title: 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.
authors.affiliation: Department of Radiology, Erasmus Medical Center, Rotterdam, The Netherlands. filippocademartiri@hotmail.com
authors.forename: Filippo
authors.initials: F
authors.lastname: Cademartiri
authors.forename: Ludovico
authors.initials: L
authors.lastname: La Grutta
authors.forename: Giuseppe
authors.initials: G
authors.lastname: Runza
authors.forename: Alessandro
authors.initials: A
authors.lastname: Palumbo
authors.forename: Erica
authors.initials: E
authors.lastname: Maffei
authors.forename: Nico R A
authors.initials: NR
authors.lastname: Mollet
authors.forename: Tommaso Vincenzo
authors.initials: TV
authors.lastname: Bartolotta
authors.forename: Pamela
authors.initials: P
authors.lastname: Somers
authors.forename: Michiel
authors.initials: M
authors.lastname: Knaapen
authors.forename: Stefan
authors.initials: S
authors.lastname: Verheye
authors.forename: Massimo
authors.initials: M
authors.lastname: Midiri
authors.forename: Ronald
authors.initials: R
authors.lastname: Hamers
authors.forename: Nico
authors.initials: N
authors.lastname: Bruining
mesh_terms: D000368:Aged; D003287:Contrast Media; D017023:Coronary Angiography; D003324:Coronary Artery Disease / Q000000981:diagnostic imaging*; D005260:Female; D006801:Humans; D007089:Image Enhancement; D007091:Image Processing, Computer-Assisted; D066298:In Vitro Techniques; D007479:Iopamidol / Q000031:analogs & derivatives; D008297:Male; D008875:Middle Aged; D008955:Models, Cardiovascular; D017202:Myocardial Ischemia / Q000000981:diagnostic imaging*; D012680:Sensitivity and Specificity; D036542:Tomography, Spiral Computed
chemical_list: D003287:Contrast Media; C057937:iomeprol; D007479:Iopamidol