Cone-beam Computed Tomography Images Research Articles

Cone Beam Computed Tomography Image-Quality Improvement Using "One-Shot" Super-resolution.

Cone beam computed tomography (CBCT) images are convenient representations for obtaining information about patients' internal organs, but their lower image quality than those of treatment planning CT images constitutes an important shortcoming. Several proposed CBCT image-quality improvement methods based on deep learning require large amounts of training data. Our newly developed model using a super-resolution method, "one-shot" super-resolution (OSSR) based on the "zero-shot" super-resolution method, requires only small amounts of training data to improve CBCT image quality using only the target CBCT image and the paired treatment planning CT image. For this study, pelvic CBCT images and treatment planning CT images of 30 prostate cancer patients were used. We calculated the root mean squared error (RMSE), peak signal-to-noise ratio (PSNR), and structural similarity (SSIM) to evaluate image-quality improvement and normalized mutual information (NMI) as a quantitative evaluation of positional accuracy. Our proposed method can improve CBCT image quality without requiring large amounts of training data. After applying our proposed method, the resulting RMSE, PSNR, SSIM, and NMI between the CBCT images and the treatment planning CT images were as much as 0.86, 1.05, 1.03, and 1.31 times better than those obtained without using our proposed method. By comparison, CycleGAN exhibited values of 0.91, 1.03, 1.02, and 1.16. The proposed method achieved performance equivalent to that of CycleGAN, which requires images from approximately 30 patients for training. Findings demonstrated improvement of CBCT image quality using only the target CBCT images and the paired treatment planning CT images.

Application of artificial intelligence-based detection of furcation involvement in mandibular first molar using cone beam tomography images- a preliminary study

BackgroundRadiographs play a key role in diagnosis of periodontal diseases. Deep learning models have been explored for image analysis in periodontal diseases. However, there is lacuna of research in the deep learning model-based detection of furcation involvements [FI]. The objective of this study was to determine the accuracy of deep learning model in the detection of FI in axial CBCT images.MethodologyWe obtained initial dataset 285 axial CBCT images among which 143 were normal (without FI) and 142 were abnormal (with FI). Data augmentation technique was used to create 600(300 normal and 300 abnormal) images by using 200 images from the training dataset. Remaining 85(43 normal and 42 abnormal) images were kept for testing of model. ResNet101V2 with transfer learning was used employed for the analysis of images.ResultsTraining accuracy of model is 98%, valid accuracy is 97% and test accuracy is 91%. The precision and F1 score were 0.98 and 0.98 respectively. The Area under curve (AUC) was reported at 0.98. The test loss was reported at 0.2170.ConclusionThe deep learning model (ResNet101V2) can accurately detect the FI in axial CBCT images. However, since our study was preliminary in nature and carried out with relatively smaller dataset, a study with larger dataset will further confirm the accuracy of deep learning models.

Deep learning based super-resolution for CBCT dose reduction in radiotherapy.

