Accelerated dual-venc 4D flow MRI for neurovascular applications

Denoising of dual-VENC PC-MRI with large high/low VENC ratios

PURPOSE

Dual velocity encoding PC-MRI can produce spurious artifacts when using high ratios of velocity encoding values (VENCs), limiting its ability to generate high-quality images across a wide range of encoding velocities. This study aims to propose and compare dual-VENC correction methods for such artifacts.

THEORY AND METHODS

Two denoising approaches based on spatiotemporal regularization are proposed and compared with a state-of-the-art method based on sign correction. Accuracy is assessed using simulated data from an aorta and brain aneurysm, as well as 8 two-dimensional (2D) PC-MRI ascending aorta datasets. Two temporal resolutions (30,60) ms and noise levels (9,12) dB are considered, with noise added to the complex magnetization. The error is evaluated with respect to the noise-free measurement in the synthetic case and to the unwrapped image without additional noise in the volunteer datasets.

RESULTS

In all studied cases, the proposed methods are more accurate than the Sign Correction technique. Using simulated 2D+T data from the aorta (60 ms, 9 dB), the Dual-VENC (DV) error0 . 82 ± 0 . 07 $$ 0.82\pm 0.07 $$ is reduced to:0 . 66 ± 0 . 04 $$ 0.66\pm 0.04 $$ (Sign Correction);0 . 34 ± 0 . 04 $$ 0.34\pm 0.04 $$ and0 . 32 ± 0 . 04 $$ 0.32\pm 0.04 $$ (proposed techniques). The methods are found to be significantly different (p-value< 0 . 05 $$ <0.05 $$ ). Importantly, brain aneurysm data revealed that the Sign Correction method is not suitable, as it increases error when the flow is not unidirectional. All three methods improve the accuracy of in vivo data.

CONCLUSION

The newly proposed methods outperform the Sign Correction method in improving dual-VENC PC-MRI images. Among them, the approach based on temporal differences has shown the highest accuracy.

4D flow MRI velocity uncertainty quantification

PURPOSE

An automatic method is presented for estimating 4D flow MRI velocity measurement uncertainty in each voxel. The velocity distance (VD) metric, a statistical distance between the measured velocity and local error distribution, is introduced as a novel measure of 4D flow MRI velocity measurement quality.

METHODS

The method uses mass conservation to assess the local velocity error variance and the standardized difference of means (SDM) velocity to estimate the velocity error correlations. VD is evaluated as the Mahalanobis distance between the local velocity measurement and the local error distribution. The uncertainty model is validated synthetically and tested in vitro under different flow resolutions and noise levels. The VD's application is demonstrated on two in vivo thoracic vasculature 4D flow datasets.

RESULTS

Synthetic results show the proposed uncertainty quantification method is sensitive to aliased regions across various velocity-to-noise ratios and assesses velocity error correlations in four- and six-point acquisitions with correlation errors at or under 3.2%. In vitro results demonstrate the method's sensitivity to spatial resolution, venc settings, partial volume effects, and phase wrapping error sources. Applying VD to assess in vivo 4D flow MRI in the aorta demonstrates the expected increase in measured velocity quality with contrast administration and systolic flow.

CONCLUSION

The proposed 4D flow MRI uncertainty quantification method assesses velocity measurement error owing to sources including noise, intravoxel phase dispersion, and velocity aliasing. This method enables rigorous comparison of 4D flow MRI datasets obtained in longitudinal studies, across patient populations, and with different MRI systems.

Super-Resolving and Denoising 4D flow MRI of Neurofluids Using Physics-Guided Neural Networks

PURPOSE

To obtain high-resolution velocity fields of cerebrospinal fluid (CSF) and cerebral blood flow by applying a physics-guided neural network (div-mDCSRN-Flow) to 4D flow MRI.

METHODS

The div-mDCSRN-Flow network was developed to improve spatial resolution and denoise 4D flow MRI. The network was trained with patches of paired high-resolution and low-resolution synthetic 4D flow MRI data derived from computational fluid dynamic simulations of CSF flow within the cerebral ventricles of five healthy cases and five Alzheimer's disease cases. The loss function combined mean squared error with a binary cross-entropy term for segmentation and a divergence-based regularization term for the conservation of mass. Performance was assessed using synthetic 4D flow MRI in one healthy and one Alzheimer' disease cases, an in vitro study of healthy cerebral ventricles, and in vivo 4D flow imaging of CSF as well as flow in arterial and venous blood vessels. Comparison was performed to trilinear interpolation, divergence-free radial basis functions, divergence-free wavelets, 4DFlowNet, and our network without divergence constraints.

RESULTS

The proposed network div-mDCSRN-Flow outperformed other methods in reconstructing high-resolution velocity fields from synthetic 4D flow MRI in healthy and AD cases. The div-mDCSRN-Flow network reduced error by 22.5% relative to linear interpolation for in vitro core voxels and by 49.5% in edge voxels.

CONCLUSION

The results demonstrate generalizability of our 4D flow MRI super-resolution and denoising approach due to network training using flow patches and physics-based constraints. The mDCSRN-Flow network can facilitate MRI studies involving CSF flow measurements in cerebral ventricles and association of MRI-based flow metrics with cerebrovascular health.

Optimizing encoding strategies for 4D Flow MRI of mean and turbulent flow

For 4D Flow MRI of mean and turbulent flow a compromise between spatiotemporal undersampling and velocity encodings needs to be found. Assuming a fixed scan time budget, the impact of trading off spatiotemporal undersampling versus velocity encodings on quantification of velocity and turbulence for aortic 4D Flow MRI was investigated. For this purpose, patient-specific mean and turbulent aortic flow data were generated using computational fluid dynamics which were embedded into the patient-specific background image data to generate synthetic MRI data with corresponding ground truth flow. Cardiac and respiratory motion were included. Using the synthetic MRI data as input, 4D Flow MRI was subsequently simulated with undersampling along pseudo-spiral Golden angle Cartesian trajectories for various velocity encoding schemes. Data were reconstructed using a locally low rank approach to obtain mean and turbulent flow fields to be compared to ground truth. Results show that, for a 15-min scan, velocity magnitudes can be reconstructed with good accuracy relatively independent of the velocity encoding scheme ( S S I M U = 0.938 ± 0.003 ) , good accuracy ( S S I M U ≥ 0.933 ) and with peak velocity errors limited to 10%. Turbulence maps on the other hand suffer from both lower reconstruction quality ( S S I M TKE ≥ 0.323 ) and larger sensitivity to undersampling, motion and velocity encoding strengths ( S S I M TKE = 0.570 ± 0.110 ) when compared to velocity maps. The best compromise to measure unwrapped velocity maps and turbulent kinetic energy given a fixed 15-min scan budget was found to be a 7-point multi- V enc acquisition with a low V enc tuned for best sensitivity to the range of expected intra-voxel standard deviations and a high V enc larger than the expected peak velocity.

Comparing Vascular Morphology and Hemodynamics in Patients with Vein of Galen Malformations Using Intracranial 4D Flow MRI

BACKGROUND AND PURPOSE

Vein of Galen malformation (VOGM) is the most common congenital cerebrovascular malformation, and many patients have high mortality rates and poor cognitive outcomes. Quantitative diagnostic tools are needed to improve clinical outcomes, and the purpose of this study was to characterize intracranial blood flow in VOGM using quantitative 4D flow MRI.

MATERIALS AND METHODS

A prospective study of children with VOGM was conducted by acquiring 4D flow MRI to quantify total blood inflow to the brain, flow in the pathologic falcine sinus, and flow in the superior sagittal sinus. Linear regression was used to test the relationships between these flows and age, clinical status, and the mediolateral diameter of the outflow tract of the lesion through the falcine or straight sinus diameter, which is a known morphologic prognostic metric.

RESULTS

In all 11 subjects (mean age, 22 [SD,17 ] weeks), total blood flow to the brain always exceeded normal levels (mean, 1063 [SD, 403] mL/minute). Significant correlations were observed between falcine sinus flow and the mediolateral diameter of the straight or falcine sinus, the posterior cerebral artery/MCA flow ratio and age at scanning, and superior sagittal sinus flow proximal to malformation inflow and age at scanning.

CONCLUSIONS

Using 4D flow MRI, we established the hemodynamic underpinnings of the mediolateral diameter of the straight or falcine sinus and investigated metrics representing parenchymal venous drainage that could be used to monitor the normalization of hemodynamics during embolization therapy.

Assessment of arterial pulsatility of cerebral perforating arteries using 7T high-resolution dual-VENC phase-contrast MRI

PURPOSE

Directly imaging the function of cerebral perforating arteries could provide valuable insight into the pathology of cerebral small vessel diseases (cSVD). Arterial pulsatility has been identified as a useful biomarker for assessing vascular dysfunction. In this study, we investigate the feasibility and reliability of using dual velocity encoding (VENC) phase-contrast MRI (PC-MRI) to measure the pulsatility of cerebral perforating arteries at 7 T.

METHODS

Twenty participants, including 12 young volunteers and 8 elder adults, underwent high-resolution 2D PC-MRI scans with VENCs of 20 cm/s and 40 cm/s at 7T. The sensitivity of perforator detection and the reliability of pulsatility measurement of cerebral perforating arteries using dual-VENC PC-MRI were evaluated by comparison with the single-VENC data. The effects of temporal resolution in the PC-MRI acquisition and aging on the pulsatility measurements were investigated.

