Highlights
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Roughness analyses of marketed dental implant screws was conducted.
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Stereo-SEM and interferometry exhibited predominant statistical differences.
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Both methods revealed different ability to discriminate between surfaces.
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A clinically relevant categorizing approach showed promise for evaluation.
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Surface analyses of implants require more sophisticated guidelines.
Abstract
Objective
Comparability of topographical data of implant surfaces in literature is low and their clinical relevance often equivocal. The aim of this study was to investigate the ability of scanning electron microscopy and optical interferometry to assess statistically similar 3-dimensional roughness parameter results and to evaluate these data based on predefined criteria regarded relevant for a favorable biological response.
Methods
Four different commercial dental screw-type implants (NanoTite Certain Prevail, TiUnite Brånemark Mk III, XiVE S Plus and SLA Standard Plus) were analyzed by stereo scanning electron microscopy and white light interferometry. Surface height, spatial and hybrid roughness parameters (Sa, Sz, Ssk, Sku, Sal, Str, Sdr) were assessed from raw and filtered data (Gaussian 50 μm and 5 μm cut-off-filters), respectively. Data were statistically compared by one-way ANOVA and Tukey–Kramer post-hoc test. For a clinically relevant interpretation, a categorizing evaluation approach was used based on predefined threshold criteria for each roughness parameter.
Results
The two methods exhibited predominantly statistical differences. Dependent on roughness parameters and filter settings, both methods showed variations in rankings of the implant surfaces and differed in their ability to discriminate the different topographies. Overall, the analyses revealed scale-dependent roughness data. Compared to the pure statistical approach, the categorizing evaluation resulted in much more similarities between the two methods.
Significance
This study suggests to reconsider current approaches for the topographical evaluation of implant surfaces and to further seek after proper experimental settings. Furthermore, the specific role of different roughness parameters for the bioresponse has to be studied in detail in order to better define clinically relevant, scale-dependent and parameter-specific thresholds and ranges.
1
Introduction
Screw-shaped dental implants have complex designs making topographical and analytical surface characterizations difficult due to uneven, too small, or inaccessible areas. Nevertheless, there is an ongoing need for thorough surface characterization since implant surfaces have been shown to determine primary interfacial reactions with bone, epithelial and connective tissue cells , such as macromolecular adsorption/desorption, conformational changes, as well as cell adhesion, proliferation and differentiation . Furthermore, surface roughness and texture have been recently identified as potentially important factors in controlling the early wound healing processes at the blood/implant interface .
Stylus profilometry , and optical scanning methods such as interferometry or confocal laser scanning microscopy have been applied to quantitatively assess the three-dimensional roughness of implant surfaces. However, different roughness values have been reported upon using different measuring methods . Therefore, there is uncertainty concerning the validity of the roughness data derived. One possible explanation for the inconsistent roughness values reported in the literature are the application of different, often unmentioned, filters used for discriminating surface roughness from waviness. Furthermore, the absence of unfiltered raw data of the scanned topographies might also be an issue of concern preventing the comparison of published results.
Optical methods have been regarded as the only acceptable tools for the roughness analysis of densely threaded implants . They are very fast, with wide measuring ranges, at both vertical and lateral directions .
Alternatively, scanning electron microscopy (SEM) can be applied for topographical evaluation providing large depth of field, high spatial resolution down to the nanometer range, and feasibility to study structures with a high aspect ratio . In SEM quantitative information can be obtained by photogrammetry using a pair of SEM-stereographs (stereo-SEM) taken with 5–10° angular displacement. The vertical resolution of stereo-SEM is a function of the applied tilt angle and magnification , whereas the lateral and vertical resolution characteristics of stereo-SEM are the inverse of optical interferometry . Stereo-SEM has been applied for roughness analysis of experimental dental implant surfaces in several studies and a complementary roughness analysis at the micro- and nanoscale . Nevertheless, there is limited information on the capacity of stereo-SEM to characterize implant surfaces equally efficiently with optical interferometry.
The aim of the present study was to investigate the ability of optical interferometric profilometry (OIP) and stereo-SEM profilometry (SSP) to similarly describe implant surfaces by raw and filtered data, respectively. A set of roughness parameters was selected to analyze amplitude, spatial, and hybrid roughness parameters, often used in the field of dental implants.
Moreover, the selected parameters should preferably be associated to a relevant biological response at an implant site, based on the current knowledge. Thus, in a categorizing approach, predefined thresholds and ranges regarded relevant for the biological response have been applied for each of the selected parameters, to compare the similarity of the clinically relevant conclusions.