Cone-beam computed tomography (CBCT) is a crucial daily imaging modality in image-guided and adaptive radiotherapy. However, the use of ionizing radiation in CBCT imaging increases the risk of secondary cancers, which is particularly concerning for pediatric patients. Deep learning super-resolution has shown promising results in enhancing the resolution of photographic and medical images but has not yet been explored in the context of CBCT dose reduction. To facilitate CBCT imaging dose reduction, we propose using an enhanced super-resolution generative adversarial network (ESRGAN) in both the projection and image domains to restore the image quality of low-dose CBCT. An extensive projection database, containing 2997 CBCT scans from head and neck cancer patients, was used to train two different ESRGAN models to generate super-resolution CBCTs. One model operated in the projection domain, using pairs of simulated low-resolution (low-dose) and original high-resolution (high-dose) projections and yielded CBCTSRpro. The other model operated in the image domain, using pairs of axial slices from reconstructed low-resolution and high-resolution CBCTs (CBCTLR and CBCTHR) and resulted in CBCTSRimg. Super-resolution CBCTs were evaluated in terms of image similarity (MAE, ME, PSNR, and SSIM), noise characteristics, spatial resolution, and registration accuracy, using the original CBCT as a reference. To test the perceptual difference between the original and super-resolution CBCT, we performed a visual Turing test. Visually, both super-resolution approaches in the projection and image domains improved the image quality of low-dose CBCTs. This was confirmed by the visual Turing test, that showed low accuracy, sensitivity, and specificity, indicating almost no perceptual difference between CBCTHR and the super-resolution CBCTs. CBCTSRimg (accuracy: 0.55, sensitivity: 0.59, specificity: 0.50) performed slightly better than CBCTSRpro (accuracy: 0.59, sensitivity: 0.61, specificity: 0.57). Image similarity metrics were affected by varying noise levels and did not reflect the visual improvements, with MAE/ME/PSNR/SSIM values of 110.4HU/2.9HU/40.4dB/0.82 for CBCTLR, 136.6HU/-0.4HU/38.6dB/0.77 for CBCTSRpro, and 128.2HU/1.9HU/39.0dB/0.80 for CBCTSRimg. In terms of spatial resolution, quantified by calculating 10% levels of the task transfer function, both CBCTSRpro and CBCTSRimg outperformed CBCTLR and nearly matched the reference CBCTHR (CBCTLR: 0.66lp/mm, CBCTSRpro: 0.88lp/mm, CBCTSRimg: 0.95lp/mm, CBCTHR: 1.01lp/mm). Noise characteristics of CBCTSRimg and CBCTSRpro were comparable to the reference CBCTHR. Registration parameters showed negligible differences for all CBCTs (CBCTLR, CBCTSRpro, CBCTSRimg), with average absolute differences in registration parameters being below 0.4° for rotations and below 0.06mm for translations (CBCTHR as reference). This study demonstrates that deep learning can be a valuable tool for CBCT dose reduction in CBCT-guided radiotherapy by acquiring low-dose CBCTs and restoring the image quality using deep learning super-resolution. The results suggest that higher quality images can be generated when super-resolution is performed in the image domain compared to the projection domain.

CT-augmented digital tomosynthesis image reconstruction in image-guided bronchoscopy interventions.

Transbronchial needle biopsy is crucial for diagnosing lung cancer, yet its efficacy depends on accurately localizing the target lesion and biopsy needle. Digital tomosynthesis (DTS) is considered a promising imaging modality for guiding bronchoscopy procedures due to its low radiation dose and small footprint relative to cone-beam computed tomography (CBCT). However, the image quality of DTS is still not sufficient for an accurate guidance, mainly due to its limited-angleacquisition. Preoperative computed tomography (CT) scans are often performed prior to bronchoscopy interventions for diagnosis or to plan the procedure. The CT images are of high quality and are characterized by a high spatial resolution compared to intraoperative DTS images. These patient-specific prior CT images and the intraoperative DTS images share a fair amount of anatomical information. The main differences only stem from patient positioning and respiratory motion. When these differences are addressed properly, prior CT images augment intraoperative DTS image reconstruction with strong prior knowledge and potentially enhance DTS imagequality. We propose in this work a prior-aided DTS image reconstruction technique leveraging prior CT images to improve DTS image quality. This technique is based on a recently published deformable CT-to-DTS image registration algorithm which is customized for bronchoscopy interventions. The main idea is to register a prior CT image to an intermediate DTS image reconstructed using the standard iterative algebraic reconstruction technique (ART), then to re-reconstruct the DTS image using ART and the registered prior CT image as a firstestimation. The proposed prior-aided reconstruction method was tested on a physical phantom and six patient bronchoscopy datasets. Real DTS data acquired with a pseudo-linear (PL) scan geometry and simulated DTS data generated according to a spherical ellipse (SE) scan geometry were considered. Results evaluated qualitatively by visual inspection and quantitatively by computing Pearson's correlation (PC) with respect to the reference CBCT images suggest significant improvements in image quality using the prior-aided DTS reconstruction compared to the standard zero-initialized ART reconstruction. PC coefficients of the six patient datasets were on average and using a zero-initialized ART reconstruction with SE data and PL data, respectively, and and using the proposed prior-aided reconstruction with SE data and PL data,respectively. While the initial estimation in iterative reconstruction algorithms is often overlooked, we proved that initial estimation is of critical importance in DTS image reconstruction and we have demonstrated the profound advantages of integrating prior CT images in intraoperative DTS image reconstruction. CT-augmented DTS offers a viable alternative to CBCT in guiding bronchoscopy interventions at a fraction of the radiation dose. Further clinical studies are needed to validate improved diagnosticyield.