RESULTS

Compared to the single VENCs, dual-VENC PC-MRI provided improved sensitivity of perforator detection and more reliable pulsatility measurements. Temporal resolution impacted the pulsatility measurements, as decreasing temporal resolution led to an underestimation of pulsatility. Elderly adults had elevated pulsatility in cerebral perforating arteries compared to young adults, but there was no difference in the number of detected perforators between the two age groups.

CONCLUSION

Dual-VENC PC-MRI is a reliable imaging method for the assessment of pulsatility of cerebral perforating arteries, which could be useful as a potential imaging biomarker of aging and cSVD.

Observation of intracranial artery and venous sinus hemodynamics using compressed sensing-accelerated 4D flow MRI: performance at different acceleration factors

Objective

To investigate the feasibility and performance of 4D flow MRI accelerated by compressed sensing (CS) for the hemodynamic quantification of intracranial artery and venous sinus.

Materials and methods

Forty healthy volunteers were prospectively recruited, and 20 volunteers underwent 4D flow MRI of cerebral artery, and the remaining volunteers underwent 4D flow MRI of venous sinus. A series of 4D flow MRI was acquired with different acceleration factors (AFs), including sensitivity encoding (SENSE, AF = 4) and CS (AF = CS4, CS6, CS8, and CS10) at a 3.0 T MRI scanner. The hemodynamic parameters, including flow rate, mean velocity, peak velocity, max axial wall shear stress (WSS), average axial WSS, max circumferential WSS, average circumferential WSS, and 3D WSS, were calculated at the internal carotid artery (ICA), transverse sinus (TS), straight sinus (SS), and superior sagittal sinus (SSS).

Results

Compared to the SENSE4 scan, for the left ICA C2, mean velocity measured by CS8 and CS10 groups, and 3D WSS measured by CS6, CS8, and CS10 groups were underestimated; for the right ICA C2, mean velocity measured by CS10 group, and 3D WSS measured by CS8 and CS10 groups were underestimated; for the right ICA C4, mean velocity measured by CS10 group, and 3D WSS measured by CS8 and CS10 groups were underestimated; and for the right ICA C7, mean velocity and 3D WSS measured by CS8 and CS10 groups, and average axial WSS measured by CS8 group were also underestimated (all p < 0.05). For the left TS, max axial WSS and 3D WSS measured by CS10 group were significantly underestimated (p = 0.032 and 0.003). Similarly, for SS, mean velocity, peak velocity, average axial WSS measured by the CS8 and CS10 groups, max axial WSS measured by CS6, CS8, and CS10 groups, and 3D WSS measured by CS10 group were significantly underestimated compared to the SENSE4 scan (p = 0.000-0.021). The hemodynamic parameters measured by CS4 group had only minimal bias and great limits of agreement compared to conventional 4D flow (SENSE4) in the ICA and every venous sinus (the max/min upper limit to low limit of the 95% limits of agreement = 11.4/0.03 to 0.004/-5.7, 14.4/0.05 to -0.03/-9.0, 12.6/0.04 to -0.03/-9.4, 16.8/0.04 to 0.6/-14.1; the max/min bias = 5.0/-1.2, 3.5/-1.4, 4.5/-1.1, 6.6/-4.0 for CS4, CS6, CS8, and CS10, respectively).

Conclusion

CS4 strikes a good balance in 4D flow between flow quantifications and scan time, which could be recommended for routine clinical use.

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.

Automated intracranial vessel segmentation of 4D flow MRI data in patients with atherosclerotic stenosis using a convolutional neural network

Introduction

Intracranial 4D flow MRI enables quantitative assessment of hemodynamics in patients with intracranial atherosclerotic disease (ICAD). However, quantitative assessments are still challenging due to the time-consuming vessel segmentation, especially in the presence of stenoses, which can often result in user variability. To improve the reproducibility and robustness as well as to accelerate data analysis, we developed an accurate, fully automated segmentation for stenosed intracranial vessels using deep learning.

Methods

154 dual-VENC 4D flow MRI scans (68 ICAD patients with stenosis, 86 healthy controls) were retrospectively selected. Manual segmentations were used as ground truth for training. For automated segmentation, deep learning was performed using a 3D U-Net. 20 randomly selected cases (10 controls, 10 patients) were separated and solely used for testing. Cross-sectional areas and flow parameters were determined in the Circle of Willis (CoW) and the sinuses. Furthermore, the flow conservation error was calculated. For statistical comparisons, Dice scores (DS), Hausdorff distance (HD), average symmetrical surface distance (ASSD), Bland-Altman analyses, and interclass correlations were computed using the manual segmentations from two independent observers as reference. Finally, three stenosis cases were analyzed in more detail by comparing the 4D flow-based segmentations with segmentations from black blood vessel wall imaging (VWI).

Results

Training of the network took approximately 10 h and the average automated segmentation time was 2.2 ± 1.0 s. No significant differences in segmentation performance relative to two independent observers were observed. For the controls, mean DS was 0.85 ± 0.03 for the CoW and 0.86 ± 0.06 for the sinuses. Mean HD was 7.2 ± 1.5 mm (CoW) and 6.6 ± 3.7 mm (sinuses). Mean ASSD was 0.15 ± 0.04 mm (CoW) and 0.22 ± 0.17 mm (sinuses). For the patients, the mean DS was 0.85 ± 0.04 (CoW) and 0.82 ± 0.07 (sinuses), the HD was 8.4 ± 3.1 mm (CoW) and 5.7 ± 1.9 mm (sinuses) and the mean ASSD was 0.22 ± 0.10 mm (CoW) and 0.22 ± 0.11 mm (sinuses). Small bias and limits of agreement were observed in both cohorts for the flow parameters. The assessment of the cross-sectional lumen areas in stenosed vessels revealed very good agreement (ICC: 0.93) with the VWI segmentation but a consistent overestimation (bias ± LOA: 28.1 ± 13.9%).

Discussion

Deep learning was successfully applied for fully automated segmentation of stenosed intracranial vasculatures using 4D flow MRI data. The statistical analysis of segmentation and flow metrics demonstrated very good agreement between the CNN and manual segmentation and good performance in stenosed vessels. To further improve the performance and generalization, more ICAD segmentations as well as other intracranial vascular pathologies will be considered in the future.

Measuring global cerebrovascular pulsatility transmission using 4D flow MRI

Pulse wave encephalopathy (PWE) is hypothesised to initiate many forms of dementia, motivating its identification and risk assessment. As candidate pulsatility based biomarkers for PWE, pulsatility index and pulsatility damping have been studied and, currently, do not adequately stratify risk due to variability in pulsatility and spatial bias. Here, we propose a locus-independent pulsatility transmission coefficient computed by spatially tracking pulsatility along vessels to characterise the brain pulse dynamics at a whole-organ level. Our preliminary analyses in a cohort of 20 subjects indicate that this measurement agrees with clinical observations relating blood pulsatility with age, heart rate, and sex, making it a suitable candidate to study the risk of PWE. We identified transmission differences between vascular regions perfused by the basilar and internal carotid arteries attributed to the identified dependence on cerebral blood flow, and some participants presented differences between the internal carotid perfused regions that were not related to flow or pulsatility burden, suggesting underlying mechanical differences. Large populational studies would benefit from retrospective pulsatility transmission analyses, providing a new comprehensive arterial description of the hemodynamic state in the brain. We provide a publicly available implementation of our tools to derive this coefficient, built into pre-existing open-source software.

Macrovascular blood flow and microvascular cerebrovascular reactivity are regionally coupled in adolescence

Cerebrovascular imaging assessments are particularly challenging in adolescent cohorts, where not all modalities are appropriate, and rapid brain maturation alters hemodynamics at both macro- and microvascular scales. In a preliminary sample of healthy adolescents (n=12, 8-25 years), we investigated relationships between 4D flow MRI-derived blood velocity and blood flow in bilateral anterior, middle, and posterior cerebral arteries and BOLD cerebrovascular reactivity in associated vascular territories. As hypothesized, higher velocities in large arteries are associated with an earlier response to a vasodilatory stimulus (cerebrovascular reactivity delay) in the downstream territory. Higher blood flow through these arteries is associated with a larger BOLD response to a vasodilatory stimulus (cerebrovascular reactivity amplitude) in the associated territory. These trends are consistent in a case study of adult moyamoya disease. In our small adolescent cohort, macrovascular-microvascular relationships for velocity/delay and flow/CVR change with age, though underlying mechanisms are unclear. Our work emphasizes the need to better characterize this key stage of human brain development, when cerebrovascular hemodynamics are changing, and standard imaging methods offer limited insight into these processes. We provide important normative data for future comparisons in pathology, where combining macro- and microvascular assessments may better help us prevent, stratify, and treat cerebrovascular disease.

Revolutionizing vascular imaging: trends and future directions of 4D flow MRI based on a 20-year bibliometric analysis

Background

Four-dimensional flow magnetic resonance imaging (4D flow MRI) is a promising new technology with potential clinical value in hemodynamic quantification. Although an increasing number of articles on 4D flow MRI have been published over the past decades, few studies have statistically analyzed these published articles. In this study, we aimed to perform a systematic and comprehensive bibliometric analysis of 4D flow MRI to explore the current hotspots and potential future directions.

