Explore the vast range of titles available.

Artificial intelligence (AI) is revolutionizing dentistry, offering new opportunities to improve the precision and efficiency of implantology. This literature review aims to evaluate the current evidence on the use of AI in implant planning assessment. The analysis was conducted through PubMed and Scopus search engines, using a combination of relevant keywords, including “artificial intelligence implantology”, “AI implant planning”, “AI dental implant”, and “implantology artificial intelligence”. Selected articles were carefully reviewed to identify studies reporting data on the effectiveness of AI in implant planning. The results of the literature review indicate a growing interest in the application of AI in implant planning, with evidence suggesting an improvement in precision and predictability compared to traditional methods. The summary of the obtained findings by the included studies represents the latest AI developments in implant planning, demonstrating its application for the automated detection of bones, the maxillary sinus, neuronal structure, and teeth. However, some disadvantages were also identified, including the need for high-quality training data and the lack of standardization in protocols. In conclusion, the use of AI in implant planning presents promising prospects for improving clinical outcomes and optimizing patient management. However, further research is needed to fully understand its potential and address the challenges associated with its implementation in clinical practice.

Objective: To assess the primary and secondary stability of dental implants with immediate loading protocol. Material and Methods: Thirty patients between the ages of 18 and 45 years who received forty dental implants were study. These cases involved bone level x modified sand blast large grit acid etch Blx Sla active implant. After surgery, the primary stability was examined while secondary stability was evaluated 3 months later. The SPSS program was used to evaluate and analyze the results employing the paired T test and independent T test at p <0.05. Results: Thirty patients, 20 females and 10 males, participated in this study and had a mean age of 32 years. In comparison to the primary stability baseline value, the mean implant stability quotient values for secondary stability after three months showed a statistically significant improvement. Sex and jaws did not differ significantly in terms of stability. Conclusion: When compared to the initial primary stability baseline values, the study found that secondary implant stability measured values for the type of dental implant studied increased significantly.

Computer aided implantology is the safest way to perform dental implants. The research of high accuracy represents a daily effort. The validated method to assess the accuracy of placed dental implants is the superimposition of a pre-operative and a post-operative cone beam computed tomography (CBCT) with planned and placed implants. This procedure is accountable for a biologic cost for the patient. To investigate alternative procedure for accuracy assessment, fifteen resin casts were printed. For each model, six implants were digitally planned and then placed following three different approaches: (a) template guided free hand, (b) static computer aided implantology (SCAI), and (c) dynamic computer aided implantology (DCAI). The placement accuracy of each implant was performed via two methods: the CBCT comparison described above and a matching between implant positions recovered from the original surgical plan with those obtained with a post-operative intraoral scan (IOS). Statistically significant mean differences between guided groups (SCAI and DCAI) and the free hand group were found at all considered deviations, while no differences resulted between the SCAI and DCAI approaches. Moreover, no mean statistically significant differences were found between CBCT and IOS assessment, confirming the validity of this new method.

Oral diseases such as tooth caries, periodontal diseases, endodontic infections, etc., are prevalent worldwide. The heavy burden of oral infectious diseases and their consequences on the patients' quality of life indicates a strong need for developing effective therapies. Advanced understandings of such oral diseases, e.g., inflammatory periodontal lesions, have raised the demand for antibacterial therapeutic strategies, because these diseases are caused by viruses and bacteria. The application of antimicrobial photodynamic therapy (aPDT) on oral infectious diseases has attracted tremendous interest in the past decade. However, aPDT had a minimal effect on the viability of organized biofilms due to the hydrophobic nature of the majority of the photosensitizers (PSs). Therefore, novel nanotechnologies were rapidly developed to target the delivery of hydrophobic PSs into microorganisms for the antimicrobial performance improvement of aPDT. This review focuses on the state-of-the-art of nanomaterials applications in aPDT against oral infectious diseases. The first part of this article focuses on the cutting-edge research on the synthesis, toxicity, and therapeutic effects of various forms of nanomaterials serving as PS carriers for aPDT applications. The second part discusses nanomaterials applications for aPDT in treatments of oral diseases. These novel bioactive nanomaterials have demonstrated great potential to serve as carriers for PSs to substantially enhance the PDT therapeutic effects. Furthermore, the novel aPDT applications not only have exciting therapeutic potential to inhibit bacterial plaque-initiated oral diseases, but also have a wide applicability to other biomedical and tissue engineering applications.