The accuracy of anatomic landmarks on the occlusal plane: a comparative study between conventional and 3D image method

BackgroundTo establish the occlusal plane, the conventional methods for facial analysis to gain accurate alignment of the occlusal plane are inadequate, while 3D technologies are an ideal diagnostic tool. The aims of this research are to compare the difference accuracy of anatomic landmarks on the occlusal plane and ala-tragus line between the conventional clinical method and 3D image method in both non-orthodontic and orthodontic treatment volunteers.MethodsA total of 44 volunteers (22 non-orthodontic and 22 orthodontic treatment volunteers) with normal occlusion were selected. All volunteers received 2 operative methods for occlusal plane determination. In conventional method, the occlusal plane was defined by the fox plane line. The ala-tragus line was defined by the radio-opaque markers. In the 3D image method, the volunteers were recorded intraoral images, 3D facial images and CBCT images. A 3D virtual picture was created using EXOCAD® software. The occlusal plane was generated by the incisal and occlusal surfaces of the teeth. Both methods, the angles and distances between the occlusal plane and ala-tragus line were measured and compared statistically on both sides of each volunteer.ResultsBoth volunteers’ group, the mean angles and distances between the occlusal plane-ala tragus line in the conventional method were reported to be significantly greater than the 3D method (P < 0.05). The percentage difference of angles in conventional method were reported to be significantly higher by 13.61–21.58% (p < 0.05) compared to the 3D method. The percentage difference of distances in the conventional method were reported to be significantly greater than the 3D method by 4.73–7.51% (p < 0.05).ConclusionsWithin the limitation of the study, it can be concluded that both conventional and digital methods for establishing the occlusal plane are not parallel to the occlusal plane. The occlusal plane and ala-tragus line in the conventional method and the 3D method were significantly different in terms of angles and distances in both non-orthodontic and orthodontic treatment volunteers. However, the deviation angle of both methods is approximately 13–20 degrees, which is clinically acceptable for occlusal plane establishment. The accuracy of both methods is still within the using in clinical implementation.

Palatal canine impaction is associated with craniofacial shape in humans.

It is unclear whether palatal canine impaction is related to genetic or local/environmental factors. If a genetic origin is assumed, then it could be expected that palatal canine impaction is associated with overall craniofacial development. Within this context, the aim of this study was to evaluate the craniofacial morphology of individuals with palatal canine impaction and compare it to a matched group of normal controls. The sample for this investigation comprised 404 individuals (232 females and 172 males). Half of these individuals presented with unilateral or bilateral palatal canine impaction confirmed clinically and radiographically. The other half were matched for sex and age with the first half and comprised individuals without tooth impaction, apart from third molars. The shape of the craniofacial structures was outlined on calibrated cephalometric images through 15 curves and 127 landmarks (11 fixed and 116 semi-landmarks). Shape configurations were superimposed using Procrustes Superimposition and the resulting shape coordinates were reduced into principal components for all subsequent analyses. The effect of palatal canine impaction on craniofacial shape was assessed with regression models, separately in females and males. All statistical tests were performed assuming a type-1 error of 5%. Individuals with palatally impacted canines appear to have a less convex face, a more brachyfacial skeletal pattern, and a sagittally extended premaxilla. In females effect sizes ranged between η2 = 0.136-0.397 (P < 0.05) and in males between η2 = 0.125-0.396 (P < 0.05, apart from the entire craniofacial configuration: P = 0.259). Palatal canine impaction was not confirmed through cone beam computer tomography images in all patients, however, in those cases, the treatment history confirmed the diagnosis. Palatal canine impaction is related to a distinct craniofacial shape in females and males. These findings allow for speculation that palatal canine impaction is affected by genetic pathways involved in overall craniofacial development.

Evaluation of Panoramic Radiography Diagnostic Accuracy in the Assessment of Interdental Alveolar Bone Loss Using CBCT.

Alveolar bone loss (ABL) and periodontal lesions are common diseases that have an undeniable effect on teeth maintenance and health. Current diagnostic methods include probing, intraoral radiography, and panoramic radiography; each has its limitations. In this study, we aimed to assess the diagnostic accuracy of panoramic radiography in the diagnosis of interdental ABL. In this cross-sectional study, panoramic and cone-beam computed tomography (CBCT) images from 80 patients were collected from the archives of an oral and maxillofacial radiology center. The amount of ABL was obtained by measuring the distance from the Cemento-Enamel Junction (CEJ) to the alveolar bone crest on both panoramic and CBCT images. Patients were divided into healthy (ABL ≤ 2 mm) and diseased (2 mm < ABL) groups in terms of periodontal disease. There was no statistically significant difference in the average ABL in the premolar, maxillary molar, and mandibular molar areas between the two techniques. However, in other areas, the ABL size was significantly lower in the panoramic view (p < 0.05). Also, the panoramic technique correctly recognized 89.1% of normal and 88.4% of ABL cases. The overall accuracy of panoramic radiography in the diagnosis of ABL was 85%, indicating the good accuracy of this technique. In maxilla, the highest diagnostic accuracy of the panoramic technique was in the molars, and the lowest was in the incisors. In the mandible, the highest and lowest diagnostic accuracy of the panoramic technique was related to molars and premolars, respectively. According to the kappa statistic, there was a significant good to very good agreement between the two types of techniques in all maxillary areas (p < 0.001). Panoramic radiography is accurate in showing ABL. Measuring ABL in the posterior mandibular areas in panoramic radiographs is quite reliable; however, in general, digital panoramic radiography shows less ABL than the actual amount.

