| Literature DB >> 27089375 |
Andrew Naylor1, Sumedh C Talwalkar2, Ian A Trail3, Thomas J Joyce4.
Abstract
The articulating surfaces of four different sizes of unused pyrolytic carbon proximal interphalangeal prostheses (PIP) were evaluated though measuring several topographical parameters using a white light interferometer: average roughness (Sa); root mean-square roughness (Sq); skewness (Ssk); and kurtosis (Sku). The radii of the articulating surfaces were measured using a coordinate measuring machine, and were found to be: 2.5, 3.3, 4.2 and 4.7 mm for proximal, and 4.0, 5.1, 5.6 and 6.3 mm for medial components. ANOVA was used to assess the relationship between the component radii and each roughness parameter. Sa, Sq and Ssk correlated negatively with radius (p = 0.001, 0.001, 0.023), whilst Sku correlated positively with radius (p = 0.03). Ergo, the surfaces with the largest radii possessed the better topographical characteristics: low roughness, negative skewness, high kurtosis. Conversely, the surfaces with the smallest radii had poorer topographical characteristics.Entities:
Keywords: kurtosis; proximal interphalangeal joint; pyrolytic carbon; roughness parameters; skewness; surface topography
Year: 2016 PMID: 27089375 PMCID: PMC4932466 DOI: 10.3390/jfb7020009
Source DB: PubMed Journal: J Funct Biomater ISSN: 2079-4983
Figure 1The relative sizes of the pyrolytic carbon prostheses evaluated in the study.
Data summary from statistical hypothesis test displaying: 95% confidence intervals; z-scores; and p-values for the respective sample means of S, S, S, and S.
| Parameter | Size | Proximal Component | Medial Component | ||||
|---|---|---|---|---|---|---|---|
| Mean (95% CI) | Mean (95% CI) | ||||||
| Size 10 | 69.2 (63.4–74.8) | 6.52 | 0.00 | 34.9 (25.6–44.1) | −3.20 | 0.00 | |
| Size 20 | 68.1 (62.1–74) | 5.96 | 0.00 | 37.4 (33.9–40.9) | −7.10 | 0.00 | |
| Size 30 | 36.8 (30.8–41.2) | −5.30 | 0.00 | 18.1 (16.4–19.8) | −36.10 | 0.00 | |
| Size 40 | 25.9 (23.6–28.3) | −20.10 | 0.00 | 13 (11.9–14) | −71.10 | 0.00 | |
| Size 10 | 88 (80.7–95.3) | 10.26 | 0.00 | 46.4 (34–58.7) | −5.80 | 0.56 | |
| Size 20 | 87.9 (80.5–95.2) | 10.10 | 0.00 | 47.1 (42.6–51.6) | −1.27 | 0.20 | |
| Size 30 | 46.7 (40.2–53.2) | −0.99 | 0.32 | 23.4 (21.3–25.5) | −24.87 | 0.00 | |
| Size 40 | 33.7 (30.1–36.5) | −11.32 | 0.00 | 17 (15.7–18.3) | −48.77 | 0.00 | |
| Size 10 | −0.036 (−0.149–0.078) | −0.62 | 0.53 | −0.342 (−0.646 to −0.038) | −2.20 | 0.05 | |
| Size 20 | 0.024 (−0.176–0.128) | 0.31 | 0.76 | 0.036 (−0.126 to 0.182) | 0.44 | 0.66 | |
| Size 30 | −0.038 (−0.148–0.072) | −0.68 | 0.50 | −0.222 (−0.486 to 0.046) | −1.62 | 0.10 | |
| Size 40 | −0.43 (−0.685 to −0.175) | −3.31 | 0.00 | −0.62 (−1.08 to −0.161) | −2.65 | 0.01 | |
| Size 10 | 4.65 (4.23–5.06) | 8.20 | 0.00 | 11.86 (7.37–16.34) | 3.87 | 0.00 | |
| Size 20 | 4.77 (4.1–5.44) | 5.210 | 0.00 | 4.16 (3.73–4.59) | 5.340 | 0.00 | |
| Size 30 | 4.16 (3.72–4.59) | 5.310 | 0.00 | 15.61 (8.94–22.28) | 3.710 | 0.00 | |
| Size 40 | 11.4 (7.84–14.97) | 4.620 | 0.00 | 29.74 (15.22–44.26) | 3.610 | 0.00 | |
Figure 2Topographical plot showing a surface with peaks (a) and histogram exhibiting a positively skewed distribution (b), obtained from medial component size 10.
Figure 3Topographical plot showing a surface with valleys (a) and histogram exhibiting a negatively skewed distribution (b), obtained from proximal component size 40.
Figure 4Topographical plot showing a flat surface (a) and histogram exhibiting a uniform Gaussian distribution (b), obtained from medial component size 30.
Figure 5Average roughness linear regression model (a) and root mean-square linear regression model (b).
ANOVA for each respective roughness parameter with respect to prosthesis radius.
| Parameter | Source of Variation | Degrees of Freedom | Sum of Squares | Mean Square | ||
|---|---|---|---|---|---|---|
| Regression | 1 | 2632 | 2632 | 37 | 0.001 | |
| Error | 6 | 426 | 71 | – | – | |
| Total | 7 | 3058 | – | – | – | |
| Regression | 1 | 4303 | 4303 | 39 | 0.001 | |
| Error | 6 | 660 | 110 | – | – | |
| Total | 7 | 4963 | – | – | – | |
| Regression | 1 | 0.215 | 0.215 | 9.1 | 0.023 | |
| Error | 6 | 0.142 | 0.204 | – | – | |
| Total | 7 | 0.356 | – | – | – | |
| Regression | 1 | 311 | 311 | 7.8 | 0.03 | |
| Error | 6 | 243 | 39 | – | – | |
| Total | 7 | 546 | – | – | – |
Figure 6Skewness linear regression model (a) and kurtosis linear regression model (b).
Figure 7A 2D profile plot (a) and histogram (b) taken across a series of valleys demonstrating high 2D kurtosis (R = 27.69) and a negative skewness (R = −3.62).