Aortic Valve Stenosis Causes Accumulation of Extracellular Hemoglobin and Systemic Endothelial Dysfunction.

BACKGROUND: Whether aortic valve stenosis (AS) can adversely affect systemic endothelial function independently of standard modifiable cardiovascular risk factors is unknown. METHODS: We therefore investigated endothelial and cardiac function in an experimental model of AS mice devoid of standard modifiable cardiovascular risk factors and human cohorts with AS scheduled for transcatheter aortic valve replacement. Endothelial function was determined by flow-mediated dilation using ultrasound. Extracellular hemoglobin (eHb) concentrations and NO consumption were determined in blood plasma of mice and humans by ELISA and chemiluminescence. This was complemented by measurements of aortic blood flow using 4-dimensional flow acquisition by magnetic resonance imaging and computational fluid dynamics simulations. The effects of plasma and red blood cell (RBC) suspensions on vascular function were determined in transfer experiments in a murine vasorelaxation bioassay system. RESULTS: In mice, the induction of AS caused systemic endothelial dysfunction. In the presence of normal systolic left ventricular function and mild hypertrophy, the increase in the transvalvular gradient was associated with elevated eryptosis, increased eHb and plasma NO consumption; eHb sequestration by haptoglobin restored endothelial function. Because the aortic valve orifice area in patients with AS decreased, postvalvular mechanical stress in the central ascending aorta increased. This was associated with elevated eHb, circulating RBC-derived microvesicles, eryptotic cells, lower haptoglobin levels without clinically relevant anemia, and consecutive endothelial dysfunction. Transfer experiments demonstrated that reduction of eHb by treatment with haptoglobin or elimination of fluid dynamic stress by transcatheter aortic valve replacement restored endothelial function. In patients with AS and subclinical RBC fragmentation, the remaining circulating RBCs before and after transcatheter aortic valve replacement exhibited intact membrane function, deformability, and resistance to osmotic and hypoxic stress. CONCLUSIONS: AS increases postvalvular swirling blood flow in the central ascending aorta, triggering RBC fragmentation with the accumulation of hemoglobin in the plasma. This increases NO consumption in blood, thereby limiting vascular NO bioavailability. Thus, AS itself promotes systemic endothelial dysfunction independent of other established risk factors. Transcatheter aortic valve replacement is capable of limiting NO scavenging and rescuing endothelial function by realigning postvalvular blood flow to near physiological patterns. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT05603520. URL: https://www.clinicaltrials.gov; Unique identifier: NCT01805739.

Higher intracranial arterial pulsatility is associated with presumed imaging markers of the glymphatic system: An explorative study.

BACKGROUND: Arterial pulsation has been suggested as a key driver of paravascular cerebrospinal fluid flow, which is the foundation of glymphatic clearance. However, whether intracranial arterial pulsatility is associated with glymphatic markers in humans has not yet been studied. METHODS: Seventy-three community participants were enrolled in the study. 4D phase-contrast magnetic resonance imaging (MRI) was used to quantify the hemodynamic parameters including flow pulsatility index (PIflow) and area pulsatility index (PIarea) from 13 major intracerebral arterial segments. Three presumed neuroimaging markers of the glymphatic system were measured: including dilation of perivascular space (PVS), diffusivity along the perivascular space (ALPS), and volume fraction of free water (FW) in white matter. We explored the relationships between PIarea, PIflow, and the presumed glymphatic markers, controlling for related covariates. RESULTS: PIflow in the internal carotid artery (ICA) C2 segment (OR, 1.05; 95 % CI, 1.01-1.10, per 0.01 increase in PI) and C4 segment (OR, 1.05; 95 % CI, 1.01-1.09) was positively associated with the dilation of basal ganglia PVS, and PIflow in the ICA C4 segment (OR, 1.06, 95 % CI, 1.02-1.10) was correlated with the dilation of PVS in the white matter. ALPS was associated with PIflow in the basilar artery (ß, -0.273, p, 0.046) and PIarea in the ICA C2 (ß, -0.239, p, 0.041) and C7 segments (ß, -0.238, p, 0.037). CONCLUSIONS: Intracranial arterial pulsatility was associated with presumed neuroimaging markers of the glymphatic system, but the results were not consistent across different markers. Further studies are warranted to confirm these findings.

Toward accurate and fast velocity quantification with 3D ultrashort TE phase-contrast imaging.

PURPOSE: Traditional phase-contrast MRI is affected by displacement artifacts caused by non-synchronized spatial- and velocity-encoding time points. The resulting inaccurate velocity maps can affect the accuracy of derived hemodynamic parameters. This study proposes and characterizes a 3D radial phase-contrast UTE (PC-UTE) sequence to reduce displacement artifacts. Furthermore, it investigates the displacement of a standard Cartesian flow sequence by utilizing a displacement-free synchronized-single-point-imaging MR sequence (SYNC-SPI) that requires clinically prohibitively long acquisition times. METHODS: 3D flow data was acquired at 3T at three different constant flow rates and varying spatial resolutions in a stenotic aorta phantom using the proposed PC-UTE, a Cartesian flow sequence, and a SYNC-SPI sequence as reference. Expected displacement artifacts were calculated from gradient timing waveforms and compared to displacement values measured in the in vitro flow experiments. RESULTS: The PC-UTE sequence reduces displacement and intravoxel dephasing, leading to decreased geometric distortions and signal cancellations in magnitude images, and more spatially accurate velocity quantification compared to the Cartesian flow acquisitions; errors increase with velocity and higher spatial resolution. CONCLUSION: PC-UTE MRI can measure velocity vector fields with greater accuracy than Cartesian acquisitions (although pulsatile fields were not studied) and shorter scan times than SYNC-SPI. As such, this approach is superior to traditional Cartesian 3D and 4D flow MRI when spatial misrepresentations cannot be tolerated, for example, when computational fluid dynamics simulations are compared to or combined with in vitro or in vivo measurements, or regional parameters such as wall shear stress are of interest.

