Using fractal geometry to examine failed implants and prostheses

Evaluation of Change in Radiographic Fractal Dimension around Dental Implants Placed with Low-Speed Drilling and Standard Drilling Protocols

Osseointegration is a process that depends on a multitude of factors, including the type of drilling, whether biological or conventional. Objective: Establish box-counting dimension values for radiological images in patients with implants placed with both drilling methods. Material and method: The sample included 129 implants corresponding to 50 patients. A double-blind study of data collection was carried out with the subsequent analysis of the fractal dimension as a comparative value of the state of the trabecular architecture. Results: We found no significant differences (p ≥ 0.05) between the two study groups comparing both drilling techniques. The values for the conventional drilling technique are 0.24 ± 0.07 and for biological drilling: 0.19 ± 0.11 with a p-value of 0.767. Conclusions: The drilling technique does not influence the success of the procedure and the osseointegration process.

Relationship between fracture toughness and fractal dimensional increment in two types of dental glass-ceramics with different fracture surface roughness

OBJECTIVES

Previous studies have reported the fractal dimensional increment of glass-ceramic fracture surfaces. The objective of this study was to determine the relationship between fracture toughness and fractal dimensional increment of two dental glass-ceramics with different volume fraction of crystals and different fracture surface roughness.

METHODS

Bar-shaped specimens were prepared from lithium disilicate (LDS) and nanofluorapatite (NFA) glass-ceramics. One face of each specimen was indented using a Knoop diamond at 25 N (LDS) or 10 N (NFA) followed by loading in 4-point, or 3-point flexure, respectively, until failure. Fracture toughness (Kc) was calculated using the surface crack in flexure (SCF) technique (ASTM C1421). Epoxy replicas of the fracture surfaces were scanned using the atomic force microscope (AFM) followed by noise filtering. The FRACTALS software was used to determine the fractal dimensional increment (D*) by the Minkowski cover algorithm.

RESULTS

Median (25%, 75% quartiles) fracture toughness of LDS bars were 1.62 (1.59, 1.69) MPa m1/2 and NFA bars were 0.68 (0.66, 0.74) MPa m1/2, respectively. The median fractal dimension (D) value (25%, 75% quartiles) before noise filtering were 2.16 (2.15, 2.17) and after noise filtering were 2.14 (2.14, 2.15) for LDS and before noise filtering were 2.29 (2.21, 2.38) and after noise filtering were 2.17 (2.17, 2.18) for NFA. Median (25%, 75% quartiles) surface roughness (Ra) before noise filtering were 139 (119, 188) nm and after noise filtering were 137 (118, 187) nm for LDS and before noise filtering were 7 (6, 15) nm and after noise filtering were 7 (6, 15) nm for NFA.

SIGNIFICANCE

Noise filtering successfully eliminated noise from the material with smooth fracture surfaces (NFA), decreasing the measured fractal dimension. The NFA data fit a Kc vs. D*1/2 statistical model for fused silica previously tested using a similar technique. The equation relating fracture toughness to the fractal dimension was modified, accounting for the toughening mechanisms. Fractal analysis with noise filtering can be used to estimate the fracture toughness of dental glass-ceramics that do not exhibit crack bridging.

Simulation of CAD/CAM milling on lithium disilicate: Mechanical and topographic analyses of surface grinding different protocols

The aim of this study was to evaluate the topography and the fatigue performance of lithium disilicate glass-ceramic after surface grinding through different laboratory protocols used to simulate the Computer-aided design/Computer-aided manufacturing (CAD/CAM) milling. Ceramic discs (IPS e.max CAD, Ø = 13.5 mm × 1.2 mm of thickness) were produced through different methodologies: milling in CAD/CAM system (CAD/CAM group); produced in-lab with a polished surface (POL group); or produced through in-lab methods and randomly distributed into five groups according to different grinding protocols to simulate the CAD/CAM milling [grinding with a CAD/CAM bur coupled to a mandrel (CAD/CAM Bur group); fine diamond bur using oscillatory movements (DBO group); fine diamond bur in x and y axes of the disc (DBXY group); #60-grit silicon carbide sandpaper (SiC group); and #60-grit wood sandpaper (WS group)]. The specimens were fatigue tested (n = 15) according to the step-stress method (initial load: 60 N; step-size: 20 N; 10,000 cycles/step; 20 Hz frequency). A roughness analysis was performed on all specimens, while fractal dimension (FD) and fractography were performed on representative samples. The Kaplan-Meier analysis showed that the POL (293.3 N) group presented better fatigue performance (higher load and number of cycles for failure) (p < 0.05) than the other groups (CAD/CAM = 222.7 N; CAD/CAM Bur = 181.3 N; DBO = 184.0 N; DBXY = 192.0 N; SiC = 182.6 N; WS = 182.6 N). For roughness, only the SiC (Ra = 1.616; Rz = 10.465) and WS (Ra = 1.673; Rz = 10.655) groups produced statistically similar Ra (μm) and Rz (μm) values to the CAD/CAM (Ra = 1.628; Rz = 9.571) group (p > 0.05). The surface created by CAD/CAM milling and POL group exhibited more complexity (FD) higher values than the experimental groups. For the ceramic surface topography images, the CAD/CAM milling visibly produced a uniform surface compared to the other groups; however, the POL group was the smoothest. The DBO, DBXY, SiC, and WS groups resulted in similar characteristics of surface topography. Therefore, although the SiC and WS groups showed similar roughness to the control group (CAD/CAM), no in-lab simulation method was fully capable to mimic the mechanical performance of the CAD/CAM-milled lithium disilicate glass-ceramic.

