High-resolution Cone-beam CT Research Articles

Gantry-Free High-Resolution Cone-Beam CT: Efficacy for Distal Radius and Scaphoid Fracture Detection and Characterization

Gantry-free cone-beam CT (CBCT) allows for comfortable patient positioning due to an open scanner architecture. Since CBCT without gantry is not yet established for clinical wrist trauma imaging, this study's aim was to investigate its diagnostic value in the preoperative workup of patients with distal radius and scaphoid fractures. Within a 12-month period, 113 patients with severe wrist trauma underwent both radiography and CBCT with the same gantry-free multi-use scanner before surgery. Two radiologists retrospectively analyzed all datasets for the morphology of distal radius (n=95) and scaphoid fractures (n=20). In all 115 wrists (two bilateral injuries), surgical reports served as the standard of reference. While accuracy for distal radius fractures was comparable among CBCT and radiographs, the former was superior with regard to scaphoid fractures (Reader 1: 100.0% vs. 75.0%; Reader 2: 100.0% vs. 65.0%). Accuracy for multi-fragmentary radius injuries (100.0% vs. 90.5%; 100.0% vs. 93.7%), and articular affliction (99.0% vs. 84.2%; 100.0% vs. 83.2%) was also higher in CBCT. Regarding scaphoid fractures, CBCT proved superior for diagnosis of proximal pole or waist involvement (100.0% vs. 70.0%; 100.0% vs. 65.0%) and comminuted patterns (100.0% vs. 70.0%; 100.0% vs. 75.0%). Median effective dose of CBCT was as low as 3.65 µSv compared with 0.16 µSv for standard radiography. Gantry-free CBCT allows for excellent diagnostic accuracy in the assessment of distal radius and scaphoid fracture morphology. Even in patients with limited mobility, very low radiation dose is sufficient to maintain high image quality.

A non-invasive method for the assessment of gingival thickness in the aesthetic zone and the concept of the gingival geometric ratio in an Asian population

The aim of this study was to investigate the gingival thickness and biologic width in the aesthetic zone (maxillary central and lateral incisors) in an Asian population using cone beam computed tomography (CBCT) as a non-invasive measurement method, prior to immediate implant placement. The gingival geometric ratio is introduced as a new parameter for assessing soft tissue stability and hence predicting the aesthetic outcome. The gingival thickness, biologic width category (normal, high, and low crest), and gingival geometric ratio (shape and configuration of the gingival tissues) were assessed for 171 central and 175 lateral incisors on high-resolution CBCT images. Thick gingivae were found in 93.6% of the central incisors and 64% of the lateral incisors (P < 0.001). The difference in thickness between the central and lateral incisors was statistically significant (P < 0.001). Regarding the biologic width of the facial gingival tissue, the majority of central (64.8%) and lateral (64.3%) incisors were categorized as low crest (>3 mm). The study found that most of the gingivae of the maxillary central incisors were thick, while thin gingivae were more prevalent in the lateral incisors. Therefore, an individual patient may have different gingival thickness types, and ‘one individual, one gingival biotype’ may not be true. Furthermore, the majority of the facial gingival tissues of the maxillary incisors were found to be low crest.

Clinical evaluation of high-resolution cone-beam computed tomography for the implantation of flow-diverter stents in intracranial aneurysms

It is well-established that complete expansion and proper apposition to the vessel wall of flow-diverter stents are critical for optimizing endovascular aneurysm outcomes by using flow diversion techniques. We aimed to evaluate the clinical value of high-resolution cone-beam CT (HR-CBCT) upon flow-diverter stent implantation in intracranial aneurysms. In this study, we retrospectively analyzed the clinical data of eighty-one patients (101 intracranial aneurysms) who underwent flow-diverter stent implantation (Pipeline™ or Tubridge™). Images were reconstructed using conventional cone-beam CT (CBCT)(voxel size 0.43 mm isotropic) and HR-CBCT(voxel size 0.15 mm isotropic). Immediately after stent deployment, dual volume 3D fusion images were obtained from 3D-digital subtraction angiography (DSA) and HR-CBCT. The image quality for stent visualization was graded from 0 to 2 (0:not able to assess, 1:limited, but able to assess; 2:clear visualization), and the stent expansion status (full, under-expanded or poor apposition) was also recorded. Finally, patients were treated using flow-diverter stents (n = 92: 17 Pipeline and 75 Tubridge). Compared to CBCT, HR-CBCT led to improved visualization of the structures of the stents and significantly improved the image quality (mean score: 0.59 ± 0.67 vs. 1.6 ± 0.63, P < 0.001). For 28 stents (seven Pipeline and 21 Tubridge), partially incomplete apposition was observed by HR-CBCT but not by conventional CBCT and resolved by microguidewire looping dilation or balloon dilation. High-resolution cone-beam CT could better display flow-diverter stent details and yielded an improved image quality, which facilitated the assessment of stent deployment, potentially reducing the incidence of complications.