Application of intraoral scanning registration implant robot in dental implant surgery.

This paper aims to investigate the application of intraoral scanning and cone beam computed tomography (CBCT) registration implant robot in dental implant surgery. The data of 40 cases with dental defect of robot-assisted implantation from November 2023 to May 2024 were retrospectively analyzed. Before the operation, the intraoral scan data and CBCT data of the positioning markers were automatically fused with the initial CBCT images, and the registration error was calculated. The average registration error of positioning markers was determined during the operation, and the implantation accuracy was analyzed after the operation. The intraoral scan data and CBCT data of 40 patients with dental defect wearing positioning markers were successfully registered with the initial CBCT image, and the registration errors were (0.157±0.026) mm and (0.154±0.033) mm, respectively. Statistical analysis showed no statistical significance between them. The registration errors of the marker was (0.037 3±0.003 6) mm. A total of 55 implants were performed, and the total deviations of the implant point and the apical point were (0.78±0.41) and (0.89±0.28) mm, respectively. The transverse deviations of the implant point and the apical point were (0.44±0.36) and (0.58±0.25) mm, respectively. The depth deviations of the implant point and the apical point were (0.51±0.32) and (0.54±0.36) mm, respectively. The deviation of the implant angle was 1.24°±0.67°. The fusion technology based on intraoral scanning and CBCT registration can meet the accuracy requirements of preoperative registration of oral implant robots. The technology increases the choice of registration methods before robot-assisted dental implant surgery and reduces the multiple radiation exposuresof the patient.

An Evaluation of the Relationship Between the Mesiobuccal Canal Configuration, the Interorifice Distance, and the Root Lengths of the Permanent Maxillary First Molars with Cone Beam Computed Tomography

This study aimed to investigate the relationship between the mesiobuccal root canal configuration (MB RCC), the interorifice distance (IOD) and the corresponding root and other root lengths of the permanent maxillary first molars. Cone beam computed tomography (CBCT) images were acquired between 2020 and 2023 for different purposes unrelated to this study. Overall, 1550 CBCT images were retrospectively evaluated. A dentomaxillofacial radiologist with 15 years of experience evaluated the CBCT images and performed the measurements. According to the MB RCC, there was no statistically significant difference between the Vertucci type II and Vertucci type IV groups in terms of the mean age and sex distribution (p = 0.694 and p = 0.273). There was no statistically significant difference in the IOD between the MB RCC groups (p = 0.755). Moreover, according to the MB RCC, there was no statistically significant difference between the Vertucci type II and Vertucci type IV groups in terms of the mesiobuccal, distobuccal, palatinal, and mean root lengths (p &gt; 0.05). In conclusion, there was no association between the IOD and the type of RCC in the maxillary first molars. New studies conducted by collecting data from different centers to explore the different morphological features of maxillary first molars and detect their anatomical differences will provide more reliable and accurate results.

Influence of Bisphosphonates on Alveolar Bone Loss around Osseointegrated Implants

ABSTRACT Context: Bisphosphonates are extensively used drugs for the management of osteoporosis and other disorders affecting the bones. The stability and lifetime of osseointegrated dental implants may be influenced by their impact on bone metabolism. Materials and Methods: A randomized controlled trial was undertaken with a sample size of 60 individuals who were implanted with orally integrated dental implants. Study participants were split into two groups: Group A (n = 30) had bisphosphonate therapy for a minimum of 1 year before implant placement, while Group B (n = 30) did not have any bisphosphonate treatment. Cone beam computed tomography images were performed to quantify the alveolar bone levels surrounding the implants at three time points: baseline, 6 months, and 12 months after implantation. Findings: At the 6-month mark, Group A had an average bone loss of 0.8 mm with a standard deviation of 0.3 mm, but Group B had a bone loss of 1.2 mm with a standard deviation of 0.4 mm. At the 12-month mark, Group A experienced an average bone loss of 1.1 mm ± 0.5 mm, while Group B had a loss of 1.6 mm ± 0.6 mm. The substantial differences in bone loss between the groups were observed at both the 6-month (P &lt; 0.05) and 12-month (P &lt; 0.01) time points. Conclusion: Bisphosphonate treatment seems to decrease the atrophy of the alveolar bone surrounding osseointegrated dental implants, indicating a possible advantage in improving the durability and lifespan of the implants.

