Literature DB >> 31810351

Accuracy of Computer-Aided Dynamic Navigation Compared to Computer-Aided Static Navigation for Dental Implant Placement: An In Vitro Study.

Alfonso Mediavilla Guzmán1, Elena Riad Deglow1, Álvaro Zubizarreta-Macho1, Rubén Agustín-Panadero2, Sofía Hernández Montero1.   

Abstract

AIM: To analyze the accuracy capability of two computer-aided navigation procedures for dental implant placement.
MATERIALS AND METHODS: A total of 40 dental implants were selected, which were randomly distributed into two study groups, namely, group A, consisting of those implants that were placed using a computer-aided static navigation system (n = 20) (guided implant (GI)) and group B, consisting of those implants that were placed using a computer-aided dynamic navigation system (n = 20) (navigation implant (NI)). The placement of the implants from group A was performed using surgical templates that were designed using 3D implant-planning software based on preoperative cone-beam computed tomography (CBCT) and a 3D extraoral surface scan, and the placement of group B implants was planned and performed using the dynamic navigation system. After placing the dental implants, a second CBCT was performed and the degree of accuracy of the planning and placement of the implants was analyzed using therapeutic planning software and Student's t-test.
RESULTS: The paired t-test revealed no statistically significant differences between GI and NI at the coronal (p = 0.6535) and apical (p = 0.9081) levels; however, statistically significant differences were observed between the angular deviations of GI and NI (p = 0.0272).
CONCLUSION: Both computer-aided static and dynamic navigation procedures allow accurate implant placement.

Entities:  

Keywords:  computer-assisted surgery; image-guided surgery; implantology; navigation system; real-time tracking

Year:  2019        PMID: 31810351      PMCID: PMC6947513          DOI: 10.3390/jcm8122123

Source DB:  PubMed          Journal:  J Clin Med        ISSN: 2077-0383            Impact factor:   4.241


1. Introduction

Dental implant placement has recently emerged as a predictable treatment option to restore edentulous patients [1]. Nevertheless, some complications are attributed to this technique, including cortical or dental perforations and damage to particular anatomical structures, such as the inferior alveolar nerve or the maxillary sinus, due to implant malpositioning [1,2]. Recently, dental implant placement using image data-based navigation has been introduced into the field of dental surgery in an attempt to improve the accuracy of dental implant placement and avoid potential risks associated with this therapeutic procedure [3]. This surgical approach was developed based on preoperative cone-beam computed tomography (CBCT) scanning and specific 3D implant-planning software, thereby allowing for accurate implant placement [4]. Generally speaking, there are two types of computer-assisted surgical implant placement system techniques, namely, static navigation and dynamic navigation. Static navigation systems require the use of surgical templates to guide the drilling process. Dynamic navigation systems recognize and track the position of optical reference markers placed over the patient and surgical instruments by means of a tracking system array. Both navigation techniques have been widely analyzed, demonstrating high accuracy levels for dental implant placement [1,3,5,6]. Static navigation systems have a mean horizontal deviation at the coronal entry point and apical endpoint of 1.2 mm (1.04–1.44 mm) and 1.4 mm (1.28–1.58 mm), respectively, and a mean angular deviation of 3.5° (3.0–3.96°) [7]. However, dynamic navigation systems demonstrated lower deviation values at the coronal entry point (0.71 ± 0.40 mm), apical endpoint (1.00 ± 0.49 mm), and angular deviation (2.26 ± 1.62°) [8], but these values have not yet been compared. The aim of this work was to analyze and compare the accuracy of dental implant placement via static and dynamic navigation systems, with a null hypothesis (H0) stating that there would be no difference between the static and dynamic navigation systems with regard to the accuracy of dental implant placement.

2. Materials and Methods

2.1. Study Design

A randomized controlled experimental trial was conducted in accordance with the principles defined in the International Organization for Standardization (ISO 14801). The study was performed at the Dental Centre of Innovation and Advanced Specialties at Alfonso X El Sabio University (Madrid, Spain) between January and March 2019. This study was authorized by the Ethical Committee of the Faculty of Health Sciences, University Alfonso X el sabio, in December 2018.

