Positional accuracy of a prosthetic treatment plan incorporated into a cone beam computed tomography scan using surface scan registration

Accuracy of manual and artificial intelligence-based superimposition of cone-beam computed tomography with digital scan data, utilizing an implant planning software: A randomized clinical study

OBJECTIVES

To investigate the accuracy of conventional and automatic artificial intelligence (AI)-based registration of cone-beam computed tomography (CBCT) with intraoral scans and to evaluate the impact of user's experience, restoration artifact, number of missing teeth, and free-ended edentulous area.

MATERIALS AND METHODS

Three initial registrations were performed for each of the 150 randomly selected patients, in an implant planning software: one from an experienced user, one from an inexperienced operator, and one from a randomly selected post-graduate student of implant dentistry. Six more registrations were performed for each dataset by the experienced clinician: implementing a manual or an automatic refinement, selecting 3 small or 3 large in-diameter surface areas and using multiple small or multiple large in-diameter surface areas. Finally, an automatic AI-driven registration was performed, using the AI tools that were integrated into the utilized implant planning software. The accuracy between each type of registration was measured using linear measurements between anatomical landmarks in metrology software.

RESULTS

Fully automatic-based AI registration was not significantly different from the conventional methods tested for patients without restorations. In the presence of multiple restoration artifacts, user's experience was important for an accurate registration. Registrations' accuracy was affected by the number of free-ended edentulous areas, but not by the absolute number of missing teeth (p < .0083).

CONCLUSIONS

In the absence of imaging artifacts, automated AI-based registration of CBCT data and model scan data can be as accurate as conventional superimposition methods. The number and size of selected superimposition areas should be individually chosen depending on each clinical situation.

Digital registration versus cone-beam computed tomography for evaluating implant position: a prospective cohort study

BACKGROUND

Postoperative cone-beam computed tomography (CBCT) examination is considered a reliable method for clinicians to assess the positions of implants. Nevertheless, CBCT has drawbacks involving radiation exposure and high costs. Moreover, the image quality can be affected by artifacts. Recently, some literature has mentioned a digital registration method (DRM) as an alternative to CBCT for evaluating implant positions. The aim of this clinical study was to verify the accuracy of the DRM compared to CBCT scans in postoperative implant positioning.

MATERIALS AND METHODS

A total of 36 patients who received anterior maxillary implants were included in this clinical study, involving a total of 48 implants. The study included 24 patients in the single implant group and 12 patients in the dual implant group. The postoperative three-dimensional (3D) positions of implants were obtained using both CBCT and DRM. The DRM included three main steps. Firstly, the postoperative 3D data of the dentition and intraoral scan body (ISB) was obtained through the intraoral scan (IOS). Secondly, a virtual model named registration unit which comprised an implant replica and a matching ISB was created with the help of a lab scanner and reverse engineering software. Thirdly, by superimposing the registration unit and IOS data, the postoperative position of the implant was determined. The accuracy of DRM was evaluated by calculating the Root Mean Square (RMS) values after superimposing the implant positions obtained from DRM with those from postoperative CBCT. The accuracy of DRM was compared between the single implant group and the dual implant group using independent sample t-tests. The superimposition deviations of CBCT and IOS were also evaluated.

RESULTS

The overall mean RMS was 0.29 ± 0.05 mm. The mean RMS was 0.30 ± 0.03 mm in the single implant group and 0.29 ± 0.06 mm in the dual implant group, with no significant difference (p = 0.27). The overall registration accuracy of the IOS and CBCT data ranged from 0.14 ± 0.05 mm to 0.21 ± 0.08 mm.

CONCLUSION

In comparison with the 3D implant positions obtained by CBCT, the implant positions located by the DRM showed clinically acceptable deviation ranges. This method can be used in single and dual implant treatments to assess the implant positions.

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.