Wavelet Guided 3D Deep Model to improve Dental Microfracture Detection.

Epidemiological studies indicate that microfractures (cracks) are the third most common cause of tooth loss in industrialized countries. An undetected crack will continue to progress, often with significant pain, until the tooth is lost. Previous attempts to utilize cone beam computed tomography (CBCT) for detecting cracks in teeth had very limited success. We propose a model that detects cracked teeth in high resolution (hr) CBCT scans by combining signal enhancement with a deep CNNbased crack detection model. We perform experiments on a dataset of 45 ex-vivo human teeth with 31 cracked and 14 controls. We demonstrate that a model that combines classical wavelet-based features with a deep 3D CNN model can improve fractured tooth detection accuracy in both micro-Computed Tomography (ground truth) and hr-CBCT scans. The CNN model is trained to predict a probability map showing the most likely fractured regions. Based on this fracture probability map we detect the presence of fracture and are able to differentiate a fractured tooth from a control tooth. We compare these results to a 2D CNN-based approach and we show that our approach provides superior detection results. We also show that the proposed solution is able to outperform oral and maxillofacial radiologists in detecting fractures from the hr-CBCT scans. Early detection of cracks will lead to the design of more appropriate treatments and longer tooth retention.

Tooth and root size as determined from 0.25- and 0.30-mm voxel size cone-beam CT imaging when contrasted to micro-CT scans (0.06 mm): An ex vivo study.

Objective:To quantify tooth volume differences from extracted teeth when using three different three-dimensional (3D) computed tomography (CT)-based imaging modalities.Design:Ex vivo study.Setting:Laboratory and clinics of the University of Alberta.Methods:Cone-beam CT (CBCT) of 12 extracted teeth were scanned using 0.25- and 0.30-mm voxel size from CBCT and a 0.06-mm voxel size from micro-CT (reference standard). 3D reconstructions for each tooth from each imaging modality were made through the software ITK-SNAP®. The mean volume differences between each pair of scanning modalities were calculated and then compared and analysed through a repeated measures ANOVA.Results:The average overestimations of the teeth volume were 15.2% for the high-resolution CBCT and 28.1% for the low-resolution CBCT compared to micro-CT measurements. The differences in absolute volume were 81.6 mm3 and 152.8 mm3, respectively. All differences were statistically significant (P < 0.05).Conclusions:Orthodontists and researchers who assess root resorption through CBCT imaging should be aware that the depicted volumes may likely be overestimating tooth volume and camouflaging real root volumetric treatment changes.

CT imaging-based approaches to cochlear duct length estimation\u2014a human temporal bone study

