Functional Connectivity Alterations of Within and Between Networks in Schizophrenia: A Retrospective Study.

Introduction: Schizophrenia (SZ) is a chronic brain disorder characterized by diverse cognitive dysfunctions due to abnormal brain connectivity. Evaluating these connectivity alterations between and within such networks (intra- and inter-connectivity) may improve the understanding of disrupted information processing patterns in SZ patients. Methods: Resting-state fMRI analysis was performed on 24 SZ patients and 27 matched healthy controls. A functional connectivity matrix was constructed for each participant based on 129 gray matter regions. All regions were classified into eight distinct functional networks. Afterward, all functional connections were segregated into inter- and intra-network connections considering the eight networks. The Mean values of connectivity weights and nodal strength were examined for within- and between-network connections in SZ patients and healthy controls. Results: This analysis revealed that the within-network connections in the somatomotor (SM) network significantly reduced (P<0.001) in SZ patients. Additionally, intra-network connections within the visual and the ventral attention (VA) networks were significantly lower (P<0.01) in the SZ group. Moreover, disrupted intra-network connectivity was detected between the following network pairs: The visual-limbic, the somatomotor-limbic, the dorsal attention-limbic, and the ventral attention-dorsal attention system. Conclusion: The results showed an extensive reduction in functional connectivity strength for SZ patients, with a particularly significant decrease in intra-network connections when compared to the inter-networks. These findings can impact the understanding of the important dysregulated connections that are implicated in the incidence of schizophrenia. Highlights: Intra-network connections are more altered in schizophrenia (SZ) compared to inter-network.The visual, somatomotor (SM), and ventral attention (VA) networks are more affected in SZ.The interactions between the limbic system and three resting-state networks (RSNs) are altered significantly.The nodal strengths in different regions of RSNs are reduced significantly in SZ. Plain Language Summary: Brain functional connectivity is altered in several brain disorders. Looking for these changes may help in better understanding the disorder effects, its diagnostic and treatment. Our brain can be organized into distinct functional modules, known as resting-state networks (RSNs). These RSNs include visual, somatomotor (SM), fronto-parietal, dorsal attention, ventral attention, default mode (DMN), and limbic functional systems. In this study, we examined the alteration of functional connectivity in schizophrenia disorder considering these brain RSNs. The functional connections were classified in two groups, the inter- and intra-network connections. Inter-network connections are defined as the links between pairs of regions from two different brain subnetworks, whereas intra- network connections are determined as the connections between pairs of regions inside each network. Our analysis indicated that the functional connectivity strengths of intra-network connections reduced more in schizophrenia. It was also found that the connection between the limbic network and others is more disrupted compared to other inter-network links. These findings can help us in better understanding the effect of schizophrenia on the brain and therefore its treatment.

Brain subnetworks most sensitive to alterations of functional connectivity in Schizophrenia: a data-driven approach.

Functional connectivity (FC) of the brain changes in various brain disorders. Its complexity, however, makes it difficult to obtain a systematic understanding of these alterations, especially when they are found individually and through hypothesis-based methods. It would be easier if the variety of brain connectivity alterations is extracted through data-driven approaches and expressed as variation modules (subnetworks). In the present study, we modified a blind approach to determine inter-group brain variations at the network level and applied it specifically to schizophrenia (SZ) disorder. The analysis is based on the application of independent component analysis (ICA) over the subject's dimension of the FC matrices, obtained from resting-state functional magnetic resonance imaging (rs-fMRI). The dataset included 27 SZ people and 27 completely matched healthy controls (HC). This hypothesis-free approach led to the finding of three brain subnetworks significantly discriminating SZ from HC. The area associated with these subnetworks mostly covers regions in visual, ventral attention, and somatomotor areas, which are in line with previous studies. Moreover, from the graph perspective, significant differences were observed between SZ and HC for these subnetworks, while there was no significant difference when the same parameters (path length, network strength, global/local efficiency, and clustering coefficient) across the same limited data were calculated for the whole brain network. The increased sensitivity of those subnetworks to SZ-induced alterations of connectivity suggested whether an individual scoring method based on their connectivity values can be applied to classify subjects. A simple scoring classifier was then suggested based on two of these subnetworks and resulted in acceptable sensitivity and specificity with an area under the ROC curve of 77.5%. The third subnetwork was found to be a less specific building block (module) for describing SZ alterations. It projected a wider range of inter-individual variations and, therefore, had a lower chance to be considered as a SZ biomarker. These findings confirmed that investigating brain variations from a modular viewpoint can help to find subnetworks that are more sensitive to SZ-induced alterations. Altogether, our study results illustrated the developed method's ability to systematically find brain alterations caused by SZ disorder from a network perspective.

