title: Effect of black blood MR image quality on vessel wall segmentation.
abstract: Black blood MRI has become a popular technique for measuring arterial wall area as an indicator of plaque size. Computer-assisted techniques for segmenting vessel boundaries have been developed to increase measurement precision. In this study, the carotid arteries of four normal subjects were imaged at seven different fields of view (FOVs), keeping all other imaging parameters fixed, to determine whether spatial resolution could be increased at the expense of image quality without sacrificing precision. Wall areas were measured via computer-assisted segmentation of the vessel boundaries performed repeatedly by two operators. Analysis of variance (ANOVA) demonstrated that the variability of wall area measurements was below 1.5 mm(2) for in-plane spatial resolutions between 0.22 mm and 0.37 mm. An inverse relationship between operator variability and the signal difference-to-noise ratio (SDNR) demonstrated that semi-automatic segmentation of the wall boundaries was robust for SDNR >3, defining a criterion above which subjective image quality can be degraded without an appreciable loss of information content. Our study also suggested that spatial resolutions higher than 0.3 mm may be required to quantify normal wall areas to within 10% accuracy, but that the reduced SNR associated with the higher resolution may be tolerated by semi-automated wall segmentation without an appreciable loss of precision.
authors.affiliation: Imaging Research Labs, John P. Robarts Research Institute, University of Western Ontario, London, Canada.
authors.forename: J B
authors.initials: JB
authors.lastname: Thomas
authors.forename: B K
authors.initials: BK
authors.lastname: Rutt
authors.forename: H M
authors.initials: HM
authors.lastname: Ladak
authors.forename: D A
authors.initials: DA
authors.lastname: Steinman
mesh_terms: D000328:Adult; D000465:Algorithms; D000704:Analysis of Variance; D001161:Arteriosclerosis / Q000175:diagnosis; D001769:Blood; D002339:Carotid Arteries / Q000033:anatomy & histology*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male