Phase-contrast Magnetic Resonance Imaging Research Articles

Phase-contrast MRI analysis of cerebral blood and CSF flow dynamic interactions

BackgroundFollowing the Monro-Kellie doctrine, the Cerebral Blood Volume Changes (CB_VC) should be mirrored by the Cerebrospinal Fluid Volume Changes (CSF_VC) at the spinal canal. Cervical level is often chosen to estimate CB_VC during the cardiac cycle. However, due to the heterogeneity in the anatomy of extracranial internal jugular veins and their high compliance, we hypothesize that the intracranial level could be a better choice to investigate blood and cerebrospinal fluid (CSF) interactions. This study aims to determine which level, intracranial or extracranial, is more suitable for measuring arterial and venous flows to study cerebral blood and CSF dynamics interactions.MethodsThe spinal CSF and cerebral blood flow measured at intracranial and extracranial levels were quantified using cine phase-contrast magnetic resonance imaging (PC-MRI) in 38 healthy young adults. Subsequently, CSF_VC and CB_VC were calculated, and by linear regression analysis (R2 and slope), the relationship between CB_VC at both levels and the spinal CSF_VC was compared. The differences between extracranial and intracranial measurements were assessed using either a paired Student’s t-test or Wilcoxon’s test, depending on the normality of the data distribution.ResultsThe CB_VC amplitude was significantly higher at the extracranial level (0.89 ± 0.28 ml/CC) compared to the intracranial level (0.73 ± 0.19 ml/CC; p < 0.001). CSF oscillations through the spinal canal do not completely balance blood volume changes. The R2 and the slope values obtained from the linear regression analysis between CSF and blood flows were significantly higher in magnitude for the intracranial CB_VC (R2: 0.82 ± 0.16; slope: − 0.74 ± 0.19) compared to the extracranial CB_VC (R2: 0.47 ± 0.37; slope: -0.36 ± 0.33; p < 0.001). Interestingly, extracranial CB_VC showed a greater variability compared to intracranial CB_VC.ConclusionOur results confirmed that CSF does not completely and instantaneously balance cerebral blood expansion during the cardiac cycle. Nevertheless, the resting volume is very small compared to the total intracranial volume. To our knowledge, this study is the first to demonstrate these findings using cerebral blood flow measured intracranially below the Circle of Willis. Additionally, our findings show that cerebral arterial and venous flow dynamic measurements during the cardiac cycle obtained by PC-MRI at the intracranial plane strongly correlate with CSF oscillations measured in the spinal canal. Therefore, the intracranial vascular plane is more relevant for analyzing cerebral blood and CSF interactions during the cardiac cycle compared to measurements taken at the cervical vascular level.

Background phase induced steady-state effects in velocity quantification using phase-contrast MRI.

Flow quantification using phase-contrast (PC) MRI is based on steady-state gradient echo (GRE) sequences and is hampered by spatially varying background phase offsets. The purpose of this work was to investigate the effect of steady-state disruptions during PC-MRI GRE sequences on these background phases. Based on these findings, a specific sequence and timing is suggested, and caution is expressed when using typical correction algorithms. Steady-state responses in stationary tissue were investigated in different prospectively triggered through-plane phase-contrast MRI sequence. Different spoiling methods (gradient spoiling/FISP versus gradient+RF spoiling/FLASH) and interleaving of flow encoding gradients (every TR vs. every ECG cycle) were investigated using simulations, in phantoms and in vivo. Additionally, the effect of relaxation times on the phase offsets was simulated and measured. The impact on image- and phantom-based background phase correction was studied. Good agreement between simulation and phantom measurements were observed. Different sequences lead to different spatiotemporal and tissue dependent background phases. Average flow rates in the popliteal artery were over- and underestimated for ECG-interleaved and TR-interleaved FISP acquisitions compared to FLASH, respectively. Background phase measurements are influenced by steady-state effects leading to potentially false background phase quantification. Current background phase correction methods cannot correct for the disturbance.

