The aim of the paper is to identify, review, analyze, and summarize available evidence in three areas on the use of cross-sectional imaging, specifically maxillofacial cone beam computed tomography ...(CBCT) in pre- and postoperative dental implant therapy: (1) Available clinical use guidelines, (2) indications and contraindications for use, and (3) assessment of associated radiation dose risk.
Three focused questions were developed to address the aims. A systematic literature review was performed using a PICO-based search strategy based on MeSH key words specific to each focused question of English-language publications indexed in the MEDLINE database retrospectively from October 31, 2012. These results were supplemented by a hand search and gray literature search.
Twelve publications were identified providing guidelines for the use of cross-sectional radiography, particularly CBCT imaging, for the pre- and/or postoperative assessment of potential dental implant sites. The publications discovered by the PICO strategy (43 articles), hand (12), and gray literature searches (1) for the second focus question regarding indications and contraindications for CBCT use in implant dentistry were either cohort or case-controlled studies. For the third question on the assessment of associated radiation dose risk, a total of 22 articles were included. Publication characteristics and themes were summarized in tabular format.
The reported indications for CBCT use in implant dentistry vary from preoperative analysis regarding specific anatomic considerations, site development using grafts, and computer-assisted treatment planning to postoperative evaluation focusing on complications due to damage of neurovascular structures. Effective doses for different CBCT devices exhibit a wide range with the lowest dose being almost 100 times less than the highest dose. Significant dose reduction can be achieved by adjusting operating parameters, including exposure factors and reducing the field of view (FOV) to the actual region of interest.
To investigate the current clinical applications and diagnostic performance of artificial intelligence (AI) in dental and maxillofacial radiology (DMFR).
Studies using applications related to DMFR to ...develop or implement AI models were sought by searching five electronic databases and four selected core journals in the field of DMFR. The customized assessment criteria based on QUADAS-2 were adapted for quality analysis of the studies included.
The initial electronic search yielded 1862 titles, and 50 studies were eventually included. Most studies focused on AI applications for an automated localization of cephalometric landmarks, diagnosis of osteoporosis, classification/segmentation of maxillofacial cysts and/or tumors, and identification of periodontitis/periapical disease. The performance of AI models varies among different algorithms.
The AI models proposed in the studies included exhibited wide clinical applications in DMFR. Nevertheless, it is still necessary to further verify the reliability and applicability of the AI models prior to transferring these models into clinical practice.
In implant dentistry, three-dimensional (3D) imaging can be realised by dental cone beam computed tomography (CBCT), offering volumetric data on jaw bones and teeth with relatively low radiation ...doses and costs. The latter may explain why the market has been steadily growing since the first dental CBCT system appeared two decades ago. More than 85 different CBCT devices are currently available and this exponential growth has created a gap between scientific evidence and existing CBCT machines. Indeed, research for one CBCT machine cannot be automatically applied to other systems.
Supported by a narrative review, recommendations for justified and optimized CBCT imaging in oral implant dentistry are provided.
The huge range in dose and diagnostic image quality requires further optimization and justification prior to clinical use. Yet, indications in implant dentistry may go beyond diagnostics. In fact, the inherent 3D datasets may further allow surgical planning and transfer to surgery via 3D printing or navigation. Nonetheless, effective radiation doses of distinct dental CBCT machines and protocols may largely vary with equivalent doses ranging between 2 to 200 panoramic radiographs, even for similar indications. Likewise, such variation is also noticed for diagnostic image quality, which reveals a massive variability amongst CBCT technologies and exposure protocols. For anatomical model making, the so-called segmentation accuracy may reach up to 200 μm, but considering wide variations in machine performance, larger inaccuracies may apply. This also holds true for linear measures, with accuracies of 200 μm being feasible, while sometimes fivefold inaccuracy levels may be reached. Diagnostic image quality may also be dramatically hampered by patient factors, such as motion and metal artefacts. Apart from radiodiagnostic possibilities, CBCT may offer a huge therapeutic potential, related to surgical guides and further prosthetic rehabilitation. Those additional opportunities may surely clarify part of the success of using CBCT for presurgical implant planning and its transfer to surgery and prosthetic solutions.
Hence, dental CBCT could be justified for presurgical diagnosis, preoperative planning and peroperative transfer for oral implant rehabilitation, whilst striving for optimisation of CBCT based machine-dependent, patient-specific and indication-oriented variables.
