Implant Deviation Assessment in Static and Dynamic Guidance: An In Vitro Study

Purpose This in vitro study aims to assess implant placement positioning accuracy using static or dynamic guidance by measuring 3D, 2D, and volumetric deviations of 20 implants compared to the reference implant position obtained following preoperative implant planning. Methods A case of single-tooth edentulism was used to simulate the situation of single implant placement. A cone beam computed tomography (CBCT) scan (Orthophos SL 3D, Dentsply Sirona, Mölndal, Sweden) of the model was taken, and implant planning was done on the Blue Sky Plan (BSP) software (Blue Sky Bio, New York City, NY), generating an implant reference position. The 20 printed models were randomly divided into two equal groups, with both receiving implant placement using either static guidance using polymethylmethacrylate (PMMA)-printed templates (group 1) or dynamic guidance using the X-Guide® (X-Nav Technologies, LLC, Lansdale, PA, USA) navigation system (group 2). A high-precision non-reflective abutment-level scan body was mounted on the implant directly after placement, and a surface scan was taken. The reference implant and placed implant standard tessellation language (STL) files were aligned using the Medit Link® software (Medit, Seoul, South Korea). Three-dimensional and 2D deviations were assessed using the Geomagic® Control X software (3D Systems, Rock Hill, SC), and volumetric deviation was assessed using the Blender™ software (Blender Foundation, Amsterdam, Netherlands). Statistical analysis was performed using RStudio version 2024.12.1 (Posit Software, Boston, MA). Results Twenty scans were obtained in total (n = 10 per group). The significance level was set at p ≤ 0.05. Statistical analysis revealed statistical significance in terms of 3D coronal deviation (p < 0.001), coronal linear deviation (CLD) (p = 0.036), coronal vertical deviation (CVD) (p < 0.001), and apical vertical deviation (AVD) (p = 0.001). However, 3D apical deviation (p = 0.131), apical linear deviation (ALD) (p = 0.945), angular deviation (p = 0.097), and accuracy percentage (p = 0.954) did not reach statistical significance. Conclusion Dynamic guidance showed higher coronal and vertical deviations compared to static guidance, while overall accuracy and global implant deviation remained comparable between the techniques. This in vitro study consisted of resin models lacking bone density or gingival tissue simulation, which limits the extrapolation of the findings to clinical practice. With that being said, further validation of these results through clinical studies involving a larger sample is required.

Authors

Publication Details

Journal
Cureus
Published
2026-03-17
DOI
https://doi.org/10.7759/cureus.105355
Primary Topic
Motor Control and Adaptation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Implant Deviation Assessment in Static and Dynamic Guidance: An In Vitro Study

Stephanie Mrad, Abdallah Menhall, Nabil Ghosn, Charbel Kachouh et al.
Cureus
Motor Control and Adaptation
article

Implant Deviation Assessment in Static and Dynamic Guidance: An In Vitro Study

Stephanie Mrad, Abdallah Menhall, Nabil Ghosn, Charbel Kachouh, Hani Tohme, Ronald Younes, Adam Saleh
article en

Abstract

Purpose This in vitro study aims to assess implant placement positioning accuracy using static or dynamic guidance by measuring 3D, 2D, and volumetric deviations of 20 implants compared to the reference implant position obtained following preoperative implant planning. Methods A case of single-tooth edentulism was used to simulate the situation of single implant placement. A cone beam computed tomography (CBCT) scan (Orthophos SL 3D, Dentsply Sirona, Mölndal, Sweden) of the model was taken, and implant planning was done on the Blue Sky Plan (BSP) software (Blue Sky Bio, New York City, NY), generating an implant reference position. The 20 printed models were randomly divided into two equal groups, with both receiving implant placement using either static guidance using polymethylmethacrylate (PMMA)-printed templates (group 1) or dynamic guidance using the X-Guide® (X-Nav Technologies, LLC, Lansdale, PA, USA) navigation system (group 2). A high-precision non-reflective abutment-level scan body was mounted on the implant directly after placement, and a surface scan was taken. The reference implant and placed implant standard tessellation language (STL) files were aligned using the Medit Link® software (Medit, Seoul, South Korea). Three-dimensional and 2D deviations were assessed using the Geomagic® Control X software (3D Systems, Rock Hill, SC), and volumetric deviation was assessed using the Blender™ software (Blender Foundation, Amsterdam, Netherlands). Statistical analysis was performed using RStudio version 2024.12.1 (Posit Software, Boston, MA). Results Twenty scans were obtained in total (n = 10 per group). The significance level was set at p ≤ 0.05. Statistical analysis revealed statistical significance in terms of 3D coronal deviation (p < 0.001), coronal linear deviation (CLD) (p = 0.036), coronal vertical deviation (CVD) (p < 0.001), and apical vertical deviation (AVD) (p = 0.001). However, 3D apical deviation (p = 0.131), apical linear deviation (ALD) (p = 0.945), angular deviation (p = 0.097), and accuracy percentage (p = 0.954) did not reach statistical significance. Conclusion Dynamic guidance showed higher coronal and vertical deviations compared to static guidance, while overall accuracy and global implant deviation remained comparable between the techniques. This in vitro study consisted of resin models lacking bone density or gingival tissue simulation, which limits the extrapolation of the findings to clinical practice. With that being said, further validation of these results through clinical studies involving a larger sample is required.

Cureus
Openalex Percentile: Top 24%
Motor Control and Adaptation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.