Significant individual variation in cardiac-cycle-linked cerebrospinal fluid production following subarachnoid hemorrhage

BackgroundSpontaneous subarachnoid hemorrhage (SAH) often results in altered cerebrospinal fluid (CSF) flow and secondary hydrocephalus, yet the mechanisms behind these phenomena remain poorly understood. This study aimed to elucidate the impact of SAH on individual CSF flow patterns and their association with secondary hydrocephalus.MethodsIn patients who had experienced SAH, changes in CSF flow were assessed using cardiac-gated phase-contrast magnetic resonance imaging (PC-MRI) at the Sylvian aqueduct and cranio-cervical junction (CCJ). Within these regions of interest, volumetric CSF flow was determined for every pixel and net CSF flow volume and direction calculated. The presence of acute or chronic hydrocephalus was deemed from ventriculomegaly and need of CSF diversion. For comparison, we included healthy subjects and patients examined for different CSF diseases.ResultsTwenty-four SAH patients were enrolled, revealing a heterogeneous array of CSF flow alterations at the Sylvian aqueduct. The cardiac-cycle-linked CSF net flow in Sylvian aqueduct differed from the traditional figures of ventricular CSF production about 0.30–0.40 mL/min. In 15 out of 24 patients (62.5%), net CSF flow was retrograde from the fourth to the third and lateral ventricles, while it was upward at the cranio-cervical junction in 2 out of 2 patients (100%). The diverse CSF flow metrics did not distinguish between individuals with acute or chronic secondary hydrocephalus. In comparison, 4/4 healthy subjects showed antegrade net CSF flow in the Sylvian aqueduct and net upward CSF flow in CCJ. These net CSF flow measures also showed interindividual variability among other patients with CSF diseases.ConclusionsThere is considerable inter-individual variation in net CSF flow rates following SAH. Net CSF flow in the Sylvian aqueduct differs markedly from the traditional ventricular CSF production rates of 0.30–0.40 mL/min in SAH patients, but less so in healthy subjects. Furthermore, the cardiac-cycle-linked net CSF flow rates in Sylvian aqueduct and CCJ suggest an important role of extra-ventricular CSF production.

Phase contrast MRI with minimized background phase errors.

Phase contrast MRI (PC-MRI) is used clinically to measure velocities in the body, but systematic background phase errors caused by magnetic field imperfections corrupt the velocity measurements with offsets that limit clinical utility. This work aims to minimize systematic background phase errors in PC-MRI, thereby maximizing the accuracy of velocity measurements. The MRI scanner's background phase errors from eddy currents and mechanical oscillations were modeled using the gradient impulse response function (GIRF). Gradient waveforms were then numerically optimized using the GIRF to create pulse sequences that minimize the background phase errors. The pulse sequences were tested in a static phantom where the predicted response could be compared directly to the measured background velocity. The optimized acquisitions were then tested in human subjects, where flow rates and background errors were compared to conventional PC-MRI. When using the GIRF-optimized gradient waveforms, the predicted background phase was within 0.6 [95% CI = -3.4, 5.4] mm/s of the measured background phase in a static phantom. Excellent agreement was seen for in vivo blood flow values (flow rate agreement = 0.96), and the background phase was reduced by 78.8 18.7%. This work shows that using a GIRF to model the effects of magnetic field imperfections combined with numerically optimized gradient waveforms enables PC-MRI waveforms to be designed to produce a minimal background phase in the most time-efficient manner. The methodology could be adapted for other MRI sequences where similar magnetic field errors affect measurements.

Automated Quantification of Simple and Complex Aortic Flow Using 2D Phase Contrast MRI

(1) Background and Objectives: Flow assessment using cardiovascular magnetic resonance (CMR) provides important implications in determining physiologic parameters and clinically important markers. However, post-processing of CMR images remains labor- and time-intensive. This study aims to assess the validity and repeatability of fully automated segmentation of phase contrast velocity-encoded aortic root plane. (2) Materials and Methods: Aortic root images from 125 patients are segmented by artificial intelligence (AI), developed using convolutional neural networks and trained with a multicentre cohort of 160 subjects. Derived simple flow indices (forward and backward flow, systolic flow and velocity) and complex indices (aortic maximum area, systolic flow reversal ratio, flow displacement, and its angle change) were compared with those derived from manual contours. (3) Results: AI-derived simple flow indices yielded excellent repeatability compared to human segmentation (p &lt; 0.001), with an insignificant level of bias. Complex flow indices feature good to excellent repeatability (p &lt; 0.001), with insignificant levels of bias except flow displacement angle change and systolic retrograde flow yielding significant levels of bias (p &lt; 0.001 and p &lt; 0.05, respectively). (4) Conclusions: Automated flow quantification using aortic root images is comparable to human segmentation and has good to excellent repeatability. However, flow helicity and systolic retrograde flow are associated with a significant level of bias. Overall, all parameters show clinical repeatability.

