Fusion of intra-oral scans in cone-beam computed tomography scans

Create virtual dentoskeletal model by superimposing digital dental cast into cone-beam computed tomography scan

PURPOSE

Many artifacts and obstacles associated with cone-beam computed tomography (CBCT) scan can obscure or distort the details of the teeth and occlusal surface, like distorted teeth, streak artifacts, noise, and some malocclusion cases with excessive overlapping between jaws cause decrease the interocclusal space, which can impact diagnosis and treatment planning, and the 3D reconstruction accuracy. Optimizing dental precision by Integrating CBCT scans with other imaging modalities, supply more information to enhance CBCT accuracy, mainly in dental areas with limited clarity.

METHODS

Performing the Structure-from-Motion (SfM) photogrammetry method, using phone camera and photograph studio setup using simple hardware, to digitize the dental casts and obtain an accurate digital dental model. Using this digital dental model to enhance dental precision in the CBCT data by performing the superimposition process, using a surface-based registration method and integration process to create a virtual dentoskeletal model. Evaluate the accuracy and quality of the superimposition results using qualitative (visual inspection) and quantitative measures.

RESULTS

The differences between the virtual dentoskeletal model and the reference CBCT model are calculating by the 3D Euclidean distance, the mean ± SD are 0.212 ± 0.169 mm and 0.26 ± 0.149 mm for the maxilla and mandible, respectively. The color-coded map shows that the two surfaces are similar, but the extremist values are concentrated in the dental region due to the presence of the noise in the reference model and the gingiva in the virtual dentoskeletal model.

CONCLUSIONS

The resulting virtual dentoskeletal model can be viewed and manipulated on a computer screen, allowing for a detailed analysis of the teeth and supporting structures. The 3D model generated by the SfM photogrammetry technique did well during the superimposition process, representing a reliable method for virtual-based processing such as orthognathic surgery planning and splint design.

Accuracy of the modified tooth-supported 3D printing surgical guides based on CT, CBCT, and intraoral scanning in maxillofacial region: A comparison study

BACKGROUND

Tooth-supported surgical guides have demonstrated superior accuracy compared with bone-supported guides. This study aimed to modify the fabrication of tooth-supported guides for compatibility with tumor resection procedures and investigate their accuracy.

METHODS

Patients with tumors who underwent osteotomy with the assistance of modified tooth- or bone-supported surgical guides were included. Virtual surgical planning (VSP) was employed to align three dimensional (3D) models extracted from intraoperative computed tomography (CT) images. The distances and angular deviations between the actual osteotomy plane and preoperative plane were recorded. A comparative analysis of osteotomy discrepancies between tooth-supported and bone-supported guides, as well as among tooth-supported guides based on CT, cone-beam CT (CBCT), or intraoral scanner (IOS) was conducted. The factors influencing the precision of the guides were analyzed.

RESULTS

Sixty patients with 81 resection planes were included in this study. In the tooth-supported group, the mean deviations in the osteotomy plane and angle were 1.39 mm and 4.30°, respectively, whereas those of the bone-supported group were 2.16 mm and 4.95°. In the tooth-supported isotype guide groups, the mean deviations of the osteotomy plane were 1.39 mm, 1.47 mm, 1.23 mm across CT, CBCT, and IOS, respectively. The accuracy of the modified tooth-supported guides remained consistent regardless of number and position of the teeth supporting the guide and location of the osteotomy lines.

CONCLUSIONS

The findings indicate that the modified tooth-supported surgical guides demonstrated high accuracy in the maxillofacial region, contributing to a reduction in the amount of surgically detached soft tissue.