Digital versus radiographic accuracy evaluation of guided implant surgery: an in vitro study

Background

Cone-beam computed tomography (CBCT) is the most widely used method for postsurgical evaluation of the accuracy of guided implant surgery. However, the disadvantages of CBCT include radiation exposure, artifacts caused by metal implants, and high cost. Few studies have introduced a digital registration method to replace CBCT for evaluating the accuracy of guided surgery. The purpose of this study was to compare digital registration to conventional CBCT in terms of the capacity to evaluate the implant positioning accuracy of guided surgery.

Materials and methods

This in vitro study included 40 acrylic resin models with posterior single mandibular tooth loss. Guided surgery software was used to determine the optimal implant position; 40 tooth-supported fully guided drilling templates were designed and milled accordingly. After the guided surgery, the accuracies of the surgical templates were evaluated by conventional CBCT and digital registration. For evaluation by conventional CBCT, postsurgical CBCT scans of the resin models were performed. The CBCT data were reconstructed and superimposed on the implant planning data. For digital registration, we constructed a virtual registration unit that consisted of an implant replica and a scan body. Next, we obtained postsurgical optical scans of resin models with the scan body. The postsurgical implant position was identified by superimposition of the registration unit and optical scan data. The implant planning data and postsurgical implant position data were superimposed; deviations were reported in terms of distance for implant entry/apex point and in terms of angle for the implant axis. Interclass correlation coefficients (ICCs) and Bland–Altman plots were used to analyze the agreement between the two evaluation methods.

Results

The ICCs between the two methods were 0.986, 0.993, and 0.968 for the entry point, apex point, and angle, respectively; all were significantly greater than 0.75 (p < 0.001). Bland–Altman plots showed that the 95% limits of agreement of the differences were − 0.144 to + 0.081 mm, − 0.135 to + 0.147 mm, and − 0.451° to + 0.729° for the entry point, apex point, and angle, respectively; all values were within the maximum tolerated difference.

Conclusion

Conventional CBCT and digital registration showed good agreement in terms of evaluating the accuracy of implant positioning using tooth-supported surgical templates.

Accuracy of markerless registration methods of DICOM and STL files used for computerized surgical guides in mandibles with metal restorations: An in vitro study

STATEMENT OF PROBLEM

Digital imaging and communications in medicine (DICOM) files together with surface scans must be accurately registered in virtual implant planning software programs to match real-life dimensions and ensure correct plan transfer through computer-aided manufactured surgical guides.

PURPOSE

The purpose of this in vitro study was to evaluate the accuracy of 3 different registration methods of DICOM data with and without metal restorations and a metal artifact reduction (MAR) tool for surface scans.

MATERIAL AND METHODS

Thirteen dentate mandibles were assigned to each group of this study (n=39). Baseplate wax was adapted to the bone surfaces of each mandible, and 5 radiopaque markers were attached. A desktop scanner was used to obtain control scans. The groups of metal-free mandibles (MFM) and mandibles with metal restorations (MRM) were scanned to obtain DICOM data without a MAR tool. Additional DICOM data for the MRM were obtained with the MAR tool (MRM-MAR). Point-based registration (PBR), best-fit registration (BFR), and automatic registration (AR) were used to align standard tessellation language (STL) and DICOM data, and 3 data sets were exported. Radiographic markers on each data set were compared with those on the control scan, and positional deviations were calculated and statistically evaluated with 1-way ANOVA followed by multiple pairwise comparisons, independent samples t test, and 2-way ANOVA (α=.05).

RESULTS

Within each group, PBR had the lowest deviation values with statistical significance in the MFM and the MRM-MAR groups (P<.001). AR showed failure in the MRM and the MRM-MAR groups. Statistically significant differences were found on comparing the average deviations among the 3 groups for PBR only (P<.001). No association was found between deviation values and the presence or absence of metal restoration, while a positive association was found with the type of registration method (P<.001).

CONCLUSIONS

PBR had the highest accuracy level compared with AR and BFR methods. An increase in the number of calculations resulted in more deviation values. The MAR tool had a positive effect on PBR in mandibles with metal restorations.

Evaluation of different registration methods and dental restorations on the registration duration and accuracy of cone beam computed tomography data and intraoral scans: a retrospective clinical study

OBJECTIVES

To evaluate whether the accuracy and duration of registration for cone beam computed tomography (CBCT) and intraoral scans differ according to the method of registration and ratio of dental restorations to natural teeth.