ObjectivesKnowledge about cochlear duct length (CDL) may assist electrode choice in cochlear implantation (CI). However, no gold standard for clinical applicable estimation of CDL exists. The aim of this study is (1) to determine the most reliable radiological imaging method and imaging processing software for measuring CDL from clinical routine imaging and (2) to accurately predict the insertion depth of the CI electrode.MethodsTwenty human temporal bones were examined using different sectional imaging techniques (high-resolution computed tomography [HRCT] and cone beam computed tomography [CBCT]). CDL was measured using three methods: length estimation using (1) a dedicated preclinical 3D reconstruction software, (2) the established A-value method, and (3) a clinically approved otosurgical planning software. Temporal bones were implanted with a 31.5-mm CI electrode and measurements were compared to a reference based on the CI electrode insertion angle measured by radiographs in Stenvers projection (CDLreference).ResultsA mean cochlear coverage of 74% (SD 7.4%) was found. The CDLreference showed significant differences to each other method (p < 0.001). The strongest correlation to the CDLreference was found for the otosurgical planning software-based method obtained from HRCT (CDLSW-HRCT; r = 0.87, p < 0.001) and from CBCT (CDLSW-CBCT; r = 0.76, p < 0.001). Overall, CDL was underestimated by each applied method. The inter-rater reliability was fair for the CDL estimation based on 3D reconstruction from CBCT (CDL3D-CBCT; intra-class correlation coefficient [ICC] = 0.43), good for CDL estimation based on 3D reconstruction from HRCT (CDL3D-HRCT; ICC = 0.71), poor for CDL estimation based on the A-value method from HRCT (CDLA-HRCT; ICC = 0.29), and excellent for CDL estimation based on the A-value method from CBCT (CDLA-CBCT; ICC = 0.87) as well as for the CDLSW-HRCT (ICC = 0.94), CDLSW-CBCT (ICC = 0.94) and CDLreference (ICC = 0.87).ConclusionsAll approaches would have led to an electrode choice of rather too short electrodes. Concerning treatment decisions based on CDL measurements, the otosurgical planning software-based method has to be recommended. The best inter-rater reliability was found for CDLA-CBCT, for CDLSW-HRCT, for CDLSW-CBCT, and for CDLreference.Key Points• Clinically applicable calculations using high-resolution CT and cone beam CT underestimate the cochlear size.• Ten percent of cochlear duct length need to be added to current calculations in order to predict the postoperative CI electrode position.• The clinically approved otosurgical planning software-based method software is the most suitable to estimate the cochlear duct length and shows an excellent inter-rater reliability.

Layered deep learning for automatic mandibular segmentation in cone-beam computed tomography

ObjectiveTo develop and validate a layered deep learning algorithm which automatically creates three-dimensional (3D) surface models of the human mandible out of cone-beam computed tomography (CBCT) imaging. Materials & methodsTwo convolutional networks using a 3D U-Net architecture were combined and deployed in a cloud-based artificial intelligence (AI) model. The AI model was trained in two phases and iteratively improved to optimize the segmentation result using 160 anonymized full skull CBCT scans of orthognathic surgery patients (70 preoperative scans and 90 postoperative scans). Finally, the final AI model was tested by assessing timing, consistency, and accuracy on a separate testing dataset of 15 pre- and 15 postoperative full skull CBCT scans. The AI model was compared to user refined AI segmentations (RAI) and to semi-automatic segmentation (SA), which is the current clinical standard. The time needed for segmentation was measured in seconds. Intra- and inter-operator consistency were assessed to check if the segmentation protocols delivered reproducible results. The following consistency metrics were used: intersection over union (IoU), dice similarity coefficient (DSC), Hausdorff distance (HD), absolute volume difference and root mean square (RMS) distance. To evaluate the match of the AI and RAI results to those of the SA method, their accuracy was measured using IoU, DSC, HD, absolute volume difference and RMS distance. ResultsOn average, SA took 1218.4s. RAI showed a significant drop (p<0.0001) in timing to 456.5s (2.7-fold decrease). The AI method only took 17s (71.3-fold decrease). The average intra-operator IoU for RAI was 99.5% compared to 96.9% for SA. For inter-operator consistency, RAI scored an IoU of 99.6% compared to 94.6% for SA. The AI method was always consistent by default. In both the intra- and inter-operator consistency assessments, RAI outperformed SA on all metrics indicative of better consistency. With SA as the ground truth, AI and RAI scored an IoU of 94.6% and 94.4%, respectively. All accuracy metrics were similar for AI and RAI, meaning that both methods produce 3D models that closely match those produced by SA. ConclusionA layered 3D U-Net architecture deep learning algorithm, with and without additional user refinements, improves time-efficiency, reduces operator error, and provides excellent accuracy when benchmarked against the clinical standard. Clinical significanceSemi-automatic segmentation in CBCT imaging is time-consuming and allows user-induced errors. Layered convolutional neural networks using a 3D U-Net architecture allow direct segmentation of high-resolution CBCT images. This approach creates 3D mandibular models in a more time-efficient and consistent way. It is accurate when benchmarked to semi-automatic segmentation.

