Influence of the Number of Scan Bodies on Full-Arch Implant Scanning: A Comparison of 2 vs 4 Implants.

Accuracy is a necessity in implant impressions to fabricate accurately fitting implant-supported prostheses. This in vitro study aimed to explore the impact of the number of scan bodies on scanning quality by comparing scans of 2 vs 4 implants, and to determine if their accuracy and precision meets acceptable clinical threshold. Two mandibular edentulous models were used: one with 4-parallel implants (4-IM) and the other with 2-parallel implants (2-IM). Each model was scanned 10 times with an intraoral scanner, while reference scans were obtained with a high-precision laboratory scanner. The accuracy of test scans was evaluated by superimposing them onto reference scans and measuring 3D and angular deviations of the scan bodies. To assess the precision, the repeatability of the scans was analyzed by measuring the 3D SDs. Independent t test was used to compare angular deviations, the Mann-Whitney U test was used for 3D deviations and 3D SDs, and 1 sample t test was used for comparing means to the clinical threshold. Angular and 3D deviations were statistically not significant between the 2 groups (P = .054 and 0.143). 3D deviation values were higher than the 150-µm threshold for 2-IM (201 µm) and 4-IM (290 µm); angular deviation in 2-IM was 0.600 degrees and 0.885 degrees for 4-IM. There was no statistically significant difference in the precision of scans between the 2 groups. (P = .161). Although scanning quality improved when 2 scan bodies were used, the difference was not statistically significant. Moreover, full-arch implant scanning did not meet acceptable levels of accuracy and precision.

Effect of geometric heterogeneity using an auxiliary device on the accuracy of complete arch implant scanning: An in vitro study of different clinical simulations.

STATEMENT OF PROBLEM: Intraoral scanning of implants supporting complete arch prostheses is limited because of the lack of geometric heterogeneity and unique reference points, creating inherent errors in the image stitching process by the scanner software program. PURPOSE: The purpose of this in vitro study was to evaluate the significance of geometric heterogeneity on complete arch implant scanning by using a novel auxiliary geometric device. Three different clinical simulations were tested to assess its significance. The study also assessed whether scans produced using the auxiliary device would meet a clinically acceptable threshold. MATERIAL AND METHODS: A total of 60 scans (n=20) were performed using an intraoral scanner in 3 different clinical simulations: 2 parallel implants, 4 parallel implants, and 4 implants with a 30-degree posterior angulation of the distal implants. Scanning alternated between using the auxiliary geometric scanning device (test groups; 4IP+, 4IA+, 2IP+) and not using the device (control groups; 4IP-, 4IA-, 2IP-). A reference scan for each model was prepared from a high precision laboratory scanner. The scans were analyzed for accuracy in 3-dimensional deviation, interimplant distance deviation, and angular deviation by using an inspection software program. The effect of the auxiliary device was statistically analyzed by comparing scans of the same group using the paired t test for normally distributed data and the Wilcoxon Signed Rank test when data were not normally distributed (α=.05). RESULTS: Significant effects of the auxiliary geometric device were found in 3-dimensional, distance and angular deviations (P<.05). Scans performed using the device were significantly more accurate in most implant positions (P<.05). Linear and angular deviations were clinically acceptable for all test groups. However, the deviations were above the clinically acceptable threshold for the control groups. CONCLUSIONS: Using an auxiliary geometric device significantly improved scanning accuracy and produced scans with clinically acceptable deviations, while standard digital scans exceeded the accepted clinical threshold.

Magnitude of misfit threshold in implant-supported restorations: A systematic review.

STATEMENT OF PROBLEM: Attaining a passive fit in implant restorations is desirable but clinically difficult to achieve, especially in screw-retained prostheses. At a certain magnitude, this misfit will not cause mechanical and biological complications, but the exact level has yet to be determined. PURPOSE: The purpose of this systematic review was to gather, compare, and appraise studies that attempted to determine the biological and mechanical tolerance of misfits. MATERIAL AND METHODS: The review protocol was published in the Prospective Register for Systematic Reviews (PROSPERO; registration no. CRD42021268399) and follows the Preferred Reporting for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. An electronic search was conducted through PubMed, Ebscohost, and Web of Science followed by a manual search up to December 2021. RESULTS: A total of 413 manuscripts were identified by electronic and manual search. After removing duplicates, nonrelevant titles, and abstract screening, 62 manuscripts were eligible for full-text assessment. Finally, a total of 13 articles (1 cross-sectional study, 1 retrospective and prospective, 7 in vitro studies, and 4 animal studies) met the eligibility criteria and were included in this review. A wide range of tolerable misfits were reported. Vertical misfit up to 1 mm and horizontal misfit up to 345 µm were associated with no adverse outcomes. CONCLUSIONS: The current literature provides inadequate data to determine a clinical threshold of an acceptable misfit. However, this review demonstrated that the mechanical response to misfit is more critical than the biological response.

Experimental Analysis in Hadoop MapReduce: A Closer Look at Fault Detection and Recovery Techniques.

Hadoop MapReduce reactively detects and recovers faults after they occur based on the static heartbeat detection and the re-execution from scratch techniques. However, these techniques lead to excessive response time penalties and inefficient resource consumption during detection and recovery. Existing fault-tolerance solutions intend to mitigate the limitations without considering critical conditions such as fail-slow faults, the impact of faults at various infrastructure levels and the relationship between the detection and recovery stages. This paper analyses the response time under two main conditions: fail-stop and fail-slow, when they manifest with node, service, and the task at runtime. In addition, we focus on the relationship between the time for detecting and recovering faults. The experimental analysis is conducted on a real Hadoop cluster comprising MapReduce, YARN and HDFS frameworks. Our analysis shows that the recovery of a single fault leads to an average of 67.6% response time penalty. Even though the detection and recovery times are well-turned, data locality and resource availability must also be considered to obtain the optimum tolerance time and the lowest penalties.