Three-vessel study of cerebral blood flow using phase-contrast magnetic resonance imaging: Effect of physical characteristics

The development of phase-contrast magnetic resonance imaging (P-C MRI) provides a noninvasive method for measurement of volumetric blood flow (VFR). We performed P-C MRI to study the effects of physical characteristics on cerebral blood flow. VFR of the left and right internal carotid arteries and basilar artery were measured using P-C MRI and total cerebral blood flow (tCBF) was calculated by summing up the VFR values in the three vessels. Moreover, we investigated the changes in these blood flows as influenced by age, head size, height, weight, body surface area, and handedness. The blood flows were 142 ± 58 ml/min (mean ± standard deviation) in the basilar artery; and 229 ± 86 ml/min in the left, and 223 ± 58 ml/min in the right internal carotid artery; and tCBF was 617 ± 128 ml/min. Significant increases were observed in head size-related change of VFR in the basilar artery (p = .028) and height-related change of tCBF (p = .045). The other characteristics did not significantly influence any VFR. The results suggest that head size and height may reflect CBF, and that these effects should be considered when changes of CBF are diagnosed. Phase-contrast MRI is useful for a noninvasive and rapid analysis of cerebral VFR and has potential for clinical use.     

Deconvolution with simple extrapolation for improved cerebral blood flow measurement in dynamic susceptibility contrast magnetic resonance imaging during acute ischemic stroke

Magnetic resonance (MR) perfusion imaging is a clinical technique for measuring brain blood flow parameters during stroke and other ischemic events. Ischemia in brain tissue can be difficult to accurately measure or visualize when using MR-derived cerebral blood flow (CBF) maps. The deconvolution techniques used to estimate flow can introduce a mean transit time-dependent bias following application of noise stabilization techniques. The underestimation of the CBF values, greatest in normal tissues, causes a decrease in the image contrast observed in CBF maps between normally perfused and ischemic tissues; resulting in ischemic areas becoming less conspicuous. Through application of the proposed simple extrapolation technique, CBF biases are reduced when missing high-frequency signal components in the MR data removed during deconvolution noise stabilization are restored. The extrapolation approach was compared with other methods and showed a statistically significant increase in image contrast in CBF maps between normal and ischemic tissues for white matter (P<.05) and performed better than most other methods for gray matter. Receiver operator characteristic curve analysis demonstrated that extrapolated CBF maps better-detected penumbral regions. Extrapolated CBF maps provided more accurate CBF estimates in simulations, suggesting that the approach may provide a better prediction of outcome in the absence of treatment.     

Single voxel vascular transport functions of arteries,capillaries and veins; and the associated arterial input function in dynamic susceptibility contrast magnetic resonance brain perfusion imaging

PurposeThe composite vascular transport function of a brain voxel consists of one convolutional component for the arteries, one for the capillaries and one for the veins in the voxel of interest. Here, the goal is to find each of these three convolutional components and the associated arterial input function.Pharmacokinetic modellingThe single voxel vascular transport functions for arteries, capillaries and veins were all modelled as causal exponential functions. Each observed multipass tissue contrast function was as a first approximation modelled as the resulting parametric composite vascular transport function convolved with a nonparametric and voxel specific multipass arterial input function. Subsequently, the residue function was used in the true perfusion equation to optimize the three parameters of the exponential functions.Deconvolution methodsFor each voxel, the parameters of the three exponential functions were estimated by successive iterative blind deconvolutions using versions of the Lucy-Richardson algorithm. The final multipass arterial input function was then computed by nonblind deconvolution using the Lucy-Richardson algorithm and the estimated composite vascular transport function.ResultsSimulations showed that the algorithm worked. The estimated mean transit time of arteries, capillaries and veins of the simulated data agreed with the known input values. For real data, the estimated capillary mean transit times agreed with known values for this parameter. The nonparametric multipass arterial input functions were used to derive the associated map of the arrival time. The arrival time map of a healthy volunteer agreed with known arterial anatomy and physiology.ConclusionClinically important new voxelwise hemodynamic information for arteries, capillaries and veins separately can be estimated using multipass tissue contrast functions and the iterative blind Lucy-Richardson deconvolution algorithm.     

Novel methodology for 3D reconstruction of carotid arteries and plaque characterization based upon magnetic resonance imaging carotid angiography data

In this study, we present a novel methodology that allows reliable segmentation of the magnetic resonance images (MRIs) for accurate fully automated three-dimensional (3D) reconstruction of the carotid arteries and semiautomated characterization of plaque type. Our approach uses active contours to detect the luminal borders in the time-of-flight images and the outer vessel wall borders in the T(1)-weighted images. The methodology incorporates the connecting components theory for the automated identification of the bifurcation region and a knowledge-based algorithm for the accurate characterization of the plaque components. The proposed segmentation method was validated in randomly selected MRI frames analyzed offline by two expert observers. The interobserver variability of the method for the lumen and outer vessel wall was -1.60%±6.70% and 0.56%±6.28%, respectively, while the Williams Index for all metrics was close to unity. The methodology implemented to identify the composition of the plaque was also validated in 591 images acquired from 24 patients. The obtained Cohen's k was 0.68 (0.60-0.76) for lipid plaques, while the time needed to process an MRI sequence for 3D reconstruction was only 30 s. The obtained results indicate that the proposed methodology allows reliable and automated detection of the luminal and vessel wall borders and fast and accurate characterization of plaque type in carotid MRI sequences. These features render the currently presented methodology a useful tool in the clinical and research arena.     

Detection of diminished response to cold pressor test in smokers: Assessment using phase-contrast cine magnetic resonance imaging of the coronary sinus

Purpose

The purposes of this study were to evaluate the reproducibility for measuring the cold pressor test (CPT)-induced myocardial blood flow (MBF) alteration using phase-contrast (PC) cine MRI, and to determine if this approach could detect altered MBF response to CPT in smokers.

Materials and methods

After obtaining informed consent, ten healthy male non-smokers (mean age: 28 ± 5 years) and ten age-matched male smokers (smoking duration ≥ 5 years, mean age: 28 ± 3 years) were examined in this institutional review board approved study. Breath-hold PC cine MR images of the coronary sinus were obtained with a 3 T MR imager with 32 channel coils at rest and during a CPT performed after immersing one foot in ice water. MBF was calculated as coronary sinus flow divided by the left ventricular (LV) mass which was given as a total LV myocardial volume measured on cine MRI multiplied by the specific gravity (1.05 g/mL).

Results

In non-smokers, MBF was 0.86 ± 0.25 mL/min/g at rest, with a significant increase to 1.20 ± 0.36 mL/min/g seen during CPT (percentage change of MBF (?MBF (%)); 39.2% ± 14.4%, p < 0.001). Inter-study reproducibility for ?MBF (%) measurements by different MR technologist was good, as indicated by the intraclass correlation coefficient of 0.93 and reproducibility coefficient of 10.5%. There was no significant difference between smokers and non-smokers for resting MBF (0.85 ± 0.32 mL/min/g, p = 0.91). However, ?MBF (%) in smokers was significantly reduced (-4.0 ± 32.2% vs. 39.2 ± 14.4%, p = 0.011).

Conclusion

PC cine MRI can be used to reproducibly quantify MBF response to CPT and to detect impaired flow response in smokers. This MR approach may be useful for monitoring the sequential change of coronary blood flow in various potentially pathologic conditions and for investigating its relationship with cardiovascular risk.