Endovascular thrombectomy for ischemic stroke 6 to 16 hours after a patient was last known to be well plus standard medical therapy resulted in better functional outcomes than standard medical therapy alone among patients with proximal middle-cerebral-artery or internal-carotid-artery occlusion and a region of tissue that was ischemic but not yet infarcted. (Funded by the National Institute of Neurological Disorders and Stroke; DEFUSE 3 ClinicalTrials.gov number, NCT02586415 .).

This article provides a summary statement of recommended implementations of arterial spin labeling (ASL) for clinical applications. It is a consensus of the ISMRM Perfusion Study Group and the European ‘ASL in Dementia’ consortium, both of whom met to reach this consensus in October 2012 in Amsterdam. Although ASL continues to undergo rapid technical development, we believe that current ASL methods are robust and ready to provide useful clinical information, and that a consensus statement on recommended implementations will help the clinical community to adopt a standardized approach. In this article we describe the major considerations and tradeoffs in implementing an ASL protocol, and provide specific recommendations for a standard approach. Our conclusions are that, as an optimal default implementation we recommend: pseudo-continuous labeling, background suppression, a segmented 3D readout without vascular crushing gradients, and calculation and presentation of both label/control difference images and cerebral blood flow in absolute units using a simplified model.

Background It is uncertain if endovascular stroke therapy leads to improved clinical outcomes due to a paucity of data from randomized placebo-controlled trials. The aim of this study was to determine if MRI can be used to identify patients who are most likely to benefit from endovascular reperfusion. Methods Consecutive patients, scheduled to undergo endovascular therapy within 12 hours of stroke onset, were enrolled in a multi-center prospective cohort study. Aided by an automated image analysis software program, investigators interpreted the baseline MRI. They determined, prior to endovascular treatment, if the patient had an MRI profile (Target Mismatch) that suggested salvageable tissue was present. Reperfusion was assessed on an early follow-up MRI and defined as a >50% reduction in the volume of the baseline perfusion lesion. A favorable clinical response was defined as a ≥8 point improvement on the NIH Stroke Scale (NIHSS) between baseline and day 30 or an NIHSS score of 0–1 at 30 days. Findings Following endovascular therapy reperfusion occurred in 46 of 78 (59%) Target Mismatch patients and in 12 of 21 (57%) No Target Mismatch patients. The adjusted odds ratio for favorable clinical response associated with reperfusion was 8·5 (95% CI 2·6 – 28) in the Target Mismatch group and 0·2 (95% CI 0·0 – 1·6) in the No Target Mismatch group (p=0·003 for difference between odds ratios). Reperfusion was associated with an increased odds of good functional outcome at 90 days (OR is 5.2, 95% CI 1.4–19) and attenuation of infarct growth at 5 days (30 ml of median growth with reperfusion vs. 73 ml without reperfusion, p=0·01) in the Target Mismatch group but not in patients without Target Mismatch. Interpretation Target Mismatch patients who achieved early reperfusion following endovascular stroke therapy had more favorable clinical outcomes and less infarct growth. No association between reperfusion and favorable outcomes was present in patients without Target Mismatch. These data support a randomized controlled trial of endovascular treatment in patients with the Target Mismatch profile.

This review provides a summary statement of recommended implementations of arterial spin labeling (ASL) for clinical applications. It is a consensus of the ISMRM Perfusion Study Group and the European ASL in Dementia consortium, both of whom met to reach this consensus in October 2012 in Amsterdam. Although ASL continues to undergo rapid technical development, we believe that current ASL methods are robust and ready to provide useful clinical information, and that a consensus statement on recommended implementations will help the clinical community to adopt a standardized approach. In this review, we describe the major considerations and trade‐offs in implementing an ASL protocol and provide specific recommendations for a standard approach. Our conclusion is that as an optimal default implementation, we recommend pseudo‐continuous labeling, background suppression, a segmented three‐dimensional readout without vascular crushing gradients, and calculation and presentation of both label/control difference images and cerebral blood flow in absolute units using a simplified model. Magn Reson Med 73:102–116, 2015. © 2014 Wiley Periodicals, Inc.

A pronounced temporal mismatch was observed between the responses of relative cerebral blood volume (rCBV) measured by magnetic resonance imaging and relative cerebral blood flow measured by laser-Doppler flowmetry in rat somatosensory cortex after electrical forepaw stimulation. The increase of relative cerebral blood flow after stimulus onset and decrease after stimulus cessation were accurately described with a single exponential time constant of 2.4 +/- 0.8 seconds. In contrast, rCBV exhibited two distinct and nearly sequential processes after both onset and cessation of stimulation. A rapid change of rCBV (1.5 +/- 0.8 seconds) occurring immediately after onset and cessation was not statistically different from the time constant for relative cerebral blood flow. However, a slow phase of increase (onset) and decrease (cessation) with an exponential time constant of 14 +/- 13 seconds began approximately 8 seconds after the rapid phase of CBV change. A modified windkessel model was developed to describe the temporal evolution of rCBV as a rapid elastic response of capillaries and veins followed by slow venous relaxation of stress. Venous delayed compliance was suggested as the mechanism for the poststimulus undershoot in blood oxygen-sensitive magnetic resonance imaging signal that has been observed in this animal model and in human data.

Undersampled magnetic resonance image (MRI) reconstruction is typically an ill-posed linear inverse task. The time and resource intensive computations require trade offs between accuracy and speed. In addition, state-of-the-art compressed sensing (CS) analytics are not cognizant of the image diagnostic quality. To address these challenges, we propose a novel CS framework that uses generative adversarial networks (GAN) to model the (low-dimensional) manifold of high-quality MR images. Leveraging a mixture of least-squares (LS) GANs and pixel-wise ℓ1/ℓ2 cost, a deep residual network with skip connections is trained as the generator that learns to remove the aliasing artifacts by projecting onto the image manifold. The LSGAN learns the texture details, while the ℓ1/ℓ2 cost suppresses high-frequency noise. A discriminator network, which is a multilayer convolutional neural network (CNN), plays the role of a perceptual cost that is then jointly trained based on high quality MR images to score the quality of retrieved images. In the operational phase, an initial aliased estimate (e.g., simply obtained by zero-filling) is propagated into the trained generator to output the desired reconstruction. This demands very low computational overhead. Extensive evaluations are performed on a large contrast-enhanced MR dataset of pediatric patients. Images rated by expert radiologists corroborate that GANCS retrieves higher quality images with improved fine texture details compared with conventional Wavelet-based and dictionary-learning based CS schemes as well as with deeplearning based schemes using pixel-wise training. In addition, it offers reconstruction times of under a few milliseconds, which is two orders of magnitude faster than current state-of-the-art CS-MRI schemes.

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SUMMARY:Resting-state fMRI was first described by Biswal et al in 1995 and has since then been widely used in both healthy subjects and patients with various neurologic, neurosurgical, and psychiatric disorders. As opposed to paradigm-or task-based functional MR imaging, resting-state fMRI does not require subjects to perform any specific task. The low-frequency oscillations of the resting-state fMRI signal have been shown to relate to the spontaneous neural activity. There are many ways to analyze resting-state fMRI data. In this review article, we will briefly describe a few of these and highlight the advantages and limitations of each. This description is to facilitate the adoption and use of resting-state fMRI in the clinical setting, helping neuroradiologists become familiar with these techniques and applying them for the care of patients with neurologic and psychiatric diseases.ABBREVIATIONS: ALFF ϭ Amplitude of Low Frequency Fluctuations; BOLD ϭ blood oxygen level-dependent; FCD ϭ functional connectivity density; ICA ϭ