were made on CBCT slices. The CBCT method was found to be reliable for both volumetric and linear measurements (CV < 3%; CCI > 0.90). Highly accurate values were obtained for the three linear measurements and volume. CBCT is a reliable and accurate method for taking volumetric and linear measurements on mandibular condyles in the presence of soft tissue, and so a valid tool for clinical diagnosis.

A novel surrogate to identify anatomical changes during radiotherapy of head and neck cancer patients.

To develop a novel method to monitor external anatomical changes in head and neck cancer patients in order to triage possible adaptive radiotherapy needs. The presented approach aims to provide information on internal anatomical changes based on variations observed in external anatomy. Setup Cone Beam Computed Tomography (CBCT) images are processed to produce an accurate external contour of the patient's skin. After registering the CBCTs to the reference planning CT, the external contours from each CBCT are transferred to the initial - first week - CBCT. Contour radii, defined as the distances between an external contour and the isocenter projection in each CBCT slice, are calculated for each scan over the full 360 degrees. The changes in external anatomy are then quantified by the difference in radial distance between the external contours of any secondary CBCT relative to the initial CBCT. Finally, the radial difference is displayed in cylindrical coordinates as a 2D intensity map to highlight regions of interests with significant changes. Weekly CBCT scans from 15 head and neck patients were retrospectively analyzed to demonstrate the utility of this approach as a proof of principle. External changes suggested by the 2D radial difference map of an example patient after 23 fractions were then correlated with the changes in the gross tumor volumes and organs at risks. The resulting dosimetric effects were evaluated. An interactive standalone software application has been developed to facilitate the generation and the interpretation of the 2D intensity map. The 2D radial difference maps provided qualitative and quantitative information, such as the location and the magnitude of external contour changes and the rate at which these deviations occur. Out of the 15 patients, 10 presented clear evidence of general external volume shrinkage due to weight loss, and nine patients had at least one site of local shrinkage. Only two patients showed no signs of anatomical change during their entire treatment course. For the example patient, the mean (±σ) radial difference was 6.7 (±3.0) mm for the left parotid and 7.3 (±2.5) mm for the right parotid. The mean dose to the left and right parotids increased from 20.1 Gy to 30 Gy and from 16.3 Gy to 29.6 Gy, respectively. This novel method provides an efficient tool to visualize 3D external anatomical changes on a single 2D map. It quickly pinpoints the location of differences in anatomy during the course of radiotherapy, which can help physicians determine if a treatment plan needs to be adapted. The interactive graphic user interface developed in this study will be evaluated in an adaptive radiotherapy workflow for head and neck patients in a future prospective trial.

Comparison of Cone Beam Computed Tomography and Multi Slice Computed Tomography Image Quality of Human Dried Mandible using 10 Anatomical Landmarks.

Cone Beam Computed Tomography (CBCT) has gained a broad acceptance in dentomaxillofacial imaging. Computed Tomography (CT) is another imaging modality for diagnosis and preoperative assessments of the head and neck region. Considering the increased radiation exposure and high cost of CT, this study sought to subjectively assess the image quality of CBCT and Multi Slice CT (MSCT). A dry human mandible was scanned by five CBCT systems (New Tom 3G, Scanora, CRANEX 3D, Promax and Galileos) and one MSCT system. Three independent oral and maxillofacial radiologists reviewed the CBCT and MSCT scans for the quality of 10 landmarks namely mental foramen, trabecular bone, Periodontal Ligament (PDL), dentin, incisive canal, mandibular canal, dental pulp, enamel, lamina dura and cortical bone using a five-point scale. Significant differences were found between MSCT and CBCT and among the five CBCT systems (p<0.05) in visualization of different anatomical structures. A fine structure such as the incisive canal was significantly less visible and more variable among the systems in comparison with other anatomical landmarks such as the mental foramen, mandibular canal, cortical bone, dental pulp, enamel and dentin (p<0.05). The Cranex 3D and Promax systems were superior to MSCT and all other CBCT systems in visualizing anatomical structures. The CBCT image quality was superior to that of MSCT even though some variability existed among different CBCT systems in visualizing fine structures. Considering the low radiation dose and high resolution, CBCT may be beneficial for dentomaxillofacial imaging.

Classification of teeth in cone-beam CT using deep convolutional neural network

Dental records play an important role in forensic identification. To this end, postmortem dental findings and teeth conditions are recorded in a dental chart and compared with those of antemortem records. However, most dentists are inexperienced at recording the dental chart for corpses, and it is a physically and mentally laborious task, especially in large scale disasters. Our goal is to automate the dental filing process by using dental x-ray images. In this study, we investigated the application of a deep convolutional neural network (DCNN) for classifying tooth types on dental cone-beam computed tomography (CT) images. Regions of interest (ROIs) including single teeth were extracted from CT slices. Fifty two CT volumes were randomly divided into 42 training and 10 test cases, and the ROIs obtained from the training cases were used for training the DCNN. For examining the sampling effect, random sampling was performed 3 times, and training and testing were repeated. We used the AlexNet network architecture provided in the Caffe framework, which consists of 5 convolution layers, 3 pooling layers, and 2 full connection layers. For reducing the overtraining effect, we augmented the data by image rotation and intensity transformation. The test ROIs were classified into 7 tooth types by the trained network. The average classification accuracy using the augmented training data by image rotation and intensity transformation was 88.8%. Compared with the result without data augmentation, data augmentation resulted in an approximately 5% improvement in classification accuracy. This indicates that the further improvement can be expected by expanding the CT dataset. Unlike the conventional methods, the proposed method is advantageous in obtaining high classification accuracy without the need for precise tooth segmentation. The proposed tooth classification method can be useful in automatic filing of dental charts for forensic identification.

The visibility of mandibular canal on orthoradial and oblique CBCT slices at molar implant sites

ABSTRACTThe aim of the present study was to compare visibility of the mandibular canal on cone beam computed tomography (CBCT)-based orthoradial and oblique slices at molar implant sites. CBCT images for 132 mandibular molar implant sites were selected for the study. After generating orthoradial and oblique slices, two observers evaluated the visibility of the mandibular canal using three-point scoring scale (1–3, good to excellent). Wilcoxon signed-rank test compared the visibility scores of the two slices. Both orthoradial and oblique slices obtained from CBCT had only very good to excellent mandibular canal visibility scores. At 114 mandibular molar implant sites, the visibility score was equal on both orthoradial and oblique slices. Although the visibility score was higher on orthoradial slices for 12 implant sites, the visibility score was higher for six implant sites on oblique slices and the difference was not significant. Therefore, the visibility of the mandibular canal was excellent and comparable on most of orthoradial and oblique slices obtained from CBCT images.