Methods

The Web of Science Core Collection searched for literature on 4D flow MRI between 2003 and 2022. CiteSpace was utilized to analyze the literature data, including co-citation, cooperative network, cluster, and burst keyword analysis.

Results

A total of 1,069 articles were extracted for this study. The main research hotspots included the following: quantification and visualization of blood flow in different clinical settings, with keywords such as "cerebral aneurysm", "heart", "great vessel", "tetralogy of Fallot", "portal hypertension", and "stiffness"; optimization of image acquisition schemes, such as "resolution" and "reconstruction"; measurement and analysis of flow components and patterns, as indicated by keywords "pattern", "KE", "WSS", and "fluid dynamics". In addition, international consensus for metrics derived from 4D flow MRI and multimodality imaging may also be the future research direction.

Conclusions

The global domain of 4D flow MRI has grown over the last 2 decades. In the future, 4D flow MRI will evolve towards becoming a relatively short scan duration with adequate spatiotemporal resolution, expansion into the diagnosis and treatment of vascular disease in other related organs, and a shift in focus from vascular structure to function. In addition, artificial intelligence (AI) will assist in the clinical promotion and application of 4D flow MRI.

Robust and fast stochastic 4D flow vector-field signature technique for quantifying composite flow dynamics from 4D flow MRI: Application to left atrial flow in atrial fibrillation

4D flow MRI is an emerging imaging modality that maps voxel-wise blood flow information as velocity vector fields that is acquired in 7-dimensional image volumes (3 spatial dimensions + 3 velocity directions + time). Blood flow in the cardiovascular system is often complex and composite involving multiple flow dynamics and patterns (e.g., vortex flow, jets, stagnating flow) that occur and interact simultaneously. The spectrum of such complex flow dynamics is embedded in the velocity vector field dynamics derived from 4D Flow MRI. However, current flow metrics cannot fully measure high-dimensional vector-field data and embedded complex composite flow data. Instead, these methods need to break down the vector-field data into secondary scalar fields of individual flow components using fluid dynamics operators. These methods are gradient-based and sensitive to data uncertainties, and only focus on individual flow components of the overall composite flow, therefore potentially underestimating the severity of overall flow changes associated with cardiovascular diseases. To address these limitations, in MICCAI 2021, we introduced a novel comprehensive stochastic 4D Flow vector-field signature technique that works directly on the entire spatiotemporal velocity vector field. This technique uses efficient stochastic gradient-free interrogation of multi-million flow vector-pairs per patient to derive the patient's unique flow profile of the complex composite flow alterations and in real-time processing. The signature technique's probabilistic gradient-free formulation should allow for highly robust quantification despite inherent errors in 4D flow MRI acquisitions. Here, we extend the application of the 4D flow vector-field signature technique to the left atrium to analyze complex composite flow changes in patients with atrial fibrillation. In 128 subjects, we performed extensive sensitivity testing and determined that the vector-field signature technique is highly robust to typical sources of data uncertainties in 4D flow MRI: degradation in spatiotemporal resolution, added Gaussian noise, and segmentation errors. We demonstrate the excellent generalizability of the stochastic convergence from the aorta to the left atrium and between different 4D Flow MRI acquisition protocols. We compare the robustness of our technique to existing advanced flow quantification metrics of kinetic energy, vorticity, and energy loss demonstrating a superior performance of up-to 14-fold. Our results show the potential diagnostic and clinical utility of our signature technique in identifying distinctly altered composite flow signatures in atrial fibrillation patients independent of existing flow metrics.

A Deep Learning Approach to Using Wearable Seismocardiography (SCG) for Diagnosing Aortic Valve Stenosis and Predicting Aortic Hemodynamics Obtained by 4D Flow MRI

In this paper, we explored the use of deep learning for the prediction of aortic flow metrics obtained using 4-dimensional (4D) flow magnetic resonance imaging (MRI) using wearable seismocardiography (SCG) devices. 4D flow MRI provides a comprehensive assessment of cardiovascular hemodynamics, but it is costly and time-consuming. We hypothesized that deep learning could be used to identify pathological changes in blood flow, such as elevated peak systolic velocity ([Formula: see text]) in patients with heart valve diseases, from SCG signals. We also investigated the ability of this deep learning technique to differentiate between patients diagnosed with aortic valve stenosis (AS), non-AS patients with a bicuspid aortic valve (BAV), non-AS patients with a mechanical aortic valve (MAV), and healthy subjects with a normal tricuspid aortic valve (TAV). In a study of 77 subjects who underwent same-day 4D flow MRI and SCG, we found that the [Formula: see text] values obtained using deep learning and SCGs were in good agreement with those obtained by 4D flow MRI. Additionally, subjects with non-AS TAV, non-AS BAV, non-AS MAV, and AS could be classified with ROC-AUC (area under the receiver operating characteristic curves) values of 92%, 95%, 81%, and 83%, respectively. This suggests that SCG obtained using low-cost wearable electronics may be used as a supplement to 4D flow MRI exams or as a screening tool for aortic valve disease.

Assessment of Beat-To-Beat Variability in Left Atrial Hemodynamics Using Real Time Phase Contrast MRI in Patients With Atrial Fibrillation

BACKGROUND

Hemodynamic assessment of left atrial (LA) flow using phase contrast MRI provides insight into thromboembolic risk in atrial fibrillation (AF). However, conventional flow imaging techniques are averaged over many heartbeats.

PURPOSE

To evaluate beat-to-beat variability and LA hemodynamics in patients with AF using real time phase contrast (RTPC) MRI.

STUDY TYPE

Prospective.

SUBJECTS

Thirty-five patients with history of AF (68 ± 10 years, nine female), 10 healthy controls (57 ± 19 years, four female).

FIELD STRENGTH/SEQUENCE

5T, 2D RTPC with through-plane velocity-encoded gradient echo sequence and 4D flow MRI with three-directional velocity-encoded gradient echo sequence.

ASSESSMENT

RTPC was continuously acquired for a mid-LA slice in all subjects. 4D flow data were interpolated at the RTPC location and normally projected for comparison with RTPC. RR intervals extracted from RTPC were used to calculate heart rate variability (HRV = interquartile range over median × 100%). Patients were classified into low (<9.7%) and high (>9.7%) HRV groups. LA peak/mean velocity and stasis (%velocities < 5.8 cm/sec) were calculated from segmented 2D images. Variability in RTPC flow metrics was quantified by coefficient of variation (CV) over all cycles.

STATISTICAL TESTS

Pearson's correlation coefficient (r), Bland-Altman analysis, Kruskal-Wallis test. A P value < 0.05 was considered statistically significant.

RESULTS

RTPC and 4D flow measurements were strongly/significantly correlated for all hemodynamic parameters (R2  = 0.75-0.83) in controls. Twenty-four patients had low HRV (mean = 4 ± 2%) and 11 patients had high HRV (27 ± 9%). In patients, increased HRV was significantly correlated with CV of peak velocity (r = 0.67), mean velocity (r = 0.51), and stasis (r = 0.41). A stepwise decrease in peak/mean velocity and increase in stasis was observed when comparing controls vs. low HRV vs. high HRV groups. Mean velocity and stasis differences were significant for control vs. high HRV groups.

CONCLUSIONS

RTPC may be suitable for assessing the impact of HRV on hemodynamics and provide insight for AF management in highly arrhythmic patients.

EVIDENCE LEVEL

1 TECHNICAL EFFICACY: Stage 2.

Automatic 4D Flow MRI Segmentation Using the Standardized Difference of Means Velocity

We present a method to automatically segment 4D flow magnetic resonance imaging (MRI) by identifying net flow effects using the standardized difference of means (SDM) velocity. The SDM velocity quantifies the ratio between the net flow and observed flow pulsatility in each voxel. Vessel segmentation is performed using an F-test, identifying voxels with significantly higher SDM velocity values than background voxels. We compare the SDM segmentation algorithm against pseudo-complex difference (PCD) intensity segmentation of 4D flow measurements in in vitro cerebral aneurysm models and 10 in vitro Circle of Willis (CoW) datasets. We also compared the SDM algorithm to convolutional neural network (CNN) segmentation in 5 thoracic vasculature datasets. The in vitro flow phantom geometry is known, while the ground truth geometries for the CoW and thoracic aortas are derived from high-resolution time-of-flight (TOF) magnetic resonance angiography and manual segmentation, respectively. The SDM algorithm demonstrates greater robustness than PCD and CNN approaches and can be applied to 4D flow data from other vascular territories. The SDM to PCD comparison demonstrated an approximate 48% increase in sensitivity in vitro and 70% increase in the CoW, respectively; the SDM and CNN sensitivities were similar. The vessel surface derived from the SDM method was 46% closer to the in vitro surfaces and 72% closer to the in vitro TOF surfaces than the PCD approach. The SDM and CNN approaches both accurately identify vessel surfaces. The SDM algorithm is a repeatable segmentation method, enabling reliable computation of hemodynamic metrics associated with cardiovascular disease.

