Ultrasonic mapping of midpalatal suture - An ex-vivo study.

OBJECTIVE: Rapid maxillary expansion is a common orthodontic procedure to correct maxillary constriction. Assessing the midpalatal suture (MPS) expansion plays a crucial role in treatment planning to determine its effectiveness. The objectives of this preliminary investigation are to demonstrate a proof of concept that the palatal bone underlying the rugae can be clearly imaged by ultrasound (US) and the reconstructed axial view of the US image accurately maps the MPS patency. METHODS: An ex-vivo US scanning was conducted on the upper jawbones of two piglet's carcasses before and after the creation of bone defects, which simulated the suture opening. The planar images were processed to enhance bone intensity distribution before being orderly stacked to fuse into a volume. Graph-cut segmentation was applied to delineate the palatal bone to generate a bone volume. The accuracy of the reconstructed bone volume and the suture opening was validated by the micro-computed tomography (µCT) data used as the ground truth and compared with cone beam computed tomography (CBCT) data as the clinical standard. Also included in the comparison is the rugae thickness. Correlation and Bland-Altman plots were used to test the agreement between the two methods: US versus µCT/CBCT. RESULTS: The reconstruction of the US palatal bone volumes was accurate based on surface topography comparison with a mean error of 0.19 mm for pre-defect and 0.15 mm and 0.09 mm for post-defect models of the two samples, respectively when compared with µCT volumes. A strong correlation (R2 ≥ 0.99) in measuring MPS expansion was found between US and µCT/CBCT with MADs of less than 0.05 mm, 0.11 mm and 0.23 mm for US, µCT and CBCT, respectively. CONCLUSIONS: It was possible to axially image the MPS opening and rugae thickness accurately using high-frequency ultrasound. CLINICAL SIGNIFICANCE: This study introduces an ionizing radiation-free, low-cost, and portable technique to accurately image a difficult part of oral cavity anatomy. The advantages of conceivable visualization could promise a successful clinical examination of MPS to support the predictable treatment outcome of maxillary transverse deficiency.

Measuring the alveolar bone level in adolescents: A comparison between ultrasound and cone beam computed tomography.

BACKGROUND: Cone beam computed tomography (CBCT) is an imaging modality, which is used routinely in orthodontic diagnosis and treatment planning but delivers much higher radiation than conventional dental radiographs. Ultrasound is a noninvasive imaging method that creates an image without ionizing radiation. AIM: To investigate the reliability of ultrasound and the agreement between ultrasound and CBCT in measuring the alveolar bone level (ABL) on the buccal/labial side of the incisors in adolescent orthodontic patients. DESIGN: One hundred and eighteen incisors from 30 orthodontic adolescent patients were scanned by CBCT with 0.3-mm voxel size and ultrasound at 20 MHz frequency. The ABL, distance from the cementoenamel junction (CEJ) to the alveolar bone crest (ABC), was measured twice to evaluate the agreement between ultrasound and CBCT. In addition, the intra- and inter-rater reliabilities in measuring the ABL by four raters were compared. RESULTS: The mean difference (MD) in the ABL between ultrasound and CBCT was -0.07 mm with 95% limit of agreement (LoA) from -0.47 to 0.32 mm for all teeth. For each jaw, the MDs between the ultrasound and CBCT were -0.18 mm (for mandible with 95% LoA from -0.53 to 0.18 mm) and 0.03 mm (for maxilla with 95% LoA from -0.28 to 0.35 mm). In comparison, ultrasound had higher intra-rater (ICC = 0.83-0.90) and inter-rater reliabilities (ICC = 0.97) in ABL measurement than CBCT (ICC = 0.56-0.78 for intra-rater and ICC = 0.69 for inter-rater reliabilities). CONCLUSION: CBCT parameters used in orthodontic diagnosis and treatment planning in adolescents may not be a reliable tool to assess the ABL for the mandibular incisors. On the contrary, ultrasound imaging, an ionizing radiation-free, inexpensive, and portable diagnostic tool, has potential to be a reliable diagnostic tool in assessing the ABL in adolescent patients.

