ICA-based denoising for ASL perfusion imaging

Arterial Spin Labelling (ASL) imaging derives a perfusion image by tracing the accumulation of magnetically labeled blood water in the brain. As the image generated has an intrinsically low signal to noise ratio (SNR), multiple measurements are routinely acquired and averaged, at a penalty of increased scan duration and opportunity for motion artefact. However, this strategy alone might be ineffective in clinical settings where the time available for acquisition is limited and patient motion are increased. This study investigates the use of an Independent Component Analysis (ICA) approach for denoising ASL data, and its potential for automation.72 ASL datasets (pseudo-continuous ASL; 5 different post-labeling delays: 400, 800, 1200, 1600, 2000 m s; total volumes = 60) were collected from thirty consecutive acute stroke patients. The effects of ICA-based denoising (manual and automated) where compared to two different denoising approaches, aCompCor, a Principal Component-based method, and Enhancement of Automated Blood Flow Estimates (ENABLE), an algorithm based on the removal of corrupted volumes. Multiple metrics were used to assess the changes in the quality of the data following denoising, including changes in cerebral blood flow (CBF) and arterial transit time (ATT), SNR, and repeatability. Additionally, the relationship between SNR and number of repetitions acquired was estimated before and after denoising the data.The use of an ICA-based denoising approach resulted in significantly higher mean CBF and ATT values (p [less than] 0.001), lower CBF and ATT variance (p [less than] 0.001), increased SNR (p [less than] 0.001), and improved repeatability (p [less than] 0.05) when compared to the raw data. The performance of manual and automated ICA-based denoising was comparable. These results went beyond the effects of aCompCor or ENABLE. Following ICA-based denoising, the SNR was higher using only 50% of the ASL-dataset collected than when using the whole raw data.The results show that ICA can be used to separate signal from noise in ASL data, improving the quality of the data collected. In fact, this study suggests that the acquisition time could be reduced by 50% without penalty to data quality, something that merits further study. Independent component classification and regression can be carried out either manually, following simple criteria, or automatically

Dual-calibrated fMRI measurement of absolute cerebral metabolic rate of oxygen consumption and effective oxygen diffusivity

Dual-calibrated fMRI is a multi-parametric technique that allows for the quantification of the resting oxygen extraction fraction (OEF), the absolute rate of cerebral metabolic oxygen consumption (CMRO2), cerebral vascular reactivity (CVR) and baseline perfusion (CBF). It combines measurements of arterial spin labelling (ASL) and blood oxygenation level dependent (BOLD) signal changes during hypercapnic and hyperoxic gas challenges. Here we propose an extension to this methodology that permits the simultaneous quantification of the effective oxygen diffusivity of the capillary network (DC). The effective oxygen diffusivity has the scope to be an informative biomarker and useful adjunct to CMRO2, potentially providing a non-invasive metric of microvascular health, which is known to be disturbed in a range of neurological diseases. We demonstrate the new method in a cohort of healthy volunteers (n = 19) both at rest and during visual stimulation. The effective oxygen diffusivity was found to be highly correlated with CMRO2 during rest and activation, consistent with previous PET observations of a strong correlation between metabolic oxygen demand and effective diffusivity. The increase in effective diffusivity during functional activation was found to be consistent with previously reported increases in capillary blood volume, supporting the notion that measured oxygen diffusivity is sensitive to microvascular physiology

Time-encoded golden angle radial arterial spin labeling: simultaneous acquisition of angiography and perfusion data