4D Flow cardiovascular magnetic resonance consensus statement: 2023 update

Hemodynamic assessment is an integral part of the diagnosis and management of cardiovascular disease. Four-dimensional cardiovascular magnetic resonance flow imaging (4D Flow CMR) allows comprehensive and accurate assessment of flow in a single acquisition. This consensus paper is an update from the 2015 '4D Flow CMR Consensus Statement'. We elaborate on 4D Flow CMR sequence options and imaging considerations. The document aims to assist centers starting out with 4D Flow CMR of the heart and great vessels with advice on acquisition parameters, post-processing workflows and integration into clinical practice. Furthermore, we define minimum quality assurance and validation standards for clinical centers. We also address the challenges faced in quality assurance and validation in the research setting. We also include a checklist for recommended publication standards, specifically for 4D Flow CMR. Finally, we discuss the current limitations and the future of 4D Flow CMR. This updated consensus paper will further facilitate widespread adoption of 4D Flow CMR in the clinical workflow across the globe and aid consistently high-quality publication standards.

Understanding development of jugular bulb stenosis in vein of galen malformations: identifying metrics of complex flow dynamics in the cerebral venous vasculature of infants

Introduction: Computational fluid dynamics (CFD) assess biological systems based on specific boundary conditions. We propose modeling more advanced hemodynamic metrics, such as core line length (CL) and critical points which characterize complexity of flow in the context of cerebral vasculature, and specifically cerebral veins during the physiologically evolving early neonatal state of vein of Galen malformations (VOGM). CFD has not been applied to the study of arteriovenous shunting in Vein of Galen Malformations but could help illustrate the pathophysiology of this malformation. Methods: Three neonatal patients with VOGM at Boston Children's Hospital met inclusion criteria for this study. Structural MRI data was segmented to generate a mesh of the VOGM and venous outflow. Boundary condition flow velocity was derived from PC-MR sequences with arterial and venous dual velocity encoding. The mesh and boundary conditions were applied to model the cerebral venous flow. We computed flow variables including mean wall shear stress (WSSmean), mean OSI, CL, and the mean number of critical points (nCrPointsmean) for each patient specific model. A critical point is defined as the location where the shear stress vector field is zero (stationary point) and can be used to describe complexity of flow. Results: The division of flow into the left and right venous outflow was comparable between PC-MR and CFD modeling. A high complexity recirculating flow pattern observed on PC-MR was also identified on CFD modeling. Regions of similar WSSmean and OSImean (<1.3 fold) in the left and right venous outflow channels of a single patient have several-fold magnitude difference in higher order hemodynamic metrics (> 3.3 fold CL, > 1.7 fold nCrPointsmean). Specifically, the side which developed JBS in each model had greater nCrPointsmean compared to the jugular bulb with no stenosis (VOGM1: 4.49 vs. 2.53, VOGM2: 1.94 vs. 0, VOGM3: 1 vs. 0). Biologically, these regions had subsequently divergent development, with increased complexity of flow associating with venous stenosis. Discussion: Advanced metrics of flow complexity identified in computational models may reflect observed flow phenomena not fully characterized by primary or secondary hemodynamic parameters. These advanced metrics may indicate physiological states that impact development of jugular bulb stenosis in VOGM.

Cerebrovascular super-resolution 4D Flow MRI - Sequential combination of resolution enhancement by deep learning and physics-informed image processing to non-invasively quantify intracranial velocity, flow, and relative pressure

The development of cerebrovascular disease is tightly coupled to regional changes in intracranial flow and relative pressure. Image-based assessment using phase contrast magnetic resonance imaging has particular promise for non-invasive full-field mapping of cerebrovascular hemodynamics. However, estimations are complicated by the narrow and tortuous intracranial vasculature, with accurate image-based quantification directly dependent on sufficient spatial resolution. Further, extended scan times are required for high-resolution acquisitions, and most clinical acquisitions are performed at comparably low resolution (>1 mm) where biases have been observed with regard to the quantification of both flow and relative pressure. The aim of our study was to develop an approach for quantitative intracranial super-resolution 4D Flow MRI, with effective resolution enhancement achieved by a dedicated deep residual network, and with accurate quantification of functional relative pressures achieved by subsequent physics-informed image processing. To achieve this, our two-step approach was trained and validated in a patient-specific in-silico cohort, showing good accuracy in estimating velocity (relative error: 15.0 ± 0.1%, mean absolute error (MAE): 0.07 ± 0.06 m/s, and cosine similarity: 0.99 ± 0.06 at peak velocity) and flow (relative error: 6.6 ± 4.7%, root mean square error (RMSE): 0.56 mL/s at peak flow), and with the coupled physics-informed image analysis allowing for maintained recovery of functional relative pressure throughout the circle of Willis (relative error: 11.0 ± 7.3%, RMSE: 0.3 ± 0.2 mmHg). Furthermore, the quantitative super-resolution approach is applied to an in-vivo volunteer cohort, effectively generating intracranial flow images at <0.5 mm resolution and showing reduced low-resolution bias in relative pressure estimation. Our work thus presents a promising two-step approach to non-invasively quantify cerebrovascular hemodynamics, being applicable to dedicated clinical cohorts in the future.

Near-wall hemodynamic parameters quantification in in vitro intracranial aneurysms with 7 T PC-MRI

OBJECTIVE

Wall shear stress (WSS) and its derived spatiotemporal parameters have proven to play a major role on intracranial aneurysms (IAs) growth and rupture. This study aims to demonstrate how ultra-high field (UHF) 7 T phase contrast magnetic resonance imaging (PC-MRI) coupled with advanced image acceleration techniques allows a highly resolved visualization of near-wall hemodynamic parameters patterns in in vitro IAs, paving the way for more robust risk assessment of their growth and rupture.

MATERIALS AND METHODS

We performed pulsatile flow measurements inside three in vitro models of patient-specific IAs using 7 T PC-MRI. To this end, we built an MRI-compatible test bench, which faithfully reproduced a typical physiological intracranial flow rate in the models.

RESULTS

The ultra-high field 7 T images revealed WSS patterns with high spatiotemporal resolution. Interestingly, the high oscillatory shear index values were found in the core of low WSS vortical structures and in flow stream intersecting regions. In contrast, maxima of WSS occurred around the impinging jet sites.

CONCLUSIONS

We showed that the elevated signal-to-noise ratio arising from 7 T PC-MRI enabled to resolve high and low WSS patterns with a high degree of detail.

Automated hemodynamic assessment for cranial 4D flow MRI

Cranial 4D flow MRI post-processing typically involves manual user interaction which is time-consuming and associated with poor repeatability. The primary goal of this study is to develop a robust quantitative velocity tool (QVT) that utilizes threshold-based segmentation techniques to improve segmentation quality over prior approaches based on centerline processing schemes (CPS) that utilize k-means clustering segmentation. This tool also includes an interactive 3D display designed for simplified vessel selection and automated hemodynamic visualization and quantification. The performances of QVT and CPS were compared in vitro in a flow phantom and in vivo in 10 healthy participants. Vessel segmentations were compared with ground-truth computed tomography in vitro (29 locations) and manual segmentation in vivo (13 locations) using linear regression. Additionally, QVT and CPS MRI flow rates were compared to perivascular ultrasound flow in vitro using linear regression. To assess internal consistency of flow measures in vivo, conservation of flow was assessed at vessel junctions using linear regression and consistency of flow along vessel segments was analyzed by fitting a Gaussian distribution to a histogram of normalized flow values. Post-processing times were compared between the QVT and CPS using paired t-tests. Vessel areas segmented in vitro (CPS: slope = 0.71, r = 0.95 and QVT: slope = 1.03, r = 0.95) and in vivo (CPS: slope = 0.61, r = 0.96 and QVT: slope = 0.93, r = 0.96) were strongly correlated with ground-truth area measurements. However, CPS (using k-means segmentation) consistently underestimated vessel areas. Strong correlations were observed between QVT and ultrasound flow (slope = 0.98, r = 0.96) as well as flow at junctions (slope = 1.05, r = 0.98). Mean and standard deviation of flow along vessel segments was 9.33e-16 ± 3.05%. Additionally, the QVT demonstrated excellent interobserver agreement and significantly reduced post-processing by nearly 10 min (p < 0.001). By completely automating post-processing and providing an easy-to-use 3D visualization interface for interactive vessel selection and hemodynamic quantification, the QVT offers an efficient, robust, and repeatable means to analyze cranial 4D flow MRI. This software is freely available at: https://github.com/uwmri/QVT.

Comparison of Improved Unidirectional Dual Velocity-Encoding MRI Methods

BACKGROUND

In phase-contrast (PC) MRI, several dual velocity encoding methods have been proposed to robustly increase velocity-to-noise ratio (VNR), including a standard dual-VENC (SDV), an optimal dual-VENC (ODV), and bi- and triconditional methods.

PURPOSE

To develop a correction method for the ODV approach and to perform a comparison between methods.

STUDY TYPE

Case-control study.

POPULATION

Twenty-six volunteers.

FIELD STRENGTH/SEQUENCE

1.5 T phase-contrast MRI with VENCs of 50, 75, and 150 cm/second.

ASSESSMENT

Since we acquired single-VENC protocols, we used the background phase from high-VENC (VENC_H ) to reconstruct the low-VENC (VENC_L ) phase. We implemented and compared the unwrapping methods for different noise levels and also developed a correction of the ODV method.

STATISTICAL TESTS

Shapiro-Wilk's normality test, two-way analysis of variance with homogeneity of variances was performed using Levene's test, and the significance level was adjusted by Tukey's multiple post hoc analysis with Bonferroni (P < 0.05).

