Journal of Osseointegration

Accuracy of artificial intelligence in the prediction of cervical vertebrae maturation stages in orthodontics: a systematic review

2024-12-23T13:01:32+00:00

Objective To assess the ability of artificial intelligence in evaluating cervical vertebrae maturation stages to enhance orthodontic diagnosis considering as main outcome the accuracy of the AI software.

Materials and methods A search was conducted of 3 databases (Cochrane Library, PubMed/MEDLINE, EMBASE) to identify studies focusing on the ability of atificial intelligence in correctly evaluating the cervical vertebrae maturation stages. Databases were searched including articles until March 2024 only published in English. The Preferred Reporting Items for Reporting Systematic Reviews and Meta Analyses (PRISMA) protocol was adopted, two independent reviewers screened the articles and the agreement was defined by Kappa statistic. The quality of the studies was assessed through the New Castle-Ottawa scale. Due to heterogeneity of data a meta-analysis could not be performed.

Results The search initially returned 2.953 results and after removing duplicated the number dropped to 1.104. At the end, a total of 7 studies were included in this review. It was evident that AI systems are very good in performing the screening among big amount of data, capable of differentiating what the operator often can not evaluate.

Conclusion AI can be considered a powerful tool in helping the orthodontic diagnosis since these softwares can manage a big amount of data and perform always the same but on the other hand training of both clinicians and devices is of detrimental importance to overcome the phenomenon of overfitting and instrumental mistakes by the clinicians.

Histopathologic assessment of soft tissue healing around Polyetheretherketone and Titanium abutments. A Randomized and controlled human study

2024-11-12T15:52:49+00:00

Aims The establishment of peri-implant mucosa is crucial for dental implant success, involving a sequence of biological events leading to tissue barrier formation. While titanium has been the traditional choice for abutments, alternatives like PEEK show comparable healing outcomes in pre-clinical and clinical studies. This randomized clinical trial aims to compare the histological and inflammatory reactions of Polyetheretherketone (PEEK) and titanium abutments in individuals with partial posterior maxillary edentulism.

Methods Systemically healthy adults were consecutively enrolled. Following implant placement (44x 8mm, 3P implants, B&B Dental, San Pietro in Casale, Italy), participants were randomly assigned to receive either titanium or PEEK abutments. After a healing period of 5 months, a minimally invasive biopsy procedure was performed, and immunohistochemical analysis of inflammatory infiltration was carried out.

Results Twenty-two implants were placed in the posterior maxillary region of enrolled patients. Both abutment groups exhibited similar degrees of inflammatory infiltrate (p > 0.05). Dystrophic calcifications were slightly higher in the PEEK group (p = 0.26). Immunohistochemical analysis revealed comparable percentages of CD3+ T cells, CD20+ B cells, CD38+ and CD68+ cells between the two groups (p > 0.05). A trend of a less marked infiltrate was observed around titanium, particularly at the mesial side (26.66% vs. 6.75%, p = 0.02).

Conclusions PEEK and titanium abutments demonstrated similar peri-implant soft tissue responses. The histological findings did not reveal a significantly increased inflammatory reaction associated with Polyetheretherketone. While a trend of less marked infiltrate around titanium was observed, further long-term observations are crucial for a definitive assessment of PEEK abutment suitability.

Evaluation of Bone Graft Need in Edentulous Posterior Sites: A CBCT Retrospective Study

2024-10-30T11:39:20+00:00

Aim This retrospective study investigates the necessity for bone graft augmentation in edentulous posterior sites, focusing on the lower premolar and molar regions.

Materials and Methods Using Cone Beam Computed Tomography (CBCT) imaging from patients treated at Umm Al-Qura University between 2019 and 2022, to evaluates bone conditions that influence dental implant placement. Digital software was employed to plan implant placement with a prosthetically driven approach. Measurement of buccal and lingual bone thickness at the coronal and middle aspect of the implant was done. Measurement less than 1mm was considered an indication for the need of bone augmentation.

Results A total of 74 CBCT scans were evaluated, representing 100 missing teeth. Premolars constitute 23% (n=23), and molars constitute 77% (n=77) of the teeth site evaluated. A significant number of sites required bone grafting due to insufficient buccal bone thickness, with 80% of implants having <1mm bone thickness. 91% of premolar implants and 89.6% of molar implants lacked adequate buccal bone. More premolars needed guided bone regeneration (GBR) than molars (p<0.0001). Overall, 80% of implants needed bone grafts, with females showing a slightly higher need (p>0.05). Lingual bone thickness was adequate.

Conclusion Number of edentulous posterior sites, specifically in the lower premolar and molar regions, necessitate bone graft augmentation for successful implant placement. Pre-surgical planning using digital software and CBCT imaging is crucial to assess bone accurately and determine the need for bone augmentation.

Statistical evaluation of the learning curve in digital impression in different types of operators

2024-10-02T14:56:34+00:00

Aim The objective of this study was to evaluate the learning curve associated with intraoral scanning using the CEREC system, comparing two groups: dental students and experienced clinicians. The study aimed to assess improvements in time, surface area acquired, and surface-time ratio (X) to determine the efficiency of repeated scanning.

Materials and Methods A total of 50 participants were recruited for the study, divided into two groups: 25 dental students from the San Raffaele Faculty of Dentistry and 25 clinicians with at least 5 years of experience. Each participant performed four intraoral scans on a plaster model using the CEREC intraoral scanner. The scans were evaluated for time (T1-T4) in minutes, surface area (SUP) in pixel units, and surface-time ratio (X) as an efficiency metric. Statistical analysis was conducted using IBM SPSS Statistics (version 25) and MeshLab 2016 to assess the learning curve and compare the two groups.

Results Both groups demonstrated a clear learning curve with significant improvements in time and surface-time ratio (X) over the four trials. For clinicians, the average time decreased from 1.399 minutes in T1 to 1.015 minutes in T4, while the surface-time ratio improved from 347.91 mm²/min to 447.77 mm²/min. Students showed a similar reduction in time, from 1.292 minutes in T1 to 1.001 minutes in T4, and an improvement in surface-time ratio from 343.96 mm²/min to 433.12 mm²/min. Clinicians consistently acquired more surface area than students, despite similar scan times, indicating that clinical experience plays a crucial role in scan accuracy.

Conclusion The study highlights the importance of clinical experience in achieving more efficient and complete scans using intraoral scanners. Both groups improved with repetition, but clinicians demonstrated superior performance in terms of surface area acquired. The learning curve plateaued after the third trial, suggesting that sustained practice is necessary for mastery. Future training programs should focus on enhancing both technical proficiency and clinical judgment to optimize the use of digital scanning technology in dentistry.