Quantification of hepatic blood flow using a high-resolution phase-contrast MRI sequence with compressed sensing acceleration.

OBJECTIVE. The objective of our study was to evaluate the performance of a high-spatial-resolution 2D phase-contrast (PC) MRI technique accelerated with compressed sensing for portal vein (PV) and hepatic artery (HA) flow quantification in comparison with a standard PC MRI sequence. SUBJECTS AND METHODS. In this prospective study, two PC MRI sequences were compared, one with parallel imaging acceleration and low spatial resolution (generalized autocalibrating partial parallel acquisition [GRAPPA]) and one with compressed sensing acceleration and high spatial resolution (sparse). Seventy-six patients were assessed, including 37 patients with cirrhosis. Two observers evaluated PC image quality. Quantitative analyses yielded a mean velocity, flow, and vessel area for the PV and HA and an arterial fraction. The PC techniques were compared using the paired Wilcoxon test and Bland-Altman statistics. The sensitivity of the flow parameters to the severity of cirrhosis was also assessed. RESULTS. Vessel delineation was significantly improved using the PC sparse sequence (p < 0.034). For both in vitro and in vivo measurements, PC sparse yielded lower estimates for vessel area and flow, and larger differences between PC GRAPPA and PC sparse were observed in the HA. PV velocity and flow were significantly lower in patients with cirrhosis on both PC sparse (p < 0.001 and p = 0.042, respectively) and PC GRAPPA (p < 0.001 and p = 0.005, respectively). PV velocity correlated negatively with Child-Pugh class (r = -0.50, p < 0.001), whereas the arterial fraction measured with PC sparse was higher in patients with Child-Pugh class B or C disease than in those with Child-Pugh class A disease, with a trend toward significance (p = 0.055). CONCLUSION. A high-spatial-resolution highly accelerated compressed sensing technique (PC sparse) allows total hepatic blood flow measurements obtained in 1 breath-hold, provides improved delineation of the hepatic vessels compared with a standard PC MRI sequence (GRAPPA), and can potentially be used for the noninvasive assessment of liver cirrhosis.

A multi-methodological MR resting state network analysis to assess the changes in brain physiology of children with ADHD.

The purpose of this work was to highlight the neurological differences between the MR resting state networks of a group of children with ADHD (pre-treatment) and an age-matched healthy group. Results were obtained using different image analysis techniques. A sample of n = 46 children with ages between 6 and 12 years were included in this study (23 per cohort). Resting state image analysis was performed using ReHo, ALFF and ICA techniques. ReHo and ICA represent connectivity analyses calculated with different mathematical approaches. ALFF represents an indirect measurement of brain activity. The ReHo and ICA analyses suggested differences between the two groups, while the ALFF analysis did not. The ReHo and ALFF analyses presented differences with respect to the results previously reported in the literature. ICA analysis showed that the same resting state networks that appear in healthy volunteers of adult age were obtained for both groups. In contrast, these networks were not identical when comparing the healthy and ADHD groups. These differences affected areas for all the networks except the Right Memory Function network. All techniques employed in this study were used to monitor different cerebral regions which participate in the phenomenological characterization of ADHD patients when compared to healthy controls. Results from our three analyses indicated that the cerebellum and mid-frontal lobe bilaterally for ReHo, the executive function regions in ICA, and the precuneus, cuneus and the clacarine fissure for ALFF, were the "hubs" in which the main inter-group differences were found. These results do not just help to explain the physiology underlying the disorder but open the door to future uses of these methodologies to monitor and evaluate patients with ADHD.