Dental microfracture detection using wavelet features and machine learning.

Microfractures (cracks) are the third most common cause of tooth loss in industrialized countries. If they are not detected early, they continue to progress until the tooth is lost. Cone beam computed tomography (CBCT) has been used to detect microfractures, but has had very limited success. We propose an algorithm to detect cracked teeth that pairs high resolution (hr) CBCT scans with advanced image analysis and machine learning. First, microfractures were simulated in extracted human teeth (n=22). hr-CBCT and microCT scans of the fractured and control teeth (n=14) were obtained. Wavelet pyramid construction was used to generate a phase image of the Fourier transformed scan which were fed to a U-Net deep learning architecture that localizes the orientation and extent of the crack which yields slice-wise probability maps that indicate the presence of microfractures. We then examine the ratio of high-probability voxels to total tooth volume to determine the likelihood of cracks per tooth. In microCT and hr-CBCT scans, fractured teeth have higher numbers of such voxels compared to control teeth. The proposed analytical framework provides a novel way to quantify the structural breakdown of teeth, that was not possible before. Future work will expand our machine learning framework to 3D volumes, improve our feature extraction in hr-CBCT and clinically validate this model. Early detection of microfractures will lead to more appropriate treatment and longer tooth retention.

Sinusitis of dental origin

In recent years, an increasing number of dental infections of the maxillary sinus has been observed. A prerequisite for a bacterial infection of the maxillary sinus is the perforation of Schneider's membrane. Pathogenetically, the ostiomeatal unit is only secondarily involved due to the infection ascending from the maxillary sinus floor. Besides the anamnesis, imaging procedures are important, whereby the high-resolution CT and CBCT (cone beam CT) have a special task due to their three-dimensional resolution. A dental X-ray or a dental examination for diagnosis is not sufficient in many cases. Due to the anatomy, the molars in particular are to be regarded as the cause of dentogenic sinusitis. The germ spectrum is polymicrobial with a dominance of anaerobes. Therapeutically, we favour one-stage surgery with rehabilitation of the underlying process and functional sinus surgery. Functional sinus surgery can also make a significant contribution to the rehabilitation of inflammatory complications in implantology.

Flow Diverter Apposition in Patients with Large or Giant Intracranial Aneurysms Evaluated on Three-Dimensional Fusion Images Acquired by High-Resolution Cone-Beam Computed Tomography and Digital Subtraction Angiography

To investigate flow diverter (FD) apposition on fused images acquired by high-resolution cone-beam computed tomography (CBCT) and 3-dimensional (3D) digital subtraction angiography. Patients with large or giant internal carotid artery aneurysms treated with Pipeline FDs who underwent CBCT imaging at our institution between October 2016 and May 2019 were included. Two neurosurgeons measured the maximum malapposition between FDs and vessel walls on 3D fusion images of high-resolution CBCT images displaying the FD and 3D digital subtraction angiography images displaying the vessels. Associations between the relative malapposition, FD diameter, vessel diameter, proximal and distal vessel diameter discrepancy, and siphon angle were evaluated by linear regression analysis. Inter-rater and intermethod (3D and 2D image) agreements of the malapposition measurements were assessed by Bland-Altman analysis and by interclass correlation coefficients. Images of 2 patients were excluded because of image artifacts or fusion errors, and 3D fusion images were acquired in the remaining 26 patients. Our results did not suggest that relative malapposition was associated with vessel diameter (P= 0.12), vessel diameter discrepancy (P= 0.60), or syphon angle (P= 0.34), but relative malapposition increased by an estimated 13% (95% confidence interval: 4%-23%, P= 0.006) for each 1 mm increase in FD diameter. Inter-rater and intermethod agreements for apposition measurements were excellent and good, respectively. Three-dimensional fusion images provided clear visualization of structures of both the stent and parent artery with excellent diagnostic reliability. Careful deployment may be needed for FDs with larger diameters, as they tended to have larger relative malapposition.