Ultrasound Imaging of the Periodontium Complex: A Reliability Study.

Background: Ultrasonography is a noninvasive, low-cost diagnostic tool widely used in medicine. Recent studies have demonstrated that ultrasound imaging might have the potential to be used intraorally to assess periodontal biomarkers. Objectives: To evaluate the reliability of interlandmark distance measurements on intraoral ultrasound images of the periodontal tissues. Materials and Methods: Sixty-four patients from the graduate periodontics (n = 33) and orthodontics (n = 31) clinics were recruited. A 20 MHz handheld intraoral ultrasound transducer was used to scan maxillary and mandibular incisors, canines, and premolars. Distances between the alveolar bone crest and cementoenamel junction (ABC-CEJ), gingival thickness (GT), and alveolar bone thickness (ABT) were measured by 3 raters. The intercorrelation coefficient (ICC) and mean absolute deviation (MAD) were calculated among and between the raters. Raters also scored images according to quality. Results: The ICC scores for intrarater reliability were 0.940 (0.932-0.947), 0.953 (0.945-0.961), and 0.859 (0.841-0.876) for ABC-CEJ, GT, and ABT, respectively. The intrarater MAD values were 0.023 (±0.019) mm, 0.014 (±0.005) mm, and 0.005 (±0.003) mm, respectively. The ICC scores for interrater reliability were 0.872 (95% CI: 0.836-0.901), 0.958 (95% CI: 0.946-0.968), and 0.836 (95% CI: 0.789-0.873) for ABC-CEJ, GT, and ABT, respectively. The interrater MAD values were 0.063 (±0.029) mm, 0.023 (±0.018) mm, and 0.027 (±0.012) mm, respectively. Conclusions: The present study showed the high reliability of ultrasound in both intrarater and interrater assessments. Results suggest there might be a potential use of intraoral ultrasound to assess periodontium.

Temporomandibular joint segmentation in MRI images using deep learning.

OBJECTIVES: Temporomandibular joint (TMJ) internal derangements (ID) represent the most prevalent temporomandibular joint disorder (TMD) in the population and its diagnosis typically relies on magnetic resonance imaging (MRI). TMJ articular discs in MRIs usually suffer from low resolution and contrast, and it is difficult to identify them. In this study, we applied two convolutional neural networks (CNN) to delineate mandibular condyle, articular eminence, and TMJ disc in MRI images. METHODS: The models were trained on MRI images from 100 patients and validated on images from 40 patients using 2D slices and 3D volume as input, respectively. Data augmentation and five-fold cross-validation scheme were applied to further regularize the models. The accuracy of the models was then compared with four raters having different expertise in reading TMJ-MRI images to evaluate the performance of the models. RESULTS: Both models performed well in segmenting the three anatomical structures. A Dice coefficient of about 0.7 for the articular disc, more than 0.9 for the mandibular condyle, and Hausdorff distance of about 2mm for the articular eminence were achieved in both models. The models reached near-expert performance for the segmentation of TMJ articular disc and performed close to the expert in the segmentation of mandibular condyle and articular eminence. They also surpassed non-experts in segmenting the three anatomical structures. CONCLUSION: This study demonstrated that CNN-based segmentation models can be a reliable tool to assist clinicians identifying key anatomy on TMJ-MRIs. The approach also paves the way for automatic diagnosis of TMD. CLINICAL SIGNIFICANCE: Accurately locating the articular disc is the hardest and most crucial step in the interpretation of TMJ-MRIs and consequently in the diagnosis of TMJ-ID. Automated software that assists in locating the articular disc and its surrounding structures would improve the reliability of TMJ-MRI interpretation, save time and assist in reader training. It will also serve as a foundation for additional automated analysis of pathology in TMJ structures to aid in TMD diagnosis.