The surgery-first approach for orthognathic correction of maxillary deficiency-is it stable? Three-dimensional assessment of CBCT scans and digital dental models

The aim of this study was to determine the skeletal stability of Le Fort I maxillary advancement following the surgery-first approach, by three-dimensional (3D) assessment of cone beam computed tomography (CBCT) scans and digital dental models. CBCT scans of 25 class III patients obtained 1 week preoperatively (T0) and 1 week (T1) and 6 months (T2) postoperatively were superimposed to measure surgical movements (T0-T1) and skeletal relapse (T1-T2). The distorted dentition of the CBCT scans at T1 was replaced with 3D images of the dental models to assess the postoperative occlusion. Surgical movements of the maxilla (mean ± standard deviation values) were 6.79 ± 2.30 mm advancement, 1.28 ± 1.09 mm vertically, and 0.71 ± 0.79 mm mediolaterally. Horizontal rotation (yaw) was 1.56° ± 1.21°, vertical rotation (pitch) 1.86° ± 1.88°, and tilting (roll) 1.63° ± 1.54°. At T2, the posterior relapse was 0.72 ± 0.43 mm (P = 0.001) and relapse in pitch was 1.56° ± 1.42° (P = 0.007). There was no correlation between the size of the surgical movements and the amount of relapse. A weak correlation was noted between the number of teeth in occlusal contact immediately following surgery and relapse of maxillary roll (r = - 0.434, P = 0.030). The stability of maxillary advancement with the surgery-first approach was satisfactory and was not correlated with the quality of the immediate postoperative occlusion.

Optimizing Orthognathic Surgery: Leveraging the Average Skull as a Dynamic Template for Surgical Simulation and Planning in 30 Patient Cases

Virtual planning has revolutionized orthognathic surgery (OGS), marking a significant advancement in the field. This study aims to showcase the practical application of our established 3D average skull template as a guiding framework for surgical planning, and to share valuable insights from our clinical experience. We enrolled 30 consecutive Taiwanese patients (18 females and 12 males) who underwent two-jaw orthognathic surgery with surgical simulation, utilizing the average skull template for planning. Results indicate the method's applicability and precision. By adhering to the surgical plan, post-operative outcomes closely aligned with the average skull template, showing negligible deviations of less than 2 mm. Moreover, patients expressed high satisfaction with post-surgery facial changes, with the chin appearance receiving the highest satisfaction scores, while the lowest scores were attributed to nose appearance. Notably, the substantial change in lower jaw position post-mandibular setback surgery contributed to increased satisfaction with the chin position. In conclusion, this study does not seek to replace established surgical planning methods, but underscores that utilizing an average skull as a surgical design template provides a viable, accurate, and efficient option for OGS patients.

Intra-oral scan segmentation using deep learning

OBJECTIVE

Intra-oral scans and gypsum cast scans (OS) are widely used in orthodontics, prosthetics, implantology, and orthognathic surgery to plan patient-specific treatments, which require teeth segmentations with high accuracy and resolution. Manual teeth segmentation, the gold standard up until now, is time-consuming, tedious, and observer-dependent. This study aims to develop an automated teeth segmentation and labeling system using deep learning.

MATERIAL AND METHODS

As a reference, 1750 OS were manually segmented and labeled. A deep-learning approach based on PointCNN and 3D U-net in combination with a rule-based heuristic algorithm and a combinatorial search algorithm was trained and validated on 1400 OS. Subsequently, the trained algorithm was applied to a test set consisting of 350 OS. The intersection over union (IoU), as a measure of accuracy, was calculated to quantify the degree of similarity between the annotated ground truth and the model predictions.

RESULTS

The model achieved accurate teeth segmentations with a mean IoU score of 0.915. The FDI labels of the teeth were predicted with a mean accuracy of 0.894. The optical inspection showed excellent position agreements between the automatically and manually segmented teeth components. Minor flaws were mostly seen at the edges.

CONCLUSION

The proposed method forms a promising foundation for time-effective and observer-independent teeth segmentation and labeling on intra-oral scans.

CLINICAL SIGNIFICANCE

Deep learning may assist clinicians in virtual treatment planning in orthodontics, prosthetics, implantology, and orthognathic surgery. The impact of using such models in clinical practice should be explored.