Diagnostic radiology is an essential component of treatment planning in the field of implant dentistry. This narrative review will present current concepts for the use of cone beam computed ...tomography imaging, before and after implant placement, in daily clinical practice and research. Guidelines for the selection of three‐dimensional imaging will be discussed, and limitations will be highlighted. Current concepts of radiation dose optimization, including novel imaging modalities using low‐dose protocols, will be presented. For preoperative cross‐sectional imaging, data are still not available which demonstrate that cone beam computed tomography results in fewer intraoperative complications such as nerve damage or bleeding incidents, or that implants inserted using preoperative cone beam computed tomography data sets for planning purposes will exhibit higher survival or success rates. The use of cone beam computed tomography following the insertion of dental implants should be restricted to specific postoperative complications, such as damage of neurovascular structures or postoperative infections in relation to the maxillary sinus. Regarding peri‐implantitis, the diagnosis and severity of the disease should be evaluated primarily based on clinical parameters and on radiological findings based on periapical radiographs (two dimensional). The use of cone beam computed tomography scans in clinical research might not yield any evident beneficial effect for the patient included. As many of the cone beam computed tomography scans performed for research have no direct therapeutic consequence, dose optimization measures should be implemented by using appropriate exposure parameters and by reducing the field of view to the actual region of interest.
Objective
The aim of this systematic review was to identify, review, analyze, and summarize available evidence on the accuracy of linear measurements when using maxillofacial cone beam computed ...tomography (CBCT) specifically in the field of implant dentistry.
Material and methods
The search was undertaken in April 2017 in the National Library of Medicine database (Medline) through its online site (PubMed), followed by searches in the Cochrane, EMBASE, ScienceDirect, and ProQuest Dissertation and Thesis databases. The main inclusion criterion for studies was that linear CBCT measurements were performed for quantitative assessment (e.g., height, width) of the alveolar bone at edentulous sites or measuring distances from anatomical structures related to implant dentistry. The studies should compare these values to clinical data (humans) or ex vivo and/or experimental (animal) findings from a “gold standard.”
Results
The initial search yielded 2,516 titles. In total, 22 studies were included in the final analysis. Of those, two were clinical and 20 ex vivo investigations. The major findings of the review indicate that CBCT provides cross‐sectional images that demonstrate high accuracy and reliability for bony linear measurements on cross‐sectional images related to implant treatment. A wide range of error has been reported when performing linear measurements on CBCT images, with both over‐ and underestimation of dimensions in comparison with a gold standard. A voxel size of 0.3 to 0.4 mm is adequate to provide CBCT images of acceptable diagnostic quality for implant treatment planning.
Conclusions
CBCT can be considered as an appropriate diagnostic tool for 3D preoperative planning. Nevertheless, a 2 mm safety margin to adjacent anatomic structures should be considered when using CBCT. In clinical practice, the measurement accuracy and reliability of linear measurements on CBCT images are most likely reduced through factors such as patient motion, metallic artefacts, device‐specific exposure parameters, the software used, and manual vs. automated procedures.
Analysis of dental radiographs is an important part of the diagnostic process in daily clinical practice. Interpretation by an expert includes teeth detection and numbering. In this project, a novel ...solution based on convolutional neural networks (CNNs) is proposed that performs this task automatically for panoramic radiographs.
A data set of 1352 randomly chosen panoramic radiographs of adults was used to train the system. The CNN-based architectures for both teeth detection and numbering tasks were analyzed. The teeth detection module processes the radiograph to define the boundaries of each tooth. It is based on the state-of-the-art Faster R-CNN architecture. The teeth numbering module classifies detected teeth images according to the FDI notation. It utilizes the classical VGG-16 CNN together with the heuristic algorithm to improve results according to the rules for spatial arrangement of teeth. A separate testing set of 222 images was used to evaluate the performance of the system and to compare it to the expert level.
For the teeth detection task, the system achieves the following performance metrics: a sensitivity of 0.9941 and a precision of 0.9945. For teeth numbering, its sensitivity is 0.9800 and specificity is 0.9994. Experts detect teeth with a sensitivity of 0.9980 and a precision of 0.9998. Their sensitivity for tooth numbering is 0.9893 and specificity is 0.9997. The detailed error analysis showed that the developed software system makes errors caused by similar factors as those for experts.
The performance of the proposed computer-aided diagnosis solution is comparable to the level of experts. Based on these findings, the method has the potential for practical application and further evaluation for automated dental radiograph analysis. Computer-aided teeth detection and numbering simplifies the process of filling out digital dental charts. Automation could help to save time and improve the completeness of electronic dental records.
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