Objectives: The widespread adoption of three-dimensional (3D)-printed resins in restorative dentistry has introduced significant challenges in establishing strong and lasting bonds with resin-based cements. Despite the development of numerous surface treatment techniques designed to improve adhesion, a clear consensus on the most effective approach remains elusive. This systematic review and meta-analysis critically examined the impact of various surface treatment protocols on the bond strength of 3D-printed resins. By comparing treated versus untreated surfaces, the study aimed to determine the most reliable strategies for enhancing adhesion, ultimately offering evidence-based guidance to inform clinical decision-making. Methods: This review identified relevant studies through a comprehensive search of MEDLINE via PubMed, Web of Science, Scielo, Scopus, and EMBASE databases, supplemented by manual reference checks, to identify in vitro studies published up to February 2025. Studies assessing the bonding of 3D-printed resins following various surface treatments and bonding protocols were included. Data on bond strength outcomes, such as shear bond strength, microtensile bond strength, and microshear bond strength, were extracted. Data extraction included study details, type of 3D-printed resin and printing technology, surface treatment protocols, bond strength testing methods, storage conditions, and results. The quality of included studies was assessed using the ROBDEMat tool. Meta-analyses were performed using the Review Manager Software (version 5.4, The Cochrane Collaboration, Copenhagen, Denmark), with statistical significance set at p < 0.05. Statistical heterogeneity among studies was evaluated using the Cochran Q test and the I² inconsistency test. Results: Nine studies met the criteria for qualitative analysis, with eight included in the meta-analysis. The findings revealed that surface treatment protocols significantly enhanced the immediate bond strength to 3D-printed resins (p = 0.01), with only sandblasting and silane demonstrating a statistically significant effect (p < 0.007). Similarly, after aging, surface treatments continued to improve bond strength (p = 0.01), with sandblasting and hydrofluoric acid being the only methods to produce a significant increase in bond strength values (p < 0.001). Conclusions: This meta-analysis underscores the importance of combining mechanical and chemical surface treatments, especially sandblasting and silane application, to achieve reliable and durable bonding to 3D-printed resins.

Background/Objectives: Digital workflows for implant-supported full-arch restorations remain challenging. This study evaluated the accuracy and precision of digital impressions using reverse scan body (RSB) prototypes and intraoral scanners (IOSs) for rehabilitating fully edentulous patients following the All-on-4 protocol. Secondary objectives included comparing accuracy between expert clinicians and beginners, as well as desktop scanners and various RSB designs. Methods: An in vitro study was conducted using a fully edentulous mandible model with four Osstem TSIII implants. A final-year dental student and an expert clinician captured digital impressions using IOSs and desktop scanners. Four groups were analyzed: (A) original scan bodies with the IOS, (B) short RSBs with the IOS, (C) RSBs with desktop scanners (short sandblasted, long sandblasted, long coated), and (D) a control group using original scan bodies with a desktop scanner. Root mean square (RMS) values measured dimensional differences, with statistical analysis performed using the Wilcoxon signed-rank test and one-way ANOVA (α = 0.05). Results: A total of 42 scans were analyzed. No significant difference was found between expert and student for original scan bodies using the IOS (p = 0.220), while RSB prototypes showed significant differences (p = 0.008). No significant accuracy differences were noted between original scan bodies and RSBs with the IOS, but IOSs outperformed desktop scanners. Among RSBs scanned with desktop scanners, no significant differences were observed between designs. Conclusions: RSB prototypes are a viable alternative to original scan bodies for fully digital workflows in All-on-4 rehabilitations, with IOSs offering superior accuracy. However, proper training is crucial for optimizing RSB accuracy. Variations in height and coating did not impact overall accuracy.

Background: The accuracy and consistency of complete-arch digital impressions are fundamental for long-term success of implant-supported rehabilitations. Recently, artificial intelligence (AI)-assisted tools, such as SmartX (Medit Link v3.4.2, MEDIT Corp., Seoul, South of Korea), have been introduced to enhance scan body recognition and data alignment during intraoral scanning. Objective: This in vitro study aimed to evaluate the impact of SmartX on impression accuracy, consistency, operator confidence, and technique sensitivity in complete-arch implant workflows. Methods: Seventy-two digital impressions were recorded on edentulous mandibular models with four dummy implants, using six experimental subgroups based on scan body design (double- or single-wing), scanning technique (occlusal or combined straight/zigzag), and presence/absence of SmartX tool. Each group was scanned by both an expert and a novice operator (n = 6 scans per subgroup). Root mean square (RMS) deviation and scanning time were assessed. Data were tested for normality (Shapiro–Wilk). Parametric tests (t-test, repeated measures ANOVA with Greenhouse–Geisser correction) or non-parametric equivalents (Mann–Whitney U, Friedman) were applied as appropriate. Post hoc comparisons used Tukey HSD or Dunn–Bonferroni tests (α = 0.05). Results: SmartX significantly improved consistency and operator confidence, especially among novices, although it did not yield statistically significant differences in scan accuracy (p > 0.05). The tool mitigated early scanning errors and reduced dependence on operator technique. SmartX also enabled successful library alignment with minimal data; however, scanning time was generally longer with its use, particularly for beginners. Conclusions: While SmartX did not directly enhance trueness, it substantially improved scan reliability and user experience in complete-arch workflows. Its ability to minimize technique sensitivity and improve reproducibility makes it a valuable aid in both training and clinical settings. Further clinical validation is warranted to support its integration into routine practice.