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.

Evaluating a Phase-Specific Approach to Aortic Flow: A 4D Flow MRI Study.

BACKGROUND: Aortic flow parameters can be quantified using 4D flow MRI. However, data are sparse on how different methods of analysis influence these parameters and how these parameters evolve during systole. PURPOSE: To assess multiphase segmentations and multiphase quantification of flow-related parameters in aortic 4D flow MRI. STUDY TYPE: Prospective. POPULATION: 40 healthy volunteers (50% male, 28.9 ± 5.0 years) and 10 patients with thoracic aortic aneurysm (80% male, 54 ± 8 years). FIELD STRENGTH/SEQUENCE: 4D flow MRI with a velocity encoded turbo field echo sequence at 3 T. ASSESSMENT: Phase-specific segmentations were obtained for the aortic root and the ascending aorta. The whole aorta was segmented in peak systole. In all aortic segments, time to peak (TTP; for flow velocity, vorticity, helicity, kinetic energy, and viscous energy loss) and peak and time-averaged values (for velocity and vorticity) were calculated. STATISTICAL TESTS: Static vs. phase-specific models were assessed using Bland-Altman plots. Other analyses were performed using phase-specific segmentations for aortic root and ascending aorta. TTP for all parameters was compared to TTP of flow rate using paired t-tests. Time-averaged and peak values were assessed using Pearson correlation coefficient. P < 0.05 was considered statistically significant. RESULTS: In the combined group, velocity in static vs. phase-specific segmentations differed by 0.8 cm/sec for the aortic root, and 0.1 cm/sec (P = 0.214) for the ascending aorta. Vorticity differed by 167 sec-1 mL-1 (P = 0.468) for the aortic root, and by 59 sec-1 mL-1 (P = 0.481) for the ascending aorta. Vorticity, helicity, and energy loss in the ascending aorta, aortic arch, and descending aorta peaked significantly later than flow rate. Time-averaged velocity and vorticity values correlated significantly in all segments. DATA CONCLUSION: Static 4D flow MRI segmentation yields comparable results as multiphase segmentation for flow-related parameters, eliminating the need for time-consuming multiple segmentations. However, multiphase quantification is necessary for assessing peak values of aortic flow-related parameters. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY STAGE: 3.

Differentiation Between the Low and High Trans-Stenotic Pressure Gradient in Patients With Idiopathic Intracranial Hypertension Using 4D Flow MRI-Derived Hemodynamic Parameters.

BACKGROUND: Trans-stenotic pressure gradient (TPG) measurement is essential for idiopathic intracranial hypertension (IIH) patients with transverse sinus (TS) stenosis. Four-D flow MRI may provide a noninvasive imaging method for differentiation of IIH patients with different TPG. PURPOSE: To investigate the associations between 4D flow parameters and TPG, and to evaluate the diagnostic performance of 4D flow parameters in differentiating patients with high TPG (GroupHP) from low TPG (GroupLP). STUDY TYPE: Prospective. POPULATION: 31 IIH patients with TS stenosis (age, 38 ± 12 years; 23 females) and 5 healthy volunteers (age, 25 ± 1 years; 2 females). FIELD STRENGTH/SEQUENCE: 3T, 3D phase contrast MR venography, and gradient recalled echo 4D flow sequences. ASSESSMENT: Scan-rescan reproducibility of 4D flow parameters were performed. The correlation between TPG and flow parameters was analyzed. The netflow and velocity difference between inflow plane, outflow plane, and the stenosis plane were calculated and compared between GroupHP and GroupLP. STATISTICAL TESTS: Pearson's correlation or Spearman's rank correlation coefficient, Independent samples t-test or Wilcoxon rank-sum test, Intra-class correlation coefficient (ICC), Bland-Altman analyses, Receiver operating characteristic curves. A P value <0.05 was considered significant. RESULTS: Significant correlations were found between TPG and netflow parameters including Favg,out-s, Favg,in-s, Fmax,out-s, and Fmax,in-s (r = 0.525-0.565). Significant differences were found in Favg,out-s, Fmax,out-s, Favg,in-s, and Fmax,in-s between GroupHP and GroupLP. Using the cut-off value of 2.19 mL/sec, the Favg,out-s showed good estimate performance in distinguishing GroupHP from GroupLP (AUC = 0.856). The ICC (ranged 0.905-0.948) and Bland-Altman plots indicated good scan-rescan reproducibility. DATA CONCLUSIONS: 4D flow MRI derived flow parameters showed good correlations with TPG in IIH patients with TS stenosis. Netflow difference between outflow and stenosis location at TS shows the good performance in differentiating GroupHP and GroupLP cases. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 2.

Evaluation of 4D Flow MRI-Derived Relative Residence Time as a Marker for Cirrhosis Associated Portal Vein Thrombosis.

