Perfusion tensor imaging

Current status in spatiotemporal analysis of contrast-based perfusion MRI

In perfusion MRI, image voxels form a spatially organized network of systems, all exchanging indicator with their immediate neighbors. Yet the current paradigm for perfusion MRI analysis treats all voxels or regions-of-interest as isolated systems supplied by a single global source. This simplification not only leads to long-recognized systematic errors but also fails to leverage the embedded spatial structure within the data. Since the early 2000s, a variety of models and implementations have been proposed to analyze systems with between-voxel interactions. In general, this leads to large and connected numerical inverse problems that are intractible with conventional computational methods. With recent advances in machine learning, however, these approaches are becoming practically feasible, opening up the way for a paradigm shift in the approach to perfusion MRI. This paper seeks to review the work in spatiotemporal modelling of perfusion MRI using a coherent, harmonized nomenclature and notation, with clear physical definitions and assumptions. The aim is to introduce clarity in the state-of-the-art of this promising new approach to perfusion MRI, and help to identify gaps of knowledge and priorities for future research.

Update on state-of-the-art for arterial spin labeling (ASL) human perfusion imaging outside of the brain

This review article provides an overview of developments for arterial spin labeling (ASL) perfusion imaging in the body (i.e., outside of the brain). It is part of a series of review/recommendation papers from the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group. In this review, we focus on specific challenges and developments tailored for ASL in a variety of body locations. After presenting common challenges, organ-specific reviews of challenges and developments are presented, including kidneys, lungs, heart (myocardium), placenta, eye (retina), liver, pancreas, and muscle, which are regions that have seen the most developments outside of the brain. Summaries and recommendations of acquisition parameters (when appropriate) are provided for each organ. We then explore the possibilities for wider adoption of body ASL based on large standardization efforts, as well as the potential opportunities based on recent advances in high/low-field systems and machine-learning. This review seeks to provide an overview of the current state-of-the-art of ASL for applications in the body, highlighting ongoing challenges and solutions that aim to enable more widespread use of the technique in clinical practice.

Assessment of single-vessel cerebral blood velocity by phase contrast fMRI

Current approaches to high-field functional MRI (fMRI) provide 2 means to map hemodynamics at the level of single vessels in the brain. One is through changes in deoxyhemoglobin in venules, i.e., blood oxygenation level-dependent (BOLD) fMRI, while the second is through changes in arteriole diameter, i.e., cerebral blood volume (CBV) fMRI. Here, we introduce cerebral blood flow-related velocity-based fMRI, denoted CBFv-fMRI, which uses high-resolution phase contrast (PC) MRI to form velocity measurements of flow. We use CBFv-fMRI in measure changes in blood velocity in single penetrating microvessels across rat parietal cortex. In contrast to the venule-dominated BOLD and arteriole-dominated CBV fMRI signals, CBFv-fMRI is comparable from both arterioles and venules. A single fMRI platform is used to map changes in blood pO2 (BOLD), volume (CBV), and velocity (CBFv). This combined high-resolution single-vessel fMRI mapping scheme enables vessel-specific hemodynamic mapping in animal models of normal and diseased states and further has translational potential to map vascular dementia in diseased or injured human brains with ultra-high-field fMRI.

Pattern recognition analysis of directional intravoxel incoherent motion MRI in ischemic rodent brains

This study aimed to demonstrate a reliable automatic segmentation method for independently separating reduced diffusion and decreased perfusion areas in ischemic stroke brains using constrained nonnegative matrix factorization (cNMF) pattern recognition in directional intravoxel incoherent motion MRI (IVIM-MRI). First, the feasibility of cNMF-based segmentation of IVIM signals was investigated in both simulations and in vivo experiments. The cNMF analysis was independently performed for S₀ -normalized and scaled (by the difference between the maximum and minimum) IVIM signals, respectively. Segmentations of reduced diffusion (from S₀ -normalized IVIM signals) and decreased perfusion (from scaled IVIM signals) areas were performed using the corresponding cNMF pattern weight maps. Second, Monte Carlo simulations were performed for directional IVIM signals to investigate the relationship between the degree of vessel alignment and the direction of the diffusion gradient. Third, directional IVIM-MRI experiments (x, y and z diffusion-gradient directions, 20 b values at 7 T) were performed for normal (n = 4), sacrificed (n = 1, no flow) and ischemic stroke models (n = 4, locally reduced flow). The results showed that automatic segmentation of the hypoperfused lesion using cNMF analysis was more accurate than segmentation using the conventional double-exponential fitting. Consistent with the simulation, the double-exponential pattern of the IVIM signals was particularly strong in white matter and ventricle regions when the directional flows were aligned with the applied diffusion-gradient directions. cNMF analysis of directional IVIM signals allowed robust automated segmentation of white matter, ventricle, vascular and hypoperfused regions in the ischemic brain. In conclusion, directional IVIM signals were simultaneously sensitive to diffusion and aligned flow and were particularly useful for automatically segmenting ischemic lesions via cNMF-based pattern recognition.

