Evaluation of Implant Stability and Patient-centered Outcomes of Conventional versus Artificial Intelligence-Assisted/Computer Guided Electromagnetic Mallet-Assisted Ridge Split and expansion with Sim

Vollständiger Abstract

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Background: Horizontal maxillary ridge defect rehabilitation is still a clinical challenge. In this randomized clinical trial, artificial intelligence (AI)assisted/computer-guided electromagnetic mallet-assisted alveolar ridge split and expansion (ARSES) with simultaneous guided implant placement was compared to conventional freehand in order to assess implant stability and patient-centered outcomes. Methods: Group 1 (conventional freehand ARSES; n = 11 implants) and Group 2 (AI-assisted/computer-guided ARSES using patient-specific surgical templates; n = 11 implants) were randomly assigned (1:1 ratio) to 22 implants placed in eight patients with horizontal maxillary ridge deficiencies (3–6 mm width, 10 mm height). Both groups used an electromagnetic mallet for surgical procedures. Using magnetic resonance frequency analysis (Implant Stability Quotient; ISQ), primary and secondary stability were assessed right after implantation as well as three and six months later. Over the course of a 12-month follow-up period, secondary outcomes included intraoperative pain and discomfort, actual surgical duration, overall patient satisfaction (as determined by a 100-mm VAS), and implant success rate according to Pisa criteria. Results: With no surgical complications, both cohorts had a 100% implant success rate. There was no statistically significant difference in baseline primary stability between Group 1 (43.25±6.45) and Group 2 (46.14±3.34; p=0.206). At three months (77.34±2.35 vs. 69.88±5.75; p=0.002) and six months (83.40±2.91 vs. 79.41±4.82; p=0.032), Group 2 showed noticeably greater secondary stability. A significant Group × Time interaction at 3 months (p=0.029) was found by linear mixed model analysis, suggesting that the guided group had an accelerated early osseointegration trajectory. Despite clinical trends supporting the AI-guided workflow, differences in surgical duration (50.75±27.65 vs. 37.50±14.15 min; p=0.561), intraoperative pain (p=0.874), discomfort (p=0.172), and overall satisfaction (p=0.053) did not reach statistical significance. Conclusion: In comparison to the traditional freehand method, AI-assisted/computerguided electromagnetic mallet ARSES accelerates the trajectory of secondary stability and improves early osseointegration, offering a predictable and minimally invasive option for maxillary horizontal ridge expansion.