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Biomechanical Influence of Different Cervical Micro-Thread Forms over Narrow-Diameter Implants (2.9 mm) Using Finite
Qiannian Zhang1,2, Waikit Lau1,2, Nalini Cheong1,2
1Hospital of Stomatology, Zhongshan City, Zhongshan 528400, China.
Journal of Functional Biomaterials
|November 26, 2025
Summary
Optimizing thread forms and face angles in narrow-diameter implants (NDIs) enhances mechanical stability. Specific angles (30-60 degrees) improve stress distribution and stability in the bone-implant interface.
Area of Science:
- Biomaterials Engineering
- Dental Implantology
- Biomechanics
Background:
- Narrow-diameter implants (NDIs) are crucial for areas with limited bone volume.
- The cervical region of implants is a stress concentration zone affecting long-term stability.
- Implant thread design significantly influences stress distribution and bone response.
Purpose of the Study:
- To investigate the impact of varying thread forms and face angles on stress and strain in NDIs.
- To determine optimal thread parameters for enhanced mechanical performance and bone integration.
- To analyze stress distribution in the implant-bone interface and peri-implant bone tissue.
Main Methods:
- Finite element analysis (FEA) was used to model nine NDI designs with varied thread forms and face angles.
- Models were implanted into Type III bone and subjected to 100 N vertical and oblique occlusal forces.
- Biomechanical evaluation included von Mises stress, maximum equivalent elastic strain, and abutment stress.
Main Results:
- Optimal thread face angles varied by thread group: 60° for RB, 45° for B, and 30° for V threads.
- These optimized angles reduced stress concentrations at the bone-implant interface.
- Improved strain distribution was observed in the peri-implant bone tissue with optimized designs.
Conclusions:
- Thread form and face angle are critical factors in NDI biomechanical performance.
- Tailoring thread parameters to specific designs can optimize stress distribution and enhance implant stability.
- This research provides valuable insights for designing more robust NDIs.
