Optimized Hemodynamic Assessment to Predict Stroke Risk in Vertebrobasilar Disease: Analysis From the VERiTAS Study

Abstract

Background Atherosclerotic vertebrobasilar disease is a significant etiology of posterior circulation stroke. The prospective observational VERiTAS (Vertebrobasilar Flow Evaluation and Risk of Transient Ischemic Attack and Stroke) study demonstrated that distal hemodynamic status is a robust predictor of subsequent vertebrobasilar stroke risk. We sought to compare predictive models using thresholds for posterior circulation vessel flows standardized to age and vascular anatomy to optimize risk prediction. Methods and Results VERiTAS enrolled patients with recent vertebrobasilar transient ischemic attack or stroke and ≥50% atherosclerotic stenosis/occlusion in vertebral and/or basilar arteries. Quantitative magnetic resonance angiography measured large-vessel vertebrobasilar territory flow, and patients were designated as low or normal flow based on a prespecified empiric algorithm considering distal territory regional flow and collateral capacity. For the present study, post hoc analysis was performed to generate additional predictive models using age-specific normalized flow measurements. Sensitivity, specificity, and time-to-event analyses were compared between the algorithms. The original prespecified algorithm had 50% sensitivity and 79% specificity for future stroke risk prediction; using a predictive model based on age-normalized flows in the basilar and posterior cerebral arteries, standardized to vascular anatomy, optimized flow status thresholds were identified. The optimized algorithm maintained sensitivity and increased specificity to 84%, while demonstrating a larger and more significant hazard ratio for stroke on time-to-event analysis. Conclusions These results indicate that flow remains a strong predictor of stroke across different predictive models, and suggest that prediction of future stroke risk can be optimized by use of vascular anatomy and age-specific normalized flows.

Keywords: blood flow; magnetic resonance angiography; magnetic resonance imaging; quantitative magnetic resonance angiography; stroke vertebrobasilar disease.

Figure 1. Flow stratification algorithms.

A, The original algorithm for determining a low‐flow vs normal flow state. Flow algorithm for symptomatic VB disease. *In the case of fetal PCA, determination of flow status is as follows. If 1 PCA is fetal, only the flow in nonfetal PCA is considered; if both PCAs are fetal, only flow in the BA is considered (low flow if <40 mL/min). ^¶Additional criteria in borderline cases: ominous BA flow waveform oscillating ≈0, ominous symptom complex (symptoms exacerbated with head position, cannot be on anti‐coagulation/antiplatelets, requires very elevated blood pressure to avert symptoms); flow in nonoccluded proximal BA <40 mL/min. B, The optimized anatomy‐specific and age‐stratified normalizing algorithm for determining a low or normal flow state. BA indicates basilar artery; PCA, posterior cerebral artery; and QMRA, quantitative magnetic resonance angiography. *The PCA anatomy is classified as bilateral fetal PCA, unilateral fetal PCA, or no fetal PCA. ^†The age of patients with no fetal PCA is stratified as 18 to 60 or >60 years old. Each stratification has distinct averages and standard deviations of normal BA and PCA flows (Table 1). ^‡The BA flow Z score is calculated $\frac{(\text{BA flow}-\text{mean normal BA flow})}{\text{standard deviation of the normal BA flow}}$. ^§The PCA flow Z score is calculated as the average of normal configuration PCA Z scores, where PCA Z scores are $\frac{(\text{PCA flow}-\text{mean normal PCA flow})}{\text{standard deviation of the normal PCA flow}}$.

Figure 2. The receiver operating characteristic shows the behavior of the optimized algorithm along the range of possible basilar artery and posterior cerebral artery cutoffs.

The optimum threshold is found at a Youden's J statistic shown as a vertical line, delineated by the 2 asterisks. The prior algorithm is plotted as a singular point, below the receiver operating characteristic of the optimized algorithm, with a smaller Youden's J statistic shown as the vertical line below this point.

Figure 3. Cumulative probabilities of stroke.

A, The log‐rank analysis of event occurrence with the original algorithm. B, The optimized algorithm distinguishes the low‐ and high‐flow groups in a more statistically significant fashion.