Comparative evaluation of the upper pharyngeal airway among children with/without UCLP and with/without OSA.

To evaluate the volume and the most constricted cross-sectional area (lumen) sizes of the upper pharyngeal airway among children with/without unilateral cleft lip and palate (UCLP) and with/without obstructive sleep apnea (OSA). This prospective study was conducted on 66 Thai children aged 5 to 12 years, encompassing demographic information, polysomnographic data, and sex distribution: 34 with non-syndromic UCLP (16 with OSA; 18 without OSA) and 32 non-cleft children (16 with OSA; 16 without OSA). Subjects were divided into two age groups: preadolescent group (ages 10-12) and younger group (ages 5-9). Cone-beam computed tomography images were acquired with subjects in a supine position. Subsequent measurements were conducted using the Dolphin imaging program (version 11.7 premium) to investigate and compare the volumes and lumens of the nasopharyngeal, oropharyngeal, and hypopharyngeal airways. In the younger group, the UCLP with OSA group exhibited significantly smaller volumes and lumens in the oropharyngeal airway compared to the non-cleft group without OSA (volume: p = 0.044; lumen: p = 0.031, 95% CI). All upper pharyngeal airway parts had comparable volumes and lumens between age groups. However, preadolescence reported no significant differences. Statistically significant differences were observed only in the oropharyngeal airway measurements in the younger sample compared to the adolescent sample. This underscores the importance of considering oropharyngeal airway structure in diagnosing and preventing OSA in children. However, it is essential to note that while airway size is a fundamental factor, it may not be the sole determinant of OSA occurrence. Other factors likely contribute to the condition as well.

First linac-mounted photon counting detector for image guided radiotherapy: Planar image quality characterization.

Image guided radiotherapy (IGRT) with cone-beam computed tomography (CBCT) is limited by the sub-optimal soft-tissue contrast and spatial resolution of energy-integrating flat panel detectors (FPDs) which produce quasi-quantitative CT numbers. Spectral CT with high resolution photon-counting detectors (PCDs) could improve tumor delineation by enhancing the soft-tissue contrast, spatial resolution, dose-efficiency, and CT numberaccuracy. This study presents the first linac-mounted PCD. On the journey to developing spectral cone-beam CT for IGRT, the planar image quality of a linac-mounted PCD is first fundamentally characterized and compared to an FPD in terms of the 2D spatial resolution, noise, andcontrast. A Medipix3RX-based PCD was mounted to the kV FPD of an x-ray volume imaging (XVI) system on an Elekta linac and the PCD acquisition was synchronized with the pulsed kV source. The energy calibration of the Medipix3RX was determined with various radioisotope gamma emissions up to 60 keV. To compare the 2D spatial resolution and noise between the PCD and FPD, the pre-sampling modulation transfer function (MTF) and normalized noise power spectrum (NPS) were measured using an RQA5 spectrum and a fluoroscopy phantom was imaged to determine the limiting resolution of line pairs. Spectral planar images of phantom inserts containing two different concentrations of calcium (60 and 240 mg/cc) and iodine (5 and 15 mg/cc) were optimally energy weighted to maximize the contrast using tube voltages of 60, 80, 100, and 120 kV. To account for drifts in the sensor temperature, the PCD was dynamically translated in and out of the insert shadow during acquisitions to obtain flat field corrections per frame. The raw contrast of the resultant planar images was compared to the energy-integrating FPD. The energy calibration of the Medipix3RX was observed to be linear up to 60 keV. The limiting resolution observed on the fluoroscopy phantom was 2 lp/mm for the FPD and 5 lp/mm for the PCD. The pre-sampling MTF was higher across all frequencies comparing the PCD to the FPD. The normalized NPS of the PCD did not vary with frequency, whereas the spectrum for the FPD decreased monotonically and was lower than the PCD noise power across most of the spatial frequency range studied due to optical light spreading. Optimal energy weights were applied to the dynamically acquired PCD images and the raw contrast of the 60 mg/cc calcium insert increased by factors of and at 60 and 120 kV respectively compared to theFPD. A Medipix3RX-based PCD was successfully integrated with the kilovoltage imaging system on an Elekta linac. The initial planar image quality characterization indicated improvements in the MTF and energy-weighted contrast compared to the FPD. Future work will focus on obtaining linac-mounted spectral CBCT images with a translate-rotate geometry, however this initial study indicates that variations in the PCD sensor response during acquisitions must be addressed to realise the full potential of linac-mounted spectralCBCT.