2
Materials and methods
2.1
Test specimens
Commercially available screw-type implants with different surface treatments were selected for the study ( Table 1 ). The corresponding surface treatments are as follows:
| Implant/code code/lot | Material | Diameter/length a (mm) | Thread height/pitch b (μm) | Manufacturer |
|---|---|---|---|---|
| NanoTite Certain Prevail NT/636712 | Titanium alloy (Ti6Al4V) | 4.0/18 | 332/620 | Biomet 3i, USA |
| TiUnite Brånemark Mk III TiU RP TU/682547 & 680467 | Titanium grade 4 | 4.0/18 | 325/622 | Nobel Biocare, Sweden |
| XiVE S Plus XV/103391611223 | Titanium grade 2 | 4.5/18 | 486/889 | Dentsply Friadent, Germany |
| SLA Standard Plus SL/J7377 | Titanium grade 4 | 4.1/14 | 335/1284 | Institute Straumann, Switzerland |
2.1.1
NanoTite (NT)
Calcium-phosphate (CaP) nanoparticle modification of a minimally rough titanium alloy surface. The surface has been described as being created by a particulate sol–gel deposition method using discrete crystalline deposition (DCD) of CaP (nominal crystal size 20–100 nm) and 50% surface coverage .
2.1.2
TiUnite (TU)
Anodically oxidized, composed of a duplex oxide structure with an outer microporous film (4 μm pore size) and an inner pore-free barrier film without micropores. The crystal structure has been reported to be composed of anatase and rutile phases .
2.1.3
XIVE S plus (XV)
Grit-blasted and acid etched in hydrochloric acid/sulfuric acid/hydrofluoric acid/oxalic acid solution and subsequently neutralized .
2.1.4
SLA (SL)
Grit-blasted (0.25–0.5 mm corundum/5 bar), followed by acid etching resulting in a complex topography consisting of craters (30–100 μm in diameter) overlaid with micro-pits (0.5–3 μm in diameter) with sharply pointed projections ∼700 nm in height .
2.2
Macroscopic evaluation
The shape of the implants and their screw geometry was analyzed by a digital optical microscope (VHX-600 3CCD, Keyence, Germany). Thread height and pitch of the implants were measured by 3D-picture profile measuring, respectively.
2.3
Scanning electron microscopy (SEM) and stereo-SEM profilometry (SSP)
For qualitative surface analysis, the implants were sputter-coated (SCD 050, Baltec, Germany) by a 20 nm thin Au–Pd layer to prevent charging and investigated in a scanning electron microscope (Leo 1430 SEM, Zeiss, Germany) at 15 kV accelerating voltage and 650× and 5000× magnifications employing a secondary electron detector. To obtain quantitative information about the roughness, stereoscopic pairs of micrographs were used to reconstruct 3D-surface features (stereo-SEM). Secondary electron images were obtained by eucentrically tilting the sample stage about a horizontal x-axis by +6° (right image) vs 0° (left image) at 650×. The stereoscopic reconstruction of digital surface models and the analysis of different roughness parameters were computed using the MeX 5.0 software (Alicona Imaging, Graz, Austria).
2.4
Optical interferometric profilometry (OIP)
On the Au–Pd sputtered implants used before for the SEM analyses, the 3D-surface roughness parameters were likewise evaluated by an optical profiler (Wyko NT1100, Veeco, Tuscon, AZ, USA) operated under the following conditions: Mirau lens (20 × 2 FOV), vertical scanning mode (VSI), 41.6× magnification, tilt correction 50 μm (F50) and 5 μm (F05), high-pass Gaussian Fourier filtering at a resolution of 0.1 nm (z-axis) and 0.2 μm (x, y axis).
2.5
Roughness analysis
The tested implants were analyzed by scanning root part areas of 200 × 100 μm 2 . Areas were selected either within the grooves between the threads of the respective implant screws only ( Fig. 1 a–e) or, if available, at the apex-oriented cutting grooves. The demand for the operator was for the optical method to measure at the same implant sites as chosen for SEM. This was in detail: for NanoTite, Xive, and Mk II TiUnite to measure at 6 different grooves between threads and at 3 areas within cutting grooves, respectively. For SLA, an implant type without cutting grooves, the demand was to measure at 9 different thread groove sites. For both SSP and OIP, raw data have been collected and roughness was separated from waviness at the micro and near-submicron level by applying Gaussian filters with a cut-off-filter length of 50 and 5 μm (F50 and F05), respectively.
