From 2D to 4D Phase-Contrast MRI in the Neurovascular System: Will It Be a Quantum Jump or a Fancy Decoration?

Four-dimensional flow MRI for quantitative assessment of cerebrospinal fluid dynamics: Status and opportunities

Neurological disorders can manifest with altered neurofluid dynamics in different compartments of the central nervous system. These include alterations in cerebral blood flow, cerebrospinal fluid (CSF) flow, and tissue biomechanics. Noninvasive quantitative assessment of neurofluid flow and tissue motion is feasible with phase contrast magnetic resonance imaging (PC MRI). While two-dimensional (2D) PC MRI is routinely utilized in research and clinical settings to assess flow dynamics through a single imaging slice, comprehensive neurofluid dynamic assessment can be limited or impractical. Recently, four-dimensional (4D) flow MRI (or time-resolved three-dimensional PC with three-directional velocity encoding) has emerged as a powerful extension of 2D PC, allowing for large volumetric coverage of fluid velocities at high spatiotemporal resolution within clinically reasonable scan times. Yet, most 4D flow studies have focused on blood flow imaging. Characterizing CSF flow dynamics with 4D flow (i.e., 4D CSF flow) is of high interest to understand normal brain and spine physiology, but also to study neurological disorders such as dysfunctional brain metabolite waste clearance, where CSF dynamics appear to play an important role. However, 4D CSF flow imaging is challenged by the long T1 time of CSF and slower velocities compared with blood flow, which can result in longer scan times from low flip angles and extended motion-sensitive gradients, hindering clinical adoption. In this work, we review the state of 4D CSF flow MRI including challenges, novel solutions from current research and ongoing needs, examples of clinical and research applications, and discuss an outlook on the future of 4D CSF flow.

Imaging of Intracranial Aneurysms: A Review of Standard and Advanced Imaging Techniques

The treatment of intracranial aneurysms is dictated by its risk of rupture in the future. Several clinical and radiological risk factors for aneurysm rupture have been described and incorporated into prediction models. Despite the recent technological advancements in aneurysm imaging, linear length and visible irregularity with a bleb are the only radiological measure used in clinical prediction models. The purpose of this article is to summarize both the standard imaging techniques, including their limitations, and the advanced techniques being used experimentally to image aneurysms. It is expected that as our understanding of advanced techniques improves, and their ability to predict clinical events is demonstrated, they become an increasingly routine part of aneurysm assessment. It is important that neurovascular specialists understand the spectrum of imaging techniques available.

Modeling and evaluation of biomechanics and hemodynamic based on patient-specific small intracranial aneurysm using fluid-structure interaction

BACKGROUND AND OBJECTIVE

Rupture of small intracranial aneurysm (IA) often leads to the development of highly fatal clinical syndromes such as subarachnoid hemorrhage. Due to the patient specificity of small IA, there are many difficulties in evaluating the rupture risk of small IA such as multiple influencing factors, high clinical experience requirements and poor reusability.

METHODS

In this study, clinical methods such as transcranial doppler (TCD) and magnetic resonance imaging (MRI) are used to obtain patient-specific parameters, and the fluid-structure interaction method (FSI) is used to model and evaluate the biomechanics and hemodynamics of patient-specific small IA.

RESULTS

The results show that a spiral vortex stably exists in the patient-specific small IA. Due to the small size of the patient-specific small IA, the blood flow velocity still maintains a high value with maximum reaching 3 m/s. The inertial impact of blood flow and vortex convection have certain influence on hemodynamic and biomechanics parameters. They cause three high value areas of WSSM on the patient-specific small IA with maximum of 180 Pa, 130 Pa and 110 Pa, respectively. They also cause two types of WSS concentration points, positive normal stress peak value areas and negative normal stress peak value areas to appear.

CONCLUSION

This paper found that the factors affecting hemodynamic parameters and biomechanical parameters are different. Unlike hemodynamic parameters, biomechanical parameters are also affected by blood pressure in addition to blood flow velocity. This study reveals the relationship between the flow field distribution and changes of patient-specific small IA, biomechanics and hemodynamics.