Real-time radial tagging for quantification of left ventricular torsion.

PURPOSE: To develop a real-time radial tagging MRI for accurate measurement of rotational motion and twist of the left ventricle (LV). METHODS: A FLASH-based radial tagging sequence with an undersampled radial reading scheme was developed for both single and double-slice imaging in real-time. The Polar Fourier Transform was used for reconstruction to push the undersampling artifacts out of a reduced FOV. The developed technique was used to image five normal subjects during rest, plus one during both exercise and rest conditions. LV rotational motions were estimated for five consecutive cardiac cycles in all cases. The process was validated using a numerical phantom. The real-time measurement of global rotational motion was compared with those measured from a non-real-time exam using linear regression analysis and the Bland-Altman plot. RESULTS: The real-time acquisition was performed successfully with a temporal resolution of 46.2 ms. Image quality was sufficient for the reproducible calculation of rotation at rest and exercise. The feasibility of double-slice acquisition on human was further studied and a real-time twist of the left ventricle was demonstrated. The difference between LV global rotations from real-time and non-real-time approaches was 0.27 degrees. A significant reverse recoiling, induced by exercise, was reproducibly measured by the technique. CONCLUSION: A real-time radial tagging MRI technique was developed based on the undersampled radial acquisition and Polar Fourier Transform reconstruction, for accurate measuring of the heart rotational motion and twist. The technique was able to extract a meaningful change of diastolic recoiling under stress test conditions during physical activities (cycling).

SSFP fMRI at 3 tesla: Efficiency of polar acquisition-reconstruction technique.

SSFP-based fMRI techniques, known for their high specificity and low geometrical distortion, look promising for high-resolution brain mapping. Nevertheless, they suffer from lack of speed and sensitivity, leading them to be exploited mostly in high-field scanners. Radial acquisition can help with these inefficiencies through better tSNR and more effective coverage of the spatial frequencies. Here, we present a SSFP-fMRI approach and experimentally investigate it at 3 T scanners using radial readout for acquisition. In particular, the visual activity is mapped through three bSSFP techniques: 1- Cartesian, 2- Radial with re-gridding reconstruction, 3- Radial with Polar Fourier Transform (PFT) reconstruction. In the PFT technique streaking artifacts, generated at high acceleration rates by re-gridding reconstruction, are avoided and pixel size in the final framework is retrospectively selectable. General agreement, but better tSNR of Radial reading, was first confirmed for these techniques in detection of neural activities at 2 × 2 mm2 in-plane resolution for all 28 subjects,. Next the outcome of the PFT algorithm with 1 × 1 mm2 pixel size was compared to images reconstructed by re-gridding (from the same raw data) with the identical pixel size through interpolation. The localization of the activity showed improvement in PFT over interpolation both qualitatively (i.e., well-fitting in gray-matter) and quantitatively (i.e., higher z-scores and tSNR). The proposed technique can therefore be considered as a remedy for lack of speed and sensitivity in SSFP-based fMRI, in conventional field strengths. The proposed approach is particularly useful in task-based studies when we concentrate on a ROI considerably smaller than FOV, without sacrificing spatial resolution.

Interindividual Covariations of Brain Functional and Structural Connectivities Are Decomposed Blindly to Subnetworks: A Fusion-Based Approach.

BACKGROUND: Studying brain interindividual variations has recently gained interest to understand different human behaviors. It is particularly important to investigate how a variety of functional differences can be associated with a few differences in brain structure. It would be more meaningful if such an investigation is performed jointly at the network level to connect structural building blocks to functional variations modules. PURPOSE: To decompose the interindividual variations of brain in the form of mutual functional and structural subnetworks based on a data-driven approach. STUDY TYPE: Retrospective. POPULATION: In all, 92 healthy subjects. FIELD STRENGTH/SEQUENCE: 3T Siemens/MPRAGE, diffusion spectrum imaging (DSI) acquisition protocol, gradient echo sequence. ASSESSMENT: The proposed approach was quantitatively assessed by examining the consistency of the networks against the number of subjects. Distribution of the obtained components across brain regions was studied and their relevance was qualitatively evaluated by comparison to variations that had been independently reported previously. STATISTICAL TESTS: Permutation test, two-sample t-test, Pearson correlation coefficient. RESULTS: Ten pairs of components including functional and structural subnetworks were obtained. Assessing the reproducibility of the proposed method with respect to the sample size indicated reliable detection of connections (above 70%) for all components by reducing the number of subjects to 70. Specifically, one of the functional subnetworks can be used to distinguish left-handed from right-handed people (P = 2.6 × 10-8 ) as the basic interindividual variation. This functional subnetwork has a main overlap (40.18%) with the somatomotor system and the Broca part was captured in its corresponding structural subnetwork. DATA CONCLUSION: These results show that the proposed method can reveal intersubject variations systematically through a mathematical algorithm of joint independent component analysis. They confirm that intersubject variations can be expressed in the form of building blocks. In contrast to the functional subnetworks that were discoverable independently, their structural counterparts were found and interpreted only in conjunction with the functional subnetworks. LEVEL OF EVIDENCE: 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;51:1779-1788.

