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Published on: April 29, 2014
Accuracy of the Emergence Profile of Dental Implant Restorations using different gingival mask techniques
Firas Abdulameer Farhan1, Ali Jameel Abdul Sahib2, Mustafa Mahdi Jassim3
1PhD. Assistant Professor, Department of Prosthodontics, College of Dentistry, University of Baghdad, Bab Al-Muadham campus of the University of Baghdad, 1417, Baghdad, Iraq.
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.
