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Reliability of wear measurements of CAD-CAM restorative materials after artificial aging in a mastication simulator


Grau, Alexander; Stawarczyk, Bogna; Roos, Malgorzata; Theelke, Björn; Hampe, Rüdiger (2018). Reliability of wear measurements of CAD-CAM restorative materials after artificial aging in a mastication simulator. Journal of the Mechanical Behavior of Biomedical Materials, 86:185-190.

Abstract

OBJECTIVES
The purpose of this in vitro study was to assess the 2-body wear behavior of computer-aided design and computer-aided manufacturing (CAD-CAM) restorative materials and additionally to validate an automatic approach to wear quantification as provided by newly developed software.

MATERIALS AND METHODS
Two composite resins (Experimental Composite, Shofu Block HC), 1 polymethyl methacrylate- (PMMA)-based material (Telio CAD), and 1 dual-network material (VITA Enamic) were tested (n = 12). The materials were stored in distilled water at 37 °C for 14 days, then aged in a mastication simulator (cycles: 400 000, 50 N, 1.2 Hz, 5/55 °C) for 2-body wear testing with human molars as antagonists. Software was developed as a freely available function in R for automatic wear quantification and was applied to 2 (vertical and horizontal) images obtained by an optical laser scanner (SDM). Wear measurements were validated with a reference confocal laser scanning microscope (LSM) system. The Kruskal-Wallis with Tukey-Kramer post hoc test (α = 0.05), coefficient of variation, Bland-Altman method, and intraclass correlation were applied.

RESULTS
Shofu Block HC showed the greatest wear, and no differences were found among other materials. The automatic wear measurements agreed well with the reference LSM system. The reliability of the SDM scans was 98.5%.

CONCLUSIONS
The wear resistance caused by two-body wear differed among the restorative materials tested, with the mean wear resistance of the 2 composite resin materials differing significantly. Wear quantification with R software based on SDM scans showed satisfactory agreement with the reference LSM system.

Abstract

OBJECTIVES
The purpose of this in vitro study was to assess the 2-body wear behavior of computer-aided design and computer-aided manufacturing (CAD-CAM) restorative materials and additionally to validate an automatic approach to wear quantification as provided by newly developed software.

MATERIALS AND METHODS
Two composite resins (Experimental Composite, Shofu Block HC), 1 polymethyl methacrylate- (PMMA)-based material (Telio CAD), and 1 dual-network material (VITA Enamic) were tested (n = 12). The materials were stored in distilled water at 37 °C for 14 days, then aged in a mastication simulator (cycles: 400 000, 50 N, 1.2 Hz, 5/55 °C) for 2-body wear testing with human molars as antagonists. Software was developed as a freely available function in R for automatic wear quantification and was applied to 2 (vertical and horizontal) images obtained by an optical laser scanner (SDM). Wear measurements were validated with a reference confocal laser scanning microscope (LSM) system. The Kruskal-Wallis with Tukey-Kramer post hoc test (α = 0.05), coefficient of variation, Bland-Altman method, and intraclass correlation were applied.

RESULTS
Shofu Block HC showed the greatest wear, and no differences were found among other materials. The automatic wear measurements agreed well with the reference LSM system. The reliability of the SDM scans was 98.5%.

CONCLUSIONS
The wear resistance caused by two-body wear differed among the restorative materials tested, with the mean wear resistance of the 2 composite resin materials differing significantly. Wear quantification with R software based on SDM scans showed satisfactory agreement with the reference LSM system.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Epidemiology, Biostatistics and Prevention Institute (EBPI)
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:October 2018
Deposited On:04 Jan 2019 14:23
Last Modified:04 Jan 2019 14:24
Publisher:Elsevier
ISSN:1751-6161
OA Status:Closed
Publisher DOI:https://doi.org/10.1016/j.jmbbm.2018.06.030
PubMed ID:29986292

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