282 - Quantitative assessment of bladder fluid dynamics using Phase-Contrast Magnetic Resonance Imaging: a pilot study

282 - Quantitative assessment of bladder fluid dynamics using Phase-Contrast Magnetic Resonance Imaging: a pilot study

Quantifying CSF Dynamics disruption in idiopathic normal pressure hydrocephalus using phase lag between transmantle pressure and volumetric flow rate

Background and purposeIdiopathic normal pressure hydrocephalus (iNPH) is a cerebrospinal fluid (CSF) dynamics disorder as evidenced by the delayed ascent of radiotracers over the cerebral convexity on radionuclide cisternography. However, the exact mechanism causing this disruption remains unclear. Elucidating the pathophysiology of iNPH is crucial, as it is a treatable cause of dementia. Improving the diagnosis and treatment prognosis rely on the better understanding of this disease. In this study, we calculated the pulsatile transmantle pressure and investigated the phase lag between this pressure and the volumetric CSF flow rate as a novel biomarker of CSF dynamics disruption in iNPH. Methods44 iNPH patients and 44 age- and sex-matched cognitively unimpaired (CU) control participants underwent MRI scans on a 3T Siemens scanner. Pulsatile transmantle pressure was calculated analytically and computationally using volumetric CSF flow rate, cardiac frequency, and aqueduct dimensions as inputs. CSF flow rate through the aqueduct was acquired using phase-contrast MRI. The aqueduct length and radius were measured using 3D T1-weighted anatomical images. ResultsPeak pressure amplitudes and the pressure load (integrated pressure exerted over a cardiac cycle) were similar between the groups, but the non-dimensionalized pressure load (adjusted for anatomical factors) was significantly lower in the iNPH group (p<0.001, Welch's t-test). The phase lag between the pressure and the flow rate, arising due to viscous drag, was significantly higher in the iNPH group (p<0.001). ConclusionThe increased phase lag is a promising new biomarker for quantifying CSF dynamics dysfunction in iNPH. Statement of SignificanceThe exact mechanism causing the disruption of CSF circulation in idiopathic normal pressure hydrocephalus (iNPH) remains unclear. Elucidating the pathophysiology of iNPH is crucial, as it is a treatable cause of dementia. In this study, we provided an analytical and a computational method to calculate the pulsatile transmantle pressure and the phase lag between the pressure and the volumetric CSF flow rate across the cerebral aqueduct. The phase lag was significantly higher in iNPH patients than in controls and may serve as a novel biomarker of CSF dynamics disruption in iNPH.

Pelvic congestion syndrome analysis through quantitative 2-dimensional phase-contrast magnetic resonance imaging: A promising vision from an observational cohort study.

To examine the application of quantitative 2-dimensional phase-contrast magnetic resonance imaging (2D PC-MRI) for treating patients with pelvic congestion syndrome (PCS). We conducted a retrospective cross-sectional analysis by using quantitative 2D PC-MRI data enrolled between April 2017 and Sep 2023. In addition, 32 healthy female controls (HCs) were included. Most patients with PCS presented with chronic pelvic pain and more than half had extra-pelvic venous symptoms (80/81, 98% and 45/81, 56%, respectively). Quantitative 2D PC-MRI analyzed the 81 patients with PCS, 239 patients without PCS, and 32 HCs. The patients with PCS had higher stroke volume (SV), absolute SV (ASV), and mean flux (MF) in the calf region (interstitial pixel shift) than did the HCs. In the left gonadal vein, the patients with PCS had higher SV, backward flow volume (BFV), ASV, and MF and lower forward flow volume (FFV), stroke distance (SD), and mean velocity (MV) than did the HCs. However, the patients with PCS had lower SV, FFV, MF, SD, and MV in the great saphenous veins. Quantitative 2D PC-MRI analysis revealed that the PCS group had higher SV, FFV, BFV, ASV, and MF in the calf region than did the non-PCS group. The variables that most strongly differentiated the patients with PCS from the HCs were SV in the great saphenous veins, SD in the great saphenous veins and left gonadal vein, and MV in the great saphenous veins and left gonadal vein. Caudal flow in the left gonadal vein was identified in half of the patients with PCS (39/81, 48.1%); 14 of them received embolization for left gonadal vein. In additional to providing an objective 3-dimensional morphology of the pelvic veins and extra-pelvic leaks, quantitative 2D PC-MRI analysis reveals distinct hemodynamic profiles between patients with PCS, those without PCS, and HCs, especially in the gonadal veins and regional perfusion of the calves.

Evaluation of the presence and severity of spontaneous splenorenal or gastrorenal shunts via four-dimensional flow magnetic resonance imaging: a preliminary study.