BACKGROUND: Portal vein thrombosis (PVT) is thought to arise from stagnant blood flow, yet conclusive evidence is lacking. Relative residence time (RRT) assessed using 4D Flow MRI may offer insight into portal flow stagnation. PURPOSE: To explore the relationship between RRT values and the presence of PVT in cirrhotic participants. STUDY TYPE: Prospective. POPULATION: Forty-eight participants with liver cirrhosis (27 males, median age 67 years [IQR: 57-73]) and 20 healthy control participants (12 males, median age 45 years [IQR: 40-54]). FIELD STRENGTH/SEQUENCE: 3 T/4D Flow MRI. ASSESSMENT: Laboratory (liver and kidney function test results and platelet count) and clinical data (presence of tumors and other imaging findings), and portal hemodynamics derived from 4D Flow MRI (spatiotemporally averaged RRT [RRT-mean], flow velocity, and flow rate) were analyzed. STATISTICAL TESTS: We used multivariable logistic regression, adjusted by selected covariates through the Lasso method, to explore whether RRT-mean is an independent risk factor for PVT. The area under the ROC curve (AUC) was also calculated to assess the model's discriminative ability. P < 0.05 indicated statistical significance. RESULTS: The liver cirrhosis group consisted of 16 participants with PVT and 32 without PVT. Higher RRT-mean values (odds ratio [OR] 11.4 [95% CI: 2.19, 118]) and lower platelet count (OR 0.98 per 1000 µL [95% CI: 0.96, 0.99]) were independent risk factors for PVT. The incorporation of RRT-mean (AUC, 0.77) alongside platelet count (AUC, 0.75) resulted in an AUC of 0.84. When including healthy control participants, RRT-mean had an adjusted OR of 12.4 and the AUC of the combined model (RRT-mean and platelet count) was 0.90. DATA CONCLUSION: Prolonged RRT values and low platelet count were significantly associated with the presence of PVT in cirrhotic participants. RRT values derived from 4D Flow MRI may have potential clinical relevance in the management of PVT. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Evaluation of Left Ventricular Flow Kinetic Energy by Four-Dimensional Blood Flow MRI in Nondialysis Chronic Kidney Disease Patients.

BACKGROUND: Chronic kidney disease (CKD) is associated with increased, and early cardiovascular disease risk. Changes in hemodynamics within the left ventricle (LV) respond to cardiac remodeling. The LV hemodynamics in nondialysis CKD patients are not clearly understood. PURPOSE: To use four-dimensional blood flow MRI (4D flow MRI) to explore changes in LV kinetic energy (KE) and the relationship between LV KE and LV remodeling in CKD patients. STUDY TYPE: Retrospective. POPULATION: 98 predialysis CKD patients (Stage 3: n = 21, stage 4: n = 21, and stage 5: n = 56) and 16 age- and sex-matched healthy controls. FIELD STRENGTH/SEQUENCE: 3.0 T/balanced steady-state free precession (SSFP) cine sequence, 4D flow MRI with a fast field echo sequence, T1 mapping with a modified Look-Locker SSFP sequence, and T2 mapping with a gradient recalled and spin echo sequence. ASSESSMENT: Demographic characteristics (age, sex, height, weight, blood pressure, heart rate, aortic regurgitation, and mitral regurgitation) and laboratory data (eGFR, Creatinine, hemoglobin, ferritin, transferrin saturation, potassium, and carbon dioxide bonding capacity) were extracted from patient records. Myocardial T1, T2, LV ejection fraction, end diastolic volume (EDV), end systolic volume, LV flow components (direct flow, delayed ejection, retained inflow, and residual volume) and KE parameters (peak systolic, systolic, diastolic, peak E-wave, peak A-wave, E/A ratio, and global) were assessed. The KE parameters were normalized to EDV (KEiEDV). Parameters were compared between disease stage in CKD patients, and between CKD patients and healthy controls. STATISTICAL TESTS: Differences in clinical and imaging parameters between groups were compared using one-way ANOVA, Kruskal Walls and Mann-Whitney U tests, chi-square test, and Fisher's exact test. Pearson or Spearman's correlation coefficients and multiple linear regression analysis were used to compare the correlation between LV KE and other clinical and functional parameters. A P-value of <0.05 was considered significant. RESULTS: Compared with healthy controls, peak systolic (24.76 ± 5.40 µJ/mL vs. 31.86 ± 13.18 µJ/mL), systolic (11.62 ± 2.29 µJ/mL vs. 15.27 ± 5.10 µJ/mL), diastolic (7.95 ± 1.92 µJ/mL vs. 13.33 ± 5.15 µJ/mL), peak A-wave (15.95 ± 4.86 µJ/mL vs. 31.98 ± 14.51 µJ/mL), and global KEiEDV (9.40 ± 1.64 µJ/mL vs. 14.02 ± 4.14 µJ/mL) were significantly increased and the KEiEDV E/A ratio (1.16 ± 0.67 vs. 0.69 ± 0.53) was significantly decreased in CKD patients. As the CKD stage progressed, both diastolic KEiEDV (10.45 ± 4.30 µJ/mL vs. 12.28 ± 4.85 µJ/mL vs. 14.80 ± 5.06 µJ/mL) and peak E-wave KEiEDV (15.30 ± 7.06 µJ/mL vs. 14.69 ± 8.20 µJ/mL vs. 19.33 ± 8.29 µJ/mL) increased significantly. In multiple regression analysis, global KEiEDV (ß* = 0.505; ß* = 0.328), and proportion of direct flow (ß* = -0.376; ß* = -0.410) demonstrated an independent association with T1 and T2 times. DATA CONCLUSION: 4D flow MRI-derived LV KE parameters show altered LV adaptations in CKD patients and correlate independently with T1 and T2 mapping that may represent myocardial fibrosis and edema. TECHNICAL EFFICACY: Stage 3.