2.6
Roughness parameter definition and evaluation criteria
Amplitude, spatial, and hybrid surface texture parameters were chosen to describe the 3D-characteristics of the implant topographies according to ISO 25178 as follows:
2.6.1
Amplitude parameters
2.6.1.1
Sa (roughness average)
Represents an overall measure of the surface texture but cannot differentiate peaks, valleys and spacing of the various texture features. Surfaces with Sa ranging from 0.0 to 0.4 μm are classified as smooth, from 0.5 μm to 1 μm as minimal rough, from 1 μm to 2 μm as moderate rough and higher than 2 μm as maximal rough, after F50 application .
2.6.1.2
Sz (ten point height)
Sz is given by the average difference between the 5 highest peaks and the 5 deepest valleys within the sampling area. Since high Sz values indicate unwanted deviations from a uniform surface, Sz < 10 μm has been defined as a positive criterion for evaluation.
2.6.1.3
Ssk (skewness of the height distribution)
Ssk indicates the asymmetry of surface deviations around the mean plane. A symmetric shape, as represented by a Gaussian surface height distribution, implies a zero skewness. An asymmetric height distribution leads to a negative skewness in case of increased frequency of features below the mean plane (valleys) or to a positive skewness in case of increased frequency above the mean plane (summits). Thus, a negative Ssk value points at a surface with more and/or deeper valleys than summits . A positive skewness is regarded, according to computer simulations, to have higher interfacial shear strength to bone compared to a mirror imaged surface with the same absolute but negative skewness . Therefore, Ssk > 0 was regarded a preferable category in our study.
2.6.1.4
Sku (kurtosis of the height distribution)
Sku distinguishes a sharper peak from a more rounded peak of the height distribution. A peak as given for a normal distribution has a Sku of 3. Sku > 3 represents height distributions with stronger and sharper peaks, caused by a few very deep valleys or very high summits on the analyzed surface, and with fatter tails. Sku < 3 represents height distributions with lower and wider peaks and thinner tails, and indicate more uniform surfaces and rounded peaks. Due to stress peaks in the bone adjacent to roughness peaks, a higher kurtosis indicating sharp peaks will favor bone resorption . Therefore, we predefined in the categorizing approach a Sku < 5 as preferable.
2.6.2
Spatial parameters
2.6.2.1
Sal (auto-correlation length)
Sal is based on the autocorrelation function (ACF) and represents the fastest decay autocorrelation length. It is defined as the horizontal distance of the ACF that has the fastest decay to 0.2 (indicating a distance of low correlation). Surfaces that are dominated by high-frequency components have smaller Sal values than that dominated by low-frequency components. Medium scaled Sal < 10 was set in this study a threshold for the categorizing approach.
2.6.2.2
Str (texture-aspect ratio)
Str is also based on the ACF and provides information about the isotropy or directionality of the surface texture. Str is defined by the ratio of the length of the fastest decay of the autocorrelation function to the length of the slowest decay to 0.2. Str ranges between 0 and 1. Larger values >0.5 indicate isotropic, uniform texture, whereas smaller values indicate an anisotropic, directional surface. A uniform surface has the same properties regardless of the direction . In our study, Str > 0.5 has been predefined preferable.
2.6.3
Hybrid parameters
2.6.3.1
Sdr (developed interfacial area ratio)
Sdr expresses the ratio of the increment of the interfacial surface area and the projected area, i.e., the percentage of additional surface area contributed by the texture as compared to an ideal plane. Sdr = 0 indicates a totally flat surface. Practically speaking, Sdr describes the ratio between the 3-D measurement and a 2-D reference plane . An Sdr value of about 50% is regarded superior for a strong bone response . We predefined in our study an Sdr between 40% and 60% as preferable.
2.7
Statistical analysis and categorizing approach
Two implants from each type were analyzed. All roughness measurements by SSP and OIP were done at least at 8 sites on each single implant, respectively (n = 16). Data are presented as means and corresponding standard deviations. Differences between means were statistically analyzed by one-way analysis of variance (ANOVA) followed by Tukey-Kramer test for pair-wise comparisons. The independent variables were the analyzing method (SSP, OIP) and the applied filter levels (unfiltered, F50, F05). Additionally, ANOVA followed by Tukey Kramer has been applied in order to test the differences between means for each implant type (at each method/filter combination), resulting in the corresponding implant surface ranking. The dependent variable was the numerical value of the respective roughness parameter. Differences were regarded statistically significant for p < 0.05 (calculated by JMP 5.0.1, SAS Institute Inc., Cary, NC, USA).
In the categorizing approach, based on the pre-described evaluation criteria, the percentage of measurements that met the respective criteria were tested for each implant/filter combination. Furthermore, it was examined whether both methods, based on the median values of each implant-filter combination, pointed to the same classification and therefore to a similar prediction of the biological effect.