Applications of three-dimensional imaging techniques in craniomaxillofacial surgery: A literature review

Three-dimensional (3D) imaging technologies are increasingly used in craniomaxillofacial (CMF) surgery, especially to enable clinicians to get an effective approach and obtain better treatment results during different preoperative and postoperative phases, namely during image acquisition and diagnosis, virtual surgical planning (VSP), actual surgery, and treatment outcome assessment. The article presents an overview of 3D imaging technologies used in the aforementioned phases of the most common CMF surgery. We searched for relevant studies on 3D imaging applications in CMF surgery published over the past 10 years in the PubMed, ProQuest (Medline), Web of Science, Science Direct, Clinical Key, and Embase databases. A total of 2094 articles were found, of which 712 were relevant. An additional 26 manually searched articles were included in the analysis. The findings of the review demonstrated that 3D imaging technology is becoming increasingly popular in clinical practice and an essential tool for plastic surgeons. This review provides information that will help researchers and clinicians consider the use of 3D imaging techniques in CMF surgery to improve the quality of surgical procedures and achieve satisfactory treatment outcomes.

Synergy between artificial intelligence and precision medicine for computer-assisted oral and maxillofacial surgical planning

OBJECTIVES

The aim of this review was to investigate the application of artificial intelligence (AI) in maxillofacial computer-assisted surgical planning (CASP) workflows with the discussion of limitations and possible future directions.

MATERIALS AND METHODS

An in-depth search of the literature was undertaken to review articles concerned with the application of AI for segmentation, multimodal image registration, virtual surgical planning (VSP), and three-dimensional (3D) printing steps of the maxillofacial CASP workflows.

RESULTS

The existing AI models were trained to address individual steps of CASP, and no single intelligent workflow was found encompassing all steps of the planning process. Segmentation of dentomaxillofacial tissue from computed tomography (CT)/cone-beam CT imaging was the most commonly explored area which could be applicable in a clinical setting. Nevertheless, a lack of generalizability was the main issue, as the majority of models were trained with the data derived from a single device and imaging protocol which might not offer similar performance when considering other devices. In relation to registration, VSP and 3D printing, the presence of inadequate heterogeneous data limits the automatization of these tasks.

CONCLUSION

The synergy between AI and CASP workflows has the potential to improve the planning precision and efficacy. However, there is a need for future studies with big data before the emergent technology finds application in a real clinical setting.

CLINICAL RELEVANCE

The implementation of AI models in maxillofacial CASP workflows could minimize a surgeon's workload and increase efficiency and consistency of the planning process, meanwhile enhancing the patient-specific predictability.

How to Avoid Errors When Using Navigation to Place Implants - A Narrative Review

PURPOSE

Surgeons placing implants use navigation for implant placement accuracy. The importance of this review is to document the sources of error that are involved with navigation so surgeons can recognize factors to decrease error. The objective is to provide surgeons with a reference to optimize navigation.

METHODS

Pubmed.gov was the information source. Years reviewed included 2010 to 2022. The inclusion criteria included only articles in peer-reviewed journals. In vitro results were included only if they involved testing of variables microgap, cone beam computerized tomography (CBCT) accuracy evaluation, or accuracy of printed models. Variables were searched and evaluated. Data collected included the objectives and outcomes of the study including statistical significance. The conclusions made by the authors were confirmed by evaluating the data analysis, and then these conclusions were listed in each error-related topic.

RESULTS

The search used terms which included guided implant surgery complications (n = 4,029), accuracy of CBCT scanners (n = 319), accuracy of implant navigation (n = 983), and the error between drills and static guides (n = 3). From this search, 70 articles were collated that satisfied the inclusion criteria. There are multiple sources of error that are less than 1 mm, including but not limited to errors associated with the scanner and method for scanning, errors associated with merging scanned files with the CBCT scan, errors using different guide stent fabrication methods, errors associated with intraoperative techniques, the learning curve, and planning error. If small errors are not taken into consideration, implant placement errors can exceed 1-2 mm of platform location and angulation errors in excess of 8°.

CONCLUSION

The surgeon needs to take into consideration controllable factors that will result in the avoidance of implant malposition and thus be able to effectively utilize navigation for accurate implant placement.

Immediate reconstruction of defects after a partial maxillectomy with a digitally planned, prefabricated, 3-dimensionally printed, esthetic obturator prosthesis

A digital workflow was used to design and prefabricate a 3-dimensionally printed, esthetic obturator prosthesis for immediate placement after a partial maxillectomy. The approach involved simultaneous reciprocation and support of the maxillary defect during the surgery and minimized the incidence of cicatricial contracture of the soft tissue, preventing permanent facial deformity and dysfunction.

