28 research outputs found
Time-dependent parameter of perfusion imaging as independent predictor of clinical outcome in symptomatic carotid artery stenosis
Normalised time-to-peak-distribution curves correlate with cerebral white matter hyperintensities – Could this improve early diagnosis?
Hemodynamic alterations in unilateral chronic middle cerebral artery stenosis patients and the effect of percutaneous transluminal angioplasty and stenting: a perfusion-computed tomography study
Assessment of Cortical Hemodynamics by Multichannel Near-Infrared Spectroscopy in Steno-Occlusive Disease of the Middle Cerebral Artery
Improved Quantification of Cerebral Hemodynamics Using Individualized Time Thresholds for Assessment of Peak Enhancement Parameters Derived from Dynamic Susceptibility Contrast Enhanced Magnetic Resonance Imaging
A quantitative comparison of clinically employed parameters in the assessment of acute cerebral ischemia using dynamic susceptibility contrast magnetic resonance imaging
Purpose: Perfusion magnetic resonance imaging (P-MRI) is part of the mismatch concept employed for therapy decisions in acute ischemic stroke. Using dynamic susceptibility contrast (DSC) MRI the time-to-maximum (Tmax) parameter is quite popular, but its inconsistently defined computation, arterial input function (AIF) selection, and the applied deconvolution method may introduce bias into the assessment. Alternatively, parameter free methods, namely, standardized time-to-peak (stdTTP), zf-score, and standardized-zf (stdZ) are also available, offering consistent calculation procedures without the need of an AIF or deconvolution. Methods: Tmax was compared to stdTTP, zf-, and stdZ to evaluate robustness of infarct volume estimation in 66 patients, using data from two different sites and MR systems (i.e., 1.5T vs. 3T; short TR (= 689 ms) vs. medium TR (= 1,390 ms); bolus dose 0.1 or 0.2 ml/kgBW, respectively). Results: Quality factors (QF) for Tmax were 0.54 ± 0.18 (sensitivity), 0.90 ± 0.06 (specificity), and 0.87 ± 0.05 (accuracy). Though not significantly different, best specificity (0.93 ± 0.05) and accuracy (0.90 ± 0.04) were found for stdTTP with a sensitivity of 0.56 ± 0.17. Other tested parameters performed not significantly worse than Tmax and stdTTP, but absolute values of QFs were slightly lower, except for zf showing the highest sensitivity (0.72 ± 0.16). Accordingly, in ROC-analysis testing the parameter performance to predict the final infarct volume, stdTTP and zf showed the best performance. The odds for stdTTP to obtain the best prediction of the final infarct size, was 6.42 times higher compared to all other parameters (odds-ratio test; p = 2.2*10–16). Conclusion: Based on our results, we suggest to reanalyze data from large cohort studies using the parameters presented here, particularly stdTTP and zf-score, to further increase consistency of perfusion assessment in acute ischemic stroke