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2D cine phase contrast (CPC) MRI provides quantitative information on blood velocity and flow within the human vasculature. However, data acquisition is time‐consuming, motivating the reconstruction of the velocity field from undersampled measurements to reduce scan times. In this work, neural fields are proposed as a continuous spatiotemporal parametrization of complex‐valued images, jointly modeling magnitude and phase across multiple echoes to enable velocity estimation, and leveraging their inductive bias for the reconstruction of the velocity data. Additionally, to compensate for the oversmoothing tendency observed in neural‐field reconstructions under severe undersampling, a simple voxel‐based postprocessing step is introduced. The method is validated numerically in Cartesian and radial k‐space with both high and low temporal resolution data. This approach achieves accurate reconstructions at high acceleration factors, with low errors even at 32 and 64 undersampling for the high temporal resolution data, and 16 for the low temporal resolution data, and consistently outperforms classical locally low‐rank regularized voxel‐based methods in both flow estimates and anatomical depiction.

Background: The assessment of Fontan circuit’s flow is traditionally evaluated by multiple through-plane phase-contrast MRI acquisitions (2D flow), while recently, a single volumetric 4D-flow MRI acquisition is emerging as a comprehensive tool for the hemodynamic evaluation in congenital heart diseases. Purpose: To compare 2D and 4D-flow MRI measurements in patients after Fontan palliation and to evaluate parameters affecting potential disagreement. Methods: 39 patients after Fontan palliation (23 males, age 22 ± 11 years) who underwent cardiac MRI with 2D and 4D-flow MRI acquisition were included in the study. In all patients, blood flow quantification in the Fontan circuit and aorta by 2D flow and by 4D flow MRI acquisition blinding to the 2D results was performed. The agreement between 2D and 4D-flow MRI was calculated as the intraclass correlation coefficient (ICC). The mean absolute differences between 4D and 2D flows were analyzed using linear regression models. Results: 4D-flow MRI acquisition time was slightly lower than 2D (7.6 ± 1.8 min vs. 9.4 ± 3.3 min, p = 0.03). Flow was slightly predominant in the right pulmonary artery (58% of total pulmonary flow). Conduit/tunnel-pulmonary arteries flow accounted for 60% of the Fontan circuit. Agreement between 2D and 4D was overall good-to-excellent from ICC: 0.817 95% CI: 0.637–0.907 to 0.932 95% CI: 0.866–0.965. There was no significant influence of evaluated parameters on the agreement on 4D and 2D flow. Conclusions: 4D-flow MRI represents a valid tool in Fontan’s flow quantification. Further larger studies are needed to confirm our results and to evaluate the impact of advanced 4D-flow MRI parameters on the prognostic stratification in patients after Fontan palliation.

Magnetic resonance imaging (MRI) can potentially be used for non-invasive screening of patients with stable angina pectoris to identify probable obstructive coronary artery disease. MRI-based coronary blood flow quantification has to date only been performed in a 2D fashion, limiting its clinical applicability. In this study, we propose a framework for coronary blood flow quantification using accelerated 4D flow MRI with respiratory motion correction and compressed sensing image reconstruction. We investigate its feasibility and repeatability in healthy subjects at rest. Fourteen healthy subjects received 8 times-accelerated 4D flow MRI covering the left coronary artery (LCA) with an isotropic spatial resolution of 1.0 mm 3 . Respiratory motion correction was performed based on 1) lung-liver navigator signal, 2) real-time monitoring of foot-head motion of the liver and LCA by a separate acquisition, and 3) rigid image registration to correct for anterior-posterior motion. Time-averaged diastolic LCA flow was determined, as well as time-averaged diastolic maximal velocity (V MAX ) and diastolic peak velocity (V PEAK ). 2D flow MRI scans of the LCA were acquired for reference. Scan-rescan repeatability and agreement between 4D flow MRI and 2D flow MRI were assessed in terms of concordance correlation coefficient (CCC) and coefficient of variation (CV). The protocol resulted in good visibility of the LCA in 11 out of 14 subjects (six female, five male, aged 28 ± 4 years). The other 3 subjects were excluded from analysis. Time-averaged diastolic LCA flow measured by 4D flow MRI was 1.30 ± 0.39 ml/s and demonstrated good scan-rescan repeatability (CCC/CV = 0.79/20.4%). Time-averaged diastolic V MAX (17.2 ± 3.0 cm/s) and diastolic V PEAK (24.4 ± 6.5 cm/s) demonstrated moderate repeatability (CCC/CV = 0.52/19.0% and 0.68/23.0%, respectively). 4D flow- and 2D flow-based diastolic LCA flow agreed well (CCC/CV = 0.75/20.1%). Agreement between 4D flow MRI and 2D flow MRI was moderate for both diastolic V MAX and V PEAK (CCC/CV = 0.68/20.3% and 0.53/27.0%, respectively). In conclusion, the proposed framework of accelerated 4D flow MRI equipped with respiratory motion correction and compressed sensing image reconstruction enables repeatable diastolic LCA flow quantification that agrees well with 2D flow MRI.