2.2. Experimental Procedure

Forty dental implants (BioHorizons, Birmingham, AL, USA) were placed in tooth positions 2.4 and 2.6 (4.6 mm × 12 mm, conical wall and internal taper) in twenty standardized polyurethane models of partially edentulous upper jaws (Sawbones Europe AB, Malmo, Sweden) based on one obtained from a real clinical case. The dental implants were randomized (Epidat 4.1, Galicia, Spain) and assigned to one of two study groups: group A, consisting of dental implants that were placed using a computer-aided static navigation system (NemoStudio®, Nemotec, Madrid, Spain) (n = 20) (guided implant (GI)) and group B, consisting of dental implants that were placed using a computer-aided dynamic navigation system (Navident, ClaroNav, Toronto, Canada) (n = 20) (navigation implant (NI)). The dental implants were first placed in tooth position 2.4, followed by position 2.6, in consideration of a real situation. The GI jaw models were submitted for a preoperative CBCT scan (WhiteFox, Satelec, Merignac, France) with the following exposure parameters: 105.0 kV peak, 8.0 mA, 7.20 s, and a field of view of 15 mm × 13 mm. Afterward, the ten jaw models assigned to the GI study group were submitted for a 3D-extraoral surface scan (EVO, Ceratomic, Protechno, Girona, Spain). Datasets obtained from the digital workflow were uploaded into 3D implant-planning software (NemoStudio®) to design virtual templates for GI implant placement. The 3D surface scan and CBCT data were matched by aligning the key points present in the partially edentulous upper jaw models. A virtual implant drill was designed with a diameter and length of 4.6 and 12 mm, respectively, as per the measurements of the selected implant (Figure 1A,B). After designing the virtual templates (Figure 1C,D), they were fabricated using the stereolithography technique (ProJet 6000, 3D Systems, Rock Hill, SC, USA) (Figure 1E), except for the 5 mm stainless steel cylinders, which were manually attached to the templates. The templates fit the model and did not need further adjustments.
Figure 1

(A–C) Dental implant planning with the computer-aided static navigation system using a cone-beam computed tomography (CBCT) scan (green lines); (C,D) virtual template design according to the planned virtual dental implant placement; (E) manufactured stereolithography template fixed over the dental surface of the teeth and placed over the partially edentulous upper jaw models.

The NI jaw models were submitted to a preoperative CBCT scan prior to placement of the thermoplastic template (Navistent, ClaroNav, Toronto, ON, Canada) that includes a radiographic marker and an attached handle with a black and white jaw tag, which was fixed over the dental surface of the teeth. CBCT datasets were imported into the treatment-planning software on a mounted laptop computer in a mobile unit (Navident, ClaroNav, Toronto, Canada) to simulate dental implant placement (Figure 2A). Another black and white drill tag was attached to the handpiece. Both optical reference markers were calibrated and recognized by the optical triangulation tracking system composed of stereoscopic motion-tracking cameras which guided the drilling process at the planned angle, pathway, and depth in real time. Socket drilling was performed with a drill (Ref. TSD2041, BioHorizons) and was monitored using the laptop computer containing the computer-aided dynamic navigation system (Figure 2B).
Figure 2

(A) Dental implant planning as seen in the treatment-planning software of the computer-aided dynamic navigation system (yellow cylinders) and (B) dental implant placement (green cylinders) controlled at all planes and depths.

2.3. Measurement Procedure

Following the dental implant placement, postoperative CBCT scans were taken. Dental implant planning and postoperative CBCT scans of the study groups were uploaded into 3D implant-planning software (NemoScan, Nemotec, Madrid, Spain) and matched to analyze apical deviation, which was measured at the apical endpoint; coronal deviation, which was measured at the entry point; and angular deviation, which was measured in the center of the cylinder. All noted deviations of all of the implants were evaluated and compared in the axial, sagittal, and coronal views (Figure 3A,B) using the same expertise operator. Results were expressed according to each position.
Figure 3

(A) Dental implant planning (green cylinders) and dental implant placement (red cylinders) using the computer-aided static navigation system and (B) the computer-aided dynamic navigation system.