The Impact of Technological Innovation on Dentistry

Technology has revolutionized the way dentists are able to treat their patients. These technological advances have paved the way for the creation of virtual patient models utilizing these 3-dimensional intra-oral patient models, cone bean computer tomography (CBCT) radiograph scans, extraoral 3-dimensional scans, and jaw motion tracings to create a patient-specific model. These models are advantageous in planning surgical treatments by providing 3-dimensional views of vital anatomical structures to accurately identify the location, size, and shape of a structure or defect in order to plan accordingly. Virtual augmentation of either hard tissue (bone) and/or soft tissue (i.e., gingiva) can also be accomplished.Technology has allowed the capture of the dynamic motions of the jaw and combined them with the virtual patient to develop permanent restorations in harmony with the patient's orofacial complex. With the introduction of new technology in the realm of digital dentistry, patient care is being brought to a new and higher level. This creates a level of more optimal care that a dentist can deliver to patients.

The Prediction Accuracy of Digital Orthodontic Setups for the Orthodontic Phase before Orthognathic Surgery

The purpose of this study was to verify whether pre-treatment digital setups can accurately predict the tooth positions after presurgical orthodontic treatment has been performed in a 3-dimensional way. Twenty-six patients who underwent a combined orthodontic-orthognathic surgical treatment were included. Pre-treatment digital dental models were merged with cone beam computed tomography (CBCT) scans. One operator fabricated virtual setups to simulate the tooth movements of the presurgical orthodontic treatment. Prior to surgery, digital dental models were merged with the CBCT scans. Differences between de virtual setups and the presurgical dental models were calculated using linear mixed model analyses. Differences in tooth displacements exceeding the boundaries of clinical acceptance (>2 degrees for rotations and >0.6 mm for translations) were found in 75% of the rotational and 52% of translational mean differences in the maxilla and in 74% of the rotational mean differences and 44% of the translational mean differences in the mandible. Significant differences were found for all tooth types and in all tooth displacement directions with significant effects of extractions and surgically assisted rapid maxillary expansion (SARME) procedures. The accuracy of the digital setup is still too limited to correctly simulate the presurgical orthodontic treatment.

Plaster Casts vs. Intraoral Scans: Do Different Methods of Determining the Final Occlusion Affect the Simulated Outcome in Orthognathic Surgery?

A virtual occlusal adjustment in orthognathic surgery has many advantages; however, the haptic information offered by plaster casts is missing when using intraoral scans. Feeling the interferences may be helpful in defining the best possible occlusion. Whether the use of a virtual occlusal adjustment instead of the conventional approach has a significant effect on the postsurgical position of the jaws is a question that remains unanswered. This study compares a virtual method to the conventional method of defining the final occlusion. Twenty-five orthognathic patients were included. Bimaxillary and single-jaw orthognathic surgery (mandible only) was simulated. The two methods were compared regarding discrepancies in the simulated postsurgical position of the mandible, measured three-dimensionally using MeshLab (MeshLab 2020.12 3D). An analysis using SPSS revealed no significant differences between the tested methods (p-values: 0.580 to 0.713). The mean absolute discrepancies ranged from 0.14 mm to 0.72 mm, laying within the scope of the clinically acceptable inaccuracies of an osteosynthesis in orthognathic surgery. The lack of haptic information in virtual planning had no relevant influence on the definition of the final occlusion and the simulated postsurgical outcome. However, in individual cases, plaster models might still be helpful in finding the adequate occlusion, especially in the sagittal dimension and in cases of patients with an anterior open bite, but this remains to be tested.