Blood flow velocity in the cerebral perforating arteries can be quantified in a two-dimensional plane with phase contrast magnetic imaging (2D PC-MRI). The velocity pulsatility index (PI) can inform on the stiffness of these perforating arteries, which is related to several cerebrovascular diseases. Currently, there is no open-source analysis tool for 2D PC-MRI data from these small vessels, impeding the usage of these measurements. In this study we present the Small vessEL MArker (SELMA) analysis software as a novel, user-friendly, open-source tool for velocity analysis in cerebral perforating arteries. The implementation of the analysis algorithm in SELMA was validated against previously published data with a Bland–Altman analysis. The inter-rater reliability of SELMA was assessed on PC-MRI data of sixty participants from three MRI vendors between eight different sites. The mean velocity (v mean ) and velocity PI of SELMA was very similar to the original results (v mean : mean difference ± standard deviation: 0.1 ± 0.8 cm/s; velocity PI: mean difference ± standard deviation: 0.01 ± 0.1) despite the slightly higher number of detected vessels in SELMA (N detected : mean difference ± standard deviation: 4 ± 9 vessels), which can be explained by the vessel selection paradigm of SELMA. The Dice Similarity Coefficient of drawn regions of interest between two operators using SELMA was 0.91 (range 0.69–0.95) and the overall intra-class coefficient for N detected , v mean , and velocity PI were 0.92, 0.84, and 0.85, respectively. The differences in the outcome measures was higher between sites than vendors, indicating the challenges in harmonizing the 2D PC-MRI sequence even across sites with the same vendor. We show that SELMA is a consistent and user-friendly analysis tool for small cerebral vessels.

To compare 4D flow magnetic resonance imaging (MRI) and 2D phase contrast (PC) MRI when evaluating bicuspid (BAV) and tricuspid (TAV) aortic valves. A total of 83 subjects (35 BAV, 48 TAV) were explored with 4D flow and 2D PC MRI. Systolic peak velocity, peak flow and regurgitation fraction were analysed at two pre-defined aortic levels (aortic root, mid-tubular). Furthermore, the two methods of 4D flow analysis (Heart and Artery) were compared. Correlation between the 2D PC MRI and 4D flow MRI derived parameters ranged from moderate (R=0.58) to high (R=0.90). 4D flow MRI yielded significantly higher peak velocities in the tubular aorta in both groups. Regarding the aortic root, peak velocities were significantly higher in the TAV group with 4D flow MRI, but in the BAV group 4D flow MRI yielded non-significantly lower values. Findings on peak flow differences between the two modalities followed the same pattern as the differences in peak velocities. 4D flow MRI derived regurgitation fraction values were lower in both locations in both groups. Interobserver agreement for different 4D flow MRI acquired parameters varied from poor (ICC=0.07) to excellent (ICC=1.0) in the aortic root, and it was excellent in the tubular aorta (ICC=0.8-1.0). 4D flow MRI seems to be accurate in comparison to 2D PC MRI in normal aortic valves and in BAV with mild to moderate stenosis. However, the varying interobserver reproducibility and impaired accuracy at higher flow velocities should be taken into account in clinical practice when using the 4D flow method.

This study investigates the crucial factors influencing the end-systolic and end-diastolic volumes in MRI volumetry and their direct effects on the derived functional parameters. Through the simultaneous acquisition of 2D-cine and 3D whole-heart slices in end-diastole and end-systole, we present a novel direct comparison of the volumetric measurements from both methods. A prospective study was conducted with 18 healthy participants. Both 2D-cine and 3D whole-heart sequences were obtained. Despite the differences in the creation of 3D volumes and trigger points, the impact on the LV volume was minimal (134.9 mL ± 16.9 mL vs. 136.6 mL ± 16.6 mL, p < 0.01 for end-diastole; 50.6 mL ± 11.0 mL vs. 51.6 mL ± 11.2 mL, p = 0.03 for end-systole). In our healthy patient cohort, a systematic underestimation of the end-systolic volume resulted in a significant overestimation of the SV (5.6 mL ± 2.6 mL, p < 0.01). The functional calculations from the 3D whole-heart method proved to be highly accurate and correlated well with function measurements from the phase-contrast sequences. Our study is the first to demonstrate the superiority of 3D whole-heart volumetry over 2D-cine volumetry and sheds light on the systematic error inherent in 2D-cine measurements.