Cerebral Sinus Hemodynamics in Adults Revealed by 4D Flow MRI.

BACKGROUND: The hemodynamics of the cerebral sinuses play a vital role in understanding blood flow-related diseases, yet the hemodynamics of the cerebral sinuses in normal adults remains an unresolved issue. PURPOSE: To evaluate hemodynamics in the cerebral sinus of adults using 4-dimensional flow MRI (4D Flow MRI). STUDY TYPE: Cross-sectional. POPULATION: Ninety-nine healthy volunteers (mean age, 42.88 ± 13.16 years old; females/males, 55/44). FIELD STRENGTH/SEQUENCE: 3 T/4D Flow MRI. ASSESSMENT: The blood flow velocity, average blood flow rate (Q), and vortexes at the superior sagittal sinus (SSS), straight sinus (STS), transverse sinus, sigmoid sinus, and jugular bulb of each volunteer were evaluated by two independent neuroradiologists. The relationship between the total cerebral Q and sex and age was also assessed. Twelve volunteers underwent two scans within a month. STATISTICAL TESTS: The intraclass correlation coefficient (ICC) evaluated the inter-observer agreement. Blood flow parameters among volunteers were compared by the independent-sample t-test or Mann-Whitney U test. The multiple linear regression equation was used to evaluate the relationship between total cerebral Q and age and sex. P < 0.05 indicated statistical significance. RESULTS: The test-retest and interobserver reliability of average velocity and Q were moderate to high (ICC: 0.54-0.99). Cerebral sinus velocity varied by segment and cardiac cycle. The SSS's velocity and Q increased downstream and Q near torcular herophili was 3.5 times that through the STS. The total cerebral Q decreased by 0.06 mL/s per year (ß = -0.06 ± 0.013) and was sex-independent within the group. Vortexes were found in 12.12%, 8.9%, and 59.8% of torcular herophili, transverse-sigmoid junction, and jugular bulb, respectively, and were related to higher upstream flow. DATA CONCLUSION: Cerebral sinuses could be measured visually and quantitatively in vivo by 4D Flow MRI, providing a basis for future research on pulsating tinnitus, multiple sclerosis, and other related diseases. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 1.

Prerequisites for Clinical Implementation of Whole-Heart 4D-Flow MRI: A Delphi Analysis.

Whole-heart 4D-flow MRI is a valuable tool for advanced visualization and quantification of blood flow in cardiovascular imaging. Despite advantages over 2D-phase-contrast flow, clinical implementation remains only partially exploited due to many hurdles in all steps, from image acquisition, reconstruction, postprocessing and analysis, clinical embedment, reporting, legislation, and regulation to data storage. The intent of this manuscript was 1) to evaluate the extent of clinical implementation of whole-heart 4D-flow MRI, 2) to identify hurdles hampering clinical implementation, and 3) to reach consensus on requirements for clinical implementation of whole-heart 4D-flow MRI. This study is based on Delphi analysis. This study involves a panel of 18 experts in the field on whole-heart 4D-flow MRI. The experience with and opinions of experts (mean 13 years of experience, interquartile range 6) in the field were aggregated. This study showed that among experts in the cardiovascular field, whole-heart 4D-flow MRI is currently used for both clinical and research purposes. Overall, the panelists agreed that major hurdles currently hamper implementation and utilization. The sequence-specific hurdles identified were long scan time and lack of standardization. Further hurdles included cumbersome and time-consuming segmentation and postprocessing. The study concludes that implementation of whole-heart 4D-flow MRI in clinical routine is feasible, but the implementation process is complex and requires a dedicated, multidisciplinary team. A predefined plan, including risk assessment and technique validation, is essential. The reported consensus statements may guide further tool development and facilitate broader implementation and clinical use. LEVEL OF EVIDENCE: NA TECHNICAL EFFICACY: Stage 5.

4D Flow Cardiac MR in Primary Mitral Regurgitation.

BACKGROUND: Four-dimensional-flow cardiac MR (4DF-MR) offers advantages in primary mitral regurgitation. The relationship between 4DF-MR-derived mitral regurgitant volume (MR-Rvol) and the post-operative left ventricular (LV) reverse remodeling has not yet been established. PURPOSE: To ascertain if the 4DF-MR-derived MR-Rvol correlates with the LV reverse remodeling in primary mitral regurgitation. STUDY TYPE: Prospective, single-center, two arm, interventional vs. nonintervention observational study. POPULATION: Forty-four patients (male N = 30; median age 68 [59-75]) with at least moderate primary mitral regurgitation; either awaiting mitral valve surgery (repair [MVr], replacement [MVR]) or undergoing "watchful waiting" (WW). FIELD STRENGTH/SEQUENCE: 5 T/Balanced steady-state free precession (bSSFP) sequence/Phase contrast imaging/Multishot echo-planar imaging pulse sequence (five shots). ASSESSMENT: Patients underwent transthoracic echocardiography (TTE), phase-contrast MR (PMRI), 4DF-MR and 6-minute walk test (6MWT) at baseline, and a follow-up PMRI and 6MWT at 6 months. MR-Rvol was quantified by PMRI, 4DF-MR, and TTE by one observer. The pre-operative MR-Rvol was correlated with the post-operative decrease in the LV end-diastolic volume index (LVEDVi). STATISTICAL TESTS: Included Student t-test/Mann-Whitney test/Fisher's exact test, Bland-Altman plots, linear regression analysis and receiver operating characteristic curves. Statistical significance was defined as P < 0.05. RESULTS: While Bland-Altman plots demonstrated similar bias between all the modalities, the limits of agreement were narrower between 4DF-MR and PMRI (bias 15; limits of agreement -36 mL to 65 mL), than between 4DF-MR and TTE (bias -8; limits of agreement -106 mL to 90 mL) and PMRI and TTE (bias -23; limits of agreement -105 mL to 59 mL). Linear regression analysis demonstrated a significant association between the MR-Rvol and the post-operative decrease in the LVEDVi, when the MR-Rvol was quantified by PMRI and 4DF-MR, but not by TTE (P = 0.73). 4DF-MR demonstrated the best diagnostic performance for reduction in the post-operative LVEDVi with the largest area under the curve (4DF-MR 0.83; vs. PMRI 0.78; and TTE 0.51; P = 0.89). DATA CONCLUSION: This study demonstrates the potential clinical utility of 4DF-MR in the assessment of primary mitral regurgitation. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 5.