RESULTS

Statistical analysis revealed no extreme outliers, normally distributed residuals, and homogeneous variances. We found statistically significant interaction between noise levels and the unwrapping methods. This implies that the number of non-unwrapped pixels increased with the noise level. We found that for β = VENC_L /VENC_H  = 1/2, unwrapping methods were more robust to noise. The post hoc test showed a significant difference between the ODV corrected and the other methods, offering the best results regarding the number of unwrapped pixels.

DATA CONCLUSIONS

All methods performed similarly without noise, but the ODV corrected method was more robust to noise at the price of a higher computational time.

LEVEL OF EVIDENCE

4 TECHNICAL EFFICACY STAGE: 1.

Venc Design and Velocity Estimation for Phase Contrast MRI

In phase-contrast magnetic resonance imaging (PC-MRI), spin velocity contributes to the phase measured at each voxel. Therefore, estimating velocity from potentially wrapped phase measurements is the task of solving a system of noisy congruence equations. We propose Phase Recovery from Multiple Wrapped Measurements (PRoM) as a fast, approximate maximum likelihood estimator of velocity from multi-coil data with possible amplitude attenuation due to dephasing. The estimator can recover the fullest possible extent of unambiguous velocities, which can greatly exceed twice the highest venc. The estimator uses all pairwise phase differences and the inherent correlations among them to minimize the estimation error. Correlations are directly estimated from multi-coil data without requiring knowledge of coil sensitivity maps, dephasing factors, or the actual per-voxel signal-to-noise ratio. Derivation of the estimator yields explicit probabilities of unwrapping errors and the probability distribution for the velocity estimate; this, in turn, allows for optimized design of the phase-encoded acquisition. These probabilities are also incorporated into spatial post-processing to further mitigate wrapping errors. Simulation, phantom, and in vivo results for three-point PC-MRI acquisitions validate the benefits of reduced estimation error, increased recovered velocity range, optimized acquisition, and fast computation. A phantom study at 1.5T demonstrates 48.5% decrease in root mean squared error using PRoM with post-processing versus a conventional "dual-venc" technique. Simulation and 3T in vivo results likewise demonstrate the proposed benefits.

Distribution and regional variation of wall shear stress in the curved middle cerebral artery using four-dimensional flow magnetic resonance imaging

BACKGROUND

To investigate the distribution and regional variation of wall shear stress (WSS) in the curved middle cerebral artery (MCA) in healthy individuals using four-dimensional (4D) flow magnetic resonance imaging (MRI).

METHODS

A total of 44 healthy participants (18 males; mean ages: 27.16±5.69 years) were included in this cross-sectional study. The WSS parameters of mean, minimum, and maximum values, the coefficient of variation of time-averaged WSS (TAWSSCV), and the maximum values of the oscillatory shear index (OSI) were calculated and compared in the curved proximal (M1) segments. Three cross-sectional planes were selected: the location perpendicular to the beginning of the long axis of the curved M1 segment of the MCA (proximal section), the most curved M1 location (curved M1 section), and the location before the insular (M2) segment bifurcation (distal section). The WSS and OSI parameters of the proximal, curved, and distal sections of the curved M1 segment were compared, including the inner and outer curvatures of the curved M1 section.

RESULTS

Of the curved M1 segments, the curved M1 section had significantly lower minimum TAWSS values than the proximal (P=0.031) and distal sections (P=0.002), and the curved M1 section had significantly higher maximum OSI values than the distal section (P=0.001). The TAWSSCV values at the curved M1 section were significantly higher than the proximal (P=0.001) and distal sections (P<0.001). At the curved M1 section, the inner curvature showed a significantly lower minimum TAWSS (P=0.013) and higher maximum OSI values (P=0.002) than the outer curvature.

CONCLUSIONS

There are distribution variation of WSS and OSI parameters at the curved M1 section of the curved MCA, and the inner curvature of the curved M1 section has the lowest WSS and highest OSI distribution. The local hemodynamic features of the curved MCA may be related to the predilection for atherosclerotic plaque development.

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.

Accelerated dual-venc 4D flow MRI with variable high-venc spatial resolution for neurovascular applications

PURPOSE

Dual-velocity encoded (dual-venc or DV) 4D flow MRI achieves wide velocity dynamic range and velocity-to-noise ratio (VNR), enabling accurate neurovascular flow characterization. To reduce scan time, we present interleaved dual-venc 4D Flow with independently prescribed, prospectively undersampled spatial resolution of the high-venc (HV) acquisition: Variable Spatial Resolution Dual Venc (VSRDV).

METHODS

A prototype VSRDV sequence was developed based on a Cartesian acquisition with eight-point phase encoding, combining PEAK-GRAPPA acceleration with zero-filling in phase and partition directions for HV. The VSRDV approach was optimized by varying z, the zero-filling fraction of HV relative to low-venc, between 0%-80% in vitro (realistic neurovascular model with pulsatile flow) and in vivo (n = 10 volunteers). Antialiasing precision, mean and peak velocity quantification accuracy, and test-retest reproducibility were assessed relative to reference images with equal-resolution HV and low venc (z = 0%).

RESULTS

In vitro results for all z demonstrated an antialiasing true positive rate at least 95% for R PEAK - GRAPPA $$ {R}_{\mathrm{PEAK}-\mathrm{GRAPPA}} $$  = 2 and 5, with no linear relationship to z (p = 0.62 and 0.13, respectively). Bland-Altman analysis for z = 20%, 40%, 60%, or 80% versus z = 0% in vitro and in vivo demonstrated no bias >1% of venc in mean or peak velocity values at any R ZF $$ {R}_{\mathrm{ZF}} $$ . In vitro mean and peak velocity, and in vivo peak velocity, had limits of agreement within 15%.

CONCLUSION

VSRDV allows up to 34.8% scan time reduction compared to PEAK-GRAPPA accelerated DV 4D Flow MRI, enabling large spatial coverage and dynamic range while maintaining VNR and velocity measurement accuracy.

Intracranial Blood Flow Quantification by Accelerated Dual-venc 4D Flow MRI: Comparison With Transcranial Doppler Ultrasound

BACKGROUND

Dual-venc 4D flow MRI, recently introduced for the assessment of intracranial hemodynamics, may provide a promising complementary approach to well-established tools such as transcranial Doppler ultrasound (TCD) and overcome some of their disadvantages. However, data comparing intracranial flow measures from dual-venc 4D flow MRI and TCD are lacking.

PURPOSE

To compare cerebral blood flow velocity measures derived from dual-venc 4D flow MRI and TCD.

STUDY TYPE

Prospective cohort.

SUBJECTS

A total of 25 healthy participants (56 ± 4 years old, 44% female).

FIELD STRENGTH/SEQUENCE

A 3 T/dual-venc 4D flow MRI using a time-resolved three-dimensional phase-contrast sequence with three-dimensional velocity encoding.

ASSESSMENT

Peak velocity measurements in bilateral middle cerebral arteries (MCA) were quantified from dual-venc 4D flow MRI and TCD. The MRI data were quantified by two independent observers (S.M and Y.M.) and TCD was performed by a trained technician (A.L.M.). We assessed the agreement between 4D flow MRI and TCD measures, and the interobserver agreement of 4D flow MRI measurements.

STATISTICAL TESTS

Peak velocity from MRI and TCD was compared using Bland-Altman analysis and coefficient of variance. Intraclass correlation coefficient (ICC) was used to assess MRI interobserver agreement. A P value < 0.05 was considered statistically significant.

RESULTS

There was excellent interobserver agreement in dual-venc 4D flow MRI-based measurements of peak velocity in bilateral MCA (ICC = 0.97 and 0.96 for the left and right MCA, respectively). Dual-venc 4D flow MRI significantly underestimated peak velocity in the left and right MCA compared to TCD (bias = 0.13 [0.59, -0.33] m/sec and 0.15 [0.47, -0.17] m/sec, respectively). The coefficient of variance between dual-venc 4D flow MRI and TCD measurements was 26% for the left MCA and 22% for the right MCA.

DATA CONCLUSION

There was excellent interobserver agreement for the assessment of MCA peak velocity using dual-venc 4D flow MRI, and ≤20% under-estimation compared with TCD.

EVIDENCE LEVEL

3 TECHNICAL EFFICACY: Stage 2.

Abdominal applications of quantitative 4D flow MRI

4D flow MRI is a quantitative MRI technique that allows the comprehensive assessment of time-resolved hemodynamics and vascular anatomy over a 3-dimensional imaging volume. It effectively combines several advantages of invasive and non-invasive imaging modalities like ultrasound, angiography, and computed tomography in a single MRI acquisition and provides an unprecedented characterization of velocity fields acquired non-invasively in vivo. Functional and morphological imaging of the abdominal vasculature is especially challenging due to its complex and variable anatomy with a wide range of vessel calibers and flow velocities and the need for large volumetric coverage. Despite these challenges, 4D flow MRI is a promising diagnostic and prognostic tool as many pathologies in the abdomen are associated with changes of either hemodynamics or morphology of arteries, veins, or the portal venous system. In this review article, we will discuss technical aspects of the implementation of abdominal 4D flow MRI ranging from patient preparation and acquisition protocol over post-processing and quality control to final data analysis. In recent years, the range of applications for 4D flow in the abdomen has increased profoundly. Therefore, we will review potential clinical applications and address their clinical importance, relevant quantitative and qualitative parameters, and unmet challenges.