Forensic and reliability analyses of fixed dental prostheses

This article describes the protocol for determining the cause of failure for retrieved failed implant supported fixed dental prostheses (FDPs) in a clinical study of three-unit bridges. The results of loading of flexure bars of different veneer compositions at different stress rates were presented for two veneer materials (leucite reinforced and fluorapatite glass-ceramic veneers) and a Y-TZP core zirconia ceramic used in the clinical study. From these results, the strengths of the fast loading conditions were used to determine the fracture toughness of these materials. Fractal dimension measurements of the flexure bars and selected FDPs of the same materials demonstrated that the values were the same for both the bars and the FDPs. This allowed the use of fracture toughness values from the flexure bars to determine the strengths of the FDPs. The failure analysis of clinically obtained FDP replicates to determine the size of the fracture initiating cracks was then performed. Using the information from the flexure bars and the size of the fracture initiating cracks for the failed FDPs, the strengths of the FDPs were determined. The clinical failures were determined to be most likely the result of repeated crack growth due to initial overload and continuous use after initial cracking.

Fractal analysis at varying locations of clinically failed zirconia dental implants

OBJECTIVES

Previous studies have shown that the fracture toughness of ceramics can be determined from the fractal dimensions (D) of their fracture surfaces and that the surface should be leveled to obtain an accurate D measurement. This study was to determine the effects of leveling operations and distance from the failure origin on the D values.

METHODS

Twelve clinically failed zirconia implants from four different manufacturers: Axis Biodental (n=7), Z-Systems (n=3), Straumann (n=1), and Swiss Dental Solutions (n=1) were obtained from one of the authors and thoroughly cleaned. Epoxy replicas were made of three locations along the crack path in the center region of each fracture surface (near origin (O), hackle (H), and near compression curl (CC)) using a light body polyvinyl siloxane impression material. Surfaces were scanned in ScanAsyst mode with a scan size of 5μm×5μm and a scan rate of 0.592Hz using the atomic force microscope. The surface scans were then leveled using 1st order flattening operation in the AFM analysis software. The height data before and after the operation were imported into a custom MathCAD script, and FRACTALS software was used to determine the D value by Minkowski Cover algorithm, which was shown previously to be the algorithm with the highest precision. A Wilcoxon signed-rank test, two-way repeated-measures ANOVA, and one-way repeated-measures ANOVA were performed as detailed below.

RESULTS

The data were not normally distributed (S-W p≤0.05), so a non-parametric repeated measures test (Wilcoxon signed-rank test) was selected. The median D values before and after leveling were 2.161 and 2.174, respectively. There was a significant difference before and after leveling (p<0.001). The two-way repeated-measures ANOVA showed no significant difference among the D values for different implant brands (p=0.66) and scanning locations on the fracture surface (p=0.83). After eliminating the implant brand as a factor, the data passed normality and equal variance tests (S-W p=0.88, BF p=0.15). The mean D values and standard deviations from the three locations (O, H, CC) were 2.183±0.031, 2.179±0.024, and 2.175±0.018, respectively. One-way repeated measures ANOVA showed no significant effect of scanning location (p=0.74).

SIGNIFICANCE

The leveling operation successfully removed the tilt without decreasing surface tortuosity, as it increased the D values significantly. The fractal dimension was the same at the three locations on the fracture surfaces. This means that hackle and compression curl regions can be used to determine fracture toughness when the failure origin has been lost.