Four-dimensional phase-contrast magnetic resonance imaging (4D flow MRI) is a relatively new type of MRI acquisition technique that provides a unique and comprehensive set of information within a single acquisition, including hemodynamic and anatomical information. This study was designed to noninvasively evaluate the correlation between the presence and severity of spontaneous splenorenal shunt (SRS) or gastrorenal shunt (GRS) and 4D flow MRI-derived parameters. This retrospective case-control study enrolled 70 patients who were diagnosed with hepatocirrhosis portal hypertension and admitted to the Second Affiliated Hospital of Chongqing Medical University. Patients were divided into three groups according to the diameter of the SRS and GRS. 4D flow MRI-derived parameters, including the turbulent kinetic energy, total volume (TV), flow velocity, blood flow volume (BFV), maximum flow (MF), wall shear stress, and relative pressure, were obtained for eight cut planes: proximal to the splenomesenteric confluence and liver hilum of the portal vein (PV1/PV2); the left/right branch of the bifurcation of the PV (LPV/RPV), at the mesosplenic confluence of the splenic vein (SV1), at the splenic hilum of the SV (SV2); at the proximal to the splenomesenteric confluence of the superior mesenteric vein (SMV1), and 5 cm from the splenomesenteric confluence of the SMV (SMV2). Comparisons among the three groups were based on one-way analysis of variance (ANOVA). Logistic regression was used to identify the risk factors for small SRS/GRS (S-SRS/GRS) and for large SRS/GRS (L-SRS/GRS). Receiver operating characteristic curves were used to evaluate the diagnostic performance of the independent risk factors for SRS and GRS. The associations between the clinical data and the 4D flow MRI-derived parameters of GRS and SRS were assessed via Spearman correlation coefficient analysis. The presence of SRS or GRS was correlated with TVLPV (r=-0.302; P=0.035), TVPV1 (r=-0.385; P=0.001), TVPV2 (r=-0.301; P=0.013), BFVPV1 (r=-0.360; P=0.010), BFVSMV2 (r=0.371; P=0.008), MFPV1 (r=-0.341; P=0.004), and MFPV2 (r=-0.291; P=0.017). Meanwhile, the severity of the SRS or GRS was correlated with alanine aminotransferase level (r=-0.535; P<0.001), BFVLPV (r=-0.560; P=0.008), aspartate aminotransferase level (r=-0.321; P=0.038), and model for end-stage liver disease score (r=0.323; P=0.039). TVPV1, TVPV2, BFVPV1, BFVPV2, and MFSMV2 were found to be independent risk factors for L-SRS/GRS, with intermediate diagnostic efficacy, with the area under the curve (AUC)TV PV1=0.706 [95% confidence interval (CI): 0.519-0.853; sensitivity, 61.54%; specificity, 80.77%; P=0.018], AUCBFV PV1 =0.694 (95% CI: 0.507-0.844; sensitivity, 95.00%; specificity, 63.16%; P=0.035), AUCTV PV2 =0.729 (95% CI: 0.544-0.870; sensitivity, 77.78%; specificity, 66.67%; P=0.016), AUCBFV PV2 =0.718 (95% CI: 0.531-0.862; sensitivity, 60.00%; specificity, 82.35%; P=0.017), and AUCMF SMV2 =0.788 (95% CI: 0.608-0.912; sensitivity, 44.00%; specificity, 84.46%; P=0.005), respectively. As the TV of PV1 and PV2 and the BFV of PV1 and PV2 decreased, the risk of L-SRS/GRS increased. As the MF of SMV2 increased, the risk of the presence of L-SRS/GRS increased. 4D flow MRI-derived parameters correlated with the presence and severity of SRS or GRS. Meanwhile, the independent risk factors for the presence of L-SRS/GRS were the TV of LPV, PV1, and PV2; the BFV of PV1 and SMV2; and the MF of PV1 and PV2.

An Eulerian formulation for the computational modeling of phase-contrast MRI.

Computational simulation of phase-contrast MRI (PC-MRI) is an attractive way to physically interpret properties and errors in MRI-reconstructed flow velocity fields. Recent studies have developed PC-MRI simulators that solve the Bloch equation, with the magnetization transport being modeled using a Lagrangian approach. Because this method expresses the magnetization as spatial distribution of particles, influences of particle densities and their spatial uniformities on numerical accuracy are well known. This study developed an alternative method for PC-MRI modeling using an Eulerian approach in which the magnetization is expressed as a spatially smooth continuous function. The magnetization motion was described using the Bloch equation with an advection term and computed on a fixed grid using a finite difference method, and k-space sampling was implemented using the spoiled gradient echo sequence. PC-MRI scans of a fully developed flow in straight and stenosed cylinders were acquired to provide numerical examples. Reconstructed flow in a straight cylinder showed excellent agreement with input velocity profiles and mean errors were less than 0.5% of the maximum velocity. Numerical cases of flow in a stenosed cylinder successfully demonstrated the velocity profiles, with displacement artifacts being dependent on scan parameters and intravoxel dephasing due to flow disturbances. These results were in good agreement with those obtained using the Lagrangian approach with a sufficient particle density. The feasibility of the Eulerian approach to PC-MRI modeling was successfully demonstrated.