Localization of cementoenamel junction in intraoral ultrasonographs with machine learning.

OBJECTIVE: Our goal was to automatically identify the cementoenamel junction (CEJ) location in ultrasound images using deep convolution neural networks (CNNs). METHODS: Three CNNs were evaluated using 1400 images and data augmentation. The training and validation were performed by an experienced nonclinical rater with 1000 and 200 images, respectively. Four clinical raters with different levels of experience with ultrasound tested the networks using the other 200 images. In addition to the comparison of the best approach with each rater, we also employed the simultaneous truth and performance level estimation (STAPLE) algorithm to estimate a ground truth based on all labelings by four clinical raters. The final CEJ location estimate was obtained by taking the first moment of the posterior probability computed using the STAPLE algorithm. The study also computed the machine learning-measured CEJ-alveolar bone crest distance. RESULTS: Quantitative evaluations of the 200 images showed that the comparison of the best approach with the STAPLE-estimate yielded a mean difference (MD) of 0.26 mm, which is close to the comparison with the most experienced nonclinical rater (MD=0.25 mm) but far better than the comparison with clinical raters (MD=0.27-0.33 mm). The machine learning-measured CEJ-alveolar bone crest distances correlated strongly (R = 0.933, p < 0.001) with the manual clinical labeling and the measurements were in good agreement with the 95% Bland-Altman's lines of agreement between -0.68 and 0.57 mm. CONCLUSIONS: The study demonstrated the feasible use of machine learning methodology to localize CEJ in ultrasound images with clinically acceptable accuracy and reliability. Likelihood-weighted ground truth by combining multiple labels by the clinical experts compared favorably with the predictions by the best deep CNN approach. CLINICAL SIGNIFICANCE: Identification of CEJ and its distance from the alveolar bone crest play an important role in the evaluation of periodontal status. Machine learning algorithms can learn from complex features in ultrasound images and have potential to provide a reliable and accurate identification in subsecond. This will greatly assist dental practitioners to provide better point-of-care to patients and enhance the throughput of dental care.

Reliability and accuracy of a method for measuring temporomandibular joint condylar volume.

OBJECTIVE: The aim of this study was to develop and validate a technique for mandibular condyle segmentation and volume determination by using cone beam computed tomography (CBCT). STUDY DESIGN: A dry skull was used to generate 3 dimensional (3-D)-printed mandible models that were then imaged by using CBCT. Semiautomatic segmentation of condyles was completed. The Frankfurt plane was established and translated to the most inferior point of the sigmoid notch, and the condylar volume superior to the plane was determined. This procedure was repeated on 3-D-printed mandibles by using physical landmarks and the water displacement method to obtain the physical volume. This was repeated 3 times to evaluate reliability. Sensitivity analysis was performed to demonstrate the effect of discrepancies in locating landmarks in the Frankfurt plane. Condylar volume measurements obtained from CBCT were compared with physical measurements through repeated-measures analysis of variance (ANOVA) to determine accuracy. RESULTS: Condylar volume obtained from CBCT and physical measurements resulted in an intraclass correlation coefficient of 0.988 (0.918, 0.998) (P < .01) with both modalities, demonstrating excellent intrarater reliability. The mean difference of volume measurements between the modalities was not statistically significant (P = .365). Potential discrepancies in porion coordinates had minimal impact on condylar volume change. CONCLUSIONS: The condylar segmentation technique proved to be a reliable and accurate method for evaluating condylar volume.

Reliability and accuracy of segmentation of mandibular condyles from different three-dimensional imaging modalities: a systematic review.