Advances in arterial spin labelling MRI methods for measuring perfusion and collateral flow

With the publication in 2015 of the consensus statement by the perfusion study group of the International Society for Magnetic Resonance in Medicine (ISMRM) and the EU-COST action 'ASL in dementia' on the implementation of arterial spin labelling MRI (ASL) in a clinical setting, the development of ASL can be considered to have become mature and ready for clinical prime-time. In this review article new developments and remaining issues will be discussed, especially focusing on quantification of ASL as well as on new technological developments of ASL for perfusion imaging and flow territory mapping. Uncertainty of the achieved labelling efficiency in pseudo-continuous ASL (pCASL) as well as the presence of arterial transit time artefacts, can be considered the main remaining challenges for the use of quantitative cerebral blood flow (CBF) values. New developments in ASL centre around time-efficient acquisition of dynamic ASL-images by means of time-encoded pCASL and diversification of information content, for example by combined 4D-angiography with perfusion imaging. Current vessel-encoded and super-selective pCASL-methodology have developed into easily applied flow-territory mapping methods providing relevant clinical information with highly similar information content as digital subtraction angiography (DSA), the current clinical standard. Both approaches seem therefore to be ready for clinical use.

Separating blood and water: Perfusion and free water elimination from diffusion MRI in the human brain

The assessment of the free water fraction in the brain provides important information about extracellular processes such as atrophy and neuroinflammation in various clinical conditions as well as in normal development and aging. Free water estimates from diffusion MRI are assumed to account for freely diffusing water molecules in the extracellular space, but may be biased by other pools of molecules in rapid random motion, such as the intravoxel incoherent motion (IVIM) of blood, where water molecules perfuse in the randomly oriented capillary network. The goal of this work was to separate the signal contribution of the perfusing blood from that of free-water and of other brain diffusivities. The influence of the vascular compartment on the estimation of the free water fraction and other diffusivities was investigated by simulating perfusion in diffusion MRI data. The perfusion effect in the simulations was significant, especially for the estimation of the free water fraction, and was maintained as long as low b-value data were included in the analysis. Two approaches to reduce the perfusion effect were explored in this study: (i) increasing the minimal b-value used in the fitting, and (ii) using a three-compartment model that explicitly accounts for water molecules in the capillary blood. Estimation of the model parameters while excluding low b-values reduced the perfusion effect but was highly sensitive to noise. The three-compartment model fit was more stable and additionally, provided an estimation of the volume fraction of the capillary blood compartment. The three-compartment model thus disentangles the effects of free water diffusion and perfusion, which is of major clinical importance since changes in these components in the brain may indicate different pathologies, i.e., those originating from the extracellular space, such as neuroinflammation and atrophy, and those related to the vascular space, such as vasodilation, vasoconstriction and capillary density. Diffusion MRI data acquired from a healthy volunteer, using multiple b-shells, demonstrated an expected non-zero contribution from the blood fraction, and indicated that not accounting for the perfusion effect may explain the overestimation of the free water fraction evinced in previous studies. Finally, the applicability of the method was demonstrated with a dataset acquired using a clinically feasible protocol with shorter acquisition time and fewer b-shells.

MRI of cerebral micro-vascular flow patterns: A multi-direction diffusion-weighted ASL approach

The study and clinical assessment of brain disease is currently hindered by a lack of non-invasive methods for the detailed and accurate evaluation of cerebral vascular pathology. Angiography can detect aberrant flow in larger feeding arteries/arterioles but cannot resolve the micro-vascular network. Small vessels are a key site of vascular pathology that can lead to haemorrhage and infarction, which may in turn trigger or exacerbate neurodegenerative processes. In this study, we describe a method to investigate microvascular flow anisotropy using a hybrid arterial spin labelling and multi-direction diffusion-weighted MRI sequence. We present evidence that the technique is sensitive to the mean/predominant direction of microvascular flow in localised regions of the rat cortex. The data provide proof of principle for a novel and non-invasive imaging tool to investigate cerebral micro-vascular flow patterns in healthy and disease states.

Mapping blood flow directionality in the human brain

Diffusion properties of tissue are often expressed on the basis of directional variance, i.e., diffusion tensor imaging. In comparison, common perfusion-weighted imaging such as arterial spin labeling yields perfusion in a scalar quantity. The purpose of this study was to test the feasibility of mapping cerebral blood flow directionality using alternate ascending/descending directional navigation (ALADDIN), a recently-developed arterial spin labeling technique with sensitivity to blood flow directions. ALADDIN was applied along 3 orthogonal directions to assess directional blood flow in a vector form and also along 6 equally-spaced directions to extract blood flow tensor matrix (P) based on a blood flow ellipsoid model. Tensor elements (eigenvalues, eigenvectors, etc) were calculated to investigate characteristics of the blood flow tensor, in comparison with time-of-flight MR angiogram. While the directions of the main eigenvectors were heterogeneous throughout the brain, regional clusters of blood flow directionality were reproducible across subjects. The technique could show heterogeneous blood flow directionality within and around brain tumor, which was different from that of the contralateral normal side. The proposed method is deemed to provide information of blood flow directionality, which has not been demonstrated before. The results warrant further studies to assess changes in the directionality map as a function of scan parameters, to understand the signal sources, to investigate the possibility of mapping local blood perfusion directionality, and to evaluate its usefulness for clinical diagnosis.