Modeling Bias Error in 4D Flow MRI Velocity Measurements

We present a model to estimate the bias error of 4D flow magnetic resonance imaging (MRI) velocity measurements. The local instantaneous bias error is defined as the difference between the expectation of the voxel's measured velocity and actual velocity at the voxel center. The model accounts for bias error introduced by the intra-voxel velocity distribution and partial volume (PV) effects. We assess the intra-voxel velocity distribution using a 3D Taylor Series expansion. PV effects and numerical errors are considered using a Richardson extrapolation. The model is applied to synthetic Womersley flow and in vitro and in vivo 4D flow MRI measurements in a cerebral aneurysm. The bias error model is valid for measurements with at least 3.75 voxels across the vessel diameter and signal-to-noise ratio greater than 5. All test cases exceeded this diameter to voxel size ratio with diameters, isotropic voxel sizes, and velocity ranging from 3-15mm, 0.5-1mm, and 0-60cm/s, respectively. The model accurately estimates the bias error in voxels not affected by PV effects. In PV voxels, the bias error is an order of magnitude higher, and the accuracy of the bias error estimation in PV voxels ranges from 67.3% to 108% relative to the actual bias error. The bias error estimated for in vivo measurements increased two-fold at systole compared to diastole in partial volume and non-partial volume voxels, suggesting the bias error varies over the cardiac cycle. This bias error model quantifies 4D flow MRI measurement accuracy and can help plan 4D flow MRI scans.

Assessment of hepatic arterial hemodynamics with 4D flow MRI: in vitro analysis of motion and spatial resolution related error and in vivo feasibility study in 20 volunteers

OBJECTIVES

To assess the ability of four-dimensional (4D) flow MRI to measure hepatic arterial hemodynamics by determining the effects of spatial resolution and respiratory motion suppression in vitro and its applicability in vivo with comparison to two-dimensional (2D) phase-contrast MRI.

METHODS

A dynamic hepatic artery phantom and 20 consecutive volunteers were scanned. The accuracies of Cartesian 4D flow sequences with k-space reordering and navigator gating at four spatial resolutions (0.5- to 1-mm isotropic) and navigator acceptance windows (± 8 to ± 2 mm) and one 2D phase-contrast sequence (0.5-mm in -plane) were assessed in vitro at 3 T. Two sequences centered on gastroduodenal and hepatic artery branches were assessed in vivo for intra - and interobserver agreement and compared to 2D phase-contrast.

RESULTS

In vitro, higher spatial resolution led to a greater decrease in error than narrower navigator window (30.5 to -4.67% vs -6.64 to -4.67% for flow). In vivo, hepatic and gastroduodenal arteries were more often visualized with the higher resolution sequence (90 vs 71%). Despite similar interobserver agreement (κ = 0.660 and 0.704), the higher resolution sequence had lower variability for area (CV = 20.04 vs 30.67%), flow (CV = 34.92 vs 51.99%), and average velocity (CV = 26.47 vs 44.76%). 4D flow had lower differences between inflow and outflow at the hepatic artery bifurcation (11.03 ± 5.05% and 15.69 ± 6.14%) than 2D phase-contrast (28.77 ± 21.01%).

CONCLUSION

High-resolution 4D flow can assess hepatic artery anatomy and hemodynamics with improved accuracy, greater vessel visibility, better interobserver reliability, and internal consistency.

KEY POINTS

• Motion-suppressed Cartesian four-dimensional (4D) flow MRI with higher spatial resolution provides more accurate measurements even when accepted respiratory motion exceeds voxel size. • 4D flow MRI with higher spatial resolution provides substantial interobserver agreement for visualization of hepatic artery branches. • Lower peak and average velocities and a trend toward better internal consistency were observed with 4D flow MRI as compared to 2D phase-contrast.

New Insights Into Cerebrovascular Pathophysiology and Hypertension

Despite advances in acute management and prevention of cerebrovascular disease, stroke and vascular cognitive impairment together remain the world's leading cause of death and neurological disability. Hypertension and its consequences are associated with over 50% of ischemic and 70% of hemorrhagic strokes but despite good control of blood pressure (BP), there remains a 10% risk of recurrent cerebrovascular events, and there is no proven strategy to prevent vascular cognitive impairment. Hypertension evolves over the lifespan, from predominant sympathetically driven hypertension with elevated mean BP in early and mid-life to a late-life phenotype of increasing systolic and falling diastolic pressures, associated with increased arterial stiffness and aortic pulsatility. This pattern may partially explain both the increasing incidence of stroke in younger adults as well as late-onset, chronic cerebrovascular injury associated with concurrent systolic hypertension and historic mid-life diastolic hypertension. With increasing arterial stiffness and autonomic dysfunction, BP variability increases, independently predicting the risk of ischemic and intracerebral hemorrhage, and is potentially modifiable beyond control of mean BP. However, the interaction between hypertension and control of cerebral blood flow remains poorly understood. Cerebral small vessel disease is associated with increased pulsatility in large cerebral vessels and reduced reactivity to carbon dioxide, both of which are being targeted in early phase clinical trials. Cerebral arterial pulsatility is mainly dependent upon increased transmission of aortic pulsatility via stiff vessels to the brain, while cerebrovascular reactivity reflects endothelial dysfunction. In contrast, although cerebral autoregulation is critical to adapt cerebral tone to BP fluctuations to maintain cerebral blood flow, its role as a modifiable risk factor for cerebrovascular disease is uncertain. New insights into hypertension-associated cerebrovascular pathophysiology may provide key targets to prevent chronic cerebrovascular disease, acute events, and vascular cognitive impairment.

Multiple motion encoding in phase-contrast MRI: A general theory and application to elastography imaging

While MRI allows to encode the motion of tissue in the magnetization's phase, it remains yet a challenge to obtain high fidelity motion images due to wraps in the phase for high encoding efficiencies. Therefore, we propose an optimal multiple motion encoding method (OMME) and exemplify it in Magnetic Resonance Elastography (MRE) data. OMME is formulated as a non-convex least-squares problem for the motion using an arbitrary number of phase-contrast measurements with different motion encoding gradients (MEGs). The mathematical properties of OMME are proved in terms of standard deviation and dynamic range of the motion's estimate for arbitrary MEGs combination which are confirmed using synthetically generated data. OMME's performance is assessed on MRE data from in vivo human brain experiments and compared to dual encoding strategies. The unwrapped images are further used to reconstruct stiffness maps and compared to the ones obtained using conventional unwrapping methods. OMME allowed to successfully combine several MRE phase images with different MEGs, outperforming dual encoding strategies in either motion-to-noise ratio (MNR) or number of successfully reconstructed voxels with good noise stability. This lead to stiffness maps with greater resolution of details than obtained with conventional unwrapping methods. The proposed OMME method allows for a flexible and noise robust increase in the dynamic range and thus provides wrap-free phase images with high MNR. In MRE, the method may be especially suitable when high resolution images with high MNR are needed.

Clinical Applications of 4D Flow MRI in the Portal Venous System

Evaluation of the hemodynamics in the portal venous system plays an essential role in many hepatic pathologies. Changes in portal flow and vessel morphology are often indicative of disease.Routinely used imaging modalities, such as CT, ultrasound, invasive angiography, and MRI, often focus on either hemodynamics or anatomical imaging. In contrast, 4D flow MRI facilitiates a more comprehensive understanding of pathophysiological mechanisms by simultaneously and noninvasively acquiring time-resolved flow and anatomical information in a 3D imaging volume.Though promising, 4D flow MRI in the portal venous system is especially challenging due to small vessel calibers, slow flow velocities, and breathing motion. In this review article, we will discuss how to account for these challenges when planning and conducting 4D flow MRI acquisitions in the upper abdomen. We will address patient preparation, sequence acquisition, postprocessing, quality control, and analysis of 4D flow data.In the second part of this article, we will review potential clinical applications of 4D flow MRI in the portal venous system. The most promising area for clinical utilization is the diagnosis and grading of liver cirrhosis and its complications. Relevant parameters acquired by 4D flow MRI include the detection of reduced or reversed flow in the portal venous system, characterization of portosystemic collaterals, and impaired response to a meal challenge. In patients with cirrhosis, 4D flow MRI has the potential to address the major unmet need of noninvasive detection of gastroesophageal varices at high risk for bleeding. This could replace many unnecessary, purely diagnostic, and invasive esophagogastroduodenoscopy procedures, thereby improving patient compliance with follow-up. Moreover, 4D flow MRI offers unique insights and added value for surgical planning and follow-up of multiple hepatic interventions, including transjugular intrahepatic portosystemic shunts, liver transplantation, and hepatic disease in children. Lastly, we will discuss the path to clinical implementation and remaining challenges.