Accuracy of the WatchBP Office Central as a Type 2 device for non-invasive estimation of central aortic blood pressure in children and adolescents.

High blood pressure (BP) in childhood is a recognised precursor of elevated cardiovascular risk in adulthood. Brachial BP is normally used for clinical decision making, but central BP may be a better marker of pressure load on the heart. There is a paucity of validated non-invasive, automated devices for estimating central BP in children and adolescents. In this study, we compared the WatchBP Office Central (a Type 2 central pressure estimation device) against a high-fidelity micromanometer in the ascending aorta of anaesthetised patients undergoing clinically-indicated catheterisation (n = 15, age 4-16 years). As a secondary aim, central systolic BP (cSBP) was also compared to two non-invasive estimation methods in 34 awake patients undergoing routine cardiac MRI (age 10-18 years). WatchBP substantially overestimated cSBP compared to the intra-arterial gold-standard reference (26.1 ± 7.4mmHg), and recruitment was terminated at n = 11 (included in the analysis) due to high statistical certainty that the device would not pass the validation criteria of 5±8 mmHg. WatchBP cSBP was also substantially higher than values obtained from a phase contrast MRI method (11.8 ± 7.9 mmHg) and the SphygmoCor XCEL (13.5 ± 8.9 mmHg) in the awake patient group, which translate to 21-23 mmHg on average after accounting for known/estimated biases in these non-invasive comparators. Compared with invasive central diastolic and systolic BPs, the brachial measures from WatchBP yielded errors of 0.1 ± 5.6 and 12.5 ± 6.0 mmHg respectively. We conclude that the WatchBP substantially overestimates cSBP in children and adolescents. These findings reinforce the need for central BP-measuring devices to be further developed and validated in this population.

Verification Study of in Silico Computed Intracardiac Blood Flow With 4D Flow MRI.

Major challenges for clinical applications of in silico medicine are limitations in time and computational resources. Computational approaches should therefore be tailored to specific applications with relatively low complexity and must be verified and validated against clinical gold standards. This study performed computational fluid dynamics simulations of left ventricular hemodynamics of different complexity based on shape reconstruction from steady state gradient echo magnetic resonance imaging (MRI) data. Computed flow results of a rigid wall model (RWM) and a prescribed motion fluid-structure interaction (PM-FSI) model were compared against phase-contrast MRI measurements for three healthy subjects. Extracted boundary conditions from the steady state MRI sequences as well as computed metrics, such as flow rate, valve velocities, and kinetic energy show good agreement with in vivo flow measurements. Regional flow analysis reveals larger differences. Basic flow structures are well captured with RWM and PM-FSI. For the computation of further biomarkers like washout or flow efficiency, usage of PM-FSI is required. Regarding boundary-near flow, more accurate anatomical models are inevitable. These results delineate areas of application of both methods and lay a foundation for larger validation studies and sensitivity analysis for healthy and diseased cases, being an essential step upon clinical translations.

Abstract 24: Effects Of Intensive Blood Pressure Lowering on Brain Tissue Pulsatility in Hypertensive Patients