Efficacy of Constructing Digital Hybrid Skull-Dentition Images Using an Intraoral Scanner and Cone-Beam Computed Tomography

Cone-beam computed tomography (CBCT) can distort dentition, and additional imaging is often required. A plaster model to help digitize dental images has been widely used in clinical practice, but there are some inconveniences such as complexity of the process and the risk of damage. The aim of this study was to evaluate the potential for improving dentition imaging with CBCT scans using an intraoral scanner instead of a plaster model. The study used laser model-scanned images of plaster models, imaging from two intraoral scanners, and CBCT images from 20 patients aged 12-18 years. CS 3600 (Carestream Dental, Atlanta, USA) and i700 (Medit, Seoul, Korea) were used as intraoral scanners. The full arch was scanned at once or in three sections using intraoral scanners. The segmented scans were merged to obtain full-arch images. With i700, full-arch images were additionally acquired using its "smart stich" function. The virtual skull-dentition hybrid images obtained from intraoral scanners were superimposed with images obtained using a plaster cast. The difference and distance of coordinate values at each reference point were measured. The average distances from the images obtained with the plaster cast were smaller than 0.39 mm, which is the voxel size of CBCT. Scanning the complete or partial arch using CS 3600 or i700 satisfactorily complemented the CBCT when compared to the plaster model. The virtual skull-dentition hybrid image obtained from intraoral scanners will be clinically useful, especially for patients and surgeons who have difficulty in scanning the complete arch at once.

A new protocol to accurately track long-term orthodontic tooth movement and support patient-specific numerical modeling

Numerical simulation of long-term orthodontic tooth movement based on Finite Element Analysis (FEA) could help clinicians to plan more efficient and mechanically sound treatments. However, most of FEA studies assume idealized loading conditions and lack experimental calibration or validation. The goal of this paper is to propose a novel clinical protocol to accurately track orthodontic tooth displacement in three-dimensions (3D) and provide 3D models that may support FEA. Our protocol uses an initial cone beam computed tomography (CBCT) scan and several intra-oral scans (IOS) to generate 3D models of the maxillary bone and teeth ready for use in FEA. The protocol was applied to monitor the canine retraction of a patient during seven months. A second CBCT scan was performed at the end of the study for validation purposes. In order to ease FEA, a frictionless and statically determinate lingual device for maxillary canine retraction was designed. Numerical simulations were set up using the 3D models provided by our protocol to show the relevance of our proposal. Comparison of numerical and clinical results highlights the suitability of this protocol to support patient-specific FEA.

Registration-free workflow for electromagnetic and optical navigation in orbital and craniofacial surgery

The accuracy of intra-operative navigation is largely dependent on the intra-operative registration procedure. Next to accuracy, important factors to consider for the registration procedure are invasiveness, time consumption, logistical demands, user-dependency, compatibility and radiation exposure. In this study, a workflow is presented that eliminates the need for a registration procedure altogether: registration-free navigation. In the workflow, the maxillary dental model is fused to the pre-operative imaging data using commercially available virtual planning software. A virtual Dynamic Reference Frame on a splint is designed on the patient’s fused maxillary dentition: during surgery, the splint containing the reference frame is positioned on the patient’s dentition. This alleviates the need for any registration procedure, since the position of the reference frame is known from the design. The accuracy of the workflow was evaluated in a cadaver set-up, and compared to bone-anchored fiducial, virtual splint and surface-based registration. The results showed that accuracy of the workflow was greatly dependent on tracking technique used: the workflow was the most accurate with electromagnetic tracking, but the least accurate with optical tracking. Although this method offers a time-efficient, non-invasive, radiation-free automatic alternative for registration, clinical implementation is hampered by the unexplained differences in accuracy between tracking techniques.

Non-Invasive Optical Coherence Tomography Data-Based Quantitative Algorithm for the Assessment of Residual Adhesive on Bracket-Removed Dental Surface

The aim of this study was to quantitatively assess the residual adhesive on orthodontic ceramic bracket-removed dental surface. In orthodontic process, ceramic bracket was repeated debonding physically, then the adhesive remained on the dental surface. The residual adhesive caused a lack of adhesive strength between dental and ceramic bracket. Since commonly used adhesive in orthodontics is translucent, residual adhesive is hard to be detected with conventional microscopes. Therefore, 1310 nm center wavelength swept-source OCT system based on laboratory customized image processing algorithm was used for the precise detection of residual adhesive on tooth surface. The algorithm separates residual adhesive from dental surface by comparing the height of adjacent B-scan images, while providing color-scaled images emphasizing the thickness information of residual adhesive. Finally, the acquired results were compared with microscopic and adhesive remnant index scoring gold standards, while the comparison confirmed the potential merits and the improvements of the proposed method over gold standards.