OBJECTIVE: To critically synthesize the literature surrounding segmentation of the mandibular condyle using three-dimensional imaging modalities. Specifically, analyzing the reliability and accuracy of methods used for three-dimensional condyle segmentation. METHODS: Three electronic databases were searched for studies reporting the reliability and accuracy of various methods used to segment mandibular condyles from three-dimensional imaging modalities. Two authors independently reviewed articles for eligibility and data extraction. RESULTS: Nine studies fulfilled the inclusion criteria. Eight studies assessed the condylar segmentation from CBCT images and limited studies were available on non-CBCT three-dimensional imaging modalities. Threshold-based volume segmentation, manual segmentation, and semi-automatic segmentation techniques were presented. Threshold-based volume segmentation reported higher accuracy when completed by an experienced technician compared to clinicians. Adequate reliability and accuracy were observed in manual segmentation. Although adequate reliability was reported in semi-automatic segmentation, data on its accuracy were lacking. CONCLUSION: A definitive conclusion with regards to which current technique is most reliable and accurate to efficiently segment the mandibular condyle cannot be made with the currently available evidence. This is especially true in terms of non-CBCT imaging modalities with very limited literature available.

Fully Automated Segmentation of Alveolar Bone Using Deep Convolutional Neural Networks from Intraoral Ultrasound Images.

Delineation of alveolar bone aids the diagnosis and treatment of periodontal diseases. In current practice, conventional 2D radiography and 3D cone-beam computed tomography (CBCT) imaging are used as the non-invasive approaches to image and delineate alveolar bone structures. Recently, high-frequency ultrasound imaging is proposed as an alternative to conventional imaging methods to prevent the harmful effects of ionizing radiation. However, the manual delineation of alveolar bone from ultrasound imaging is time-consuming and subject to inter and intraobserver variability. This study proposes to use a convolutional neural network-based machine learning framework to automatically segment the alveolar bone from ultrasound images. The proposed method consists of a homomorphic filtering based noise reduction and a u-net machine learning framework for automated delineation. The proposed method was evaluated over 15 ultrasound images of tooth acquired from procine specimens. The comparisons against manual ground truth delineations performed by three experts in terms of mean Dice score and Hausdorff distance values demonstrate that the proposed method yielded an improved performance over a recent state of the art graph cuts based method.

Comparison of ultrasound imaging and cone-beam computed tomography for examination of the alveolar bone level: A systematic review.

BACKGROUND AND OBJECTIVE: The current methods to image alveolar bone in humans include intraoral 2D radiography and cone-beam computed tomography (CBCT). However, these methods expose the subject to ionizing radiation. Therefore, ultrasound imaging has been investigated as an alternative technique, as it is both non-invasive and free from ionizing radiation. In order to assess the validity and reliability of ultrasonography in visualizing alveolar bone, a systematic review was conducted comparing ultrasound imaging to CBCT for examination of the alveolar bone level. STUDY DESIGN: Seven databases were searched. Studies addressing examination of alveolar bone level via CBCT and ultrasound were selected. Risk of bias under Cochrane guidelines was used as a methodological quality assessment tool. RESULTS: All the four included studies were ex vivo studies that used porcine or human cadaver samples. The alveolar bone level was measured by the distance from the alveolar bone crest to certain landmarks such as cemento-enamel junction or gingival margin. The risk of bias was found as low. The mean difference between ultrasound and CBCT measurements ranged from 0.07 mm to 0.68 mm, equivalent to 1.6% - 8.8%. CONCLUSIONS: There is currently preliminary evidence to support the use of ultrasonography as compared to CBCT for the examination of alveolar bone level. Further studies comparing ultrasound to gold standard methods would be necessary to help validate the accuracy of ultrasonography as a diagnostic technique in periodontal imaging.

RANKL release from self-assembling nanofiber hydrogels for inducing osteoclastogenesis in vitro.