MATERIALS AND METHODS

CBCT data and intraoral scans of eligible patients were grouped as follows according to the ratio of the number of dental restorations to the number of natural teeth (N): group 1, N = 0%; group 2, 0% < N < 50%; group 3, 50% ≤ N < 100%; and group 4, 100% ≤ N. Marker-free registration was performed with a deep learning-based platform and four implant planning software with different registration methods (two point-based, one surface-based, and one manual registration software) by a single operator, and the time consumption was recorded. Registration accuracy was evaluated by measuring the distances between the three-dimensional models of CBCT data and intraoral scans.

RESULTS

A total of 36 patients, one jaw per patient, were enrolled. Although registration accuracy was similar, the time consumed for registration significantly differed for the different methods. The deep learning-based registration method consumed the least time. Greater proportions of dental restorations significantly reduced the registration accuracy for semi-automatic and deep learning-based methods and reduced the time consumed for semi-automatic registration.

CONCLUSIONS

No superiority in registration accuracy was found. The proportion of dental restorations significantly affects the accuracy and duration of registration for CBCT data and intraoral scans.

CLINICAL TRIAL REGISTRATION

ClinicalTrials.gov Identifier: KCT0006710 CLINICAL RELEVANCE: Registration accuracy for virtual implant planning decreases when the proportion of dental restorations increases regardless of registration methods.

The question about the numerical value and quantitative data transfer of implant prosthodontics-orom experience guidance to digital guidance

The correct implant site design and placement are the basic clinical techniques that must be known for implant restoration. For a long time, most implants have been placed by free hands, and the choice of site is mostly dependent on the accumulation of long-term experience of the surgeon. The selection of implant site guided by this experience analogy logic is often based on the surgeon's level of experience,which often makes it very easy to produce complications related to the implant restoration of the incorrect site. In contrast, a clinical program using digital guidance and real-time measurable verification has emerged based on the restoration-oriented implantation concept, which marks the formation of an accurate, measurable and verifiable whole-process digital implant prototype. Furthermore, from the perspective of surveying, the numerical requirements that digital implant restoration relies on are actually incomplete to the four elements of measurement, which leading to the doubts about its authenticity. This article will question the numbers in implant restoration, and conduct a preliminary demonstration, and propose a new reliable actual measurement and verification method of the correct location and the numerical requirements of the restoration space and a new clinical program that relies on numbers from the perspective of the evolution of digital restoration, guided implantology and actual measurement technology. And this article further discusses the current mainstream implant restoration technology based on experience analogy which cannot effectively support the whole process of digital implant restoration and provides a new logical cognitive basis for the final realization of the entire process of digital implant restoration.

Automatic Registration Between Dental Cone-Beam CT and Scanned Surface via Deep Pose Regression Neural Networks and Clustered Similarities

Computerized registration between maxillofacial cone-beam computed tomography (CT) images and a scanned dental model is an essential prerequisite for surgical planning for dental implants or orthognathic surgery. We propose a novel method that performs fully automatic registration between a cone-beam CT image and an optically scanned model. To build a robust and automatic initial registration method, deep pose regression neural networks are applied in a reduced domain (i.e., two-dimensional image). Subsequently, fine registration is performed using optimal clusters. A majority voting system achieves globally optimal transformations while each cluster attempts to optimize local transformation parameters. The coherency of clusters determines their candidacy for the optimal cluster set. The outlying regions in the iso-surface are effectively removed based on the consensus among the optimal clusters. The accuracy of registration is evaluated based on the Euclidean distance of 10 landmarks on a scanned model, which have been annotated by experts in the field. The experiments show that the registration accuracy of the proposed method, measured based on the landmark distance, outperforms the best performing existing method by 33.09%. In addition to achieving high accuracy, our proposed method neither requires human interactions nor priors (e.g., iso-surface extraction). The primary significance of our study is twofold: 1) the employment of lightweight neural networks, which indicates the applicability of neural networks in extracting pose cues that can be easily obtained and 2) the introduction of an optimal cluster-based registration method that can avoid metal artifacts during the matching procedures.