2.4. Statistical Analysis

Statistical analysis of all variables was carried out using SAS 9.4 (SAS Institute Inc., Cary, NC, USA). Descriptive statistics were expressed as mean and standard deviation (SD) values for quantitative variables and as absolute numbers and percentages for qualitative variables. Comparative analysis was performed by comparing the mean deviation values between planned and performed implant placements using Student’s t-test as the variables had a normal distribution. The statistical significance was set at p ˂ 0.05.

3. Results

Table 1 shows the mean and SD values. Mean deviations of 0.78 ± 0.43 mm (min: 0.20 mm; max: 1.70 mm) and 0.85 ± 0.48 mm (min: 0.30 mm; max: 1.90 mm) were observed at the coronal entry point of the GI (Figure 3A) and NI (Figure 3B) study groups, respectively (Figure 4).
Table 1

Descriptive deviation values at the apical (mm), coronal (mm), and angular (°) levels (guided implant (GI): static navigation system; navigation implant (NI): dynamic navigation system).

n MeanSDMinimumMaximum
CORONALGI200.780.430.201.70
NI200.850.480.301.90
APICALGI201.200.480.302.10
NI201.180.600.202.50
ANGULARGI202.951.480.605.20 *
NI204.001.411.606.10
Figure 4

Box plots of the coronal deviations observed in the experimental groups. The horizontal lines in each box represent the median values (GI: static navigation system; NI: dynamic navigation system).

The paired t-test revealed no statistically significant differences between the coronal deviations of GI and NI (p = 0.6535). Mean deviations of 1.20 ± 0.48 mm (min: 0.30 mm; max: 2.10 mm) and 1.18 ± 0.60 mm (min: 0.20 mm; max: 2.50 mm) were observed at the apical endpoint of the GI (Figure 3A) and NI (Figure 3B) study groups, respectively (Figure 5).
Figure 5

Box plots of the apical deviations observed in the experimental groups. The horizontal lines in each box represent the median values (GI: static navigation system; NI: dynamic navigation system).

The paired t-test revealed no statistically significant differences between the apical deviations of GI and NI (p = 0.9081). Mean deviations of 2.95° ± 1.48° (min: 0.60°; max: 5.20°) and 4.00° ± 1.41° (min: 1.60°; max: 6.10°) were observed in the GI (Figure 3A) and NI (Figure 3B) study groups, respectively (Figure 6). The paired t-test revealed statistically significant differences between the angular deviations of GI and NI (p = 0.0272).
Figure 6

Box plots of the angular deviations observed in the experimental groups. The horizontal lines in each box represent the median values (GI: static navigation system; NI: dynamic navigation system).

4. Discussion

The results obtained in the present study rejected the null hypothesis (H0) that stated that there would be no difference between computer-aided static and dynamic navigation systems with regard to the accuracy of dental implant placement. This in vitro study has potential limits related to the precision and stability of the surgical template due to the use of models, which may have significantly differed from what is encountered in a real clinical situation. In recent literature, the accuracy of surgical computer-aided navigation techniques has been widely evaluated and compared. Hoffmann et al. [9] reported statistically significant differences in the accuracy of implant placement between computer-aided dynamic navigation systems and manual implant placement, with mean angular deviations of 4.2 ± 1.8° and 11.2 ± 5°, respectively. Although the methods and selection criteria were slightly different from those used in the present study, implant placement using a computer-aided dynamic navigation system offered a greater degree of accuracy than manual implant placement. Chang-Kai et al. [10] reported similar mean horizontal deviation values at the apical endpoint when using a computer-aided dynamic navigation system (1.35 ± 0.55 mm), a computer-aided static navigation system (1.50 ± 0.79 mm), and manual implant placement (2 ± 0.79 mm). Higher angular deviation values were reported for the computer-aided dynamic navigation system (4.45 ± 1.97°), the computer-aided static navigation system (6.02 ± 3.71°), and manual implant placement (9.26 ± 3.62°). The accuracy of implant placement with computer-aided navigation systems was shown to be better than the degree of accuracy during manual procedures, but the angular deviation values were different from the present findings. The learning requirements of computer-aided dynamic navigation systems might explain the differences between static and dynamic navigation systems [8]. Computer-aided static navigation techniques performed using surgical templates prevent the need for drilling guidance during surgery [1,3,4,5]. Therefore, implant placement accuracy depends directly on the design and manufacturing process of the surgical template; if there is an inaccuracy during the fabrication process, this might lead to intraoperative complications [3]. On the other hand, computer-aided dynamic navigation systems allow for a direct view of the surgical field and provide clinicians with the ability to relocalize the position of an implant, if necessary [9,10]. In addition, these systems are particularly useful in cases of limited mouth openings or treatments in the posterior region [1,8]. The main disadvantage of computer-aided dynamic navigation systems is the difficulty in keeping sight of the dynamic navigation system display during the surgical procedure. However, augmented reality devices could be used to display the virtual image of the computer-aided dynamic navigation system without losing sight of the surgical field [11,12]. Image-guided navigation systems demonstrated comparable accuracy rates regarding control of the depth, position, and angle of implants, which is necessary to avoid intraoperative surgical complications and poor positioning of implants, thereby compromising primary stability and immediate-loading restoration techniques [8,9,12]. In addition, they also avoid the wide excisions often needed to expose the implant platform after the healing period, and enable a minimally invasive transgingival approach to implant placement [1,12]. This is especially helpful in high-risk patients, such as cardiovascular patients taking anticoagulation medications or patients with edentulous, atrophic mandibles [12]. This study shows that computer-aided static and dynamic navigation procedures allow accurate dental implant placement. Nevertheless, further research is needed to determine the influence of the dental implant placement procedure on the accuracy of dental implant positioning and potential clinical complications.

