An in vitro study using confocal laser scanning microscopy to evaluate the marginal misfits of different implant‐supported frameworks

Abstract

AbstractPurposeThis study aimed to develop and evaluate a simple, non‐destructive method for assessing the misfit and passivity of implant‐retained prostheses frameworks.Materials and MethodsTo simulate the rehabilitation of a mandible posterior partially edentulous area using 3‐unit screw‐retained frameworks supported by two implants were fabricated and divided into the following five groups (n = 10 in each group): OP = one‐piece framework cast in Co‐Cr with the conventional method (control‐group); Co‐Cr frameworks sectioned and welded by laser (=LAS) or tungsten inert gas (=TIG); Co‐Cr CAD‐CAM = milled Co‐Cr framework; Zir CAD‐CAM = milled zirconia framework. The horizontal |X| and vertical |Y| misfits were measured using confocal laser scanning microscopy with one or both screws tightened. Data were analyzed by a two‐way ANOVA with repeated measures and Bonferroni correction (α = 0.05).ResultsThe greatest |X| misfit was observed in the OP group with both screws tightened (290 µm) and one screw tightened (388 and 340 µm). The conventional casting groups sectioned and welded by laser or TIG had lower mean values (235.35 µm, both screws tightened; and 275 µm, one screw tightened) than the OP framework. However, these values still exceeded those of the milled Co‐Cr and zirconia frameworks (190 and 216 µm with both screws tightened). Across all reading conditions, every framework subjected to testing consistently maintained vertical |Y| misfit levels below the threshold of 53 µm; however, the milled frameworks exhibited higher vertical misfits than the frameworks obtained by the conventional cast method.ConclusionsThe frameworks, whether cast and sectioned with laser welding or milled from Co‐Cr, exhibit improved marginal misfit and enhanced passive fit when compared to other fabrication methods. Additionally, the use of confocal laser scanning microscopy is highly effective for passivity and misfit analysis.