RESUMO
BACKGROUND AND PURPOSE: MR imaging-detected carotid intraplaque hemorrhage indicates vulnerable plaque with high stroke risk. Angiotensin II stimulates intraplaque hemorrhage in animal models, and the angiotensin system is highly regulated by vitamin D. Our purpose was to determine whether low vitamin D levels predict carotid intraplaque hemorrhage in humans. MATERIALS AND METHODS: In this cross-sectional study, 65 patients with carotid disease underwent carotid MR imaging and blood draw. Systemic clinical confounders and local lumen imaging markers were recorded. To determine the association of low vitamin D levels with MR imaging detected intraplaque hemorrhage, we performed multivariable Poisson regression by using generalized estimating equations to account for up to 2 carotid arteries per patient and backward elimination of confounders. MR imaging detected intraplaque hemorrhage volume was also correlated with vitamin D levels and maximum plaque thickness. Thirty-five patients underwent carotid endarterectomy, and histology-detected intraplaque hemorrhage was correlated with vitamin D levels and total plaque area. RESULTS: Low vitamin D levels (<30 ng/mL, prevalence ratio = 2.05, P = .03) were a significant predictor of MR imaging detected intraplaque hemorrhage, along with plaque thickness (prevalence ratio = 1.40, P < .001). MR imaging detected intraplaque hemorrhage volume linearly correlated with plaque thickness (partial r = 0.45, P < .001) and low vitamin D levels (partial r = 0.26, P = .003). Additionally, histology-detected intraplaque hemorrhage area linearly correlated with plaque area (partial r = 0.46, P < .001) and low vitamin D levels (partial r = 0.22, P = .03). The association of intraplaque hemorrhage volume with low vitamin D levels was also higher with ischemic stroke. CONCLUSIONS: Low vitamin D levels and plaque thickness predict carotid intraplaque hemorrhage and outperform lumen markers of vulnerable plaque. This research demonstrates a significant link between low vitamin D levels and carotid intraplaque hemorrhage.
RESUMO
BACKGROUND AND PURPOSE: MR imaging detects intraplaque hemorrhage with high accuracy by using the magnetization-prepared rapid acquisition of gradient echo sequence. Still, MR imaging is not readily available for all patients, and many undergo CTA instead. Our goal was to determine essential clinical and lumen imaging predictors of intraplaque hemorrhage, as indicators of its presence and clues to its pathogenesis. MATERIALS AND METHODS: In this retrospective cross-sectional study, patients undergoing stroke work-up with MR imaging/MRA underwent carotid intraplaque hemorrhage imaging. We analyzed 726 carotid plaques, excluding vessels with non-carotid stroke sources (n = 420), occlusions (n = 7), or near-occlusions (n = 3). Potential carotid imaging predictors of intraplaque hemorrhage included percentage diameter and millimeter stenosis, plaque thickness, ulceration, and intraluminal thrombus. Clinical predictors were recorded, and a multivariable logistic regression model was fitted. Backward elimination was used to determine essential intraplaque hemorrhage predictors with a thresholded 2-sided P < .10. Receiver operating characteristic analysis was also performed. RESULTS: Predictors of carotid intraplaque hemorrhage included plaque thickness (OR = 2.20, P < .001), millimeter stenosis (OR = 0.46, P < .001), ulceration (OR = 4.25, P = .020), age (OR = 1.11, P = .001), and male sex (OR = 3.23, P = .077). The final model discriminatory value was excellent (area under the curve = 0.932). This was significantly higher than models using only plaque thickness (area under the curve = 0.881), millimeter stenosis (area under the curve = 0.830), or ulceration (area under the curve= 0.715, P < .001). CONCLUSIONS: Optimal discrimination of carotid intraplaque hemorrhage requires information on plaque thickness, millimeter stenosis, ulceration, age, and male sex. These factors predict intraplaque hemorrhage with high discriminatory power and may provide clues to the pathogenesis of intraplaque hemorrhage. This model could be used to predict the presence of intraplaque hemorrhage when MR imaging is contraindicated.