Fully Automated Valve Segmentation for Blood Flow Assessment From 4D Flow MRI Including Automated Cardiac Valve Tracking and Transvalvular Velocity Mapping.

BACKGROUND: Automated 4D flow MRI valvular flow quantification without time-consuming manual segmentation might improve workflow. PURPOSE: Compare automated valve segmentation (AS) to manual (MS), and manually corrected automated segmentation (AMS), in corrected atrioventricular septum defect (c-AVSD) patients and healthy volunteers, for assessing net forward volume (NFV) and regurgitation fraction (RF). STUDY TYPE: Retrospective. POPULATION: 27 c-AVSD patients (median, 23 years; interquartile range, 16-31 years) and 24 healthy volunteers (25 years; 12.5-36.5 years). FIELD STRENGTH/SEQUENCE: Whole-heart 4D flow MRI and cine steady-state free precession at 3T. ASSESSMENT: After automatic valve tracking, valve annuli were segmented on time-resolved reformatted trans-valvular velocity images by AS, MS, and AMS. NFV was calculated for all valves, and RF for right and left atrioventricular valves (RAVV and LAVV). NFV variation (standard deviation divided by mean NFV) and NFV differences (NFV difference of a valve vs. mean NFV of other valves) expressed internal NFV consistency. STATISTICAL TESTS: Comparisons between methods were assessed by Wilcoxon signed-rank tests, and intra/interobserver variability by intraclass correlation coefficients (ICCs). P < 0.05 was considered statistically significant, with multiple testing correction. RESULTS: AMS mean analysis time was significantly shorter compared with MS (5.3 ± 1.6 minutes vs. 9.1 ± 2.5 minutes). MS NFV variation (6.0%) was significantly smaller compared with AMS (6.3%), and AS (8.2%). Median NFV difference of RAVV, LAVV, PV, and AoV between segmentation methods ranged from -0.7-1.0 mL, -0.5-2.8 mL, -1.1-3.6 mL, and - 3.1--2.1 mL, respectively. Median RAVV and LAVV RF, between 7.1%-7.5% and 3.8%-4.3%, respectively, were not significantly different between methods. Intraobserver/interobserver agreement for AMS and MS was strong-to-excellent for NFV and RF (ICC ≥0.88). DATA CONCLUSION: MS demonstrates strongest internal consistency, followed closely by AMS, and AS. Automated segmentation, with or without manual correction, can be considered for 4D flow MRI valvular flow quantification. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 3.

MRI Investigation of the Association of Left Atrial and Left Atrial Appendage Hemodynamics with Silent Brain Infarction.

BACKGROUND: Left atrial (LA) myopathy is thought to be associated with silent brain infarctions (SBI) through changes in blood flow hemodynamics leading to thrombogenesis. 4D-flow MRI enables in-vivo hemodynamic quantification in the left atrium (LA) and LA appendage (LAA). PURPOSE: To determine whether LA and LAA hemodynamic and volumetric parameters are associated with SBI. STUDY TYPE: Prospective observational study. POPULATION: A single-site cohort of 125 Participants of the multiethnic study of atherosclerosis (MESA), mean age: 72.3 ± 7.2 years, 56 men. FIELD STRENGTH/SEQUENCE: 1.5T. Cardiac MRI: Cine balanced steady state free precession (bSSFP) and 4D-flow sequences. Brain MRI: T1- and T2-weighted SE and FLAIR. ASSESSMENT: Presence of SBI was determined from brain MRI by neuroradiologists according to routine diagnostic criteria in all participants without a history of stroke based on the MESA database. Minimum and maximum LA volumes and ejection fraction were calculated from bSSFP data. Blood stasis (% of voxels <10 cm/sec) and peak velocity (cm/sec) in the LA and LAA were assessed by a radiologist using an established 4D-flow workflow. STATISTICAL TESTS: Student's t test, Mann-Whitney U test, one-way ANOVA, chi-square test. Multivariable stepwise logistic regression with automatic forward and backward selection. Significance level P < 0.05. RESULTS: 26 (20.8%) had at least one SBI. After Bonferroni correction, participants with SBI were significantly older and had significantly lower peak velocities in the LAA. In multivariable analyses, age (per 10-years) (odds ratio (OR) = 1.99 (95% confidence interval (CI): 1.30-3.04)) and LAA peak velocity (per cm/sec) (OR = 0.87 (95% CI: 0.81-0.93)) were significantly associated with SBI. CONCLUSION: Older age and lower LAA peak velocity were associated with SBI in multivariable analyses whereas volumetric-based measures from cardiac MRI or cardiovascular risk factors were not. Cardiac 4D-flow MRI showed potential to serve as a novel imaging marker for SBI. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Deep learning based automated left ventricle segmentation and flow quantification in 4D flow cardiac MRI.