5. Conclusions

In conclusion, within the limitations of this study, the results showed that computer-aided static and dynamic navigation procedures allow accurate implant placement. Nevertheless, it is mandatory to perform a CBCT scan and a 3D surface scan and to plan implant placement using specialized surgical planning software. Clinical trials are necessary to analyze the real behavior of these computer-aided navigation procedures.
  12 in total

1.  Accuracy of navigation-guided socket drilling before implant installation compared to the conventional free-hand method in a synthetic edentulous lower jaw model.

Authors:  Jürgen Hoffmann; Carsten Westendorff; German Gomez-Roman; Siegmar Reinert
Journal:  Clin Oral Implants Res       Date:  2005-10       Impact factor: 5.977

2.  Use of stereolithographic templates for surgical and prosthodontic implant planning and placement. Part II. A clinical report.

Authors:  Kunal Lal; George S White; Dennis N Morea; Robert F Wright
Journal:  J Prosthodont       Date:  2006 Mar-Apr       Impact factor: 2.752

Review 3.  Accuracy in computer-aided implant surgery--a review.

Authors:  Gerlig Widmann; Reto Josef Bale
Journal:  Int J Oral Maxillofac Implants       Date:  2006 Mar-Apr       Impact factor: 2.804

4.  The accuracy of static vs. dynamic computer-assisted implant surgery in single tooth space: A randomized controlled trial.

Authors:  Dechawat Kaewsiri; Soontra Panmekiate; Keskanya Subbalekha; Nikos Mattheos; Atiphan Pimkhaokham
Journal:  Clin Oral Implants Res       Date:  2019-05-07       Impact factor: 5.977

5.  Navigation in implantology.

Authors:  Insa Herklotz; Florian Beuer; Andreas Kunz; Detlef Hildebrand; Arndt Happe
Journal:  Int J Comput Dent       Date:  2017       Impact factor: 1.883

6.  The accuracy of static computer-aided implant surgery: A systematic review and meta-analysis.

Authors:  Ali Tahmaseb; Viviane Wu; Daniel Wismeijer; Wim Coucke; Christopher Evans
Journal:  Clin Oral Implants Res       Date:  2018-10       Impact factor: 5.977

7.  Accuracy of Implant Placement with a Navigation System, a Laboratory Guide, and Freehand Drilling.

Authors:  Chang-Kai Chen; Da-Yo Yuh; Ren-Yeong Huang; Earl Fu; Cheng-Feng Tsai; Cheng-Yang Chiang
Journal:  Int J Oral Maxillofac Implants       Date:  2018 Nov/Dec       Impact factor: 2.804

8.  Accuracy of a Dynamic Dental Implant Navigation System in a Private Practice.

Authors:  Luigi V Stefanelli; Bradley S DeGroot; David I Lipton; George A Mandelaris
Journal:  Int J Oral Maxillofac Implants       Date:  2018-12-05       Impact factor: 2.804