Fully Digital Workflow for Planning Static Guided Implant Surgery: A Prospective Accuracy Study

The accuracy of static guided implant surgery (sGIS) using conventional planning workflow has been extensively examined; however, more information is required to justify the application of fully digital planning protocol. The purpose of this study was to investigate the clinical accuracy of sGIS with a fully digital planning workflow. Twenty-one partially edentulous patients were enrolled in this prospective study. Cone-beam computed tomography (CBCT) and intraoral scans were taken and superimposed by matching the dental surface images directly (surface registration protocol) or by matching fiducial markers on a stereolithographic (SLA) radiographic template fabricated from the digital data of the intraoral scan (fiducial marker registration protocol). Virtual implant treatment plans were then determined, and tooth-supported SLA surgical guides were fabricated according to the plans. Twenty-six implant surgeries were performed via the surgical guide by one surgeon. Pre- and post-operative CBCT images were superimposed, and the positional and angular deviations between placed and planned implants were measured with metrology software. A total of 43 fully guided implants were placed, in which 25 implants were planned with the surface registration protocol. Implants planned based on the surface registration protocol had a larger mean angular deviation than the fiducial marker registration protocol. No significant differences were found for any deviations of the examined variables. Within the limits of this study, we concluded that the clinical accuracy of the sGIS planned with a fully digital workflow was consistent with the conventional workflow for partially edentulous patients.

Annual review of selected scientific literature: A report of the Committee on Scientific Investigation of the American Academy of Restorative Dentistry

This comprehensive review of the 2018 dental literature is provided to inform busy dentists about progress in the profession. Developed by the Committee on Scientific Investigation of the American Academy of Restorative Dentistry, each author brings discipline-specific expertise to one of the 8 sections of the report including (1) prosthodontics; (2) periodontics, alveolar bone, and peri-implant tissues; (3) implant dentistry; (4) dental materials and therapeutics; (5) occlusion and temporomandibular disorders; (6) sleep-related breathing disorders; (7) oral medicine and oral and maxillofacial surgery; and (8) dental caries and cariology. The report targets important information that will likely influence day-to-day treatment decisions. Each review is not intended to stand alone but to update interested readers so that they may visit source materials if greater detail is desired. As the profession continues its march toward evidence-based clinical decision-making, an already voluminous library of potentially valuable dental literature continues to grow. It is the intention of this review and its authors to provide assistance in navigating the extensive dental literature published in 2018. It is our hope that readers find this work useful in the clinical management of patients moving forward.

Impact of number of registration points on the positional accuracy of a prosthetic treatment plan incorporated into a cone beam computed tomography scan by surface scan registration: An in vitro study

OBJECTIVES

To evaluate the accuracy of a prosthetic treatment plan incorporation into a cone beam computed tomography (CBCT) scan using point-based registration with three registration points selected and to evaluate the impact of number of registration points on prosthetic plan accuracy.

MATERIAL AND METHODS

A CBCT scan of a completely dentate master model with removable teeth was exposed after removing the mandibular left first premolar, second premolar, and first molar. A digital scan of the master model with all teeth present was made by scanning a stone replica using a laboratory scanner. The digital model was registered onto the three-dimensional (3D) volume rendering of the CBCT scan using implant planning software. The point-based registration was repeated using three, four, five, six, seven, eight, nine, and 10 reference points. Metrology software was used to measure the 3D deviation of the registered models for each reference point group on standard tessellation language (STL) files obtained from the CBCT scans. An STL file of the master model with all teeth present obtained from another CBCT scan was used as reference.

RESULTS

Using three registration points, the registered prosthetic plan had a mean absolute deviation of 17.63 µm from the reference. Increasing the number of registration points failed to demonstrate statistically significant effects on the deviation (p > 0.05).

CONCLUSIONS

For this clinical scenario, three registration points provided adequate accuracy for prosthetic plan incorporation into CBCT scans. Increasing the number of registration points had no significant impact on the prosthetic plan accuracy in this study.