Revelation of tooth structural integrity at the microcrack site using multi-modal imaging DOI
Irma Dumbrytė, D. Narbutis, M. Androulidaki

et al.

Published: April 5, 2024

Language: Английский

Innovative Approaches in Dental Care: Electrical Impedance Analysis (EIA) for Early Caries Detection DOI Creative Commons
Liliana Sachelarie, Ioana Romanul, Daniela Domocoş

et al.

Bioengineering, Journal Year: 2025, Volume and Issue: 12(3), P. 215 - 215

Published: Feb. 20, 2025

(1) Background: Microcracks and structural fragility in teeth, often undetected by traditional methods until severe complications like fractures or pulp exposure occur, are evaluated this study using electrical impedance analysis (EIA) as a non-invasive tool for early detection assessment. (2) Methods: A total of 57 patients were recruited, including individuals with bruxism (n = 20), dental restorations 18), no significant history (control group, n 19). Electrical measurements performed on all teeth portable device, data collected from occlusal proximal surfaces. Patients abnormal values underwent additional imaging (standard radiographs) to confirm the presence microcracks. Statistical analyses included ANOVA compare between groups logistic regression assess predictors fragility. (3) Results: Teeth microcracks confirmed standard radiographs exhibited significantly lower (mean 50 kΩ) compared healthy 120 kΩ, p < 0.01). showed highest proportion (45%). Logistic identified predictor reduced (p 0.05). (4) Conclusions: demonstrates promise method detecting assessing teeth. Its application routine check-ups could enable interventions, particularly high-risk restorations.

Language: Английский

Citations

0

Multi-modal imaging of tooth microcrack DOI
Irma Dumbrytė, D. Narbutis, M. Androulidaki

et al.

Published: Jan. 26, 2024

The study aimed to combine an X-ray micro-computed tomography (μCT) with photoluminescence (PL) and convolutional neural network (CNN) assisted voxel classification volume segmentation for tooth structural integrity assessment at the microcrack site verify this approach extracted human teeth. samples were first examined using μCT segmented CNN identify enamel, dentin, cracks. A new image model was trained based on "Multiclass semantic DeepLabV3+" example implemented "TensorFlow". Secondly, buccal palatal teeth surfaces microcracks sound areas selected obtain fluorescence spectra illuminated wavelengths of 325 nm (cw) 266 (0.5 ns pulsed). proposed – in combination PL reveals possibilities crack area distinct precision versatility can be applied all microstructure surface mapping analysis.

Language: Английский

Citations

0

Revelation of tooth structural integrity at the microcrack site using multi-modal imaging DOI
Irma Dumbrytė, D. Narbutis, M. Androulidaki

et al.

Published: April 5, 2024

Language: Английский

Citations

0