Recent studies have shown an association between blood pressure (BP), particularly pulse pressure (PP), in increasing brain tissue pulsatility. However, these studies were conducted in a phantom model or in healthy normotensive adults. Effects of intensive BP lowering on brain tissue pulsatility in hypertensive patients remain unknown. Accordingly, we performed a randomized clinical trial to compare effects of intensive BP lowering to target 24-h ambulatory BP &lt;120/70 mmHg (n=26) vs. target of &lt;130/80 mmHg in the control arm (n =19) in hypertensive patients aged 55-79 with normal cognitive function. The brain tissue pulsatility was assessed by the total tissue motion over one cardiac cycle, using CINE phase contrast MRI, with the velocity encoded in all three directions. In each cardiac cycle, the velocity of the tissue was measured at 16 time points. Brain tissue pulsatility was assessed at baseline and after 1 year of follow up. We found that 24-h ambulatory systolic BP (SBP) was reduced from 134.3±9.8 to 112.1±7.2 mmHg in the intensive arm and from 138.5±11.3 to 122.4±7.8 mmHg in the control arm (both p&lt;0.01). The magnitude of 24-h SBP reduction from baseline was greater in the intensive arm than control arm (23.6 vs. 13.1 mmHg, p=0.052) while 24-h diastolic BP was reduced similarly in both groups (11.6 vs. 9.6 mmHg, p=0.8). Similarly, PP based on 24-h BP was reduced from 57.5±11.7 to 45.1±12.1 mmHg in the intensive BP arm and from 62.2±10.6 to 55.4±10.5 mmHg in the control arm (both p&lt;0.01). The magnitude of PP reduction appeared greater in the intensive compared to control arm but was not statistically different (12.4 vs. 6.8 mmHg, p=0.08). We found that the overall gray-white matter tissue pulsatility per cardiac cycle remained unchanged after 12 months in the intensive arm (0.98±0.18 mm to 0.95±0.17 mm) while the brain pulsatility tended to increase in the control arm (0.85±0.17 mm to 0.92±0.16 mm, p=0.09 for treatment group, interaction-p=0.04). Similarly, the white matter (WM) tissue motion remained unchanged in the intensive arm (0.91±0.16 mm to 0.88±0.15 mm) while the WM pulsatility tended to increase in the control arm (from 0.77±0.14 mm to 0.84±0.15 mm, p=0.06 for group, interaction p=0.03). In conclusion, our data suggested a novel effect of intensive BP lowering in preventing the rise in brain tissue pulsatility in hypertensive patients, which may have an implication in the prevention of an accelerated brain injury related to hypertension.

Computational modeling of left ventricular flow using PC-CMR-derived four-dimensional wall motion.

Intracardiac hemodynamics plays a crucial role in the onset and development of cardiac and valvular diseases. Simulations of blood flow in the left ventricle (LV) have provided valuable insight into assessing LV hemodynamics. While fully coupled fluid-solid modelings of the LV remain challenging due to the complex passive-active behavior of the LV wall myocardium, the integration of imaging-driven quantification of structural motion with computational fluid dynamics (CFD) modeling in the LV holds the promise of feasible and clinically translatable characterization of patient-specific LV hemodynamics. In this study, we propose to integrate two magnetic resonance imaging (MRI) modalities with the moving-boundary CFD method to characterize intracardiac LV hemodynamics. Our method uses the standard cine cardiac magnetic resonance (CMR) images to estimate four-dimensional myocardial motion, eliminating the need for involved myocardial material modeling to capture LV wall behavior. In conjunction with CMR, phase contrast-MRI (PC-MRI) was used to measure temporal blood inflow rates at the mitral orifice, serving as an additional boundary condition. Flow patterns, including velocity streamlines, vortex rings, and kinetic energy, were characterized and compared to the available data. Moreover, relationships between LV wall kinematic markers and flow characteristics were determined without myocardial material modeling and using a non-rigid image registration (NRIR) method. The fidelity of the simulation was quantitatively evaluated by validating the flow rate at the aortic outflow tract against respective PC-MRI measures. The proposed methodology offers a novel and feasible toolset that works with standard PC-CMR protocols to improve the clinical assessment of LV characteristics in prognostic studies and surgical planning.

A comparison of machine learning methods for recovering noisy and missing 4D flow MRI data.

Experimental blood flow measurement techniques are invaluable for a better understanding of cardiovascular disease formation, progression, and treatment. One of the emerging methods is time-resolved three-dimensional phase-contrast magnetic resonance imaging (4D flow MRI), which enables noninvasive time-dependent velocity measurements within large vessels. However, several limitations hinder the usability of 4D flow MRI and other experimental methods for quantitative hemodynamics analysis. These mainly include measurement noise, corrupt or missing data, low spatiotemporal resolution, and other artifacts. Traditional filtering is routinely applied for denoising experimental blood flow data without any detailed discussion on why it is preferred over other methods. In this study, filtering is compared to different singular value decomposition (SVD)-based machine learning and autoencoder-type deep learning methods for denoising and filling in missing data (imputation). An artificially corrupted and voxelized computational fluid dynamics (CFD) simulation as well as in vitro 4D flow MRI data are used to test the methods. SVD-based algorithms achieve excellent results for the idealized case but severely struggle when applied to in vitro data. The autoencoders are shown to be versatile and applicable to all investigated cases. For denoising, the in vitro 4D flow MRI data, the denoising autoencoder (DAE), and the Noise2Noise (N2N) autoencoder produced better reconstructions than filtering both qualitatively and quantitatively. Deep learning methods such as N2N can result in noise-free velocity fields even though they did not use clean data during training. This work presents one of the first comprehensive assessments and comparisons of various classical and modern machine-learning methods for enhancing corrupt cardiovascular flow data in diseased arteries for both synthetic and experimental test cases.