Skull Segmentation from CBCT Images via Voxel-Based Rendering.

Skull segmentation from three-dimensional (3D) cone-beam computed tomography (CBCT) images is critical for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Convolutional neural network (CNN)-based methods are currently dominating volumetric image segmentation, but these methods suffer from the limited GPU memory and the large image size (e.g., 512 × 512 × 448). Typical ad-hoc strategies, such as down-sampling or patch cropping, will degrade segmentation accuracy due to insufficient capturing of local fine details or global contextual information. Other methods such as Global-Local Networks (GLNet) are focusing on the improvement of neural networks, aiming to combine the local details and the global contextual information in a GPU memory-efficient manner. However, all these methods are operating on regular grids, which are computationally inefficient for volumetric image segmentation. In this work, we propose a novel VoxelRend-based network (VR-U-Net) by combining a memory-efficient variant of 3D U-Net with a voxel-based rendering (VoxelRend) module that refines local details via voxel-based predictions on non-regular grids. Establishing on relatively coarse feature maps, the VoxelRend module achieves significant improvement of segmentation accuracy with a fraction of GPU memory consumption. We evaluate our proposed VR-U-Net in the skull segmentation task on a high-resolution CBCT dataset collected from local hospitals. Experimental results show that the proposed VR-U-Net yields high-quality segmentation results in a memory-efficient manner, highlighting the practical value of our method.

The influence of voxel size and artifact reduction on the detection of vertical root fracture in endodontically treated teeth

Objective The aim of this study was to evaluate the effect of voxel size and artefact reduction (AR) on the identification of vertical root fractures (VRFs) in endodontically treated teeth. Methods A total of a hundred sound, extracted human mandibular single-rooted premolars were decoronated, after which root canal preparation was performed, canals were filled with gutta percha by single cone technique. Randomly selected fifty specimens were fractured, repositioned and glued together. The teeth were examined with cone beam computed tomography (CBCT) in five different voxel sizes (0.125, 0.200, 0.250, 0.300, and 0.400 voxels). Two scans were performed for each tooth, one with AR and one without AR. Two radiologists evaluated the CBCT scans. Results All voxel dimensions were successful in detecting VRFs in CBCT scans. But as the voxel size increased, the percentage of detecting VRFs decreased. High accuracy, sensitivity, specificity and predictive values were found for VRF detection on CBCT scans. Accuracy and sensitivity values decreased (from 100 to 82) while voxel dimensions increased (from 0.125 to 0.400). High-resolution images (0.125, 0.200, and 0.250 voxels) caused an increase in sensitivity for detection of VRFs. AR did not affect the accuracy, sensitivity, specificity and predictive values for VRF detection on CBCT scans. Conclusions High-resolution CBCT images resulted in an increase in sensitivity and specificity for detection of VRFs compared with lower-resolution CBCT images. The use of AR did not further improve its diagnostic potential.

Comparison of Cone Beam Computed Tomography and Digital Radiography in Detecting Separated Endodontic Files and Strip Perforation

The separation of endodontic files and strip perforation are among procedural intraoperative complications which may ultimately lead to the failure of root canal treatment. The aim of the present study was to compare the diagnostic potential of cone beam computed tomography (CBCT) and digital periapical radiographs in detecting separated rotary files and strip perforation in filled canals. Fifty human mandibular molars were selected for this study. The teeth were randomly divided into two groups based on endodontic errors (i.e., file separation and strip perforation). In each group, 25 of 50 mesial canals were randomly chosen for simulating the errors, while the other 25 canals were considered as the control group. In group one, a simulation of the separation of rotary files was performed using ProTaper F2 files. Strip perforation of the root canals in group two was achieved by number 2 and 3 Gates Glidden drills in the coronal third of the root canals. Digital periapical radiographs in two different horizontal angles and high-resolution CBCT scans were obtained from the teeth mounted on a dry human mandible with simulated soft tissue covering. Three experienced observers who were unaware of the study groups evaluated the digital periapical and CBCT image sets in two separate readings. Intraobserver and interobserver agreements, as well as accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were calculated and compared. Intraobserver and interobserver agreements ranged from poor to excellent and poor to good, respectively. The accuracy, sensitivity, specificity, PPV, and NPV for digital radiography in detecting separated files were 0.950, 0.813, 0.957, 0.929, and 0.880, respectively. The same values for CBCT were 0.747, 0.667, 0.900, 0.833, and 0.783, respectively. For the diagnosis of strip perforation, these values were 0.855, 0.800, 0.909, 0.889, and 0.833 for periapical radiography and 0.955, 1.000, 0.920, 0.926, and 1.000 for CBCT. In conclusion, CBCT was superior for diagnosing strip perforation of the filled root canals, while digital periapical radiographs performed better in the detection of separated rotary files.