PURPOSE: To develop a nanofiber hydrogel (NF-hydrogel) for sustained and controlled release of the recombinant receptor activator of NF-kB ligand; (RANKL) and to characterize the release kinetics and bioactivity of the released RANKL. METHODS: Various concentrations of fluorescently-labelled RANKL protein were added to NF-hydrogels, composed of Acetyl-(Arg-Ala-Asp-Ala)4-CONH2 [(RADA)4] of different concentrations, to investigate the resulting in vitro release rates. The nano-structures of NF-hydrogel, with and without RANKL, were determined using atomic force microscopy (AFM). Released RANKL was further analyzed for changes in secondary and tertiary structure using CD spectroscopy and fluorescent emission spectroscopy, respectively. Bioactivity of released RANKL protein was determined using NFATc1 gene expression and tartrate resistant acid phosphatase (TRAP) activity of osteoclast cells as biomarkers. RESULTS: NF-hydrogel concentration dependent sustained release of RANKL protein was measured at concentrations between 0.5 and 2%(w/v). NF-hydrogel at 2%(w/v) concentration exhibited a sustained and slow-release of RANKL protein up to 48h. Secondary and tertiary structure analyses confirmed no changes to the RANKL protein released from NF-hydrogel in comparison to native RANKL. The results of NFATc1 gene mRNA expression and TRAP activities of osteoclast, showed that the release process did not affect the bioactivity of released RANKL. CONCLUSIONS: This novel study is the first of its kind to attempt in vitro characterization of NF-hydrogel based delivery of RANKL protein to induce osteoclastogenesis. We have shown the self-assembling NF-hydrogel peptide system is amenable to the sustained and controlled release of RANKL locally; that could in turn increase local concentration of RANKL to induce osteoclastogenesis, for application to the controlled mobilization of tooth movement in orthodontic procedures. STATEMENT OF SIGNIFICANCE: Orthodontic tooth movement (OTM) occurs through controlled application of light forces to teeth, facilitating the required changes in the surrounding alveolar bone through the process of bone remodelling. The RANKL system regulates alveolar bone remodelling and controls root resorption during OTM. The use of exogenous RANKL to accelerate OTM has not been attempted to date because large quantities of RANKL for systemic therapy may subsequently cause serious systemic loss of skeletal bone. The controlled and sustained local release of RANKL from a carrier matrix could maximize its therapeutic benefit whilst minimizing systemic side effects. In this study a NF-hydrogel was used for sustained and controlled release of RANKL and the release kinetics and biofunctionality of the released RANKL was characterized. Our results provide fundamental insight for further investigating the role of RANKL NF-hydrogel release systems for inducing osteoclastogenesis in vivo.

High-Resolution Ultrasonic Imaging of Dento-Periodontal Tissues Using a Multi-Element Phased Array System.

Intraoral ultrasonography uses high-frequency mechanical waves to study dento-periodontium. Besides the advantages of portability and cost-effectiveness, ultrasound technique has no ionizing radiation. Previous studies employed a single transducer or an array of transducer elements, and focused on enamel thickness and distance measurement. This study used a phased array system with a 128-element array transducer to image dento-periodontal tissues. We studied two porcine lower incisors from a 6-month-old piglet using 20-MHz ultrasound. The high-resolution ultrasonographs clearly showed the cross-sectional morphological images of the hard and soft tissues. The investigation used an integration of waveform analysis, travel-time calculation, and wavefield simulation to reveal the nature of the ultrasound data, which makes the study novel. With the assistance of time-distance radio-frequency records, we robustly justified the enamel-dentin interface, dentin-pulp interface, and the cemento-enamel junction. The alveolar crest level, the location of cemento-enamel junction, and the thickness of alveolar crest were measured from the images and compared favorably with those from the cone beam computed tomography with less than 10% difference. This preliminary and fundamental study has reinforced the conclusions from previous studies, that ultrasonography has great potential to become a non-invasive diagnostic imaging tool for quantitative assessment of periodontal structures and better delivery of oral care.

Imaging the Cemento-Enamel Junction Using a 20-MHz Ultrasonic Transducer.

