A method to evaluate the accuracy of dental implant placement without postoperative radiography after computer-guided implant surgery: A dental technique

Placement accuracy and primary stability of implants in the esthetic zone using dynamic and static computer-assisted navigation: A retrospective case-control study

STATEMENT OF PROBLEM

Both the placement accuracy and primary stability of implants are important to implant therapy in the esthetic zone. The effect of dynamic and static computer-assisted navigation on the primary stability of implants in the esthetic zone remains uncertain.

PURPOSE

The purpose of this case-control study was to investigate the effect of dynamic and static computer-assisted navigation on the placement accuracy and primary stability of implants in the esthetic zone.

MATERIAL AND METHODS

Partially edentulous participants who received at least 1 implant in the anterior maxilla using either fully guided static or dynamic computer-assisted implant surgery (s-CAIS, d-CAIS) from January 2020 to February 2022 were screened. Participant demographic information, timing of implant placement, primary stability represented by the insertion torque value (ITV) in Ncm, and implant survival were collected from the treatment record. Bone quality at the implant sites was determined according to the Lekholm and Zarb classification. The accuracy of implant placement represented by the linear (platform: Dpl, mm; apex: Dap, mm) and angular deviations (axis: Dan, degree) between the planned and placed implants was evaluated based on the preoperative surgical plan and postoperative cone beam computed tomography (CBCT) data. A statistical analysis of the data was completed by using the chi-squared, Fisher exact, Student t, and Mann-Whitney U tests (α=.05).

RESULTS

A total of 32 study participants (38 implants) were included. The groups of s-CAIS (16 participants, 18 implants) and d-CAIS (16 participants, 20 implants) were statistically comparable in sex (P=.072), age (P=.548), bone quality (P=.671), and timing of implant placement (P=.719). All implants survived during an average follow-up period of 13 months. The d-CAIS group showed close linear deviations (Dpl 1.07 ±0.57 mm, Dap 1.26 ±0.53 mm) but lower angular deviation (Dan 2.14 ±1.20 degrees) and primary stability (ITV 25.25 ±7.52 Ncm) than the s-CAIS group (Dpl 0.92 ±0.46 mm, Dap 1.31 ±0.43 mm, Dan 3.31 ±1.61 degrees, ITV 30.56 ±11.23 Ncm, PDpl=.613, PDap=.743, PDan=.016, PITV=.028).

CONCLUSIONS

Comparable linear positioning accuracy and higher angular deviation were found for implants placed in the esthetic zone by using s-CAIS than when using d-CAIS. Higher primary stability of implants may be achieved by using s-CAIS, as s-CAIS seemed to have higher osteotomy accuracy than d-CAIS.

Advancing accuracy in guided implant placement: A comprehensive meta-analysis: Meta-Analysis evaluation of the accuracy of available implant placement Methods

OBJECTIVES

This meta-analysis aimed to determine the accuracy of currently available computer-assisted implant surgery (CAIS) modalities under in vitro conditions and investigate whether these novel techniques can achieve clinically acceptable accuracy.

DATA

In vitro studies comparing the postoperative implant position with the preoperative plan were included. Risk of bias was assessed using the Quality Assessment Tool For In Vitro Studies (QUIN Tool) and a sensitivity analysis was conducted using funnel plots.

SOURCES

A systematic search was performed on April 18, 2023, using the following three databases: MEDLINE (via PubMed), EMBASE, and Cochrane Central Register of Controlled Trials. No filters or restrictions were applied during the search.

RESULTS

A total of 5,894 studies were included following study selection. Robotic- and static CAIS (sCAIS) had the most accurate and clinically acceptable outcomes. sCAIS was further divided according to the guidance level. Among the sCAIS groups, fully guided implant placement had the greatest accuracy. Augmented reality-based CAIS (AR-based CAIS) had clinically acceptable results for all the outcomes except for apical global deviation. Dynamic CAIS (dCAIS) demonstrated clinically safe results, except for horizontal apical deviation. Freehand implant placement was associated with the greatest number of errors.