BACKGROUND: 4D flow MRI enables assessment of cardiac function and intra-cardiac blood flow dynamics from a single acquisition. However, due to the poor contrast between the chambers and surrounding tissue, quantitative analysis relies on the segmentation derived from a registered cine MRI acquisition. This requires an additional acquisition and is prone to imperfect spatial and temporal inter-scan alignment. Therefore, in this work we developed and evaluated deep learning-based methods to segment the left ventricle (LV) from 4D flow MRI directly. METHODS: We compared five deep learning-based approaches with different network structures, data pre-processing and feature fusion methods. For the data pre-processing, the 4D flow MRI data was reformatted into a stack of short-axis view slices. Two feature fusion approaches were proposed to integrate the features from magnitude and velocity images. The networks were trained and evaluated on an in-house dataset of 101 subjects with 67,567 2D images and 3030 3D volumes. The performance was evaluated using various metrics including Dice, average surface distance (ASD), end-diastolic volume (EDV), end-systolic volume (ESV), LV ejection fraction (LVEF), LV blood flow kinetic energy (KE) and LV flow components. The Monte Carlo dropout method was used to assess the confidence and to describe the uncertainty area in the segmentation results. RESULTS: Among the five models, the model combining 2D U-Net with late fusion method operating on short-axis reformatted 4D flow volumes achieved the best results with Dice of 84.52% and ASD of 3.14 mm. The best averaged absolute and relative error between manual and automated segmentation for EDV, ESV, LVEF and KE was 19.93 ml (10.39%), 17.38 ml (22.22%), 7.37% (13.93%) and 0.07 mJ (5.61%), respectively. Flow component results derived from automated segmentation showed high correlation and small average error compared to results derived from manual segmentation. CONCLUSIONS: Deep learning-based methods can achieve accurate automated LV segmentation and subsequent quantification of volumetric and hemodynamic LV parameters from 4D flow MRI without requiring an additional cine MRI acquisition.

Comprehensive sex-specific and age-dependent analysis of 4D-flow MRI assessed aortic blood flow-related parameters in normal subjects using single-vendor MR systems and single-vendor software.

BACKGROUND: Aortic blood flow characterization by 4D flow MRI is increasingly performed in aneurysm research. A limited number of studies have established normal values that can aid the recognition of abnormal flow at an early stage. This study aims to establish additional sex-specific and age-dependent reference values for flow-related parameters in a large cohort of healthy adults. METHODS: 212 volunteers were included, and 191 volunteers completed the full study protocol. All underwent 4D flow MRI of the entire aorta. Quantitative values for velocity, vorticity, helicity, as well as total, circumferential, and axial wall shear stress [WSS] were determined for the aortic root [AoR], ascending aorta [AAo], aortic arch [AoA], descending [DAo], suprarenal [SRA], and infrarenal aorta [IRA]. Vorticity and helicity were indexed for segment volume (mL). RESULTS: The normal values were estimated per sex- and age-group, where significant differences between males (M) and females (F) were found only for specific age groups. More specifically, the following variables were significantly different after applying the false discovery rate correction for multiple testing: 1) velocity in the AAo and DAo in the 60-70 years age group (mean±SD: (M) 47.0 ± 8.2cm/s vs. (F) 38.4 ± 6.9cm/s, p=0.001 and, (M) 55.9 ± 9.9cm/s vs. (F) 46.5 ± 5.5cm/s, p=0.002), 2) normalized vorticity in AoR in the 50-59 years age group ((M) 27539 ± 5042s-1mL-1 vs. (F) 30849 ± 7285s-1mL-1, p=0.002), 3) axial WSS in the Aao in the 18-29 age group ((M) 1098 ± 203 mPa vs. (F) 921 ± 121 mPa, p=0.002). Good to strong negative correlations with age were seen for almost all variables, in different segments, and for both sexes. CONCLUSION: This study describes reference values for aortic flow-related parameters as acquired by 4D flow MRI. We observed limited differences between males and females. A negative relationship with age was seen for almost all flow-related parameters and segments.

Interval Changes in 4D Flow-Derived in vivo Hemodynamics Stratify Aortic Growth in Type B Aortic Dissection Patients.

