Diagnosis of cracked tooth: Clinical status and research progress

Human Tooth Crack Image Analysis with Multiple Deep Learning Approaches

Tooth cracks, one of the most common dental diseases, can result in the tooth falling apart without prompt treatment; dentists also have difficulty locating cracks, even with X-ray imaging. Indocyanine green (ICG) assisted near-infrared fluorescence (NIRF) dental imaging technique can solve this problem due to the deep penetration of NIR light and the excellent fluorescence characteristics of ICG. This study extracted 593 human cracked tooth images and 601 non-cracked tooth images from NIR imaging videos. Multiple imaging analysis methods such as classification, object detection, and super-resolution were applied to the dataset for cracked image analysis. Our results showed that machine learning methods could help analyze tooth crack efficiently: the tooth images with cracks and without cracks could be well classified with the pre-trained residual network and squeezenet1_1 models, with a classification accuracy of 88.2% and 94.25%, respectively; the single shot multi-box detector (SSD) was able to recognize cracks, even if the input image was at a different size from the original cracked image; the super-resolution (SR) model, SR-generative adversarial network demonstrated enhanced resolution of crack images using high-resolution concrete crack images as the training dataset. Overall, deep learning model-assisted human crack analysis improves crack identification; the combination of our NIR dental imaging system and deep learning models has the potential to assist dentists in crack diagnosis.

Fracture resistance and failure mode of three esthetic CAD-CAM post and core restorations

BACKGROUND

The rising demand for improved aesthetics has driven the utilization of recently introduced aesthetic materials for creating custom post and core restorations. However, information regarding the fracture resistance of these materials remains unclear, which limits their practical use as custom post and core restorations in clinical applications. AIM OF THE STUDY: This study aimed to evaluate the fracture resistance of three non-metallic esthetic post and core restorations and their modes of failure.

MATERIALS AND METHODS

Thirty-nine single-rooted human maxillary central incisors were endodontically treated. A standardized post space preparation of 9mm length was performed to all teeth to receive custom-made post and core restorations. The prepared teeth were randomly allocated to receive a post and core restoration made of one of the following materials (n=13): glass fiber-reinforced composite (FRC), polyetheretherketone (PEEK) and polymer-infiltrated ceramic-network (PICN). An intraoral scanner was used to scan all teeth including the post spaces. Computer-aided design and computer-aided manufacturing (CAD-CAM) was used to fabricate post and core restorations. Post and core restorations were cemented using self-adhesive resin cement. All specimens were subjected to fracture resistance testing using a universal testing machine. Failure mode analysis was assessed using a stereomicroscope and SEM. The data was statistically analyzed using One-Way ANOVA test followed by multiple pairwise comparisons using Bonferroni adjusted significance level.

RESULTS

Custom PEEK post and core restorations displayed the least fracture load values at 286.16 ± 67.09 N. In contrast, FRC exhibited the highest average fracture load at 452.60 ± 105.90 N, closely followed by PICN at 426.76 ± 77.99 N. In terms of failure modes, 46.2% of specimens with PICN were deemed non-restorable, while for PEEK and FRC, these percentages were 58.8% and 61.5%, respectively.

CONCLUSIONS

Within the limitation of this study, both FRC and PICN demonstrated good performance regarding fracture resistance, surpassing that of PEEK.

Influence of restorative materials on the mechanical properties of maxillary first molars with different degrees of cryptic fractures and defects: A finite element analysis

This study aimed to apply finite element analysis to evaluate the effects of pile materials with different elastic moduli and cement materials on the stress distribution between the remaining tooth tissue and cryptic fracture defects. A three-dimensional finite element model was established for 20 maxillary first molars with hidden fissures and mesial tongue-tip defects. Two levels of hidden cracks and three types of pile and adhesive materials were used in the design. The stress distribution and maximum stress peak in the remaining tooth tissue and crack defects were determined by simulating the normal bite, maximum bite, and lateral movement forces. When titanium posts, zinc phosphate binders, and porcelain crowns were used to repair the two types of deep cracked teeth, the maximum principal stress at the crack and dentin was the smallest. As the crack depth increased, the maximum principal stress of the residual dentin and crack defects increased.