Assessment of Debris Apical Extrusion, Unprepared Surface Areas, and Dentinal Crack Formation after Root Canal Preparation Using ProTaper Next, ProTaper Ultimate, and R-Motion File Systems

This study evaluated and compared the amount of apically extruded debris, unprepared wall surface areas, and dentinal crack formation resulting from root canal preparation using ProTaper Next (PTN), ProTaper Ultimate (PTU), and R-Motion (RM) file systems. Forty-five palatal roots of maxillary first molars were shortened to a uniform length of 12mm. The samples were divided randomly into three groups (n = 15/group) to be prepared using either PTN, PTU, and RM file systems. The investigator adopted modified Myers and Montgomery's approach to replicate the temperature of the human body. Debris was collected in vials and weighed before and after instrumentation with a sensitive balance. Every specimen was irrigated using distilled water during preparation, utilizing a side-vented needle. Weight before instrumentation was subtracted from weight after instrumentation to identify the weight of the collected debris. CBCT scans were taken before and after canal preparation using a Planmeca ProMax CBCT machine. The unprepared canal surface area was calculated by superimposing preoperative and postoperative CBCT images using the Mimics Medical program. After preparation, a low-speed diamond disc horizontally sectioned the roots at three, six, and nine millimeters from the apex. The specimens were examined under a digital microscope to detect crack formation. Statistical analysis was carried out using one-way (ANOVA) and Tukey (HSD) tests, with a significance level of p<0.05. There was no statistically significant difference in the quantity of debris extruded apically and dentinal crack numbers between the three shaping files (p > 0.05). Only the apical third of root canals prepared by PTU displayed a significantly lower unprepared surface area compared to PTN and RM. Instrumentation with PTN, PTU, and RM yielded similar amounts of apically extruded debris and dentinal cracks. The PTU files demonstrated higher effectiveness in preparing the apical third by reducing the unprepared surface area in the prepared root canal.

Automatic jawbone structure segmentation on dental CBCT images via deep learning.

This study developed and evaluated a two-stage deep learning-based system for automatic segmentation of mandibular cortical bone, mandibular cancellous bone, maxillary cortical bone and maxillary cancellous bone on cone beam computed tomography (CBCT) images. A dataset containing 155 CBCT scans acquired with different parameters was obtained. A two-stage deep learning-based system was developed for automatically segmenting jawbone structures. The Dice similarity coefficient (DSC) and average symmetric surface distance (ASSD) were used to assess the segmentation performance of the system by comparing the automatic segmentation results with the ground truth. The impact of dental and quality abnormalities on segmentation performance was analysed, and a comparison of automatic segmentation (AS) with manually refined segmentation (MRS) was reported. The system achieved promising segmentation performance, with average DSC values of 93.69%, 96.83%, 86.14% and 95.57% and average ASSD values of 0.13mm, 0.16mm, 0.29mm and 0.41mm for the mandibular cortical bone, mandibular cancellous bone, maxillary cortical bone and maxillary cancellous bone, respectively. Quality abnormalities had a negative impact on segmentation performance. The performance metrics (DSCs > 98.8% and ASSDs < 0.1mm) indicated high overlap between the AS and MRS. The proposed system offers an accurate and time-efficient method for segmenting jawbone structures on CBCT images. Automatically segmenting jawbone structures is essential in most digital dental workflows. The proposed system has considerable potential for application in digital clinical workflows to assist dentists in making more accurate diagnoses and developing patient-specific treatment plans.

Application of Radiomics Features in Differential Diagnosis of Odontogenic Cysts.

