Carotid Artery Wall Imaging: Perspective and Guidelines from the ASNR Vessel Wall Imaging Study Group and Expert Consensus Recommendations of the American Society of Neuroradiology

SUMMARY: Identification of carotid artery atherosclerosis is conventionally based on measurements of luminal stenosis and surface irregularities using in vivo imaging techniques including sonography, CT and MR angiography, and digital subtraction angiography. However, histopathologic studies demonstrate considerable differences between plaques with identical degrees of stenosis and indicate that certain plaque features are associated with increased risk for ischemic events. The ability to look beyond the lumen using highly developed vessel wall imaging methods to identify plaque vulnerable to disruption has prompted an active debate as to whether a paradigm shift is needed to move away from relying on measurements of luminal stenosis for gauging the risk of ischemic injury. Further evaluation in randomized clinical trials will help to better define the exact role of plaque imaging in clinical decision-making. However, current carotid vessel wall imaging techniques can be informative. The goal of this article is to present the perspective of the ASNR Vessel Wall Imaging Study Group as it relates to the current status of arterial wall imaging in carotid artery disease

High-resolution intravascular magnetic resonance quantification of atherosclerotic plaque at 3T

<p>Abstract</p> <p>Background</p> <p>The thickness of fibrous caps (FCT) of atherosclerotic lesions is a critical factor affecting plaque vulnerability to rupture. This study tests whether 3 Tesla high-resolution intravascular cardiovascular magnetic resonance (CMR) employing tiny loopless detectors can identify lesions and accurately measure FCT in human arterial specimens, and whether such an approach is feasible <it>in vivo </it>using animal models.</p> <p>Methods</p> <p>Receive-only 2.2 mm and 0.8 mm diameter intravascular loopless CMR detectors were fabricated for a clinical 3 Tesla MR scanner, and the absolute signal-to-noise ratio determined. The detectors were applied in a two-step protocol comprised of CMR angiography to identify atherosclerotic lesions, followed by high-resolution CMR to characterize FCT, lesion size, and/or vessel wall thickness. The protocol was applied in fresh human iliac and carotid artery specimens in a human-equivalent saline bath. Mean FCT measured by 80 μm intravascular CMR was compared with histology of the same sections. <it>In vivo </it>studies compared aortic wall thickness and plaque size in healthy and hyperlipidemic rabbit models, with post-mortem histology.</p> <p>Results</p> <p>Histology confirmed plaques in human specimens, with calcifications appearing as signal voids. Mean FCT agreed with histological measurements within 13% on average (correlation coefficient, <it>R </it>= 0.98; Bland-Altman analysis, -1.3 ± 68.9 μm). <it>In vivo </it>aortic wall and plaque size measured by 80 μm intravascular CMR agreed with histology.</p> <p>Conclusion</p> <p>Intravascular 3T CMR with loopless detectors can both locate atherosclerotic lesions, and accurately measure FCT at high-resolution in a strategy that appears feasible <it>in vivo</it>. The approach shows promise for quantifying vulnerable plaque for evaluating experimental therapies.</p

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

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/∞) 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