Vortical Structures Promote Atheroprotective Wall Shear Stress Distributions in a Carotid Artery Bifurcation Model

Carotid artery diseases, such as atherosclerosis, are a major cause of death in the United States. Wall shear stresses are known to prompt plaque formation, but there is limited understanding of the complex flow structures underlying these stresses and how they differ in a pre-disposed high-risk patient cohort. A 'healthy' and a novel 'pre-disposed' carotid artery bifurcation model was determined based on patient-averaged clinical data, where the 'pre-disposed' model represents a pathological anatomy. Computational fluid dynamic simulations were performed using a physiological flow based on healthy human subjects. A main hairpin vortical structure in the internal carotid artery sinus was observed, which locally increased instantaneous wall shear stress. In the pre-disposed geometry, this vortical structure starts at an earlier instance in the cardiac flow cycle and persists over a much shorter period, where the second half of the cardiac cycle is dominated by perturbed secondary flow structures and vortices. This coincides with weaker favorable axial pressure gradient peaks over the sinus for the 'pre-disposed' geometry. The findings reveal a strong correlation between vortical structures and wall shear stress and imply that an intact internal carotid artery sinus hairpin vortical structure has a physiologically beneficial role by increasing local wall shear stresses. The deterioration of this beneficial vortical structure is expected to play a significant role in atherosclerotic plaque formation.

Non-Contrast Magnetic Resonance Angiography: Techniques, Principles, and Applications

Several non-contrast magnetic resonance angiography (MRA) techniques have been developed, providing an attractive alternative to contrast-enhanced MRA and a radiation-free alternative to computed tomography (CT) CT angiography. This review describes the physical principles, limitations, and clinical applications of bright-blood (BB) non-contrast MRA techniques. The principles of BB MRA techniques can be broadly divided into (a) flow-independent MRA, (b) blood-inflow-based MRA, (c) cardiac phase dependent, flow-based MRA, (d) velocity sensitive MRA, and (e) arterial spin-labeling MRA. The review also includes emerging multi-contrast MRA techniques that provide simultaneous BB and black-blood images for combined luminal and vessel wall evaluation.

Accelerated 4D-flow MRI with 3-point encoding enabled by machine learning

PURPOSE

To investigate the acceleration of 4D-flow MRI using a convolutional neural network (CNN) that produces three directional velocities from three flow encodings, without requiring a fourth reference scan measuring background phase.

METHODS

A fully 3D CNN using a U-net architecture was trained in a block-wise fashion to take complex images from three flow encodings and to produce three real-valued images for each velocity component. Using neurovascular 4D-flow scans (n = 144), the CNN was trained to predict velocities computed from four flow encodings by standard reconstruction including correction for residual background phase offsets. Methods to optimize loss functions were investigated, including magnitude, complex difference, and uniform velocity weightings. Subsequently, 3-point encoding was evaluated using cross validation of pixelwise correlation, flow measurements in major arteries, and in experiments with data at differing acceleration rates than the training data.

RESULTS

The CNN-produced 3-point velocities showed excellent agreements with the 4-point velocities, both qualitatively in velocity images, in flow rate measures, and quantitatively in regression analysis (slope = 0.96, R²  = 0.992). Optimizing the training to focus on vessel velocities rather than the global velocity error and improved the correlation of velocity within vessels themselves. The lowest error was observed when the loss function used uniform velocity weighting, in which the magnitude-weighted inverse of the velocity frequency uniformly distributed weighting across all velocity ranges. When applied to highly accelerated data, the 3-point network maintained a high correlation with ground truth data and demonstrated a denoising effect.

CONCLUSION

The 4D-flow MRI can be accelerated using machine learning requiring only three flow encodings to produce three-directional velocity maps with small errors.

