Objectives: This study aimed to evaluate the feasibility of monolithic zirconia laminate veneers (MZLV) compared to lithium disilicate laminate veneers (LDLV).
Materials and methods: Sixty resin replicas, each prepared with depths of 0.5 mm, 0.7 mm, and 1 mm, were produced using a 3D printer from acrylic teeth. Laminate veneers of these thicknesses were milled from pre-sintered monolithic zirconia (3rd generation) and lithium disilicate blocks. The intaglio surface of MZLV was treated with air abrasion using 110 μm diameter silica-modified aluminium oxide particles and ceramic primer, while LDLV was etched with etchant gel and treated with the ceramic primer before cementation with resin cement. Vertical marginal discrepancy (VMD) was assessed using a stereomicroscope, and a load-to-failure test was conducted using a universal testing machine. Failure modes were evaluated macroscopically on fractured surfaces. Data were analysed statistically using Two-way ANOVA and Bonferroni correction (α = 0.05).
Results: LDLV samples exhibited significantly larger VMD compared to MZLV samples across all thicknesses, especially in cervical, palatal, and mean data. Within the LDLV group, load-to-fracture values for 0.7 mm and 1.0 mm thicknesses were similar, whereas for 0.5 mm thickness, it was significantly lower. In the MZLV group, load-to-fracture values were lower for 0.7 mm and 1.0 mm thicknesses compared to LDLV, but higher for 0.5 mm thickness.
Conclusions: Material choice and restoration thickness significantly influence laminate veneer restorations' success. MZLV generally exhibits superior vertical marginal fit compared to LDLV, with varying load-to-failure values across different thicknesses. Clinical management of debonding in MZLV is simpler compared to restoration fracture in LDLV.
Clinical relevance: Considering clinical factors, MZLV may be a preferable option to LDLV for this restoration with the thickness of 0.5 mm.
Keywords: Laminate veneer; Lithium disilicate; Load-to-failure; Monolithic zirconia; Vertical marginal discrepancy.
© 2024. The Author(s).