BACKGROUND: Aortic diameter growth in type B aortic dissection (TBAD) is associated with progressive aortic dilation, resulting in increased mortality in patients with both de novo TBAD (dnTBAD) and residual dissection after type A dissection repair (rTAAD). Preemptive thoracic endovascular aortic repair may improve mortality in patients with TBAD, although it is unclear which patients may benefit most from early intervention. In vivo hemodynamic assessment using four-dimensional (4D) flow magnetic resonance imaging (MRI) has been used to characterize TBAD patients with growing aortas. In this longitudinal study, we investigated whether changes over time in 4D flow derived true and false lumen (TL, FL) hemodynamic parameters correlate with aortic growth rate which is a marker of increased risk. METHODS: We retrospectively identified TBAD patients with baseline and follow-up 4D flow MRI at least 120 days apart. Patients with TBAD intervention before baseline or between scans were excluded. 4D flow MRI data analysis included segmentation of the TL and FL, followed by voxel-wise calculation of TL and FL total kinetic energy (KE), maximum velocity (MV), mean forward flow (FF), and mean reverse flow (RF). Changes over time (Δ) were calculated for all hemodynamic parameters. Maximal diameter in the descending aorta was measured from MR angiogram images acquired at the time of 4D flow. Aortic growth rate was defined as the change in diameter divided by baseline diameter and standardized to scan interval. RESULTS: 32 patients met inclusion criteria (age: 56.9±14.1 years, Female: 13, n=19 rTAAD, n=13 dnTBAD). Mean follow up time was 538 days (range: 135-1689). Baseline aortic diameter did not correlate with growth rate. In the entire cohort, Δ FL MV (rho=0.37, p=.04) and Δ FL RF (rho=0.45, p=0.01) correlated with growth rate. In rTAAD only, Δ FL MV (rho=0.48, p=.04) and Δ FL RF (rho=0.51, p=0.03) correlated with growth rate, while in dnTBAD only, Δ TL KE (rho=0.63, p=.02) and Δ TL MV (rho=0.69, p=.01) correlated with growth rate. CONCLUSIONS: 4D flow derived longitudinal hemodynamic changes correlate with aortic growth rate in TBAD and may provide additional prognostic value for risk stratification. 4D flow MRI could be integrated into existing imaging protocols to allow for identification of TBAD patients who would benefit from preemptive surgical or endovascular intervention.

Combined free-running four-dimensional anatomical and flow magnetic resonance imaging with native contrast using Synchronization of Neighboring Acquisitions by Physiological Signals.

BACKGROUND: Four-dimensional (4D) flow magnetic resonance imaging (MRI) often relies on the injection of gadolinium- or iron-oxide-based contrast agents to improve vessel delineation. In this work, a novel technique is developed to acquire and reconstruct 4D flow data with excellent dynamic visualization of blood vessels but without the need for contrast injection. Synchronization of Neighboring Acquisitions by Physiological Signals (SyNAPS) uses pilot tone (PT) navigation to retrospectively synchronize the reconstruction of two free-running three-dimensional radial acquisitions, to create co-registered anatomy and flow images. METHODS: Thirteen volunteers and two Marfan syndrome patients were scanned without contrast agent using one free-running fast interrupted steady-state (FISS) sequence and one free-running phase-contrast MRI (PC-MRI) sequence. PT signals spanning the two sequences were recorded for retrospective respiratory motion correction and cardiac binning. The magnitude and phase images reconstructed, respectively, from FISS and PC-MRI, were synchronized to create SyNAPS 4D flow datasets. Conventional two-dimensional (2D) flow data were acquired for reference in ascending (AAo) and descending aorta (DAo). The blood-to-myocardium contrast ratio, dynamic vessel area, net volume, and peak flow were used to compare SyNAPS 4D flow with Native 4D flow (without FISS information) and 2D flow. A score of 0-4 was given to each dataset by two blinded experts regarding the feasibility of performing vessel delineation. RESULTS: Blood-to-myocardium contrast ratio for SyNAPS 4D flow magnitude images (1.5 ± 0.3) was significantly higher than for Native 4D flow (0.7 ± 0.1, p < 0.01) and was comparable to 2D flow (2.3 ± 0.9, p = 0.02). Image quality scores of SyNAPS 4D flow from the experts (M.P.: 1.9 ± 0.3, E.T.: 2.5 ± 0.5) were overall significantly higher than the scores from Native 4D flow (M.P.: 1.6 ± 0.6, p = 0.03, E.T.: 0.8 ± 0.4, p < 0.01) but still significantly lower than the scores from the reference 2D flow datasets (M.P.: 2.8 ± 0.4, p < 0.01, E.T.: 3.5 ± 0.7, p < 0.01). The Pearson correlation coefficient between the dynamic vessel area measured on SyNAPS 4D flow and that from 2D flow was 0.69 ± 0.24 for the AAo and 0.83 ± 0.10 for the DAo, whereas the Pearson correlation between Native 4D flow and 2D flow measurements was 0.12 ± 0.48 for the AAo and 0.08 ± 0.39 for the DAo. Linear correlations between SyNAPS 4D flow and 2D flow measurements of net volume (r2 = 0.83) and peak flow (r2 = 0.87) were larger than the correlations between Native 4D flow and 2D flow measurements of net volume (r2 = 0.79) and peak flow (r2 = 0.76). CONCLUSION: The feasibility and utility of SyNAPS were demonstrated for joint whole-heart anatomical and flow MRI without requiring electrocardiography gating, respiratory navigators, or contrast agents. Using SyNAPS, a high-contrast anatomical imaging sequence can be used to improve 4D flow measurements that often suffer from poor delineation of vessel boundaries in the absence of contrast agents.

Impact of training data composition on the generalizability of CNN aortic cross section segmentation in 4D Flow MRI.

