Quantification and characterization of carotid calcium with multi-detector CT-angiography.

Eur J Vasc Endovasc Surg

Department of Vascular Surgery, Universidad Autonoma de Barcelona, Hospital Universitario de Mar, Passeig Marítim 27-29, 0803 Barcelona, Spain.

Published: November 2006

Objective: The aim of this study was to assess the accuracy of CT-angiography for identification and measurement of calcification of carotid atherosclerotic plaques and to characterise the content and distribution pattern of mineral calcium (hydroxyapatite, Ca) in carotid bifurcations and investigate its relationship with neurological symptoms.

Methods: Twenty-six patients with ICA stenosis > 60% (13 symptomatic, 13 asymptomatic) were selected for study. Ca was estimated from the weight of the ashed remnants of carotid endarterectomy (CEA) specimens in 11 patients. Calcium content (calcification volume (mm3),CV), and average calcium density (Hounsfield units (HU),CD), were determined by CT-angiography. The distribution pattern of calcium within the lesion (base (posterior), shoulder or luminal surface) was assessed in all cases.

Results: CT-derived estimation of CV and Ca mass (modified Agatston Score, (mAS) = CV x CD) showed a good correlation with its direct measurement in CEA specimens (r = 0.911 and 0.993 respectively, p < 0,005). Asymptomatic patients with ICA stenosis > 60% showed statistically significant higher content of Ca than those who were symptomatic (mAS: 122.6 +/- 138.0 HU mm3 vs 42.8 +/- 59.1 HU mm3, p = 0.04). Calcification on the surface of the plaque was observed more commonly in asymptomatic patients (9/12 vs 3/15, p = 0.006). Non-calcified or plaques with posterior calcification were 12 times more likely to be symptomatic (OR: 12, 95%CI 1.5-91.1, p = 0.021).

Conclusions: CT-angiography permits the reliable quantification of calcification of carotid plaques. A lower content of calcium in carotid plaques, as well as its distribution in the base of the lesion, was associated with a greater prevalence of neurological symptoms. These parameters may be useful to identify those patients at higher risk of stroke.

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