Objectives To assess the accuracy of dynamic computer–aided implant surgery (dCAIS) systems when used to place dental implants and to compare its accuracy with static computer–aided implant surgery (sCAIS) systems and freehand implant placement. Materials and Methods An electronic search was made to identify all relevant studies reporting on the accuracy of dCAIS systems for dental implant placement. The following PICO question was developed: “In patients or artificial models, is dental implant placement accuracy higher when dCAIS systems are used in comparison with sCAIS systems or with freehand placement? The main outcome variable was angular deviation between the central axes of the planned and final position of the implant. The data were extracted in descriptive tables, and a meta-analysis of single means was performed in order to estimate the deviations for each variable using a random-effects model. Results Out of 904 potential articles, the 24 selected assessed 9 different dynamic navigation systems. The mean angular and entry 3D global deviations for clinical studies were 3.68° (95% CI: 3.61 to 3.74; I 2 = 99.4%) and 1.03 mm (95% CI: 1.01 to 1.04; I 2 = 82.4%), respectively. Lower deviation values were reported in in vitro studies (mean angular deviation of 2.01° (95% CI: 1.95 to 2.07; I 2 = 99.1%) and mean entry 3D global deviation of 0.46 mm (95% CI: 0.44 to 0.48 ; I 2 = 98.5%). No significant differences were found between the different dCAIS systems. These systems were significantly more accurate than sCAIS systems (mean difference (MD): −0.86°; 95% CI: −1.35 to −0.36) and freehand implant placement (MD: −4.33°; 95% CI: −5.40 to −3.25). Conclusion dCAIS systems allow highly accurate implant placement with a mean angular of less than 4°. However, a 2-mm safety margin should be applied, since deviations of more than 1 mm were observed. dCAIS systems increase the implant placement accuracy when compared with freehand implant placement and also seem to slightly decrease the angular deviation in comparison with sCAIS systems. Clinical Relevance The use of dCAIS could reduce the rate of complications since it allows a highly accurate implant placement.

A minimally invasive implant treatment approach for future full arch implant prosthetic rehabilitations of trophic jaws represents a challenge. An optimal implant planning is strongly related with an accurate merge of the prosthetic information and the radiographic data. To comply with that, most computer aided implantology (CAI) systems require additional steps, as radiographic stents or fiducial markers to overlap digital jaw scans to cone beam computed tomography (CBCT) data. Using dynamic CAI, residual teeth (up to three) make it possible for the merge to avoid new radiographic scans. An additional challenge is the treatment involving immediate implants compared with delayed implants placed into healed bone. As for other static CAI systems, the operator’s experience and the quality of the CBCT data make the planning affordable and secure the entire implants placement procedure. The literature reports accuracies in terms of comparison between placed implants and planned implants, following a double CBCT approach, based on radiographic volume overlapping. Thirteen consecutive future totally edentulous patients (77 implants), divided into two groups (group A: 3–4 teeth traced; group B: 5–6 teeth traced) requiring a full arch implant prosthetic rehabilitation were included in the reported case series. A dynamic CAI was used to plan and to place all implants following all the recommended digital steps. The software used provided a tool (Trace and Place) that made the merge between X-ray views of the residual teeth and their own positions possible. This method definitely registered that teeth positions comply with the required accuracy live check. After implants placement, a post-operative CBCT was taken in order to evaluate the deviations of the achieved implants at coronal, apical, and depth level as well as angular deviations. Statistically significant radiological mean difference between the two groups was found in the coronal position of implants (0.26 mm, p < 0.001), in the apical position of implants (0.29 mm, p < 0.001), in the depth of implants (0.16 mm, p = 0.022), and in the angular deviation (0.7, p = 0.004). The use of the TaP technology for the treatment of the patients with at least three stable teeth that need to be removed for a totally implant prosthetic treatment is a promising technique. The performed accuracy analysis demonstrated that this digital protocol can be used without a loss of accuracy of the achieved implants compared to planned ones.

Background Until now, a few studies have addressed the accuracy of intraoral scanners (IOSs) in implantology. Hence, the aim of this in vitro study was to assess the accuracy of 5 different IOSs in the impressions of single and multiple implants, and to compare them. Methods Plaster models were prepared, representative of a partially edentulous maxilla (PEM) to be restored with a single crown (SC) and a partial prosthesis (PP), and a totally edentulous maxilla (TEM) to be restored with a full-arch (FA). These models were scanned with a desktop scanner, to capture reference models (RMs), and with 5 IOSs (CS 3600®, Trios3®, Omnicam®, DWIO®, Emerald®); 10 scans were taken for each model, using each IOS. All IOS datasets were loaded into a reverse-engineering software where they were superimposed on the corresponding RMs, to evaluate trueness, and superimposed on each other within groups, to determine precision. A statistical analysis was performed. Results In the SC, CS 3600® had the best trueness (15.2 ± 0.8 μm), followed by Trios3® (22.3 ± 0.5 μm), DWIO® (27.8 ± 3.2 μm), Omnicam® (28.4 ± 4.5 μm), Emerald® (43.1 ± 11.5 μm). In the PP, CS 3600® had the best trueness (23 ± 1.1 μm), followed by Trios3® (28.5 ± 0.5 μm), Omnicam® (38.1 ± 8.8 μm), Emerald® (49.3 ± 5.5 μm), DWIO® (49.8 ± 5 μm). In the FA, CS 3600® had the best trueness (44.9 ± 8.9 μm), followed by Trios3® (46.3 ± 4.9 μm), Emerald® (66.3 ± 5.6 μm), Omnicam® (70.4 ± 11.9 μm), DWIO® (92.1 ± 24.1 μm). Significant differences were found between the IOSs; a significant difference in trueness was found between the contexts (SC vs. PP vs. FA). In the SC, CS 3600® had the best precision (11.3 ± 1.1 μm), followed by Trios3® (15.2 ± 0.8 μm), DWIO® (27.1 ± 10.7 μm), Omnicam® (30.6 ± 3.3 μm), Emerald® (32.8 ± 10.7 μm). In the PP, CS 3600® had the best precision (17 ± 2.3 μm), followed by Trios3® (21 ± 1.9 μm), Emerald® (29.9 ± 8.9 μm), DWIO® (34.8 ± 10.8 μm), Omnicam® (43.2 ± 9.4 μm). In the FA, Trios3® had the best precision (35.6 ± 3.4 μm), followed by CS 3600® (35.7 ± 4.3 μm), Emerald® (61.5 ± 18.1 μm), Omnicam® (89.3 ± 14 μm), DWIO® (111 ± 24.8 μm). Significant differences were found between the IOSs; a significant difference in precision was found between the contexts (SC vs. PP vs. FA). Conclusions The IOSs showed significant differences between them, both in trueness and in precision. The mathematical error increased in the transition from SC to PP up to FA, both in trueness than in precision.

