Insertion torque/time integral as a measure of primary implant stability
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Tanja Grobecker-Karl
,
Matthias Karl
and
Constanze Steiner
Abstract
The goal of this in vitro study was to determine the insertion torque/time integral for three implant systems. Bone level implants (n = 10; BLT – Straumann Bone Level Tapered 4.1 mm × 12 mm, V3 – MIS V3 3.9 mm × 11.5 mm, ASTRA – Dentsply-Sirona ASTRA TX 4.0 mm × 13 mm) were placed in polyurethane foam material consisting of a trabecular and a cortical layer applying protocols for medium quality bone. Besides measuring maximum insertion torque and primary implant stability using resonance frequency analysis (RFA), torque time curves recorded during insertion were used for calculating insertion torque/time integrals. Statistical analysis was based on ANOVA, Tukey’s honest differences test and Pearson product moment correlation (α = 0.05). Significantly greater mean maximum insertion torque (59.9 ± 4.94 Ncm) and mean maximum insertion torque/time integral (961.64 ± 54.07 Ncm∗s) were recorded for BLT implants (p < 0.01). V3 showed significantly higher mean maximum insertion torque as compared to ASTRA (p < 0.01), but significantly lower insertion torque/time integral (p < 0.01). Primary implant stability did not differ significantly among groups. Only a single weak (r = 0.61) but significant correlation could be established between maximum insertion torque and insertion torque/time integral (p < 0.01) when all data from all three implant groups were pooled. Implant design (length, thread pitch) seems to affect insertion torque/time integral more than maximum insertion torque.
Acknowledgements
The authors wish to thank Dr. Friedrich Graef, Professor Emeritus, Department of Mathematics, University of Erlangen-Nuremberg, Germany, for statistical data analysis.
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Research funding: Authors state no funding involved.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Conflict of interest: Authors declare no conflict of interest.
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Informed consent: Informed consent was obtained from all individuals included in this study.
References
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© 2020 Walter de Gruyter GmbH, Berlin/Boston
Articles in the same Issue
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- EEG Source Imaging (ESI) utility in clinical practice
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- Scalp electroencephalography (sEEG) based advanced prediction of epileptic seizure time and identification of epileptogenic region
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- Insertion torque/time integral as a measure of primary implant stability
- A microelectromechanical system (MEMS) capacitive accelerometer-based microphone with enhanced sensitivity for fully implantable hearing aid: a novel analytical approach
- Integrating artificial neural network and scoring systems to increase the prediction accuracy of patient mortality and organ dysfunction
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Articles in the same Issue
- Frontmatter
- Reviews
- A review of foot pose and trajectory estimation methods using inertial and auxiliary sensors for kinematic gait analysis
- EEG Source Imaging (ESI) utility in clinical practice
- Research articles
- A multi-source co-frequency stimulus method for electroencephalogram (EEG) enhancement
- Analysis of statistical coefficients and autoregressive parameters over intrinsic mode functions (IMFs) for epileptic seizure detection
- Scalp electroencephalography (sEEG) based advanced prediction of epileptic seizure time and identification of epileptogenic region
- A simple model to detect atrial fibrillation via visual imaging
- Insertion torque/time integral as a measure of primary implant stability
- A microelectromechanical system (MEMS) capacitive accelerometer-based microphone with enhanced sensitivity for fully implantable hearing aid: a novel analytical approach
- Integrating artificial neural network and scoring systems to increase the prediction accuracy of patient mortality and organ dysfunction
- Sparse-FCM and Deep Convolutional Neural Network for the segmentation and classification of acute lymphoblastic leukaemia
