Asymptomatic Cerebral Vasoconstriction after Carotid Artery Stenting

BACKGROUND AND PURPOSE

Carotid artery stent placement is widely performed for treatment of carotid stenosis. The purpose of this study is to present our observations on cerebral vasoconstriction in ipsilateral anterior circulation during immediate poststenting angiography in patients with near-total occlusion of the proximal ICA.

MATERIALS AND METHODS

We retrospectively reviewed patient data from December 2008 to December 2018. There were 28 patients with carotid near-total occlusion. Two neuroradiologists reviewed the final cerebral angiographic finding of carotid artery stent placement to evaluate the presence of vasoconstriction or vasodilation.

RESULTS

A total of 28 patients with near-total occlusion (mean ± standard deviation age, 69.0 ± 6.5 years; 92.9% male) were analyzed. Ten patients showed vasoconstriction in the treated territory, and 18 patients did not show vasoconstriction after carotid artery stenting. There were no statistically significant differences in comorbidity, frequency of symptomatic lesions, antiplatelet medication, mean procedure time, and initial NIHSS and baseline modified Rankin scale scores between the 2 groups. However, vasoconstriction is more likely to happen in patients with isolated territory from the contralateral anterior and posterior circulation (66.7% in the isolated territory group and 12.5% in the not-isolated territory group; P < .05). No headache or neurologic deficit was noted in all 10 patients with cerebral vasoconstriction.

CONCLUSIONS

Cerebral vasoconstriction may occur after carotid artery stenting more frequently than expected. It occurs more frequently in patients with near-total occlusion and with isolation of the cerebral circulation. A large-scale study is necessary to assess the clinical implications of cerebral vasoconstriction after carotid artery stenting.

Glioma: Application of histogram analysis of pharmacokinetic parameters from T1-weighted dynamic contrast-enhanced MR imaging to tumor grading

BACKGROUND AND PURPOSE

The usefulness of pharmacokinetic parameters for glioma grading has been reported based on the perfusion data from parts of entire-tumor volumes. However, the perfusion values may not reflect the entire-tumor characteristics. Our aim was to investigate the feasibility of glioma grading by using histogram analyses of pharmacokinetic parameters including the volume transfer constant, extravascular extracellular space volume per unit volume of tissue, and blood plasma volume per unit volume of tissue from T1-weighted dynamic contrast-enhanced perfusion MR imaging.

MATERIALS AND METHODS

Twenty-eight patients (14 men, 14 women; mean age, 49.75 years; age range, 25-72 years) with histopathologically confirmed gliomas (World Health Organization grade II, n = 7; grade III, n = 8; grade IV, n = 13) were examined before surgery or biopsy with conventional MR imaging and T1-weighted dynamic contrast-enhanced perfusion MR imaging at 3T. Volume transfer constant, extravascular extracellular space volume per unit volume of tissue, and blood plasma volume per unit volume of tissue were calculated from the entire-tumor volume. Histogram analyses from these parameters were correlated with glioma grades. The parameters with the best percentile from cumulative histograms were identified by analysis of the area under the curve of the receiver operating characteristic analysis and were compared by using multivariable stepwise logistic regression analysis for distinguishing high- from low-grade gliomas.

RESULTS

All parametric values increased with increasing glioma grade. There were significant differences among the 3 grades in all parameters (P < .01). For the differentiation of high- and low-grade gliomas, the highest area under the curve values were found at the 98th percentile of the volume transfer constant (area under the curve, 0.912; cutoff value, 0.277), the 90th percentile of extravascular extracellular space volume per unit volume of tissue (area under the curve, 0.939; cutoff value, 19.70), and the 84th percentile of blood plasma volume per unit volume of tissue (area under the curve, 0.769; cutoff value, 11.71). The 98th percentile volume transfer constant value was the only variable that could be used to independently differentiate high- and low-grade gliomas in multivariable stepwise logistic regression analysis.

CONCLUSIONS

Histogram analysis of pharmacokinetic parameters from whole-tumor volume data can be a useful method for glioma grading. The 98th percentile value of the volume transfer constant was the most significant measure.