Accuracy evaluation of 3D printed interim prosthesis fabrication using a CBCT scanning based digital model.

ObjectivesThis study aimed to evaluate the marginal and internal gaps in 3D-printed interim crowns made from digital models of cone-beam computed tomography (CBCT) conversion data.Materials and methodsSixteen polyvinylsiloxane impressions were taken from patients for single crown restorations and were scanned using CBCT. The scanning data were converted to positive Standard Triangulation Language (STL) files using custom-developed software. The fabricated stone models were scanned with an intraoral optical scanner (IOS) to compare the surface accuracy with the STL data obtained by CBCT. The converted STL files were utilized to fabricate interim crowns with a photopolymer using a digital light-processing 3D printer. The replica method was used to analyze the accuracy. The marginal and internal gaps in the replica specimen of each interim crown were measured with a digital microscope. The Friedman test and Mann-Whitney U test (Wilcoxon-signed rank test) were conducted to compare the measurements of the marginal and internal gaps with a 95% level of confidence.ResultsThe root-mean-square values of the CBCT and IOS ranged from 41.00 to 126.60 μm, and the mean was 60.12 μm. The mean values of the marginal, internal, and total gaps were 132.96 (±139.23) μm, 137.86 (±103.09) μm, and 135.68 (±120.30) μm, respectively. There were no statistically significant differences in the marginal or internal gaps between the mesiodistal and buccolingual surfaces, but the marginal area (132.96 μm) and occlusal area (255.88 μm) had significant mean differences.ConclusionThe marginal gap of the fabricated interim crowns based on CBCT STL data was within the acceptable range of clinical success. Through ongoing developments of high-resolution CBCT and the digital model conversion technique, CBCT might be an alternative method to acquire digital models for interim crown fabrication.

Assessing Inner Ear Volumetric Measurements by Using Three-Dimensional Reconstruction Imaging of High-Resolution Cone-Beam Computed Tomography

The aim of the study was to obtain volumetric data of the components of the inner ear using three-dimensional reconstruction of high-resolution cone-beam computed tomography (CBCT) images. Two hundred three CBCT image series of the temporal bone from 118 anatomically normal patients (55 women and 63 men; mean age: 49.4 ± 20.4 years) with different suspected disorders were included in this study. Normative volumetric measurements of the inner ear, the cochlea, the semicircular canals (SSC), and the vestibule were determined using a semi-automated reconstruction method of the Workstation. Volumetric measurements were successfully completed in all 118 patients. Mean inner ear, cochlear, and vestibule volumes were statistically significantly larger in males than in females on both sides (p < 0.001). Regarding the semicircular canals, no statistically significant (p = 0.053) volume difference was found. The difference between the volumes on both sides was not significant. No correlation between the patient’s age and the volume of the compartments was seen (p > 0.05). There was no significant difference between mean bony inner ear volumes when the clinical diagnoses were compared (p > 0.05 for all clinical diagnoses and volumes). Our study concluded that three-dimensional reconstruction and assessment of the volumetric measurements of the inner ear can be obtained using high-resolution CBCT imaging.