Advanced cross-sectional imaging of cerebral aneurysms

While the rupture rate of cerebral aneurysms is only 1% per year, ruptured aneurysms are associated with significant morbidity and mortality, while aneurysm treatments have their own associated risk of morbidity and mortality. Conventional markers for aneurysm rupture include patient-specific and aneurysm-specific characteristics, with the development of scoring systems to better assess rupture risk. These scores, however, rely heavily on aneurysm size, and their accuracy in assessing risk in smaller aneurysms is limited. While the individual risk of rupture of small aneurysms is low, due to their sheer number, the largest proportion of ruptured aneurysms are small aneurysms. Conventional imaging techniques are valuable in characterizing aneurysm morphology; however, advanced imaging techniques assessing the presence of inflammatory changes within the aneurysm wall, hemodynamic characteristics of blood flow within aneurysm sacs, and imaging visualization of irregular aneurysm wall motion have been used to further determine aneurysm instability that otherwise cannot be characterized by conventional imaging techniques. The current manuscript reviews conventional imaging techniques and their value and limitations in cerebral aneurysm characterization, and evaluates the applications, value and limitations of advanced aneurysm imaging and post-processing techniques including intracranial vessel wall MRA, 4D-flow, 4D-CTA, and computational fluid dynamic simulations.

Motion-corrected 4D-Flow MRI for neurovascular applications

Neurovascular 4D-Flow MRI has emerged as a powerful tool for comprehensive cerebrovascular hemodynamic characterization. Clinical studies in at risk populations such as aging adults indicate hemodynamic markers can be confounded by motion-induced bias. This study develops and characterizes a high fidelity 3D self-navigation approach for retrospective rigid motion correction of neurovascular 4D-Flow data. A 3D radial trajectory with pseudorandom ordering was combined with a multi-resolution low rank regularization approach to enable high spatiotemporal resolution self-navigators from extremely undersampled data. Phantom and volunteer experiments were performed at 3.0T to evaluate the ability to correct for different amounts of induced motions. In addition, the approach was applied to clinical-research exams from ongoing aging studies to characterize performance in the clinical setting. Simulations, phantom and volunteer experiments with motion correction produced images with increased vessel conspicuity, reduced image blurring, and decreased variability in quantitative measures. Clinical exams revealed significant changes in hemodynamic parameters including blood flow rates, flow pulsatility index, and lumen areas after motion correction in probed cerebral arteries (Flow: P<0.001 Lt ICA, P=0.002 Rt ICA, P=0.004 Lt MCA, P=0.004 Rt MCA; Area: P<0.001 Lt ICA, P<0.001 Rt ICA, P=0.004 Lt MCA, P=0.004 Rt MCA; flow pulsatility index: P=0.042 Rt ICA, P=0.002 Lt MCA). Motion induced bias can lead to significant overestimation of hemodynamic markers in cerebral arteries. The proposed method reduces measurement bias from rigid motion in neurovascular 4D-Flow MRI in challenging populations such as aging adults.

Magnetic Resonance Imaging Manifestations of Pediatric Purulent Meningitis Based on Immune Clustering Algorithm

The purpose of this study was to analyze the diagnostic value of magnetic resonance imaging (MRI) based on the immune clustering algorithm (ICA) in children with purulent meningitis. In this study, 235 children with suspected pediatric purulent meningitis (PPM) were routinely scanned, and the artificial immune algorithm (AIA) and ICA were applied to image processing. In order to quantitatively analyze the accuracy and precision of the processed image, precision rate was introduced as the evaluation of accuracy, and the True Positive Vis Fox, False Negative Vis Fo, and False Positive Vis Fo were selected as the evaluation indicators. After comparison, the accuracy, sensitivity, and specificity of ICA detection were higher than those of AIA and conventional plain scanning, and the differences were statistically obvious (P < 0.05). Comparison on image display effects showed that compared with AIA, the image processed by the ICA algorithm constructed in this study showed the highest definition and contrast and the best denoising effect and image quality, showing a statistically obvious difference (P < 0.05). All in all, the display effect of MRI images of pediatric purulent meningitis based on ICA was more accurate and clearer than that of the traditional image processing, and it can provide a more accurate auxiliary basis in the diagnosis of lesion details. It also showed a higher clinical value for the development of a diagnosis and treatment plan for complicated PPM.