CONCLUSIONS

Fully guided sCAIS demonstrated the most predictable outcomes, whereas freehand sCAIS demonstrated the lowest accuracy. AR-based and robotic CAIS may be promising alternatives.

CLINICAL SIGNIFICANCE

To our knowledge, this is the first meta-analysis to evaluate the accuracy of robotic CAIS and investigate the accuracy of various CAIS modalities.

Proposal and Validation of a New Nonradiological Method for Postoperative Three-Dimensional Implant Position Analysis Based on the Dynamic Navigation System: An In Vitro Study

PURPOSE

To propose a novel, radiation-free method for postoperative three-dimensional (3D) position analysis of dental implants based on the dynamic navigation system (DNS) and evaluate its accuracy in vitro.

METHODS

A total of 60 implants were digitally planned and then placed in the standardized plastic models with a single-tooth gap and a free-end gap under the guidance of the DNS. Postoperative 3D positions of the inserted implants were evaluated using specially designed navigation-based software, and its datasets were superimposed onto those of cone beam computed tomography (CBCT) for accuracy analyses. Deviations at the coronal, apical, and angular levels were measured and statistically analyzed.

RESULTS

The mean 3D deviation was 0.88 ± 0.37 mm at the entry point and 1.02 ± 0.35 mm at the apex point. The mean angular deviation was 1.83 ± 0.79 degrees. No significant differences were noted in the deviations between implants placed in the single-tooth gap and the free-end situation (p > 0.05) or between different tooth positions at distal extensions (p > 0.05).

CONCLUSIONS

This non-radiographic method provides facile, efficient, and reliable postoperative implant position evaluation and may be a potential substitute for CBCT, particularly for implants placed under the guidance of dynamic navigation.

Accuracy of Guided Implant Surgery in the Edentulous Jaw Using Desktop 3D-Printed Mucosal Supported Guides

Purpose: The aim of this in vitro study is to evaluate the accuracy of implant position using mucosal supported surgical guides, produced by a desktop 3D printer. Methods: Ninety implants (Bone Level Roxolid, 4.1 mm × 10 mm, Straumann, Villerat, Switzerland) were placed in fifteen mandibular casts (Bonemodels, Castellón de la Plana, Spain). A mucosa-supported guide was designed and printed for each of the fifteen casts. After placement of the implants, the location was assessed by scanning the cast and scan bodies with an intra-oral scanner (Primescan^®, Dentsply Sirona, York, PA, USA). Two comparisons were performed: one with the mucosa as a reference, and one where only the implants were aligned. Angular, coronal and apical deviations were measured. Results: The mean implant angular deviation for tissue and implant alignment were 3.25° (SD 1.69°) and 2.39° (SD 1.42°) respectively, the coronal deviation 0.82 mm (SD 0.43 mm) and 0.45 mm (SD 0.31 mm) and the apical deviation 0.99 mm (SD 0.45 mm) and 0.71 mm (SD 0.43 mm). All three variables were significantly different between the tissue and implant alignment (p < 0.001). Conclusion: Based on the results of this study, we conclude that guided implant surgery using desktop 3D printed mucosa-supported guides has a clinically acceptable level of accuracy. The resilience of the mucosa has a negative effect on the guide stability and increases the deviation in implant position.

Influence of bone condition on implant placement accuracy with computer-guided surgery

BACKGROUND

The impact of the jaw bone condition, such as bone quantity and quality in the implant placement site, affecting the accuracy of implant placement with computer-guided surgery (CGS) remains unclear. Therefore, this study aimed to evaluate the influence of bone condition, i.e., bone density, bone width, and cortical bone thickness at the crestal bone on the accuracy of implant placement with CGS.