The cemento-enamel junction (CEJ), which is the intersection between enamel and cementum, is an important landmark in the diagnosis of periodontal disease. Pulse-echo ultrasound was used to image the CEJs of six porcine lower central incisors with a single 20-MHz transducer. A notch was longitudinally created on the enamel as a stable marker, from which the CEJ was measured. Data were acquired along the tooth's axis at 0.4-mm intervals. Time-distance data were bandpass-filtered to enhance signal-to-noise ratio and record density was increased fourfold to 0.1-mm spacing by a frequency-distance interpolation scheme. Reflections from the CEJ were unambiguously identified along with those from enamel, dentin and cementum. The notch-CEJ distances measured by the ultrasound and micro-computed tomography methods correlated strongly (r = 0.996, p < 0.05) and were in good agreement with the 95% lines of agreement between -0.49 and 0.17 mm, as statistically determined by Bland-Altman analysis. The results indicate the potential of ultrasound to be a reliable and non-ionizing technique to image the CEJ.

Impact of bisphosphonate drug burden in alveolar bone during orthodontic tooth movement in a rat model: a pilot study.

INTRODUCTION: The aim of this pilot study was to investigate the effect of long-term bisphosphonate drug use (bone burden) on orthodontic tooth movement in a rat model. METHODS: Sprague Dawley rats were used for orthodontic protraction of the maxillary first molars with nickel-titanium coil springs and temporary anchorage devices as anchorage. Four groups of 5 rats each were included in the study; the first 2 groups were dosed with alendronate or a vehicle during concurrent orthodontic tooth movement. The third and fourth groups were pretreated for 3 months with alendronate or vehicle injections, and bisphosphonate drug treatment was discontinued before orthodontic tooth movement. Tooth movement measurements were obtained at 0, 4, and 8 weeks using high-resolution in-vivo microcomputed tomography, and the tissues were analyzed with histology and dynamic labeling of bone turnover. RESULTS: Appreciable tooth movement was achieved during the 8-week duration of this study with nickel-titanium coil springs and temporary anchorage devices. Both bisphosphonate treatment groups exhibited reduced tooth movement compared with the vehicle-dosed controls with a tendency toward more severe reduction in the bisphosphonate predosed group. Concurrent dosing of the bisphosphonate drug resulted in 56% and 65% reductions in tooth protraction at the 4-week and 8-week times, respectively. The impact of bisphosphonate bone burden in retarding tooth movement was even greater, with 77% and 86% reductions in tooth movement at 4 and 8 weeks, respectively. CONCLUSIONS: In this study, we used a robust rat model of orthodontic tooth movement with temporary anchorage devices. It has provided evidence that the bone burden of previous bisphosphonate use will significantly inhibit orthodontic tooth movement.

Accuracy of computer programs in predicting orthognathic surgery soft tissue response.

PURPOSE: The aim of the present systematic review is to investigate the accuracy of computer programs in predicting soft tissue response subsequent to skeletal changes after orthognathic surgery. MATERIALS AND METHODS: A systematic computerized database search was conducted using Ovid Medline, Ovid Medline in-process and other nonindexed citations, all EBM reviews (including Cochrane DSR, ACP Journal, DARE, CCTR), Embase Experta Medica, Pascal, and Thomsen's ISI Web of Science databases. The terms orthognathic surgery, orthodontic treatment, computer prediction, computer simulation, growth prediction, accuracy, precision, forecast, and human studies were used for the searches. The reference lists of all the selected articles were also searched for any potential articles that might have been missed in the electronic search of the database, and additional information not available through the articles was obtained directly from the source (by contacting the author). RESULTS: Out of the 40 initially identified articles only 7 articles fulfilled the final selection criteria. All 7 studies in general showed accurate prediction outcomes (less than 2 mm) when compared with actual results in both horizontal and vertical directions. From all the available computer prediction programs Quick Ceph, DentoFacial Planner (DFP), and Computer-Assisted Simulation System for Orthognathic Surgery (CASSOS) were the most frequently used. CONCLUSIONS: The most significant area of error in prediction through the available computer prediction programs was the lower lip area. Although the individual errors are almost always minimal (less than 2 mm), the composite addition of these minimal errors could have clinical implications.