Cysts in jaws may have similar radiographic features. However, it is important to clarify the diagnosis prior to surgery. The aim of this study was to compare the radiomic features of radicular cysts (RCs), dentigerous cysts (DCs) and odontogenic keratocysts (OKCs) as a non-invasive diagnostic alternative to biopsy. In total, 161 odontogenic cysts diagnosed histopathologically (55 RCs, 53 DCs and 53 OKCs) were included in the present study. Each cyst was semi-automatically segmented on CBCT images, and radiomic features were extracted by an observer. A second observer repeated 20% of the evaluations and the radiomic features. Those achieving an inter-observer agreement level above 0.850 were included in the study. Consequently, 5 shape-based and 22 textural features were investigated in the study. Statistical analysis was performed comparing both three cyst features and making pairwise comparisons. All features included in the study showed statistical differences between cysts, with the exception of one textural feature (NGTDM coarseness) (p < 0.05). However, only one shape-based feature (shericity) and one textural feature (GLSZM large area emphasis) were statistically different in pairwise comparisons of all three cysts (p < 0.05). Radiomics features of the RCs, DCs and OKCs showed significant differences, and may have the potential to be used as a non-invasive method in the differential diagnosis of cysts.

Is model-based dose calculation based on cone-beam computed tomography suitable for adaptive treatment planning in brachytherapy?

Model-based dose calculation considering tissue compositions is increasingly being investigated in brachytherapy. The aim of this study was to assess the suitability of modern cone-beam computed tomography (CBCT) imaging compared to conventional computed tomography (CT) scans for this purpose. By means of aphantom study, we evaluated the CT numbers and electron densities measured using amodern CBCT device as well as aconventional CT scanner for various materials. Based on this, we compared dose calculations (using the TG-43 formalism as well as model-based collapsed cone calculations assuming uniform materials [ACEuniform] and considering CT numbers [ACECT#]) on planning CTs and control CBCTs for patients with cervical and breast cancer as well as phantom-simulated skin cancer cases. Assessing dosimetric deviations between the planning CTs and control CBCTs acquired during the treatment course served to estimate interfractional implant variations. The comparison of ACEuniform-ACECT# deviations between planning CTs and control CBCTs revealed no statistically significant difference for almost all examined dose parameters. Dosimetric deviations between model-based dose calculations and TG-43 were partly significant but of small magnitude (< 10 cGy per fraction). Interfractional dosimetric variations were substantially larger than the dosimetric differences found between the various dose calculation procedures. Model-based dose calculation based on modern CBCT imaging was suitable. However, the found differences between these calculations and the TG-43 formalism should be investigated in dose-outcome analyses. The observed interfractional dosimetric variations revealed the importance of performing treatment quality assurance.

Assessment of operator performance during dynamically guided osteotomy and root-end resection in endodontic microsurgery: a cross-sectional in vitro study

ObjectivesTo compare in vitro the magnitude of deviations, task-focused performance, and perspective on instrumentation of two operators with different levels of experience using computer-assisted dynamic navigation (C-ADN) systems during osteotomy/root-end resection (RER) in models mimicking thick bone layers overlying the apices. MethodsEight models with 15 tooth replicas each were assigned equally to two operators (experienced/less experienced). Pre- and post-operative cone-beam computed tomography images were superimposed using a C-ADN software to determine discrepancies between the planned and real trajectory of the trephine bur. Task-focused operator performance and subjective aspects derived from operator's perspective related to C-ADN were also analyzed. Statistical analysis was completed through parametric methods and Chi-square/fisher exact tests. ResultsPearson correlation tests showed positive correlations between the distance from buccal cortical plate to root apex regarding deviation at apex, trephination depth, and visuomotor coordination time. The less experienced operator had significantly greater values of visuomotor coordination time, deviation at buccal entry point and apex, trephination depth, and angular deviation, as well as a significantly higher frequency of apex location failures, poor RER quality, and mishaps in comparison with those of the experienced operator, thus leading to a significantly higher task-focused performance for the experienced operator. Both operators improved the visuomotor task through diverse attempts, acknowledged enhanced situation awareness, surgical procedure quality, and patient safety associated to the use of C-ADN, and reported a positive impact on the developing and maintaining navigational skills. Concerns regarding perceived workload, mental demand, and usability difficulties were reported only by the less experienced operator. ConclusionsDynamically guided osteotomy and RER prepared with trephine burs entail a subset of visuomotor skills requiring a special learning which may vary depending on the operator's experience and the procedure complexity as determined by dentoalveolar anatomy. Likewise, the perceived usability about C-ADN systems increases insofar the complexity of the user interface decreases and upsurge the earlier experience with these systems. Statement of clinical relevanceThis study shows that both the technical characteristics involved in the function of C-ADN systems and the subjective operators' perceptions are critical for the accuracy of task-focused performance during endodontic microsurgery.

