Arterial Wall Imaging: Evaluation with 16-Section Multidetector CT in Blood Vessel Phantoms and ex Vivo Coronary Arteries

Abstract

To evaluate the diagnostic performance of 16-section multidetector computed tomography (CT) for assessment of plaques in phantoms and ex vivo coronary arteries, with intravascular ultrasonography (US) and optical coherence tomography (OCT) as reference standards. Research protocol was HIPAA compliant and approved by institutional review board, without informed consent required. Blood vessel and lesion composition phantoms and ex vivo coronary arteries were imaged with 16-section CT. Wall areas of phantoms and ex vivo coronary arteries were measured with multidetector CT and intravascular US. Sensitivity and specificity for lipid detection were determined in lesion composition phantoms. CT numbers of blood vessel wall were determined in ex vivo coronary arteries and compared with lesion classification results from OCT. Agreement in dimensional measurements was compared (paired t tests). CT numbers within blood vessel wall of CT cross sections classified as lipid rich, fibrous, and calcified at OCT were compared (Kruskal-Wallis tests). Mean blood vessel wall areas measured with CT and US in phantoms were 9.2 mm(2) +/- 1.8 (standard deviation) and 10.4 mm(2) +/- 3.4 (bias, -1.3 mm(2) +/- 3.1; P < .05), respectively. Mean blood vessel wall areas measured in ex vivo coronary arteries with CT and US were 10.9 mm(2) +/- 4.1 and 9.1 mm(2) +/- 3.1 (bias, 1.8 mm(2) +/- 3.0; P < .001), respectively. Sensitivity and specificity of 93% and 92%, respectively, for identification of lipid-rich lesions were observed in lesion composition phantoms. Mean CT numbers in blood vessel wall of ex vivo coronary arteries identified at OCT as predominantly lipid rich, fibrous, and calcified were 29 HU +/- 43, 101 HU +/- 21, and 135 HU +/- 199, respectively (P < .001). Determination of composition of individual plaques from attenuation values can be more challenging because of overlapping values for different tissue types.