3D Quantitative-Amplified Magnetic Resonance Imaging (3D q-aMRI).

Amplified MRI (aMRI) is a promising new technique that can visualize pulsatile brain tissue motion by amplifying sub-voxel motion in cine MRI data, but it lacks the ability to quantify the sub-voxel motion field in physical units. Here, we introduce a novel post-processing algorithm called 3D quantitative amplified MRI (3D q-aMRI). This algorithm enables the visualization and quantification of pulsatile brain motion. 3D q-aMRI was validated and optimized on a 3D digital phantom and was applied in vivo on healthy volunteers for its ability to accurately measure brain parenchyma and CSF voxel displacement. Simulation results show that 3D q-aMRI can accurately quantify sub-voxel motions in the order of 0.01 of a voxel size. The algorithm hyperparameters were optimized and tested on in vivo data. The repeatability and reproducibility of 3D q-aMRI were shown on six healthy volunteers. The voxel displacement field extracted by 3D q-aMRI is highly correlated with the displacement measurements estimated by phase contrast (PC) MRI. In addition, the voxel displacement profile through the cerebral aqueduct resembled the CSF flow profile reported in previous literature. Differences in brain motion was observed in patients with dementia compared with age-matched healthy controls. In summary, 3D q-aMRI is a promising new technique that can both visualize and quantify pulsatile brain motion. Its ability to accurately quantify sub-voxel motion in physical units holds potential for the assessment of pulsatile brain motion as well as the indirect assessment of CSF homeostasis. While further research is warranted, 3D q-aMRI may provide important diagnostic information for neurological disorders such as Alzheimer's disease.

Velocity of cerebrospinal fluid in the aqueduct measured by phase-contrast MRI in rat.

Cerebrospinal fluid (CSF) circulation plays a key role in cerebral waste clearance via the glymphatic system. Although CSF flow velocity is an essential component of CSF dynamics, it has not been sufficiently characterized, and particularly, in studies of the glymphatic system in rat. To investigate the relationship between the flow velocity of CSF in the brain aqueduct and the glymphatic waste clearance rate, using phase-contrast MRI we performed the first measurements of CSF velocity in rats. Phase-contrast MRI was performed using a 7T system to map mean velocity of CSF flow in the aqueduct in rat brain. The effects of age (3months old versus 18 months old), gender, strain (Wistar, RNU, Dark Agouti), anesthetic agents (isoflurane versus dexmedetomidine), and neurodegenerative disorder (Alzheimer' disease in Fischer TgF344-AD rats, males and females) on CSF velocity were investigated in eight independent groups of rats (12 rats per group). Our results demonstrated that quantitative velocities of CSF flow in the aqueduct averaged 5.16 ± 0.86 mm/s in healthy young adult male Wistar rats. CSF flow velocity in the aqueduct was not altered by rat gender, strain, and the employed anesthetic agents in all rats, also age in the female rats. However, aged (18 months) Wistar male rats exhibited significantly reduced the CSF flow velocity in the aqueduct (4.31 ± 1.08 mm/s). In addition, Alzheimer's disease further reduced the CSF flow velocity in the aqueduct of male and female rats.

MR Assessment of Acute Changes of Cerebral Perfusion, Metabolism, and Blood-Brain Barrier Permeability in Response to Aerobic Exercise.

It remains unclear how a single bout of exercise affects brain perfusion, oxygen metabolism, and blood-brain barrier (BBB) permeability. Addressing this unresolved issue is essential to understand the acute changes in cerebral physiology induced by aerobic exercise. To dynamically monitor the acute changes in cerebral physiology subsequent to a single aerobic exercise training session using noninvasive MRI measurements. Prospective. Twenty-three healthy participants (18-35 years, 10 females/13 males) were enrolled and divided into 10-minute exercising (N = 10) and 20-minute exercising (N = 13) groups. 3.0 T/Phase Contrast (PC) MRI (gradient echo), T2-Relaxation-Under-Spin-Tagging (TRUST) MRI (gradient echo EPI), Water-Extraction-with-Phase-Contrast-Arterial-Spin-Tagging (WEPCAST) MRI (gradient echo EPI) and T1-weighted magnetization-prepared-rapid-acquisition-of-gradient-echo (MPRAGE) (gradient echo). A baseline MR measurement plus four repeated MR measurements immediately after 10 or 20 minutes moderate running exercise. MR measurements included cerebral blood flow (CBF) as measured by PC MRI, venous oxygenation (Yv) and cerebral metabolic rate of oxygen (CMRO2) as assessed by TRUST MRI, water extraction fraction (E), and BBB permeability-surface-area product (PS) as determined by WEPCAST MRI. The time dependence of the physiological parameters was studied with a linear mixed-effect model. Additionally, pairwise t-tests comparison of the physiological parameters at each time point was conducted. A P-value of <0.05 was considered statistically significant. There was an initial drop (8.22 ± 2.60%) followed by a recovery in CBF after exercise, while Yv revealed a significant decrease (6.37 ± 0.92%), i.e., an increased oxygen extraction, and returned to baseline at later time points. CMRO2 showed a trend of increase (5.68 ± 3.04%) and a significant interaction between time and group. In addition, E increased significantly (3.86% ± 0.89) and returned to baseline level at later time points, while PS remained elevated (13.33 ± 4.79%). A single bout of moderate aerobic exercise can induce acute alterations in cerebral perfusion, metabolism, and BBB permeability. 2 TECHNICAL EFFICACY: Stage 2.

