Eighteen images of carotid plaques producing stenosis greater than 50% were included in this study. These were obtained from consecutive asymptomatic patients, participants of the Asymptomatic Carotid Stenosis and Risk of Stroke (ACSRS) multicenter natural history study [18]. Stenosis severity was estimated with velocity ratios (European Carotid Surgery Trial – ECST – method), as previously described [19], using an ATL HDI 3000 scanner (Philips Medical Systems, Bothell, WA, USA). A linear post-processing curve was used during carotid scanning, B-mode and colour-coded still images (Figures 1 and 2) were stored on magneto-optical disks as Tagged Image File Format (TIFF) files [resolution of 576 pixels (height) × 768 pixels (width)]; the same still (frozen) B-mode images were zoomed off-line using the zoom feature of the scanner (zoom factor of 1.3, default of the ultrasound scanner) and also stored on the magneto-optical disk. B-mode images were 8-bit i.e. they had 256 (range 0–255) shades of grey. All digital (unzoomed and zoomed) images were recorded using a standardised protocol [7, 10] and subsequently transferred to a PC and normalised for brightness, using blood and arterial adventitia as reference points, as previously described [7], using commercially available software (Adobe ® Photoshop version 5.5, Adobe Systems Inc., Palo Alto, CA, USA). Normalisation (linear scaling) of the image was performed with the "curves" option of the software so that in the secondary image the grey scale median (GSM) of blood is 0 to 5 and that of the adventitia is 185 to 195. To reduce variability, a single GSM measurement of reference points (adventitia and blood) was used for the process of normalisation of both the unzoomed and zoomed images. Subsequently, the normalised resolution, i.e. the number of pixels per cm of image depth (using the image depth scale) was calculated. Although in some of the images, due to deeply situated carotid arteries, image depth was increased and therefore normalised resolution decreased, it was realised that the zoomed image had invariably increased resolution, 1.3 times more than the unzoomed image. The original B-mode images were subsequently interpolated (resampled) to increase their pixel resolution 1.3 times, to match the zoom factor of the scanner and therefore simulate the zoom process of the scanner. This resolution standardisation was achieved by using the image size (resampling) feature of the Adobe ® Photoshop software (version 5.5). The bilinear and bicubic interpolation methods (Appendix I) were used to resample the images. With the aid of the colour-coded image, the region of interest (carotid plaques) of the original, the zoomed and two resampled images (all grey-scale or B-mode) for each case were outlined and texture features were calculated. Texture analysis of the plaque outlines was performed with a custom-made computer program (Figure 3) and a MATLAB platform (The MathWorks, Inc, Natick, Mass, USA); the program also counts the number of pixels included in the plaque outline. Results were saved by downloading them to a text file, which can be imported by most statistical packages. Textural features calculated included:
A. Histogram measures
Percentage of pixels below grey level 30 (PP < 30) and 50 (PP <50).
Percentage of pixels of each of the 10 contours of the 0–255 grey level spectrum (PPC1-PPC10), the first 2 contours (grey level 0–51) analysed further into 5 sub-contours (PPCS1-PPCS5). These are novel features described by the authors. PPC1 is the percentage of image pixels having a grey level between 0–26, PPCS1 is the percentage of image pixels having a grey level between 0–10, ect.
B. First order grey level parameters [20, 21]
Mean grey level, variance, median (GSM), mode, kurtosis, skewness, energy, entropy.
C. Second order (texture) statistics
1. The Spatial Gray Level Dependence Matrices (SGLDM) algorithm, known also as co-occurrence matrix method [22]. We used an interpixel distance (d) of 1 and an average angle measure calculated by averaging the values from the measures calculated at angles 0, 45, 90 and 135, as previously described [12, 23, 24]. The following features were calculated: angular second moment (ASM), contrast, correlation, variance (sum of squares), inverse difference moment (IDM), sum average, sum variance, sum entropy, entropy, difference variance, difference entropy, information measures of correlation-1 and -2 (InM1 and InM2).
2. Gray level difference statistics (GLDS) [25]: Entropy, contrast, mean, angular second moment – Homogeneity, energy.
3. Gray level run length statistics [26]: Short run emphasis (SRE), grey level distribution (GLD), run length distribution (RLD), long run emphasis (LRE), run percentage (RP).
4. Radial and angular sum of the Fourier power spectrum (FPS) were calculated [25].
Statistics
Because of the small sample size (<50), the Shapiro-Wilk test was used to test the results for normal distribution; because some of them were not normally distributed, the Wilcoxon signed ranks test was used to test the difference between unzoomed and zoomed images.
The results were expressed as median and interquartile range (IQR). SPSS for Windows, version 11.5 (SPSS Inc., Chicago, IL, USA), was the statistical package used for statistical analysis. P values of 0.05 or less were considered statistically significant.