2
Materials and methods
2.1
Test specimens
Commercially available screw-type implants with different surface treatments were selected for the study ( Table 1 ). The corresponding surface treatments are as follows:
| Implant/code code/lot | Material | Diameter/length a (mm) | Thread height/pitch b (μm) | Manufacturer |
|---|---|---|---|---|
| NanoTite Certain Prevail NT/636712 | Titanium alloy (Ti6Al4V) | 4.0/18 | 332/620 | Biomet 3i, USA |
| TiUnite Brånemark Mk III TiU RP TU/682547 & 680467 | Titanium grade 4 | 4.0/18 | 325/622 | Nobel Biocare, Sweden |
| XiVE S Plus XV/103391611223 | Titanium grade 2 | 4.5/18 | 486/889 | Dentsply Friadent, Germany |
| SLA Standard Plus SL/J7377 | Titanium grade 4 | 4.1/14 | 335/1284 | Institute Straumann, Switzerland |
2.1.1
NanoTite (NT)
Calcium-phosphate (CaP) nanoparticle modification of a minimally rough titanium alloy surface. The surface has been described as being created by a particulate sol–gel deposition method using discrete crystalline deposition (DCD) of CaP (nominal crystal size 20–100 nm) and 50% surface coverage .
2.1.2
TiUnite (TU)
Anodically oxidized, composed of a duplex oxide structure with an outer microporous film (4 μm pore size) and an inner pore-free barrier film without micropores. The crystal structure has been reported to be composed of anatase and rutile phases .
2.1.3
XIVE S plus (XV)
Grit-blasted and acid etched in hydrochloric acid/sulfuric acid/hydrofluoric acid/oxalic acid solution and subsequently neutralized .
2.1.4
SLA (SL)
Grit-blasted (0.25–0.5 mm corundum/5 bar), followed by acid etching resulting in a complex topography consisting of craters (30–100 μm in diameter) overlaid with micro-pits (0.5–3 μm in diameter) with sharply pointed projections ∼700 nm in height .
2.2
Macroscopic evaluation
The shape of the implants and their screw geometry was analyzed by a digital optical microscope (VHX-600 3CCD, Keyence, Germany). Thread height and pitch of the implants were measured by 3D-picture profile measuring, respectively.
2.3
Scanning electron microscopy (SEM) and stereo-SEM profilometry (SSP)
For qualitative surface analysis, the implants were sputter-coated (SCD 050, Baltec, Germany) by a 20 nm thin Au–Pd layer to prevent charging and investigated in a scanning electron microscope (Leo 1430 SEM, Zeiss, Germany) at 15 kV accelerating voltage and 650× and 5000× magnifications employing a secondary electron detector. To obtain quantitative information about the roughness, stereoscopic pairs of micrographs were used to reconstruct 3D-surface features (stereo-SEM). Secondary electron images were obtained by eucentrically tilting the sample stage about a horizontal x-axis by +6° (right image) vs 0° (left image) at 650×. The stereoscopic reconstruction of digital surface models and the analysis of different roughness parameters were computed using the MeX 5.0 software (Alicona Imaging, Graz, Austria).
2.4
Optical interferometric profilometry (OIP)
On the Au–Pd sputtered implants used before for the SEM analyses, the 3D-surface roughness parameters were likewise evaluated by an optical profiler (Wyko NT1100, Veeco, Tuscon, AZ, USA) operated under the following conditions: Mirau lens (20 × 2 FOV), vertical scanning mode (VSI), 41.6× magnification, tilt correction 50 μm (F50) and 5 μm (F05), high-pass Gaussian Fourier filtering at a resolution of 0.1 nm (z-axis) and 0.2 μm (x, y axis).
2.5
Roughness analysis
The tested implants were analyzed by scanning root part areas of 200 × 100 μm 2 . Areas were selected either within the grooves between the threads of the respective implant screws only ( Fig. 1 a–e) or, if available, at the apex-oriented cutting grooves. The demand for the operator was for the optical method to measure at the same implant sites as chosen for SEM. This was in detail: for NanoTite, Xive, and Mk II TiUnite to measure at 6 different grooves between threads and at 3 areas within cutting grooves, respectively. For SLA, an implant type without cutting grooves, the demand was to measure at 9 different thread groove sites. For both SSP and OIP, raw data have been collected and roughness was separated from waviness at the micro and near-submicron level by applying Gaussian filters with a cut-off-filter length of 50 and 5 μm (F50 and F05), respectively.