Decoding pulsatile patterns of cerebrospinal fluid dynamics through enhancing interpretability in machine learning

Analyses of complex behaviors of Cerebrospinal Fluid (CSF) have become increasingly important in diseases diagnosis. The changes of the phase-contrast magnetic resonance imaging (PC-MRI) signal formed by the velocity of flowing CSF are represented as a set of velocity-encoded images or maps, which can be thought of as signal data in the context of medical imaging, enabling the evaluation of pulsatile patterns throughout a cardiac cycle. However, automatic segmentation of the CSF region in a PC-MRI image is challenging, and implementing an explained ML method using pulsatile data as a feature remains unexplored. This paper presents lightweight machine learning (ML) algorithms to perform CSF lumen segmentation in spinal, utilizing sets of velocity-encoded images or maps as a feature. The Dataset contains 57 PC-MRI slabs by 3T MRI scanner from control and idiopathic scoliosis participants are involved to collect data. The ML models are trained with 2176 time series images. Different cardiac periods image (frame) numbers of PC-MRIs are interpolated in the preprocessing step to align to features of equal size. The fivefold cross-validation procedure is used to estimate the success of the ML models. Additionally, the study focusses on enhancing the interpretability of the highest-accuracy eXtreme gradient boosting (XGB) model by applying the shapley additive explanations (SHAP) technique. The XGB algorithm presented its highest accuracy, with an average fivefold accuracy of 0.99% precision, 0.95% recall, and 0.97% F1 score. We evaluated the significance of each pulsatile feature's contribution to predictions, offering a more profound understanding of the model's behavior in distinguishing CSF lumen pixels with SHAP. Introducing a novel approach in the field, develop ML models offer comprehension into feature extraction and selection from PC-MRI pulsatile data. Moreover, the explained ML model offers novel and valuable insights to domain experts, contributing to an enhanced scholarly understanding of CSF dynamics.

Hemodynamic evaluation of intracranial arteriovenous malformations: Pre- and post-treatment 2D phase-contrast MRI measurements.

Hemodynamic changes are seen in the feeding arteries of arteriovenous malformations (AVMs). Phase-contrast MRI (PC-MRI) enables the acquisition of hemodynamic information from blood vessels. There is insufficient knowledge on which flow or velocity parameter best discriminates AVMs from healthy subjects. To evaluate PC-MRI-measured flow and velocity in feeding arteries of AVMs before and, when possible, also after treatment and to compare these measurements to corresponding measurements in healthy controls. Highest flow (HF), lowest flow (LF), mean flow (MF), peak systolic velocity (PSV), end-diastolic velocity (EDV), and mean velocity (MV) were measured in feeding arteries in patients with intracranial AVMs using 2D PC-MRI at 3 T. Measurements were compared to previously reported values in healthy individuals. Values in patients above the 95th percentile in the healthy cohort were categorized as pathological. Nidus volume was measured using 3D time-of-flight MR angiography. Ten patients with diagnosed AVMs were examined with PC-MRI. Among these, three patients also underwent follow-up PC-MRI after treatment. Pathological velocities (PSV, EDV, and MV) were seen in all five subjects with a nidus larger or equal to 5.7cm3, whereas pathological flow values were not seen in all, that is, pathologic HF in three, pathologic LF in two, and pathologic MF in two. After treatment, there was a decrease in flow and velocity (all measured parameters). After treatment, velocities (PSV, EDV, and MV) were no longer abnormal compared to healthy controls. Patients with a large AVM nidus show pathological velocities, but less consistent flow increases. Following treatment, velocities normalize.