Effectiveness of an AI-Assisted Digital Workflow for Complete-Arch Implant Impressions: An In Vitro Comparative Study

<b>Background</b>: 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. <b>Objective</b>: 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. <b>Methods</b>: 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 (<i>t</i>-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). <b>Results</b>: SmartX significantly improved consistency and operator confidence, especially among novices, although it did not yield statistically significant differences in scan accuracy (<i>p</i> > 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. <b>Conclusions</b>: 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.

Authors

Institutions

Publication Details

Journal
Dentistry Journal
Published
2025-10-09
DOI
https://doi.org/10.3390/dj13100462
Citations
1
Primary Topic
Dental Implant Techniques and Outcomes
Type
article
Field-Weighted Citation Impact
1.79
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Effectiveness of an AI-Assisted Digital Workflow for Complete-Arch Implant Impressions: An In Vitro Comparative Study

Ieva Gendvilienė, Elisabetta Rosa, Gabriele Cervino, Wael Att et al.
1 citations
Dentistry Journal
Dental Implant Techniques and Outcomes
1.79
article

Effectiveness of an AI-Assisted Digital Workflow for Complete-Arch Implant Impressions: An In Vitro Comparative Study

Ieva Gendvilienė, Elisabetta Rosa, Gabriele Cervino, Wael Att, Rim Bourgi, Aurea Immacolata Lumbau, Silvio Mario Meloni, Marco Tallarico, Mohammad Qaddomi, Carlotta Cacciò
article en
1 citations

Abstract

<b>Background</b>: 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. <b>Objective</b>: 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. <b>Methods</b>: 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 (<i>t</i>-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). <b>Results</b>: SmartX significantly improved consistency and operator confidence, especially among novices, although it did not yield statistically significant differences in scan accuracy (<i>p</i> > 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. <b>Conclusions</b>: 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.

Dentistry JournalVol. 13(10)
University of Messina (IT), Inserm (FR), University of Sassari (IT), Vilnius University (LT), Saint Joseph University (LB), University Medical Center Freiburg (DE), Beirut Arab University (LB), Université de Strasbourg (FR), Analysis Group (United States) (US)
Openalex Percentile: Top 12%
Dental Implant Techniques and Outcomes
1.79
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.