The objective of the current study was to combine a time-encoded pseudocontinuous arterial spin labeling (te-pCASL) scheme with a golden angle radial readout for simultaneous acquisition of angiography and perfusion images from one single dataset, both in a highly flexible single-slice approach as well as within a multislice setting. A te-pCASL preparation and the golden angle radial readout were both used as a temporal resolution tool to retrospectively choose the temporal window for the reconstruction of both angiography and perfusion images from a single-slice dataset. The temporal window could be chosen retrospectively and adjusted to the hemodynamics of the volunteer on the scanner for the single-slice dataset. Angiographic images were reconstructed at a minimum temporal resolution of 69 ms. For the perfusion phase, only the densely sampled center of k-space was included in the reconstruction. For a multislice acquisition, the golden angle radial readout allowed reconstruction of images with different spatial resolutions to provide angiographic and perfusion information over 10 slices. The te-pCASL preparation was used as the only source for dynamic information. The multislice acquisition shows the ability of the golden angle radial readout to display the inflow of the labeled blood into the arteries as well as the perfusion in the tissue with full brain coverage. By combining a te-pCASL preparation with a golden angle radial readout, single-slice high temporal resolution angiography and good quality perfusion images were reconstructed in a flexible manner from a single dataset. Optimizing the golden angle radial readout for reconstructions at multiple spatial resolutions allows for multislice acquisition

Acceleration of vessel-selective dynamic MR Angiography by pseudocontinuous arterial spin labeling in combination with Acquisition of ConTRol and labEled images in the Same Shot (ACTRESS)

Purpose: The recently introduced "Acquisition of ConTRol and labEled imaging in the Same Shot" (ACTRESS) approach was designed to halve the scan time of arterial spin labeling (ASL) -based 4D-MRA by obtaining both labeled and control images in a single Look-Locker readout. However, application for vessel-selective labeling remains difficult. The aim of this study was to achieve a combination of ACTRESS and vessel-selective labeling to halve the scan time of vessel-selective 4D-MRA.Methods: By Bloch equation simulations, Look-I,ocker pseudocontinuous-ASE, (pCASL) was optimized to achieve constant static tissue signal across the multidelay readout, which is essential for the ACTRESS approach. Additionally, a new subtraction scheme was proposed to achieve visualization of the inflow phase even when labeled blood will have already arrived in the distal arteries during the first phase acquisition due to the long duration of the pCASL labeling module. In vivo studies were performed to investigate the signal variation of the static tissue, as well as to assess image quality of vessel-selective 4D-MRA with ACTRESS.Results: in in vivo studies, the mean signal variation of the static tissue was 8.98% over the Look-Locker phases, thereby minimizing the elevation of background signal. This allowed visualization of peripheral arteries and slowly arriving arterial blood with image quality as good as conventional pCASL, within half the acquisition time. Vesselselective pCASL-ACTRESS enabled the separated visualization of vessels arising from internal and external carotid arteries within this shortened acquisition time.Conclusion: By combining vessel-selective pCASL and ACTRESS approach, 4D-MRA of a single targeted arterial tree was achieved in a few minutes.Neuro Imaging Researc

Feasibility of Flat Panel Detector CT in Perfusion Assessment of Brain Arteriovenous Malformations: Initial Clinical Experience

The different results from flat panel detector CT in various pathologies have provoked some discussion. Our aim was to assess the role of flat panel detector CT in brain arteriovenous malformations, which has not yet been assessed. Five patients with brain arteriovenous malformations were studied with flat panel detector CT, DSC-MR imaging, and vessel-encoded pseudocontinuous arterial spin-labeling. In glomerular brain arteriovenous malformations, perfusion was highest next to the brain arteriovenous malformation with decreasing values with increasing distance from the lesion. An inverse tendency was observed in the proliferative brain arteriovenous malformation. Flat panel detector CT, originally thought to measure blood volume, correlated more closely with arterial spin-labeling-CBF and DSC-CBF than with DSC-CBV. We conclude that flat panel detector CT perfusion depends on the time point chosen for data collection, which is triggered too early in these patients (ie, when contrast agent appears in the superior sagittal sinus after rapid shunting through the brain arteriovenous malformation). This finding, in combination with high data variability, makes flat panel detector CT inappropriate for perfusion assessment in brain arteriovenous malformations