Navigation System Approach in Zygomatic Implant Technique

Gasparini, Giulio; Boniello, Roberto; Laforì, Andreina; Angelis, Paolo De; Deo, Vito Del; Moro, Alessandro; Saponaro, Gianmarco; Pelo, Sandro

doi:10.1097/scs.0000000000003261

Cited by 17 publications

(9 citation statements)

References 8 publications

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“…Fifteen skull models underwent ZI placement via an image‐guided oral implant system (IGOIS) developed by Chen et al, and the results showed high insertion accuracy (Xiaojun et al, 2009 ). Other navigation systems, such as VoXim (Kreissl et al, 2007 ), AccuNavi (Chen et al, 2011 ), ImplaNav (Pellegrino et al, 2015 ) and some without certain names (Franco, 2017 ; Gasparini et al, 2017 ), have also been employed in ZI surgery, achieving gratifying outcomes with high accuracy. Recently, the X‐Guide navigation system has been applied in both conventional dental and ZI surgery (Lopes et al, 2020 ; Panchal et al, 2019 ).…”

Section: Discussionmentioning

confidence: 99%

Reliability and accuracy of dynamic navigation for zygomatic implant placement

Tao

Lan

et al. 2022

Clinical Oral Implants Res

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Objectives To assess the accuracy of a real‐time dynamic navigation system applied in zygomatic implant (ZI) surgery and summarize device‐related negative events and their management. Material and methods Patients who presented with severely maxillary atrophy or maxillary defects and received dynamic navigation‐supported ZI surgery were included. The deviations of entry, exit, and angle were measured after image data fusion. A linear mixed‐effects model was used. Statistical significance was defined as p < .05. Device‐related negative events and their management were also recorded and analyzed. Results Two hundred and thirty‐one zygomatic implants (ZIs) with navigation‐guided placement were planned in 74 consecutive patients between Jan 2015 and Aug 2020. Among them, 71 patients with 221 ZIs received navigation‐guided surgery finally. The deviations in entry, exit, and angle were 1.57 ± 0.71 mm, 2.1 ± 0.94 mm and 2.68 ± 1.25 degrees, respectively. Significant differences were found in entry and exit deviation according to the number of ZIs in the zygomata (p = .03 and .00, respectively). Patients with atrophic maxillary or maxillary defects showed a significant difference in exit deviation (p = .01). A total of 28 device‐related negative events occurred, and one resulted in 2 ZI failures due to implant malposition. The overall survival rate of ZIs was 98.64%, and the mean follow‐up time was 24.11 months (Standard Deviation [SD]: 12.62). Conclusions The navigation‐supported ZI implantation is an accurate and reliable surgical approach. However, relevant technical negative events in the navigation process are worthy of attention.

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Section: Discussionmentioning

confidence: 99%

Reliability and accuracy of dynamic navigation for zygomatic implant placement

Tao

Lan

et al. 2022

Clinical Oral Implants Res

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“…Another study reported 0.72 ± 0.26 mm for the entry deviation, 0.69 ± 0.36 mm for the apical deviation and 5.33 ± 1.63° for the angle deviation 35 . Although several studies have reported that zygomatic implants can be placed under guidance of navigation systems, 2,36‐38 accuracy information was scarcely reported. Hung et al 21 measured the accuracy of zygomatic implants inserted with the help of image‐guided navigation systems, and the entry deviation, apical deviation and angle deviation were 1.35 ± 0.75 mm, 2.15 ± 0.95 mm, and 2.05 ± 1.02°, respectively.…”

Section: Discussionmentioning

confidence: 99%

Comparative accuracy of cone‐beam CT and conventional multislice computed tomography for real‐time navigation in zygomatic implant surgery

Tao

Shen

Sun

et al. 2020

Clin Implant Dent Rel Res

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Background: Cone-beam computed tomography (CBCT) and conventional multislice CT (MSCT) are both used in zygomatic implant navigation surgery but the superiority of one technique versus the other remains unclear. Purpose: This study compared the accuracy of CBCT and MSCT in zygomatic implant navigation surgery by calculating the deviations of implants. Material and methods: Patients with severely atrophic maxillae were classified into two groups according to the use of CBCT-or MSCT-guided navigation system. The entry and apical distance deviation, and the angle deviation of zygomatic implants were measured on fused operation images. A linear effect model was used for analysis, with statistical significance set at P < .05. Results: A total of 72 zygomatic implants were inserted as planned in 23 patients. The comparison of deviations in CBCT and MSCT groups showed a mean (± SD) entry deviation of 1.69 ± 0.59 mm vs 2.04 ± 0.78 mm (P = .146), apical deviation of 2 ± 0.68 mm vs 2.55 ± 0.85 (P < .001), and angle deviation of 2.32 ± 1.02 vs 3.23 ± 1.21 (P = .038). Conclusion: Real-time zygomatic implant navigation surgery with CBCT may result in higher values for accuracy than MSCT.

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“…The goals of dental implant navigation systems are to increase accuracy in dental implant surgery and to minimize the occurrence of unnecessary medical disputes and negligence due to surgeon inexperience. Gasparini et al [15] argued that mastery over the use of dental implant navigation systems and accuracy in their use can be achieved through practice. Sun et al [10] conducted that reaching the plateau of a learning curve represents mastery over dental implant navigation system use.…”

Section: Discussionmentioning

confidence: 99%

The influence of dental experience on a dental implant navigation system

2019

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Background This study evaluated the operating performance of an implant navigation system used by dental students and dentists of prosthodontic background with varying levels of experience. A surgical navigation system and optical tracking system were used, and dentists’ accuracies were evaluated in terms of differences between the positions of actually drilled holes and those of the holes planned using software before surgeries. Methods The study participants were 5 dental students or dentists who had studied in the same university and hospital but had different experience levels regarding implants. All participants were trained in operating the AqNavi system in the beginning of the study. Subsequently, using 5 pairs of dental models, each participant drilled 5 implant holes at 6 partially edentulous positions (11, 17, 26, 31, 36, and 47). In total, each participant conducted 30 drilling tests. Results In total, 150 tests among 5 dentists at 6 tooth positions (11, 17, 26, 31, 36, and 47) were conducted. Although a comparison of the tests revealed significant differences in the longitudinal error (P < .0001) and angular error (P = .0011), no significant difference was observed in the total error among the dentists. Conclusions A relatively long operating time was associated with relatively little implant experience. Through the dental navigation system, dental students can be introduced to dental implant surgery earlier than what was possible in the past. The results demonstrated that the operational accuracy of the dental implant navigation system is not restricted by participants’ implant experience levels. The implant navigation system assists the dentist in the ability to accurately insert the dental implant into the correct position without being affected by his/her own experience of implant surgery.

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Navigation System Approach in Zygomatic Implant Technique

Cited by 17 publications

References 8 publications

Reliability and accuracy of dynamic navigation for zygomatic implant placement

Reliability and accuracy of dynamic navigation for zygomatic implant placement

Comparative accuracy of cone‐beam CT and conventional multislice computed tomography for real‐time navigation in zygomatic implant surgery

The influence of dental experience on a dental implant navigation system

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