BACKGROUND: Time-resolved, three-dimensional phase-contrast magnetic resonance imaging (4D flow MRI) plays an important role in assessing cardiovascular diseases. However, the manual or semi-automatic segmentation of aortic vessel boundaries in 4D flow data introduces variability and limits reproducibility of aortic hemodynamics visualization and quantitative flow-related parameter computation. This paper explores the potential of deep learning to improve 4D flow MRI segmentation by developing models for automatic segmentation and analyzes the impact of the training data on the generalization of the model across different sites, scanner vendors, sequences, and pathologies. METHODS: The study population consists of 260 4D flow MRI datasets, including subjects without known aortic pathology, healthy volunteers, and patients with bicuspid aortic valve (BAV) examined at different hospitals. The dataset was split to train segmentation models on subsets with different representations of characteristics such as pathology, gender, age, scanner model, vendor, and field strength. An enhanced 3D U-net convolutional neural network (CNN) architecture with residual units was trained for 2D+t aortic cross-sectional segmentation. The model performance was evaluated using Dice score, Hausdorff distance, and average symmetric surface distance on test data, datasets with characteristics not represented in the training set (model-specific), and an overall evaluation set. Standard diagnostic flow parameters were computed and compared with manual segmentation results using Bland-Altman analysis and interclass correlation. RESULTS: The representation of technical factors such as scanner vendor and field strength in the training dataset had the strongest influence on the overall segmentation performance. Age had a greater impact than gender. Models solely trained on BAV patients' datasets performed well on datasets of healthy subjects but not vice versa. CONCLUSION: This study highlights the importance of considering a heterogeneous dataset for the training of widely applicable automatic CNN segmentations in 4D flow MRI, with a particular focus on the inclusion of different pathologies and technical aspects of data acquisition.

Regional Aortic Wall Shear Stress Increases over Time in Patients with a Bicuspid Aortic Valve.

BACKGROUND: Aortic wall shear stress (WSS) is a known predictor of ascending aortic growth in patients with a bicuspid aortic valve (BAV). The aim of this study was to study regional WSS and changes over time in BAV patients. METHODS: BAV patients and age-matched healthy controls underwent 4D flow CMR. Regional, peak systolic ascending aortic WSS, aortic valve function, aortic stiffness measures and aortic dimensions were assessed. In BAV patients, 4D flow CMR was repeated after three years follow-up and both at baseline and follow-up computed tomography angiography (CTA) was acquired. Aortic growth (volume increase of ≥5%) was measured on CTA. Regional WSS differences within patients' aorta and WSS changes over time were analysed using linear mixed-effect models and were associated with clinical parameters. RESULTS: Thirty BAV patients (aged 34 years [IQR 25-41]) were included in the follow-up analysis. Additionally, another 16 BAV patients and 32 healthy controls (aged 33 years [IQR 28-48]) were included for other regional analyses. Magnitude, axial, and circumferential WSS increased over time (all p<0.001) irrespective of aortic growth. The percentage of regions exposed to a magnitude WSS >95th percentile of healthy controls increased from 21% (baseline 506/2400 regions) to 31% (follow-up 734/2400 regions) (p<0.001). WSS angle, a measure of helicity near the aortic wall, decreased during follow-up. Magnitude WSS changes over time were associated with systolic blood pressure, peak aortic valve velocity, aortic valve regurgitation fraction, aortic stiffness indexes, and normalized flow displacement (all p<0.05). CONCLUSIONS: An increase of regional WSS over time was observed in BAV patients, irrespective of aortic growth. The increasing WSSs comprising a larger area of the aorta warrants further research to investigate the possible predictive value for aortic dissection.

Diastolic function assessment with four-dimensional flow cardiovascular magnetic resonance using automatic deep learning E/A ratio analysis.

BACKGROUND: Diastolic left ventricular (LV) dysfunction is a powerful contributor to the symptoms and prognosis of patients with heart failure. In patients with depressed LV systolic function, the E/A ratio, the ratio between the peak early (E) and the peak late (A) transmitral flow velocity, is the first step to defining the grade of diastolic dysfunction. Doppler echocardiography (echo) is the preferred imaging technique for diastolic function assessment, while cardiovascular magnetic resonance (CMR) is less established as a method. Previous four-dimensional (4D) Flow-based studies have looked at the E/A ratio proximal to the mitral valve, requiring manual interaction. In this study, we compare an automated, deep learning-based and two semi-automated approaches for 4D Flow CMR-based E/A ratio assessment to conventional, gold-standard echo-based methods. METHODS: Ninety-seven subjects with chronic ischemic heart disease underwent a cardiac echo followed by CMR investigation. 4D Flow-based E/A ratio values were computed using three different approaches; two semi-automated, assessing the E/A ratio by measuring the inflow velocity (MVvel) and the inflow volume (MVflow) at the mitral valve plane, and one fully automated, creating a full LV segmentation using a deep learning-based method with which the E/A ratio could be assessed without constraint to the mitral plane (LVvel). RESULTS: MVvel, MVflow, and LVvel E/A ratios were strongly associated with echocardiographically derived E/A ratio (R2 = 0.60, 0.58, 0.72). LVvel peak E and A showed moderate association to Echo peak E and A, while MVvel values were weakly associated. MVvel and MVflow EA ratios were very strongly associated with LVvel (R2 = 0.84, 0.86). MVvel peak E was moderately associated with LVvel, while peak A showed a strong association (R2 = 0.26, 0.57). CONCLUSION: Peak E, peak A, and E/A ratio are integral to the assessment of diastolic dysfunction and may expand the utility of CMR studies in patients with cardiovascular disease. While underestimation of absolute peak E and A velocities was noted, the E/A ratio measured with all three 4D Flow methods was strongly associated with the gold standard Doppler echocardiography. The automatic, deep learning-based method performed best, with the most favorable runtime of ∼40 seconds. As both semi-automatic methods associated very strongly to LVvel, they could be employed as an alternative for estimation of E/A ratio.