Abstract
Objectives: This study aimed to determine whether surface wear, identified through the superimposition of intraoral scans (IOS), can predict subsurface damage progression detected by optical coherence tomography (OCT) during fatigue testing of computer-aided design/computer-aided manufacturing (CAD/CAM) composite crowns. Methods: Monolithic CAD/CAM composite crowns (Brilliant Crios; n=8) were adhesively luted to standardized prepared human teeth and artificially aged by cyclic loading in a mouth-motion simulator (50–500 N, 2 Hz, 37 °C). Under phantom-head condition, IOS (surface wear) and handheld swept-source (SS)-OCT (subsurface damage) were performed before loading and after every 250,000 cycles. OCT crack depth/width were normalized to local thickness and cusp-tip distance; correspondence between IOS- and OCT-derived metrics at each timepoint was assessed with Spearman’s rank correlation coefficient (ρ) to test whether surface wear can predict subsurface damage under the given conditions. Results: All specimens survived without catastrophic failure, and both modalities revealed progressive damage from the earliest observation interval. OCT consistently showed higher defect percentages and larger dispersion (e.g., mean vertical defects (25.47 ± 4.97)% OCT vs. (4.36 ± 0.91)% IOS at T1 and (66.79 ± 19.53)% OCT vs. (7.78 ± 3.19)% IOS at T5). Across all timepoints, no statistically significant associations between IOS and OCT were observed (p = 0.146 to 0.955). Conclusions: Within the limitations of this exploratory, single-material in vitro study, restricted to a CAD/CAM composite (Brilliant Crios), surface-based monitoring alone did not reliably reflect subsurface damage progression. Clinically, this suggests that surface wear assessment may underestimate subsurface fatigue damage. Intraoral OCT may provide complementary, non-invasive information alongside routine IOS for individualized monitoring, but its added value needs to be confirmed in larger studies and other CAD/CAM composite materials and additional restorative material classes.
| Original language | English |
|---|---|
| Journal | Dentistry Journal |
| Volume | 14 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 01.2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 9 Industry, Innovation, and Infrastructure
Research Areas and Centers
- Academic Focus: Biomedical Engineering
DFG Research Classification Scheme
- 2.22-32 Medical Physics, Biomedical Technology
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