This study aims to systematically verify if the simplified geometry and flow profile of the left ventricular outflow tract (LVOT) assumed in 2D echocardiography is appropriate while examining the utility of 4D flow MRI to assess valvular disease. This prospective study obtained same-day Doppler echocardiography and 4D flow MRI in 37 healthy volunteers (age: 51.9 ± 18.2, 20 females) and 7 aortic stenosis (AS) patients (age: 64.2 ± 9.6, 1 female). Two critical assumptions made in echocardiography for aortic valve area assessment were examined, i.e. the assumption of (1) a circular LVOT shape and (2) a flat velocity profile through the LVOT. 3D velocity and shape information obtained with 4D flow MRI was used as comparison. It was found that the LVOT area was lower (by 26.5% and 24.5%) and the velocity time integral (VTI) was higher (by 28.5% and 30.2%) with echo in the healthy and AS group, respectively. These competing errors largely cancelled out when examining individual and cohort averaged LVOT stroke volume. The LVOT area, VTI and stroke volume measured by echo and 4D flow MRI were 3.6 ± 0.7 vs. 4.9 ± 1.0 cm2 (p < 0.001), 21.2 ± 3.0 vs 15.2 ± 2.8 cm (p < 0.001), and 75.6 ± 15.6 vs 72.8 ± 14.1 ml (p = 0.3376), respectively. In the ensemble average of LVOT area and VTI, under- and over-estimation seem to compensate each other to result in a ‘realistic’ stroke volume. However, it is important to understand that this compensation may fail. 4D flow MRI provides a unique insight into this phenomenon.

We present a computational method for calculating the distribution of wall shear stress (WSS) in the aorta based on a velocity field obtained from two-dimensional (2D) phase-contrast magnetic resonance imaging (PC-MRI) data and a finite-element method. The WSS vector was obtained from a global least-squares stress-projection method. The method was benchmarked against the Womersley model, and the robustness was assessed by changing resolution, noise, and positioning of the vessel wall. To showcase the applicability of the method, we report the axial, circumferential and magnitude of the WSS using in-vivo data from five volunteers. Our results showed that WSS values obtained with our method were in good agreement with those obtained from the Womersley model. The results for the WSS contour means showed a systematic but decreasing bias when the pixel size was reduced. The proposed method proved to be robust to changes in noise level, and an incorrect position of the vessel wall showed large errors when the pixel size was decreased. In volunteers, the results obtained were in good agreement with those found in the literature. In summary, we have proposed a novel image-based computational method for the estimation of WSS on vessel sections with arbitrary cross-section geometry that is robust in the presence of noise and boundary misplacements.

We investigated association between hemodynamic characteristics and aortic dilatation in patients with severe aortic stenosis (AS). Eighty patients with severe AS (mean age, 67.2 ± 12.5 years) who underwent multi-detector computed tomography and phase-contrast magnetic resonance imaging at the ascending aorta were retrospectively analyzed. Patients with an ascending aorta diameter >4 cm had a significantly higher forward flow rate at systole (28.5 ± 6.0 vs. 36.2 ± 8.6 L min, P < 0.001), and retrograde flow rate at systole (11.3 ± 4.2 vs. 18.8 ± 5.8 L min, P < 0.001), fractional reverse ratio (a ratio of retrograde flow rate to forward flow rate; 34.1 ± 11.9% vs. 43.5 ± 18.0%, P = 0.014), flow skewness R skewness (a ratio of sum of forward and retrograde systole flow to net systole flow rate; 2.4 ± 0.7 vs. 3.2 ± 1.0, P < 0.001). The presence of bicuspid aortic valve (BAV; odds ratio [OR] 72.01, 95% confidence interval [CI] 10.57–490.46, P < 0.001), Left ventricular mass index (LVMI; OR 1.02 /g/m 2 ; CI 1.00–1.04, P = 0.043) and R skewness (OR 5.6 per 1, 95% CI 1.8–17.1, P = 0.001) were associated with aortic dilatation. BAV, LVMI, and increased R skewness in the ascending aorta are associated with aortic dilatation in patients with AS.

Because there are no radioactive hydrogen isotopes which can be used for clinical examinations, deuterium as a non-radioactive, freely diffusible tracer has some advantages compared with the radioactive tracers in the measurement of blood flow parameters. A non-invasive technique to estimate the mean tissue blood flow parameter in vivo was developed by using deuterium nuclear magnetic resonance (NMR) imaging in rat. We obtained the NMR signal changes from deuterium NMR images in nine male Wister rats after intravenous injection of D2O and applied exponential curve fitting analyses to calculate blood flow parameters of the brain, heart and skeletal muscle. While fitting the reducing of the monoexponential function yielded a blood flow parameter of 27.9 +/- 1.6 ml/min/100 g tissue weight for the brain and 46.7 +/- 3.7 ml/min/100 g tissue weight for the heart, fitting the early reducing of the signal intensity of the biexponential function yielded a blood flow parameter of 95.6 +/- 10.9 ml/min/100 g tissue weight for the brain and 108.0 +/- 13.1 ml/min/100 g tissue weight for the heart. The mean muscle blood flow parameter determined by the monoexponential uptake function was 43.8 +/- 7.3 ml/min/100 g tissue weight. The blood flow parameter measurement by means of an imaging coil for deuterium is less invasive and reflects the mean tissue blood flow parameter for the entire tissue sample more homogeneously than spectroscopic monitoring.