Quantitative evaluation of CTP derived time-density alterations versus CTP for collateral status prediction with stroke.

BACKGROUND AND OBJECTIVES: Collateral status is a pivotal determinant of clinical outcomes in acute ischemic stroke (AIS); however, its evaluation can be challenging. We investigated the predictive value of CT perfusion (CTP) derived time and density alterations versus CTP for collateral status prediction in AIS. METHODS: Consecutive patients with anterior circulation occlusion within 24 h were retrospectively included. Time-density curves of the CTP specified ischemic core, penumbra, and the corresponding contralateral unaffected brain were obtained. The collateral status was dichotomised into robust (4-5 scores) and poor (0-3 scores) using multiphase collateral scoring, as described by Menon et al.. Receiver operating characteristic curves and multivariable regression analysis were performed to assess the predictive ability of CTP-designated tissue time and density alterations, CTP for robust collaterals, and favourable outcomes (mRS score of 0-2 at 90 days). RESULTS: One-hundred patients (median age, 68 years; interquartile range, 57-80 years; 61 men) were included. A smaller ischemic core, shorter peak time delay, lower peak density decrease, lower cerebral blood volume ratio, and cerebral blood flow ratio in the CTP specified ischemic core were significantly associated with robust collaterals (PFDR ≤ 0.004). The peak time delay demonstrated the highest diagnostic value (AUC, 0.74; P < 0.001) with 66.7 % sensitivity and 73.7 % specificity. Furthermore, the peak time delay of less than 8.5 s was an independent predictor of robust collaterals and favourable clinical outcomes. CONCLUSIONS: Robust collateral status was significantly associated with the peak time delay in the ischemic core. It is a promising image marker for predicting collateral status and functional outcomes in AIS.

Comparative analysis of the diffusion kurtosis imaging and diffusion tensor imaging in grading gliomas, predicting tumour cell proliferation and IDH-1 gene mutation status.

INTRODUCTION: Few studies have applied diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) for the comprehensive assessment of gliomas [tumour grade, isocitrate dehydrogenase-1 (IDH-1) mutation status and tumour proliferation rate (Ki-67)]. This study describes the efficacy of DKI and DTI to comprehensively evaluate gliomas, compares their results. METHODS: Fifty-two patients (18 females; median age, 47.5 years) with pathologically proved gliomas were prospectively included. All cases underwent DKI examination. DKI (mean kurtosis: MK, axial kurtosis: Ka, radial kurtosis: Kr) and DTI (mean diffusivity: MD, fractional anisotropy: FA) maps of each metric was derived. Three ROIs were manually drawn. RESULTS: MK, Ka, Kr and FA were significantly higher in HGGs than in LGGs, whereas MD was significantly lower in HGGs than in LGGs (P < 0.01). ROC analysis demonstrated that MK (specificity: 100% sensitivity: 79%) and Ka (specificity: 96% sensitivity: 82%) had the same and highest (AUC: 0.93) diagnostic value. Moreover, MK, Ka, and Kr were significantly higher in grade III than II gliomas (P ≦ 0.01). Further, DKI and DTI can significantly identify IDH-1 mutation status (P ≦ 0.03). Ka (sensitivity: 74%, specificity: 75%, AUC: 0.72) showed the highest diagnostic value. In addition, DKI metrics and MD showed significant correlations with Ki-67 (P ≦ 0.01) and Ka had the highest correlation coefficient (rs = 0.72). CONCLUSIONS: Compared with DTI, DKI has great advantages for the comprehensive assessment of gliomas. Ka might serve as a promising imaging index in predicting glioma grading, tumour cell proliferation rate and IDH-1 gene mutation status.