Cone-Beam CT Compared to Multi-Slice CT for the Diagnostic Analysis of Conductive Hearing Loss: A Feasibility Study

Multislice computed tomography (MSCT) is commonly used as a diagnostic tool for patients with a conductive hearing loss. Recent studies indicate that cone-beam computed tomography (CBCT) may be used as a low-radiation dose alternative for temporal bone imaging. This study compares image quality and radiation dose between CBCT and MSCT when assessing anatomical landmarks related to conductive hearing loss. Five human cadaver heads (10 ears) were imaged on the NewTom 5G CBCT and the Discovery CT750 HD MSCT. Visibility of 16 anatomical landmarks of the middle and inner ear was assessed by two observers on a 4-point Likert scale. Furthermore, effective radiation dose was compared, and contrast-to-noise ratio and spatial resolution were measured with a phantom head. Image quality of CBCT was assessed as superior to MSCT. Effective radiation dose of the high-resolution CBCT protocol was 30.5% of the clinical MSCT dose. High-resolution CBCT was reported as having a higher spatial resolution and superior contrast-to-noise perception in comparison with MSCT. High-resolution CBCT was evaluated as superior to MSCT in the assessment of structures related to conductive hearing loss. Furthermore, CBCT imaging resulted in a considerably lower effective radiation dose.

小照射野・高解像力歯科用CT装置の開発から矯正領域への応用・展開

小照射野・高解像力歯科用CT装置の開発から矯正領域への応用・展開

Assessment of fractures in endodontically treated teeth restored with and without root canal posts using high-resolution cone beam computed tomography.

BackgroundRoot fractures are a diagnostic challenge for dentists in endodontic treatment. This study aimed to determine the relationship between the characteristics of tooth fractures and the presence of root canal posts in endodontically treated teeth using high-resolution cone beam computed tomography (CBCT). Material and MethodsFifty high-resolution CBCT scans of endodontically treated teeth with a diagnosis of fracture were obtained, of which 30 were from women and 20 were from men. These scans were acquired with three Veraviewepocs 3D units and one 3D Accuitomo 170 unit, with a 40 × 40-mm field of view and 125 μm voxel size. The variables assessed included the type of fracture, extent of fracture, type of retention, post length, cause of endodontic failure, location of the lesion, and time required to detect the fracture (difficulty score). For data analysis, the chi-squared test, Student’s t-test, and multiple linear regression (α <0.05) were used. ResultsNo association was found between the type of fracture and type of retention or between the type of fracture and its extent (P>0.05). On the other hand, the type of fracture significantly influenced the time required for its detection. Additionally, the most difficult plane for detecting the fracture and the difficulty score were associated, with statistically significant results. ConclusionsThe type of fracture in endodontically treated teeth was not associated with the type of post used for restoration. All of the CBCT systems used to detect tooth fracture showed the same efficiency. Key words:Cone-Beam CT, Tooth Fracture, Root Canal Post.

Very deep super-resolution for efficient cone-beam computed tomographic image restoration.

PurposeAs cone-beam computed tomography (CBCT) has become the most widely used 3-dimensional (3D) imaging modality in the dental field, storage space and costs for large-capacity data have become an important issue. Therefore, if 3D data can be stored at a clinically acceptable compression rate, the burden in terms of storage space and cost can be reduced and data can be managed more efficiently. In this study, a deep learning network for super-resolution was tested to restore compressed virtual CBCT images.Materials and MethodsVirtual CBCT image data were created with a publicly available online dataset (CQ500) of multidetector computed tomography images using CBCT reconstruction software (TIGRE). A very deep super-resolution (VDSR) network was trained to restore high-resolution virtual CBCT images from the low-resolution virtual CBCT images.ResultsThe images reconstructed by VDSR showed better image quality than bicubic interpolation in restored images at various scale ratios. The highest scale ratio with clinically acceptable reconstruction accuracy using VDSR was 2.1.ConclusionVDSR showed promising restoration accuracy in this study. In the future, it will be necessary to experiment with new deep learning algorithms and large-scale data for clinical application of this technology.

Visualization of stent apposition after stent-assisted coiling of intracranial aneurysms using high resolution 3D fusion images acquired by C-arm CT

PurposeWe used an imaging technique based on 3-dimensional (3D) C-arm CT to assess the apposition of three types of stents after coiling of intracranial aneurysms.MethodsAll patients with intracranial aneurysms were...