9.  Novel Techniques with the Aid of a Staged CBCT Guided Surgical Protocol.

Authors:  Evdokia Chasioti; Mohammed Sayed; Howard Drew
Journal:  Case Rep Dent       Date:  2015-01-06

10.  Augmented reality for dental implantology: a pilot clinical report of two cases.

Authors:  Gerardo Pellegrino; Carlo Mangano; Roberto Mangano; Agnese Ferri; Valerio Taraschi; Claudio Marchetti
Journal:  BMC Oral Health       Date:  2019-07-19       Impact factor: 2.757

View more
  15 in total

1.  [In vitro evaluation of positioning accuracy of trephine bur at different depths by dynamic navigation].

Authors:  S M Liu; Y J Zhao; X Y Wang; Z H Wang
Journal:  Beijing Da Xue Xue Bao Yi Xue Ban       Date:  2022-02-18

2.  Preliminary study on the osseointegration effects of contactless automated implant cavity preparation via femtosecond laser ablation.

Authors:  Shanshan Liang; Jianqiao Zheng; Fusong Yuan
Journal:  Biomed Opt Express       Date:  2021-12-03       Impact factor: 3.732

3.  Accuracy of Computer-Assisted Dynamic Navigation in Implant Placement with a Fully Digital Approach: A Prospective Clinical Trial.

Authors:  Cornelia Edelmann; Martin Wetzel; Anne Knipper; Ralph G Luthardt; Sigmar Schnutenhaus
Journal:  J Clin Med       Date:  2021-04-21       Impact factor: 4.241

4.  Science, Innovation and Education as Pillars of High-Quality Implant Dentistry: Overcoming Challenges through Innovation Dictates Trends.

Authors:  Miguel de Araújo Nobre
Journal:  J Clin Med       Date:  2020-05-22       Impact factor: 4.241

5.  The Workflow of a New Dynamic Navigation System for the Insertion of Dental Implants in the Rehabilitation of Edentulous Jaws: Report of Two Cases.

Authors:  Armando Lopes; Miguel de Araújo Nobre; Diogo Santos
Journal:  J Clin Med       Date:  2020-02-04       Impact factor: 4.241

Review 6.  Efficacy of Computer-Aided Static Navigation Technique on the Accuracy of Endodontic Microsurgery. A Systematic Review and Meta-Analysis.

Authors:  Álvaro Zubizarreta-Macho; César Castillo-Amature; José María Montiel-Company; Jesús Mena-Álvarez
Journal:  J Clin Med       Date:  2021-01-15       Impact factor: 4.241

7.  Digital Approach for the Rehabilitation of the Edentulous Maxilla with Pterygoid and Standard Implants: The Static and Dynamic Computer-Aided Protocols.

Authors:  Alessio Franchina; Luigi Vito Stefanelli; Simone Gorini; Simone Fedi; Giuseppe Lizio; Gerardo Pellegrino
Journal:  Methods Protoc       Date:  2020-12-21

8.  A Novel Guided Zygomatic and Pterygoid Implant Surgery System: A Human Cadaver Study on Accuracy.

Authors:  Francesco Grecchi; Luigi V Stefanelli; Fabrizio Grivetto; Emma Grecchi; Rami Siev; Ziv Mazor; Massimo Del Fabbro; Nicola Pranno; Alessio Franchina; Vittorio Di Lucia; Francesca De Angelis; Funda Goker
Journal:  Int J Environ Res Public Health       Date:  2021-06-07       Impact factor: 3.390

Review 9.  Effect of Computer-Aided Navigation Techniques on the Accuracy of Endodontic Access Cavities: A Systematic Review and Meta-Analysis.

Authors:  Álvaro Zubizarreta-Macho; Sara Valle Castaño; José María Montiel-Company; Jesús Mena-Álvarez
Journal:  Biology (Basel)       Date:  2021-03-10

10.  Accuracy of Computer-Assisted Dynamic Navigation as a Function of Different Intraoral Reference Systems: An In Vitro Study.

Authors:  Sigmar Schnutenhaus; Anne Knipper; Martin Wetzel; Cornelia Edelmann; Ralph Luthardt
Journal:  Int J Environ Res Public Health       Date:  2021-03-21       Impact factor: 3.390

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.