Technical Background for 4D Flow MR Imaging

Recently, the hemodynamic assessments with 3D cine phase-contrast (PC) MRI (4D flow MRI) have attracted considerable attention from clinicians. Unlike 2D cine PC MRI, the technique allows for cardiac phase-resolved data acquisitions of flow velocity vectors within the entire FOV during a clinically viable period. Thus, the method has enabled retrospective flowmetry in the spatial and temporal axes, which are essential to derive hemodynamic parameters related to vascular homeostasis and those to the progression of the pathologies. Accelerations in imaging are critical for this technology to be clinically viable; however, a high SNR or velocity-to-noise ratio (VNR) is also vital for accurate flow measurements. In this chapter, the technologies enabling this difficult balance are discussed.

Quality Control for 4D Flow MR Imaging

In recent years, 4D flow MRI has become increasingly important in clinical applications for the blood vessels in the whole body, heart, and cerebrospinal fluid. 4D flow MRI has advantages over 2D cine phase-contrast (PC) MRI in that any targeted area of interest can be analyzed post-hoc, but there are some factors to be considered, such as ensuring measurement accuracy, a long imaging time and post-processing complexity, and interobserver variability.Due to the partial volume phenomenon caused by low spatial and temporal resolutions, the accuracy of flow measurement in 4D flow MRI is reduced. For spatial resolution, it is recommended to include at least four voxels in the vessel of interest, and if possible, six voxels. In large vessels such as the aorta, large voxels can be secured and SNR can be maintained, but in small cerebral vessels, SNR is reduced, resulting in reduced accuracy. A temporal resolution of less than 40 ms is recommended. The velocity-to-noise ratio (VNR) of low-velocity blood flow is low, resulting in poor measurement accuracy. The use of dual velocity encoding (VENC) or multi-VENC is recommended to avoid velocity wrap around and to increase VNR. In order to maintain sufficient spatio-temporal resolution, a longer imaging time is required, leading to potential patient movement during examination and a corresponding decrease in measurement accuracy.For the clinical application of new technologies, including various acceleration techniques, in vitro and in vivo accuracy verification based on existing accuracy-validated 2D cine PC MRI and 4D flow MRI, as well as accuracy verification on the conservation of mass' principle, should be performed, and intraobserver repeatability, interobserver reproducibility, and test-retest reproducibility should be checked.

Why 4D Flow MRI? Real Advantages

This special issue of Magnetic Resonance in Medical Sciences features the most recent reviews on 4D Flow MRI. These reviews deal with the current status of the emerging technique of 4D Flow MRI facilitated in various areas that are difficult to obtain with conventional flowmetry. MR signals inherently contain flow velocity information. In previous decades, in vivo blood flow measurement was traditionally performed by 2D methods, such as Doppler ultrasonography and 2D phase-contrast MRI, which have long been regarded as mature techniques in hemodynamic flowmetry. Although 2D velocimetries have many advantages over 4D Flow MRI in terms of cost and accessibility, and provide excellent temporal and in-plane spatial resolutions, they also have some disadvantages. The emerging technology of 4D Flow MRI can overcome the shortcomings of conventional 2D imaging. In recent years, hemodynamic analysis has witnessed significant progress that is primarily attributable to advances in 4D Flow MRI.

A multi-modality approach for enhancing 4D flow magnetic resonance imaging via sparse representation

This work evaluates and applies a multi-modality approach to enhance blood flow measurements and haemodynamic analysis with phase-contrast magnetic resonance imaging (4D flow MRI) in cerebral aneurysms (CAs). Using a library of high-resolution velocity fields from patient-specific computational fluid dynamic simulations and in vitro particle tracking velocimetry measurements, the flow field of 4D flow MRI data is reconstructed as the sparse representation of the library. The method was evaluated with synthetic 4D flow MRI data in two CAs. The reconstruction enhanced the spatial resolution and velocity accuracy of the synthetic MRI data, leading to reliable pressure and wall shear stress (WSS) evaluation. The method was applied on in vivo 4D flow MRI data acquired in the same CAs. The reconstruction increased the velocity and WSS by 6-13% and 39-61%, respectively, suggesting that the accuracy of these quantities was improved since the raw MRI data underestimated the velocity and WSS by 10-20% and 40-50%, respectively. The computed pressure fields from the reconstructed data were consistent with the observed flow structures. The results suggest that using the sparse representation flow reconstruction with in vivo 4D flow MRI enhances blood flow measurement and haemodynamic analysis.

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.

Divergence-Free Constrained Phase Unwrapping and Denoising for 4D Flow MRI Using Weighted Least-Squares

A novel divergence-free constrained phase unwrapping method was proposed and evaluated for 4D flow MRI. The unwrapped phase field was obtained by integrating the phase variations estimated from the wrapped phase data using weighted least-squares. The divergence-free constraint for incompressible blood flow was incorporated to regulate and denoise the resulting phase field. The proposed method was tested on synthetic phase data of left ventricular flow and in vitro 4D flow measurement of Poiseuille flow. The method was additionally applied to in vivo 4D flow measurements in the thoracic aorta from 30 human subjects. The performance of the proposed method was compared to the state-of-the-art 4D single-step Laplacian algorithm. The synthetic phase data were completely unwrapped by the proposed method for all the cases with velocity encoding (venc) as low as 20% of the maximum velocity and signal-to-noise ratio as low as 5. The in vitro Poiseuille flow data were completely unwrapped with a 60% increase in the velocity-to-noise ratio. For the in-vivo aortic datasets with venc ratio less than 0.4, the proposed method significantly improved the success rate by as much as 40% and reduced the velocity error levels by a factor of 10 compared to the state-of-the-art method. The divergence-free constrained method exhibits reliability and robustness on phase unwrapping and shows improved accuracy of velocity and hemodynamic quantities by unwrapping the low-venc 4D flow MRI data.

Hemodynamic Analysis of Cerebral AVMs with 3D Phase-Contrast MR Imaging

BACKGROUND AND PURPOSE

The hemodynamics associated with cerebral AVMs have a significant impact on their clinical presentation. This study aimed to evaluate the hemodynamic features of AVMs using 3D phase-contrast MR imaging with dual velocity-encodings.

MATERIALS AND METHODS

Thirty-two patients with supratentorial AVMs who had not received any previous treatment and had undergone 3D phase-contrast MR imaging were included in this study. The nidus diameter and volume were measured for classification of AVMs (small, medium, or large). Flow parameters measured included apparent AVM inflow, AVM inflow index, apparent AVM outflow, AVM outflow index, and the apparent AVM inflow-to-outflow ratio. Correlation coefficients between the nidus volume and each flow were calculated. The flow parameters between small and other AVMs as well as between nonhemorrhagic and hemorrhagic AVMs were compared.

RESULTS

Patients were divided into hemorrhagic (n = 8) and nonhemorrhagic (n = 24) groups. The correlation coefficient between the nidus volume and the apparent AVM inflow and outflow was .83. The apparent AVM inflow and outflow in small AVMs were significantly smaller than in medium AVMs (P < .001 for both groups). The apparent AVM inflow-to-outflow ratio was significantly larger in the hemorrhagic AVMs than in the nonhemorrhagic AVMs (P = .02).

CONCLUSIONS

The apparent AVM inflow-to-outflow ratio was the only significant parameter that differed between nonhemorrhagic and hemorrhagic AVMs, suggesting that a poor drainage system may increase AVM pressure, potentially causing cerebral hemorrhage.

Pseudo-Enhancement in Intracranial Aneurysms on Black-Blood MRI: Effects of Flow Rate, Spatial Resolution, and Additional Flow Suppression

BACKGROUND

Vessel-wall enhancement (VWE) on black-blood MRI (BB MRI) has been proposed as an imaging marker for a higher risk of rupture and associated with wall inflammation. Whether VWE is causally linked to inflammation or rather induced by flow phenomena has been a subject of debate.

PURPOSE

To study the effects of slow flow, spatial resolution, and motion-sensitized driven equilibrium (MSDE) preparation on signal intensities in BB MRI of patient-specific aneurysm flow models.

STUDY TYPE

Prospective.

SUBJECTS/FLOW ANEURYSM MODEL/VIRTUAL VESSELS

Aneurysm flow models based on 3D rotational angiography datasets of three patients with intracranial aneurysms were 3D printed and perfused at two different flow rates, with and without Gd-containing contrast agent.

FIELD STRENGTH/SEQUENCE

Variable refocusing flip angle 3D fast-spin echo sequence at 3 T with and without MSDE with three voxel sizes ((0.5 mm)³ , (0.7 mm)³ , and (0.9 mm)³ ); time-resolved with phase-contrast velocity-encoding 3D spoiled gradient echo sequence (4D flow MRI).

ASSESSMENT

Three independent observers performed a qualitative visual assessment of flow patterns and signal enhancement. Quantitative analysis included voxel-wise evaluation of signal intensities and magnitude velocity distributions in the aneurysm.

STATISTICAL TESTS

Kruskal-Wallis test, potential regressions.

RESULTS

A hyperintense signal in the lumen and adjacent to the aneurysm walls on BB MRI was colocalized with slow flow. Signal intensities increased by a factor of 2.56 ± 0.68 (P < 0.01) after administering Gd contrast. After Gd contrast administration, the signal was suppressed most in conjunction with high flows and with MSDE (2.41 ± 2.07 for slow flow without MSDE, and 0.87 ± 0.99 for high flow with MSDE). A clear result was not achieved by modifying the spatial resolution .

DATA CONCLUSIONS

Slow-flow phenomena contribute substantially to aneurysm enhancement and vary with MRI parameters. This should be considered in the clinical setting when assessing VWE in patients with an unruptured aneurysm.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 2.