Imaging Modalities for Intracranial Aneurysm: More Than Meets the Eye

Intracranial aneurysms (IA) are often asymptomatic and have a prevalence of 3 to 5% in the adult population. The risk of IA rupture is low, however when it occurs half of the patients dies from subarachnoid hemorrhage (SAH). To avoid this fatal evolution, the main treatment is an invasive surgical procedure, which is considered to be at high risk of rupture. This risk score of IA rupture is evaluated mainly according to its size and location. Therefore, angiography and anatomic imaging of the intracranial aneurysm are crucial for its diagnosis. Moreover, it has become obvious in recent years that several other factors are implied in this complication, such as the blood flow complexity or inflammation. These recent findings lead to the development of new IA imaging tools such as vessel wall imaging, 4D-MRI, or molecular MRI to visualize inflammation at the site of IA in human and animal models. In this review, we will summarize IA imaging techniques used for the patients and those currently in development.

4D flow MRI hemodynamic biomarkers for cerebrovascular diseases

Alterations in cerebral blood flow are common in several neurological diseases among the elderly including stroke, cerebral small vessel disease, vascular dementia, and Alzheimer's disease. 4D flow magnetic resonance imaging (MRI) is a relatively new technique to investigate cerebrovascular disease, and makes it possible to obtain time-resolved blood flow measurements of the entire cerebral arterial venous vasculature and can be used to derive a repertoire of hemodynamic biomarkers indicative of cerebrovascular health. The information that can be obtained from one single 4D flow MRI scan allows both the investigation of aberrant flow patterns at a focal location in the vasculature as well as estimations of brain-wide disturbances in blood flow. Such focal and global hemodynamic biomarkers show the potential of being sensitive to impending cerebrovascular disease and disease progression and can also become useful during planning and follow-up of interventions aiming to restore a normal cerebral circulation. Here, we describe 4D flow MRI approaches for analyzing the cerebral vasculature. We then survey key hemodynamic biomarkers that can be reliably assessed using the technique. Finally, we highlight cerebrovascular diseases where one or multiple hemodynamic biomarkers are of central interest.

Noninvasive quantification of cerebrovascular pressure changes using 4D Flow MRI

PURPOSE

Hemodynamic alterations are indicative of cerebrovascular disease. However, the narrow and tortuous cerebrovasculature complicates image-based assessment, especially when quantifying relative pressure. Here, we present a systematic evaluation of image-based cerebrovascular relative pressure mapping, investigating the accuracy of the routinely used reduced Bernoulli (RB), the extended unsteady Bernoulli (UB), and the full-field virtual work-energy relative pressure ( ν WERP) method.

METHODS

Patient-specific in silico models were used to generate synthetic cerebrovascular 4D Flow MRI, with RB, UB, and ν WERP performance quantified as a function of spatiotemporal sampling and image noise. Cerebrovascular relative pressures were also derived in 4D Flow MRI from healthy volunteers ( n = 8 ), acquired at two spatial resolutions (dx = 1.1 and 0.8 mm).

RESULTS

The in silico analysis indicate that accurate relative pressure estimations are inherently coupled to spatial sampling: at dx = 1.0 mm high errors are reported for all methods; at dx = 0.5 mm ν WERP recovers relative pressures at a mean error of 0.02 ± 0.25 mm Hg, while errors remain higher for RB and UB (mean error of -2.18 ± 1.91 and -2.18 ± 1.87 mm Hg, respectively). The dependence on spatial sampling is also indicated in vivo, albeit with higher correlative dependence between resolutions using ν WERP (k = 0.64, R2 = 0.81 for dx = 1.1 vs. 0.8 mm) than with RB or UB (k = 0.04, R2 = 0.03, and k = 0.07, R2 = 0.07, respectively).

CONCLUSION

Image-based full-field methods such as ν WERP enable cerebrovascular relative pressure mapping; however, accuracy is directly dependent on utilized spatial resolution.