Accuracy of the Emergence Profile of Dental Implant Restorations using different gingival mask techniques.

Abstract

Background: Accurate reproduction of peri-implant soft tissue contours is essential for the esthetics, phonetics, hygiene, and long-term success of implant-supported restorations. Gingival mask (GM) techniques play an important role in reproducing the emergence profile (EP) and peri-implant soft tissue contour. This study evaluated and compared the accuracy of crown adaptation using conventional, 3D-printed, and digital GM workflows.

Materials and methods: Forty zirconia crowns were fabricated on implant standard abutments with a straight EP using a maxillary master model obtained from a patient missing left maxillary first molar. A single implant was placed using a guided surgical protocol and cone beam computed tomography. The crowns were divided into four groups (n=10) according to the GM technique: conventional, 3D-printed, adapted digital (DI-1), and non-adapted digital (DI-2). Crown adaptation and gap dimensions were evaluated using the digital subtraction method and a high-resolution desktop optical scanner. Scanning was performed for the abutment, internal crown surface, and the seated crown-abutment assembly. Measurements were obtained at buccal (B), palatal (P), mesial (M), and distal (D) points. Statistical analysis included Levene's test, one-way ANOVA, and Tukey's and Games-Howell post hoc tests (P 0.05).

Results: The adapted digital GM group showed the lowest mean gap values at all measurement points, indicating superior adaptation accuracy, whereas the 3D-printed GM group showed the highest gap values. One-way ANOVA revealed significant differences among all GM groups at all measurement points (P=0.001). Post hoc analysis showed significant differences among most groups; however, no significant differences were found between the conventional and 3D-printed GM groups at point B or between the conventional and DI-2 groups at points P, M and D.

Conclusions: GM techniques significantly influenced the accuracy of implant-supported restorations. The adapted digital GM workflow demonstrated superior adaptation and more accurate reproduction of peri-implant tissue contours and emergence profiles compared with the other techniques.