Simultaneous Hemodynamic and Structural Imaging of Ischemic Stroke With Magnetic Resonance Fingerprinting Arterial Spin Labeling.

BACKGROUND: Perfusion and structural imaging play an important role in ischemic stroke. Magnetic resonance fingerprinting (MRF) arterial spin labeling (ASL) is a novel noninvasive method of ASL perfusion that allows simultaneous estimation of cerebral blood flow (CBF), bolus arrival time (BAT), and tissue T1 map in a single scan of <4 minutes. Here, we evaluated the utility of MRF-ASL in patients with ischemic stroke in terms of detecting hemodynamic and structural damage and predicting neurological deficits and disability. METHODS: A total of 34 patients were scanned on 3T magnetic resonance imaging. MRF-ASL, standard single-delay pseudo-continuous ASL, T2-weighted, and diffusion magnetic resonance imaging were performed. Regions of interest of lesion and contralateral normal tissues were manually delineated. CBF (with 2 different compartmental models), BAT, and tissue T1 parameters were quantified. Cross-sectional linear regression analyses were performed to examine the relationship between MRF-ASL parameters and National Institutes of Health Stroke Scale (NIHSS) and modified Rankin Scale. Receiver operating characteristic analyses were performed to determine the utility of MRF-ASL in the classification of stroke lesion voxels. RESULTS: MRF-ASL derived parameters revealed a significant difference between stroke lesion and contralateral normal regions of interest, in that lesion regions manifested a lower CBF1-compartment (P<0.001), lower CBF2-compartment (P<0.001), longer BAT (P=0.002), and longer T1 (P<0.001) compared with normal regions of interest. NIHSS scores at acute stage revealed a strong association with lesion-normal differences in CBF1-compartment,diff (ß=-0.11, P=0.008), CBF2-compartment,diff (ß=-0.16, P=0.003), and T1,diff (ß=0.008, P=0.001). MRF-ASL parameters were also predictive of NIHSS score and modified Rankin Scale scale measured at a later stage, although the degree of the associations was weaker. These associations tended to be even stronger when the MRF-ASL data were acquired at the acute/subacute stage. Compared with standard pseudo-continuous ASL, the multiparametric capability of MRF-ASL yielded higher area under curve values in the receiver operating characteristic analyses of stroke voxel classifications. CONCLUSIONS: MRF-ASL may provide a new approach for quantitative hemodynamic and structural imaging in ischemic stroke.

Predictors of clinical outcome in pediatric oligodendroglioma: meta-analysis of individual patient data and multiple imputation.

OBJECTIVE Oligodendroglioma is a rare primary CNS neoplasm in the pediatric population, and only a limited number of studies in the literature have characterized this entity. Existing studies are limited by small sample sizes and discrepant interstudy findings in identified prognostic factors. In the present study, the authors aimed to increase the statistical power in evaluating for potential prognostic factors of pediatric oligodendrogliomas and sought to reconcile the discrepant findings present among existing studies by performing an individual-patient-data (IPD) meta-analysis and using multiple imputation to address data not directly available from existing studies. METHODS A systematic search was performed, and all studies found to be related to pediatric oligodendrogliomas and associated outcomes were screened for inclusion. Each study was searched for specific demographic and clinical characteristics of each patient and the duration of event-free survival (EFS) and overall survival (OS). Given that certain demographic and clinical information of each patient was not available within all studies, a multivariable imputation via chained equations model was used to impute missing data after the mechanism of missing data was determined. The primary end points of interest were hazard ratios for EFS and OS, as calculated by the Cox proportional-hazards model. Both univariate and multivariate analyses were performed. The multivariate model was adjusted for age, sex, tumor grade, mixed pathologies, extent of resection, chemotherapy, radiation therapy, tumor location, and initial presentation. A p value of less than 0.05 was considered statistically significant. RESULTS A systematic search identified 24 studies with both time-to-event and IPD characteristics available, and a total of 237 individual cases were available for analysis. A median of 19.4% of the values among clinical, demographic, and outcome variables in the compiled 237 cases were missing. Multivariate Cox regression analysis revealed subtotal resection (p = 0.007 [EFS] and 0.043 [OS]), initial presentation of headache (p = 0.006 [EFS] and 0.004 [OS]), mixed pathologies (p = 0.005 [EFS] and 0.049 [OS]), and location of the tumor in the parietal lobe (p = 0.044 [EFS] and 0.030 [OS]) to be significant predictors of tumor progression or recurrence and death. CONCLUSIONS The use of IPD meta-analysis provides a valuable means for increasing statistical power in investigations of disease entities with a very low incidence. Missing data are common in research, and multiple imputation is a flexible and valid approach for addressing this issue, when it is used conscientiously. Undergoing subtotal resection, having a parietal tumor, having tumors with mixed pathologies, and suffering headaches at the time of diagnosis portended a poorer prognosis in pediatric patients with oligodendroglioma.