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Published on: September 8, 2023
Direct estimation of human trabecular bone stiffness using cone beam computed tomography.
Eva Klintström1, Benjamin Klintström2, Dieter Pahr3
1Department of Medical and Health Sciences and Center for Medical Image Science and Visualization (CMIV), Linköping University, Linköping, Sweden.
Estimating trabecular bone biomechanics using dental cone beam computed tomography (CBCT) is feasible. The Accuitomo 80 scanner showed strong correlations, suggesting potential for predicting implant survival through in vivo bone property estimations.
Area of Science:
- Biomechanical Engineering
- Dental Imaging
- Materials Science
Background:
- Trabecular bone biomechanical properties are crucial for predicting implant success.
- Finite element analysis (FEA) is a powerful tool for biomechanical evaluation.
- Dental cone beam computed tomography (CBCT) offers a non-invasive method for imaging bone structure.
Purpose of the Study:
- To assess the feasibility of estimating trabecular bone biomechanical properties using FEA with CBCT data.
- To compare the performance of different CBCT devices and segmentation methods for biomechanical property estimation.
Main Methods:
- Human radius specimens were scanned using three CBCT devices (Accuitomo 80, NewTom 5 G, Verity).
- Imaging data were processed using two segmentation methods.
- Biomechanical properties (stiffness, shear moduli, stiffness tensor) were calculated via FEA.
- Micro-computed tomography (micro-CT) served as the reference standard.
Main Results:
- The Accuitomo 80 demonstrated good performance in estimating stiffness and shear moduli, though sensitive to segmentation.
- NewTom 5 G and Verity showed good correlations but were less accurate than Accuitomo 80.
- All CBCT devices tended to overestimate stiffness and shear moduli compared to micro-CT.
Conclusions:
- FEA-based biomechanical calculations from CBCT data are feasible.
- The Accuitomo 80, with appropriate segmentation, provides strong correlations for bone property estimation.
- These estimations may aid in predicting implant survival through in vivo bone property assessment.
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