Morphometric Evaluation of the Greater Palatine Foramen in Patients With Cleft lip and Palate (CLP) and Controls: A CBCT Study.

This study aimed to use cone beam computed tomography (CBCT) scans to compare the morphometric characteristics of the greater palatine foramen (GPF) in unilateral and bilateral cleft lip/palate patients (CL/P) and non-cleft (NC) individuals. One hundred patients with CL/P (78 unilateral and 22 bilateral) and 100 non-cleft individuals had their GPF morphometrically assessed in CBCT images. The antero-posterior width and medio-lateral width of the GPF, the distance between the right and left GPFs, the mesio-distal location of the GPF with respect to the molar teeth, the distance between the GPF and the hamulus of the medial pterygoid plate, and the distance between the GPF and the palatine alveolar ridge were measured on these images. The Kruskal-Wallis and Chi-square tests were employed to ascertain if there were any notable disparities across the 3 groups. The GPF's antero-posterior width and medio-lateral width, and distance from the hamulus and palatine alveolar ridge were considerably smaller in the unilateral cleft lip/palate (UCL/P) and bilateral cleft lip/palate (BCL/P) patients than in the NC individuals. However, no significant difference was observed between the BCL/P and UCL/P groups in terms of these parameters. The distance between GPFs and the location of the GPF did not exhibit any significant differences among the 3 groups. Certain morphometric parameters of the GPF were significantly different in CL/P patients. Understanding the anatomy of this area is crucial for successful treatment of individuals with CL/P with minimal complications.

Factors affecting external apical root resorption of maxillary incisors associated with microimplant-assisted rapid palatal expansion.

To measure and compare the extent of root resorption in the maxillary incisors following microimplant-assisted rapid palatal expansion (MARPE) and to identify risk factors of root resorption after expansion. Cone-beam computed tomography images were obtained from a total of 60 patients both before expansion (T1) and 3 to 6 months after expansion (T2). Measurements taken included tooth length, root length, crown length and center of resistance. Resorption length (RL) and resorption length percentage (RLp), resorption volume (RV) and resorption volume percentage (RVp) and the amount of expansion were calculated. A significant difference in tooth length and volume was observed in both the central and lateral incisors before and after expansion. The resorption index (RL, RLp, RV, RVp) was significantly higher in the central incisors than in the lateral incisor. There was a significant correlation between several factors: age and RLp of the central incisors, the amount of expansion and RVp of the central incisors, tooth length of the central incisors and RL, RLp of the central incisors, root/crown ratio of the central incisors and RL of the central incisors, as well as tooth length of the lateral incisors and the RL of the lateral incisors. Significant root resorption occurs in maxillary incisors following MARPE, with central incisors root resorption being significantly higher than lateral incisors. Key risk factors for root resorption after MARPE include advanced age, a larger amount of expansion, initial tooth length, and a root/crown ratio.

Deep learning-based multiple-CT optimization: An adaptive treatment planning approach to account for anatomical changes in intensity-modulated proton therapy for head and neck cancers

BackgroundsIntensity-modulated proton therapy (IMPT) is particularly susceptible to range and setup uncertainties, as well as anatomical changes. PurposeWe present a framework for IMPT planning that employs a deep learning method for dose prediction based on multiple-CT (MCT). The extra CTs are created from cone-beam CT (CBCT) using deformable registration with the primary planning CT (PCT). Our method also includes a dose mimicking algorithm. MethodsThe MCT IMPT planning pipeline involves prediction of robust dose from input images using a deep learning model with a U-net architecture. Deliverable plans may then be created by solving a dose mimicking problem with the predictions as reference dose. Model training, dose prediction and plan generation are performed using a dataset of 55 patients with head and neck cancer in this retrospective study. Among them, 38 patients were used as training set, 7 patients were used as validation set, and 10 patients were reserved as test set for final evaluation. ResultsWe demonstrated that the deliverable plans generated through subsequent MCT dose mimicking exhibited greater robustness than the robust plans produced by the PCT, as well as enhanced dose sparing for organs at risk. MCT plans had lower D2% (76.1 Gy vs. 82.4 Gy), better homogeneity index (7.7% vs. 16.4%) of CTV1 and better conformity index (70.5% vs. 61.5%) of CTV2 than the robust plans produced by the primary planning CT for all test patients. ConclusionsWe demonstrated the feasibility and advantages of incorporating daily CBCT images into MCT optimization. This approach improves plan robustness against anatomical changes and may reduce the need for plan adaptations in head and neck cancer treatments.