ABSTRACT Aim This randomized clinical trial evaluated soft tissue thickness (STT) around immediate implants with or without soft tissue augmentation using a volume‐stable collagen matrix (VCMX). Secondary outcomes included clinical, esthetic, volumetric, and patient‐reported outcomes. Materials and Methods Participants received immediate implants in the anterior esthetic zone with (Test) or without (Control) simultaneous VCMX augmentation. Outcomes were assessed before surgery, immediately after surgery, and at 6 and 12 months. The primary outcome was STT. Within‐ and between‐group comparisons were performed using the Friedman rank test and Mann–Whitney U test, respectively. Secondary outcomes included mucosal level (ML), marginal bone level (MBL), esthetic and patient‐reported outcomes, and volumetric changes. Results Thirty‐eight out of 40 patients completed the study. STT was significantly greater in the Test group at all follow‐ups ( p < 0.05). At 12 months, STT in the Test group increased significantly at 3 mm from the gingival margin (1.85 mm, SE 0.19, p < 0.0001) and non‐significantly at 6 mm (1.29 mm, SE 0.24, p = 0.0917), whereas STT in the Control group decreased non‐significantly at 3 mm (0.18 mm, SE 0.18, p = 0.6213) and at 6 mm (0.36 mm, SE 0.10, p = 0.1054). ML remained stable in the Test group but showed significant recession in the Control group. Selected esthetic and patient‐reported outcomes favored the Test group. MBL did not change significantly over time in either group. Volumetric analysis showed no significant change over time in the Test group, whereas the Control group showed significant shrinkage ( p = 0.0201). Conclusions VCMX augmentation may improve soft tissue stability around immediate implants. Trial Registration The study protocol was registered on September 20, 2021 in the ClinicalTrials.gov database (registration number: NCT05081284)
ABSTRACT Objectives To record the accuracy and agreement of three types of probes (i.e., a common metal probe and two types of flexible probes) for peri‐implant probing depth (PD) assessment, including patient‐reported outcomes (PRO). Methods Fifty patients (85 implants) with an implant‐supported restoration were included. Peri‐implant PD was recorded with a metal, plastic, and electronic probe. Pain/discomfort and patient preference were registered. After removing the prosthetic restoration, the correct peri‐implant PD (cPD), the mucosal height (MH), and the PD measured from the implant level (iPD) were assessed. Results Good accuracy and agreement were noted for PD measurements with the metal and plastic probe. They differed in approximately 80% of the measurements by < 1.5 mm from cPD, and on average, an underestimation of 0.5 mm occurred. The accuracy of the metal probe was negatively influenced by a thick peri‐implant mucosal phenotype. A direct comparison of the metal and plastic probes showed perfect agreement in 68.7% of the cases. Patients reported significantly less pain/discomfort when the plastic probe was used compared to the metal probe. The electronic probe was unreliable and differed by ≥ 1.5 mm from cPD in 65% of the measurements. Conclusions While the electronic probe was unreliable, the metal and plastic probes were relatively accurate and comparable for assessing peri‐implant PD; the plastic probe caused less pain/discomfort. However, in approximately 1/5 of the measurements a ≥ 1.5 mm deviation from the correct value (cPD) may occur, and the accuracy of the metal probe appears negatively influenced by a thick peri‐implant mucosal phenotype. Trial Registration The protocol was registered at clinicaltrials.gov (NCT05332327)
ABSTRACT Objectives To develop and validate an AI‐driven Digital Erythema Score (DES) for objective, non‐invasive assessment of peri‐implant mucosal erythema using intraoral scan (IOS) data. Materials and Methods An internal dataset (200 patients, 265 implants) was utilized, with the reference standard established via consensus by two independent experts. We developed a U‐Net model to automatically segment the peri‐implant mucosal margins to calculate the DES and diagnose erythema (modified Gingival Index mGI 0, ≥ 1). We used the YOLO model for object detection to localize erythema regions. The system's diagnostic performance was validated on an independent external dataset (23 patients, 30 implants), supplemented by a multi‐observer study to evaluate the AI's assistance across clinicians with varying experience levels. Results The U‐Net model achieved precise ROI segmentation (Dice similarity coefficient 0.69 ± 0.11) and reliable colorimetric calculation (ICC > 0.95). At the optimal threshold, the DES accurately identified mucosal erythema (AUC, internal 0.9228 [95% CI: 0.8533 to 0.9760], external 0.9018 [0.8135 to 0.9773]). DES and mGI showed significant correlations with bleeding on probing ( B = 7.38, OR = 5.32, both p < 0.001 ). The YOLO model localized inflammatory regions (mAP internal 0.8968, external 0.6820). In the external validation, the DES‐driven diagnostic framework enhanced the diagnostic performance of observers with different levels of experience and increased the inter‐observer consistency. Conclusions The DES provides an objective metric that converts chromatic signals into a diagnostic score and is significantly correlated with clinical inflammation. This AI‐driven framework reduces clinical subjectivity and establishes a non‐invasive paradigm for teledentistry and high‐frequency, home‐based monitoring of peri‐implant health in the future after validation with patient‐accessible imaging devices. Trial Registration This study has been prospectively registered (NCT07349095)
ABSTRACT Purpose To evaluate the accuracy of complete‐arch implant scans obtained using non‐splinting and non‐calibrated implant scan body (ISB) methods captured by an intraoral scanner (IOS) with 2 scanning patterns with and without artificial intelligence (AI)‐based tools. Materials and Methods A patient with an edentulous maxillary arch and 4 implants was enrolled. Four groups were established according to scanning technique evaluated: non‐splinting with PEEK or titanium ISBs, 2 non‐calibrated ISBs methods. For each technique, the maxillary arch was scanned using an IOS, applying both a circumferential and an occlusal‐buccal‐lingual scanning pattern, with and without the use of the integrated AI‐based tool of the selected IOS. A stone cast fabricated through the conventional splinted impression was verified and digitized with a laboratory scanner to serve as reference. Linear and angular discrepancies among the designed bars for reference and experimental scans were analyzed. Results Non‐calibrated techniques demonstrated better linear trueness and better angular trueness and precision than non‐splinting methods ( p < 0.05). No significant differences were observed between the 2 non‐calibrated ISB techniques ( p > 0.05). The titanium ISBs of the non‐splinting group resulted in better trueness and precision than the PEEK ISBs ( p < 0.05). The AI‐based tool had a significant effect on the accuracy of Dynamic Abutment non‐calibrated ISB system ( p < 0.05). No significant differences were found among the evaluated scanning patterns ( p > 0.05). Conclusions Implant scanning technique and AI‐based tool of the IOS selected influenced the accuracy of the complete‐arch implant scans; however, the scanning pattern did not affect the accuracy of the scanning process.
