Influence of convolution filtering on coronary plaque attenuation values: observations in an ex vivo model of multislice computed tomography coronary angiography

Abstract

Attenuation variability (measured in Hounsfield Units, HU) of human coronary plaques using multislice computed tomography (MSCT) was evaluated in an ex vivo model with increasing convolution kernels. MSCT was performed in seven ex vivo left coronary arteries sunk into oil followingthe instillation of saline (1/infinity) and a 1/50 solution of contrast material (400 mgI/ml iomeprol). Scan parameters were: slices/collimation, 16/0.75 mm; rotation time, 375 ms. Four convolution kernels were used: b30f-smooth, b36f-medium smooth, b46f-medium and b60f-sharp. An experienced radiologist scored for the presence of plaques and measured the attenuation in lumen, calcified and noncalcified plaques and the surrounding oil. The results were compared by the ANOVA test and correlated with Pearson's test. The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were calculated. The mean attenuation values were significantly different between the four filters (p < 0.0001) in each structure with both solutions. After clustering for the filter, all of the noncalcified plaque values (20.8 +/- 39.1, 14.2 +/- 35.8, 14.0 +/- 32.0, 3.2 +/- 32.4 HU with saline; 74.7 +/- 66.6, 68.2 +/- 63.3, 66.3 +/- 66.5, 48.5 +/- 60.0 HU in contrast solution) were significantly different, with the exception of the pair b36f-b46f, for which a moderate-high correlation was generally found. Improved SNRs and CNRs were achieved by b30f and b46f. The use of different convolution filters significantly modifief the attenuation values, while sharper filtering increased the calcified plaque attenuation and reduced the noncalcified plaque attenuation.

Fig. 1

Example of proximal left coronary artery specimen. CX Left circumflex, LAD left anterior descending artery, LM left main coronary artery

Fig. 2

Mean attenuation of the four structures in the two solutions (e.g. saline and contrast) with increasing convolution filters. Whereas the convolution filter does not significantly affect the attenuation values of the lumen and the surrounding, sharper filters decrease the attenuation of the noncalcified plaque and, conversely, increase the attenuation of the calcified plaque with both solutions

Fig. 3

The SNR values appear to have a common trend with increasing convolution filtering and both solutions (e. g. saline and contrast). However, the best SNR is achieved with b30 and b46 filters. Noncalcified plaque values follow the lumen values, while the surrounding and the calcified plaque patterns are similar

Fig. 4

Example of plaque with increasing filtering using a saline and contrast solution