Successful implantation in augmented areas relies on adequate bone density and quality, along with thorough planning. The minimisation of the risks involved in the surgery and recovery phases is also of tremendous relevance. The aims of the present research were to clinically and biochemically evaluate the healing process after implant surgery (dental implants) using dynamic surgical navigation following prior bone augmentation. Thirty healthy patients who had implant treatment were analysed. The study participants (30 patients) were randomised between two groups. The 15 patients in the study group were treated with Navident dynamic navigation by using a flapless technique. The control group included 15 subjects in whom the implantation procedure was performed classically using the elevation flap full-thickness method. In all cases, the patient’s clinical condition, the patient’s subjective visual assessment of post-operative pain using the Visual Analogue Scale (VAS), and the levels of the salivary biomarkers interleukin 6 (IL 6) and C-reactive protein (CRP) immediately before surgery on the first post-operative day and on the seventh post-operative day were assessed. The healing process was shown to be faster in patients in the study group due to the low invasiveness of the treatment, which was confirmed by lower levels of pro-inflammatory cytokines in the study group versus the control group. The statistical analysis used Student’s t-test and Mann–Whitney test. The implementation of dynamic navigation and the application of the flapless technique reduced post-operative trauma, leading to a reduced risk of infection, reduced patient discomfort, and faster recovery.

The use of pterygoid implants can be an attractive alternative to sinus bone grafting in the treatment of posterior atrophic maxilla. This technique has not been widely used because of the difficulty of the surgical access, the presence of vital structures, and the prosthetic challenges. The use of dynamic computer aided implantology (DCAI) allows the clinician to utilize navigation dental implant surgery, which allows the surgeon to follow the osteotomy site and implant positioning in real time. A total of 14 patients (28 pterygoid implants and 56 intersinusal implants) were enrolled in the study for a full arch implant prosthetic rehabilitation (4 frontal implants and 2 pterygoids implants), using a dynamic navigation system. The reported accuracy of pterygoid implants inserted using DCAI was 0.72 mm at coronal point, 1.25 mm at apical 3D, 0.66 mm at apical depth, and 2.86° as angular deviation. The use of pterygoid implants in lieu of bone grafting represents a valid treatment opportunity to carry out a safe, accurate, and minimally invasive surgery, while reducing treatment time and avoiding cantilevers for a full implant prosthetic rehabilitation of the upper arch.

Aim: To analyze the accuracy capability of two computer-aided navigation procedures for dental implant placement. Materials and Methods: A total of 40 dental implants were selected, which were randomly distributed into two study groups, namely, group A, consisting of those implants that were placed using a computer-aided static navigation system (n = 20) (guided implant (GI)) and group B, consisting of those implants that were placed using a computer-aided dynamic navigation system (n = 20) (navigation implant (NI)). The placement of the implants from group A was performed using surgical templates that were designed using 3D implant-planning software based on preoperative cone-beam computed tomography (CBCT) and a 3D extraoral surface scan, and the placement of group B implants was planned and performed using the dynamic navigation system. After placing the dental implants, a second CBCT was performed and the degree of accuracy of the planning and placement of the implants was analyzed using therapeutic planning software and Student’s t-test. Results: The paired t-test revealed no statistically significant differences between GI and NI at the coronal (p = 0.6535) and apical (p = 0.9081) levels; however, statistically significant differences were observed between the angular deviations of GI and NI (p = 0.0272). Conclusion: Both computer-aided static and dynamic navigation procedures allow accurate implant placement.