A phantom study comparing radial trajectories for accelerated cardiac 4D flow MRI against a particle imaging velocimetry reference

PURPOSE

Radial sampling is one method to accelerate 4D flow MRI acquisition, making feasible dual-velocity encoding (Venc) assessment of slow flow in the left ventricle (LV). Here, two radial trajectories are compared in vitro for this application: 3D radial (phase-contrast vastly undersampled isotropic projection, PC-VIPR) versus stack of stars (phase-contrast stack of stars, PC-SOS), with benchtop particle imaging velocimetry (PIV) serving as a reference standard.

METHODS

The study contained three steps: (1) Construction of an MRI- and PIV-compatible LV model from a healthy adult's CT images. (2) In vitro PIV using a pulsatile flow pump. (3) In vitro dual-Venc 4D flow MRI using PC-VIPR and PC-SOS (two repeat experiments). Each MR image set was retrospectively undersampled to five effective scan durations and compared with the PIV reference. The root-mean-square velocity vector difference (RMSE) between MRI and PIV images was compared, along with kinetic energy (KE) and wall shear stress (WSS).

RESULTS

RMSE increased as scan time decreased for both MR acquisitions. RMSE was 3% lower in PC-SOS images than PC-VIPR images in 30-min scans (3.8 vs. 3.9 cm/s) but 98% higher in 2.5-min scans (9.5 vs. 4.8 cm/s). PIV intrasession repeatability showed a RMSE of 4.4 cm/s, reflecting beat-to-beat flow variation, while MRI had intersession RMSEs of 3.8/3.5 cm/s for VIPR/SOS, respectively. Speed, KE, and WSS were overestimated voxel-wise in 30-min MRI scans relative to PIV by 0.4/0.3 cm/s, 0.2/0.1 μJ/mL, and 36/43 mPa, respectively, for VIPR/SOS.

CONCLUSIONS

PIV is feasible for application-specific 4D flow MRI protocol optimization. PC-VIPR is better-suited to dual-Venc LV imaging with short scan times.

Quantification of the Hemodynamic Changes of Cirrhosis with Free-Breathing Self-Navigated MRI

BACKGROUND

Non-invasive assessment of the hemodynamic changes of cirrhosis might help guide management of patients with liver disease but are currently limited.

PURPOSE

To determine whether free-breathing 4D flow MRI can be used to quantify the hemodynamic effects of cirrhosis and introduce hydraulic circuit indexes of severity.

STUDY TYPE

Retrospective.

POPULATION

Forty-seven patients including 26 with cirrhosis.

FIELD STRENGTH/SEQUENCE

3 T/free-breathing 4D flow MRI with soft gating and golden-angle view ordering.

ASSESSMENT

Measurements of the supra-celiac abdominal aorta, supra-renal abdominal aorta (SRA), celiac trunk (CeT), superior mesenteric artery (SMA), splenic artery (SpA), common hepatic artery (CHA), portal vein (PV), and supra-renal inferior vena cava (IVC) were made by two radiologists. Measures of hepatic vascular resistance (hepatic arterial relative resistance [HARR]; portal resistive index [PRI]) were proposed and calculated.

STATISTICAL ANALYSIS

Bland-Altman, Pearson's correlation, Tukey's multiple comparison, and Cohen's kappa. P < 0.05 was considered significant.

RESULTS

Forty-four of 47 studies yielded adequate image quality for flow quantification (94%). Arterial structures showed high inter-reader concordance (range; ρ = 0.948-0.987) and the IVC (ρ = 0.972), with moderate concordance in the PV (ρ = 0.866). Conservation of mass analysis showed concordance between large vessels (SRA vs. IVC; ρ = 0.806), small vessels (celiac vs. CHA + SpA; ρ = 0.939), and across capillary beds (CeT + SMA vs. PV; ρ = 0.862). Splanchnic flow was increased in patients with portosystemic shunting (PSS) relative to control patients and patients with cirrhosis without PSS (P < 0.05, difference range 0.11-0.68 liter/m). HARR was elevated and PRI was decreased in patients with PSS (3.55 and 1.49, respectively) compared to both the control (2.11/3.18) and non-PSS (2.11/2.35) cohorts.

DATA CONCLUSION

4D flow MRI with self-navigation was technically feasible, showing promise in quantifying the hemodynamic effects of cirrhosis. Proposed quantitative metrics of hepatic vascular resistance correlated with PSS.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2.

4D flow MRI for non-invasive measurement of blood flow in the brain: A systematic review

The brain's vasculature is essential for brain health and its dysfunction contributes to the onset and development of many dementias and neurological disorders. While numerous in vivo imaging techniques exist to investigate cerebral haemodynamics in humans, phase-contrast magnetic resonance imaging (MRI) has emerged as a reliable, non-invasive method of quantifying blood flow within intracranial vessels. In recent years, an advanced form of this method, known as 4D flow, has been developed and utilised in patient studies, where its ability to capture complex blood flow dynamics within any major vessel across the acquired volume has proved effective in collecting large amounts of information in a single scan. While extremely promising as a method of examining the vascular system's role in brain-related diseases, the collection of 4D data can be time-consuming, meaning data quality has to be traded off against the acquisition time. Here, we review the available literature to examine 4D flow's capabilities in assessing physiological and pathological features of the cerebrovascular system. Emerging techniques such as dynamic velocity-encoding and advanced undersampling methods, combined with increasingly high-field MRI scanners, are likely to bring 4D flow to the forefront of cerebrovascular imaging studies in the years to come.

Velocity quantification in 44 healthy volunteers using accelerated multi-VENC 4D flow CMR

BACKGROUND

To evaluate the feasibility of a k-t accelerated multi-VENC 4D phase contrast flow MRI acquisition of the main heart-surrounding vessels, its benefits over a traditional single-VENC acquisition and to present reference flow and velocity values in a large cohort of volunteers.

METHODS

44 healthy volunteers were examined on a 3 T MRI scanner (Ingenia, Philips, Best, The Netherlands). 4D flow measurements were obtained with a FOV including the aorta and the pulmonary arteries. VENC values were set to 40, 100 and 200 cm/s and unfolded based on an MRI signal model. Unfolded multi-VENC data was compared to the single-VENC with VENC 200 cm/s. Flow and velocity quantification was performed in several regions of interest (ROI) placed in the ascending aorta and in the main pulmonary artery. Conservation of mass analysis was performed for single- and multi-VENC datasets. Values for mean and maximal flow velocity and stroke volume were calculated and compared to the literature.

RESULTS

Mean scan time was 13.8 ± 4 min. Differences between stroke volumes between the ascending aorta and the main pulmonary artery were significantly lower in multi-VENC datasets compared to single-VENC datasets (9.6 ± 7.8 mL vs. 25.4 ± 26.4 mL, p < 0.001). This was also true for differences in stroke volume between up- and downstream ROIs in the ascending aorta and pulmonary artery. Values for mean and maximal velocities and stroke volume were in-line with previous studies. To highlight potential clinical applications two exemplary 4D flow measurements in patients with different pathologies are shown and compared to single-VENC datasets.

CONCLUSIONS

k-t accelerated multi-VENC 4D phase contrast flow MRI acquisition of the great vessels is feasible in a clinically acceptable scan duration. It offers improvements over traditional single-VENC 4D flow, expectedly being valuable when vessels with different flow velocities or complex flow phenomena are evaluated.

The impact of 4D flow displacement artifacts on wall shear stress estimation

PURPOSE

To investigate the amplitude and spatial distribution of errors in wall shear stress (WSS) values derived from 4D flow measurements caused by displacement artifacts intrinsic to the 4D flow acquisition.

METHODS

Phase-contrast MRI velocimetry was performed in a model of a stenotic aorta using two different timing schemes, both of which are commonly applied in vivo but differ in their resulting displacement artifacts. Whereas one scheme is optimized to minimize the duration of the encoding gradients (herein called FAST), the other aims to specifically minimize displacement artifacts by synchronizing all three spatial-encoding time points (called ECHO). WSS estimates were calculated and compared to unbiased WSS values obtained by a 5-hour single-point imaging acquisition. In addition, MRI simulations based on computational fluid dynamics data were carried out to investigate the impact of gradient timings corresponding to different spatial resolutions.

RESULTS

4D flow displacement artifacts were found to have an impact on the quantified WSS peak values, spatial location, and overall WSS pattern. FAST leads to the underestimation of local WSS values in the phantom arch by up to 90%. Moreover, the corresponding WSS estimates depend on the image orientation. This effect was avoided using ECHO, which, however, results in biased WSS values within the stenosis, yielding an underestimation of peak WSS by up to 17%. Computational fluid dynamics-based simulation results show that the bias in WSS due to displacement artifacts increases with increasing spatial resolution, thus counteracting the resolution benefit for WSS due to reduced partial volume effects and segmentation errors.

CONCLUSIONS

4D flow displacement artifacts can significantly impact the WSS estimates and depend on the timing scheme as well as potentially the image orientation. Whereas FAST might allow correct WSS estimation for lower resolutions, ECHO is recommended especially when spatial resolutions of 1 mm and smaller are used. Users need to be aware of this nonnegligible effect, particularly when conducting inter-site studies or studies between vendors. The timing scheme should thus be explicitly mentioned in publications.