Development of a quantitative preclinical screening model for implant osseointegration in rat tail vertebra.

OBJECTIVES: Functional tooth replacement and bone regeneration are parts of the daily practice in modern dentistry, but well-reproducible and relatively inexpensive experimental models are still missing. We aimed to develop a new small animal model to monitor osseointegration utilizing the combination of multiple evaluation protocols. MATERIAL AND METHODS: After cutting the tail between the C4 and C5 vertebrae in Wistar rats, costume made, parallel walled, non-threaded implants were placed into the center of the tail parallel with its longitudinal axis using a surgical guide. Osseointegration of the titanium implants was followed between 4 and 16 weeks after surgery applying axial extraction force, and resonance frequency analysis as functional tests, and histomorphometry and micro-CT as structural evaluations. RESULTS: In functional tests, we observed that both methods are suitable for the detection of the time-dependent increase in osseointegration, but the sensitivity of the pull-out technique (an approximately five times increase with rather low standard error) was much higher than that of the resonance frequency analysis. In structural evaluations, changes in the detected bone implant contact values measured by histomorphometry (yielding 1.5 times increase, with low variations of data) were more reliable than micro-CT based evaluations to screen the developments of contact between bone and implant. CONCLUSION: Our results provide evidence that the caudal vertebrae osseointegration model is useful for the preclinical evaluation of implant integration into the bone. CLINICAL RELEVANCE: The combination of the biomechanical and structural tests offers a well-reproducible small animal system that can be suitable for studying the integration of various implant materials and surface treatments.

Validation of artificial intelligence application for dental caries diagnosis on intraoral bitewing and periapical radiographs.

OBJECTIVES: This study aimed to assess the reliability of AI-based system that assists the healthcare processes in the diagnosis of caries on intraoral radiographs. METHODS: The proximal surfaces of the 323 selected teeth on the intraoral radiographs were evaluated by two independent observers using an AI-based (Diagnocat) system. The presence or absence of carious lesions was recorded during Phase 1. After 4 months, the AI-aided human observers evaluated the same radiographs (Phase 2), and the advanced convolutional neural network (CNN) reassessed the radiographic data (Phase 3). Subsequently, data reflecting human disagreements were excluded (Phase 4). For each phase, the Cohen and Fleiss kappa values, as well as the sensitivity, specificity, positive and negative predictive values, and diagnostic accuracy of Diagnocat, were calculated. RESULTS: During the four phases, the range of Cohen kappa values between the human observers and Diagnocat were κ=0.66-1, κ=0.58-0.7, and κ=0.49-0.7. The Fleiss kappa values were κ=0.57-0.8. The sensitivity, specificity and diagnostic accuracy values ranged between 0.51-0.76, 0.88-0.97 and 0.76-0.86, respectively. CONCLUSIONS: The Diagnocat CNN supports the evaluation of intraoral radiographs for caries diagnosis, as determined by consensus between human and AI system observers. CLINICAL SIGNIFICANCE: Our study may aid in the understanding of deep learning-based systems developed for dental imaging modalities for dentists and contribute to expanding the body of results in the field of AI-supported dental radiology..

Comparative evaluation of cone-beam CT equipment with micro-CT in the visualization of root canal system.

The aim of this study was to compare three different cone-beam CT (CBCT) instruments used in dental clinical practice with micro-CT as gold standard. Three female monkeys' (Macaca fascicularis) skulls were selected and scanned by the tested CBCT-s. The most apical visible root canal level on the CBCT images was used as reference level (RL). After the image acquisition by CBCT-s dental jaw sections were scanned by micro-CT at a resolution of 17 µm. Out of the left second and third molars 25 root canals were selected and analysed by three observers at RL and following cross sectional parameters were determined: area of the lumen, major and minor diameters, aspect ratio and mean thickness. Results suggest that only high resolution CBCT instruments allow dentists detecting the full length of the root canal.