A tracer-kinetic field theory for medical imaging

Dynamic imaging data are currently analyzed with a tracer-kinetic theory developed for individual time curves measured over whole organs. The assumption is that voxels represent isolated systems which all receive indicator through the same arterial inlet. This leads to well-known systematic errors, but also fails to exploit the spatial structure of the data. In this study, a more general theoretical framework is developed which makes full use of the specific structure of image data. The theory encodes the fact that voxels receive indicator from their immediate neighbors rather than from an upstream arterial input. This results in a tracer-kinetic field theory where the tissue parameters are functions of space which can be measured by analyzing the temporal and spatial patterns in the concentrations. The implications are evaluated through a number of field models for common tissue types. The key benefits of a tracer-kinetic field theory are that: 1) long-standing systematic errors can be corrected, specifically the issue of bolus dispersion and the contamination of large-vessel blood flow on tissue perfusion measurements; 2) additional tissue parameters can be measured that characterize convective or diffusive exchange between voxels; 3) the need to measure a separate arterial input function can be eliminated.

An optimized velocity selective arterial spin labeling module with reduced eddy current sensitivity for improved perfusion quantification

Velocity-selective (VS) arterial spin labeling is a promising method for measuring perfusion in areas of slow or collateral flow by eliminating the bolus arrival delay associated with other spin labeling techniques. However, B(0) and B(1) inhomogeneities and eddy currents during the VS preparation hinder accurate quantification of perfusion with VS arterial spin labeling. In this study, it is demonstrated through simulations and experiments in healthy volunteers that eddy currents cause erroneous tagging of static tissue. Consequently, mean gray matter perfusion is overestimated by up to a factor of 2, depending on the VS preparation used. A novel eight-segment B(1) insensitive rotation VS preparation is proposed to reduce eddy current effects while maintaining the B(0) and B(1) insensitivity of previous preparations. Compared to two previous VS preparations, the eight-segment B(1) insensitive rotation is the most robust to eddy currents and should improve the quality and reliability of VS arterial spin labeling measurements in future studies.

QUantitative Imaging of eXtraction of oxygen and TIssue consumption (QUIXOTIC) using venular-targeted velocity-selective spin labeling

While oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO(2)) are fundamental parameters of brain health and function, a robust MRI-based mapping of OEF and CMRO(2) amenable to functional MRI (fMRI) has not been established. To address this issue, a novel method called QUantitative Imaging of eXtraction of Oxygen and TIssue Consumption, or QUIXOTIC, is introduced. The key innovation in QUIXOTIC is the use of velocity-selective spin labeling to isolate MR signal exclusively from postcapillary venular blood on a voxel-by-voxel basis. Measuring the T(2) of this venular-targeted blood allows calibration to venular oxygen saturation (Y(v)) via theoretical and experimental T(2) versus blood oxygen saturation relationships. Y(v) is converted to OEF, and baseline CMRO(2) is subsequently estimated from OEF and additional cerebral blood flow and hematocrit measurements. Theory behind the QUIXOTIC technique is presented, and implications of cutoff velocity (V(CUTOFF)) and outflow time parameters are discussed. Cortical gray matter values obtained with QUIXOTIC in 10 healthy volunteers are Y(v) = 0.73 ± 0.02, OEF = 0.26 ± 0.02, and CMRO(2) = 125 ± 15 μmol/100 g min. Results are compared to global measures obtained with the T(2) relaxation under spin tagging (TRUST) technique. The preliminary data presented suggest that QUIXOTIC will be useful for mapping Y(v), OEF, and CMRO(2), in both clinical and functional MRI settings.

Brain MR perfusion-weighted imaging with alternate ascending/descending directional navigation

In this study, a new arterial spin labeling technique that requires no separate spin preparation pulse was developed. Sequential two-dimensional slices were acquired in ascending and descending orders by turns using balanced steady state free precession for pair-wise subtraction. Simulation studies showed this new technique, alternate ascending/descending directional navigation (ALADDIN), has high sensitivity to both slow- (1-10 cm/sec) and fast-moving (>10 cm/sec) blood because of the presence of multiple labeling planes proximal to imaging planes and sensitivity of balanced steady state free precession to initial magnetization differences. ALADDIN provided high-resolution multislice perfusion-weighted images in ∼ 3 min. About 80-90% of signals in a slice were ascribed to spins saturated in the four prior slices. Three to five edge slices on each side of imaging group were affected by transient magnetization transfer effects and incomplete T(1) recovery between successive acquisitions. ALADDIN signals were dependent on many imaging parameters, implying room for improvement. Sagittal and coronal ALADDIN images demonstrated perfusion direction in gray matter regions was mostly from center to lateral, anterior, or posterior, whereas that in some white matter regions was reversed. ALADDIN is likely useful for many studies requiring perfusion-weighted imaging with short scan time, insensitiveness to arterial transit time, directional information, high resolution, and/or wide coverage.