METHODS

A total of 47 tissue-level implants from 25 patients placed in the posterior mandibular area were studied. Implant placement position was planned on the simulation software, Simplant® Pro 16, by superimposing preoperative computed tomography images with stereolithography data of diagnostic wax-up on the dental cast. Implant placement surgery was performed using the surgical guide plate to reflect the planned implant position. The post-surgical dental cast was scanned to determine the position of the placed implant. Linear and vertical deviations between planned and placed implants were calculated. Deviations at both platform and apical of the implant were measured in the bucco-lingual and mesio-distal directions. Intra- and inter-observer variabilities were calculated to ensure measurement reliability. Multiple linear regression analysis was employed to investigate the effect of the bone condition, such as density, width, and cortical bone thickness at the implant site area, on the accuracy of implant placement (α = 0.05).

RESULT

Intra- and inter-observer variabilities of these measurements showed excellent agreement (intra class correlation coefficient ± 0.90). Bone condition significantly influenced the accuracy of implant placement using CGS (p < 0.05). Both bone density and width were found to be significant predictors.

CONCLUSIONS

Low bone density and/or narrow bucco-lingual width near the alveolar bone crest in the implant placement site might be a risk factor influencing the accuracy of implant placement with CGS.

Effect of Tooth Types on the Accuracy of Dental 3D Scanners: An In Vitro Study

The purpose of this study was to evaluate the accuracy of dental three-dimensional (3D) scanners according to the types of teeth. A computer-aided design (CAD) reference model (CRM) was obtained by scanning the reference typodont model using a high-precision industrial scanner (Solutionix C500, MEDIT). In addition, a CAD test model (CTM) was obtained using seven types of dental 3D scanners (desktop scanners (E1 and DOF Freedom HD) and intraoral scanners (CS3500, CS3600, Trios2, Trios3, and i500)). The 3D inspection software (Geomagic control X, 3DSystems) was used to segment the CRM according to the types of teeth and to superimpose the CTM based on the segmented teeth. The 3D accuracy of the scanner was then analyzed according to the types of teeth. One-way analysis of variance (ANOVA) was used to compare the differences according to the types of teeth in statistical analysis, and the Tukey HSD test was used for post hoc testing (α = 0.05). Both desktop and intraoral scanners showed significant differences in accuracy according to the types of teeth (P < 0.001), and the accuracy of intraoral scanners tended to get worse from anterior to posterior. Therefore, when scanning a complete arch using an intraoral scanner, the clinician should consider the tendency for the accuracy to decrease from anterior to posterior.

Digital Evaluation of the Accuracy of Computer-Guided Dental Implant Placement: An In Vitro Study

Compared to traditional implant surgical guides, computer-assisted implant surgical guides can be considered for positioning implants in the final prosthesis. These computer-assisted implant surgical guides can be easily fabricated with personal 3D printers after being designed with implant planning CAD software. Although the accuracy of computer-assisted implant surgical guides fabricated using personal 3D printers is an important factor in their clinical use, there is still a lack of research examining their accuracy. Therefore, this study evaluated the accuracy of computer-assisted implant surgical guides, which were designed using two implant planning CAD software programs (Deltanine and R2gate software) and fabricated with personal 3D printers using a non-radiographic method. Amongst the patients who visited Kyungpook National University Dental Hospital, one patient scheduled to undergo surgery of the left mandibular second premolar was randomly selected. Twenty partially edentulous resin study models were produced using a 3D printer. Using the Deltanine and R2gate implant planning CAD software, 10 implant surgical guides per software were designed and produced using a personal 3D printer. The implants (SIII SA (Ø 4.0, L = 10 mm), Osstem, Busan, Korea) were placed by one skilled investigator using the computer-assisted implant surgical guides. To confirm the position of the actual implant fixture, the study models with the implant fixtures were scanned with a connected scan body to extract the STL files, and then overlapped with the scanned file by connecting the scan body-implant fixture complex. As a result, the mean apical deviation of the Deltanine and R2gate software was 0.603 ± 0.19 mm and 0.609 ± 0.18 mm, while the mean angular deviation was 1.97 ± 0.84° and 1.92 ± 0.52°, respectively. There was no significant difference between the two software programs (p > 0.05). Thus, the accuracy of the personal 3D printing implant surgical guides is in the average range allowed by the dental clinician.