The customization and handling of implant abutments in prosthetic laboratories can lead to microbial contamination, requiring disinfection before clinical use. This study evaluated cross-contamination in abutments from three prosthetic laboratories, identifying microorganisms and assessing the disinfection efficacy of 2% chlorhexidine digluconate (2% CL) and ultraviolet C (UV-C) radiation. Sixty abutments were analyzed, with contamination detected in 83%, predominantly Enterococcus faecalis (34.2%) and Staphylococcus epidermidis (17.8%). Post-disinfection, CFU reduction was 92% (UV-C) and 93% (CL), confirmed by the Wilcoxon test (Z = −4.373; p < 0.001). A comparative analysis using the Kruskal–Wallis test showed no significant difference between the two methods (p > 0.05). These findings confirm that both UV-C and CL effectively reduce microbial load, providing reliable disinfection protocols for clinical practice.

Background: Accurate and consistent complete-arch digital impressions are critical for the long-term success of implant-supported restorations. New Artificial Intelligence (AI)-assisted technologies such as SmartX (Medit Link version 3.4.2., MEDIT Corp., South Korea, Seoul) have been introduced to optimize scan body recognition and data alignment during intraoral scanning. Objective: To evaluate the effect of the SmartX tool on scan accuracy, consistency, operator confidence, and the influence of impression technique in complete-arch implant digital workflows. Materials and Methods: A total of six test subgroups were created based on scan body design (double-wing or single-wing), scanning technique (occlusal or combined zigzag/straight), and the use or absence of SmartX AI-based tool. Digital impressions were performed by both an expert and a novice operator, with six scans per subgroup per operator (n = 72 total). Each scan was assessed for consistency, operator confidence, and scan completeness, and the results were compared with those obtained from a control group using a desktop scanner. Mean root mean square (RMS) values and standard deviations were calculated for each group. A two-way analysis of variance (ANOVA) with a random effects model was used to assess differences among groups, with normality confirmed using the Shapiro–Wilk test. All statistical tests were two-tailed, with a significant level of 0.05. Results: SmartX did not significantly improve scan accuracy (p>0.0.5)but did enhance consistency and operator confidence—particularly for novice users. The tool minimized the influence of scan technique, compensating for early scanning errors. While SmartX enabled successful library matching with minimal scan data, complete-arch scanning remained the recommended approach for optimal results. However, scan times were longer when using SmartX, especially for beginners. Conclusion: Although SmartX does not enhance impression accuracy directly, it improves the reliability and user confidence during complete-arch digital impressions, especially among less experienced clinicians. Its ability to reduce technique sensitivity and support library alignment with minimal data highlights its value as a training and clinical tool. Further clinical studies are needed to assess long-term outcomes and broader clinical integration.

Background: Digital workflows have significantly improved accuracy and predictability in implant prosthodontics; however, full-arch rehabilitations in completely edentulous patients remain challenging due to the need for precise implant position transfer and passive fit of prosthetic frameworks. Although artificial intelligence (AI)–assisted digital workflows have shown promising results in vitro, prospective clinical evidence remains limited. This study aimed to clinically evaluate the accuracy of a novel AI-integrated digital impression workflow (SmartX) for all-on-X full-arch implant-supported rehabilitations. Methods: This prospective observational case series included 10 completely edentulous patients rehabilitated with all-on-X implant-supported full-arch prostheses. Digital impressions were obtained using extended SmartFlag scan bodies combined with an AI-assisted SmartX workflow and an intraoral scanner. Clinical accuracy was evaluated using visual and tactile inspection, the one-screw (Sheffield) test, and a screw resistance test, all recorded as dichotomous outcomes (acceptable passive fit: yes/no). Secondary outcomes included implant and prosthesis survival rates and the incidence of biological or technical complications. Patients were followed for a minimum of 6 months. Results: A total of 54 implants were placed (mean: 5.4 implants per patient), with no dropouts during follow-up. All cases demonstrated acceptable passive fit according to all accuracy assessments (100% positive outcomes). Progressive screw tightening revealed a consistent angular displacement of approximately 60° in all cases. Implant and prosthesis survival rates were 100%, and no biological or technical complications were observed during the follow-up period. Conclusions: Within the limitations of this prospective clinical study, the SmartX AI-assisted digital workflow combined with extended scan bodies demonstrated high clinical accuracy for full-arch implant-supported rehabilitations. This approach appears to be a reliable and clinically feasible option for digital full-arch prosthodontics. Further studies with larger sample sizes and longer follow-up periods are required to confirm these findings.