Efficient de-noising of high-resolution fMRI using local and sub-band information.

BACKGROUND: High-resolution fMRI, useful for accurate brain mapping, suffers from low functional sensitivity at a reasonable acquisition time. Conventional smoothing techniques although reduce the noise and boost the sensitivity, but degrade the spatial resolution of fMRI. NEW METHODS: We propose a novel spatial de-noising technique to increase sensitivity while preserving the boundaries of active regions in the high-resolution fMRI. A modified version of PCA that utilizes adjacent voxels information (LPCA) is first suggested for de-noising. This technique is then further empowered by its application to wavelet sub-bands (WLPCA). RESULTS: Proposed techniques were assessed on both simulated and experimental data. Identifiablity index was calculated for evaluation of the denoising on the simulated data. Maximum and mean z-scores along with LAE and SSIM were reported on experimental data for two presented techniques as well as Guassian smoothing. WLPCA outperformed other techniques in Identifiablity index, for simulation, and in preserving maximum z-score, for experimental study. COMPARISON WITH EXISTING METHODS: The presented technique was developed to simultaneously suppress the noise and preserve the boundaries of active areas against leakage. For first aim, its achievable mean z-score was compared to conventional Gaussian. For second aim, its maximum z-score was compared to that of no-smoothing. While Gaussian and no-smoothing can work fine with only one measure, WLPCA was able to improve both measures concurrently. CONCLUSIONS: The local PCA based methods, and in particular WLPCA, is an effective noise reduction step that preserves the spatial resolution by preventing activity leakage of high-resolution fMRI data.

Allergen-induced anxiety-like behavior is associated with disruption of medial prefrontal cortex - amygdala circuit.

Anxiety is prevalent in asthma, and is associated with disease severity and poor quality of life. However, no study to date provides direct experimental evidence for the effect of allergic inflammation on the structure and function of medial prefrontal cortex (mPFC) and amygdala, which are essential regions for modulating anxiety and its behavioral expression. We assessed the impact of ovalbumin (OVA)-induced allergic inflammation on the appearance of anxiety-like behavior, mPFC and amygdala volumes using MRI, and the mPFC-amygdala circuit activity in sensitized rats. Our findings exhibited that the OVA challenge in sensitized rats induced anxiety-like behavior, and led to more activated microglia and astrocytes in the mPFC and amygdala. We also found a negative correlation between anxiety-like behavior and amygdala volume. Moreover, OVA challenge in sensitized rats was associated with increases in mPFC and amygdala activity, elevation of amygdala delta-gamma coupling, and the enhancement of functional connectivity within mPFC-amygdala circuit - accompanied by an inverted direction of information transferred from the amygdala to the mPFC. We indicated that disrupting the dynamic interactions of the mPFC-amygdala circuit may contribute to the induction of anxiety-related behaviors with asthma. These findings could provide new insight to clarify the underlying mechanisms of allergic inflammation-induced psychiatric disorders related to asthma.

Effect of turbulent models on left ventricle diastolic flow patterns simulation.

Vortex structures, as one of the most important features of cardiac flow, have a crucial impact on the left ventricle function and pathological conditions. These swirling flows are closely related to the presence of turbulence in left ventricle which is investigated in the current study. Using an extended model of the left heart, including a fluid-structure interaction (FSI) model of the mitral valve with a realistic geometry, the effect of using two numerical turbulent models, k-ε and Spalart-Allmaras (SA), on diastolic flow patterns is studied and compared with results from laminar flow model. As a result of the higher dissipation rate in turbulent models (k-ε and SA), vortices are larger and stronger in the laminar flow model. Comparing E/A ratio in the three models (Laminar, k-ε, and SA) with experimental data from healthy subjects, it is concluded that the results from k-ε model are more accurate.

A robust SSFP technique for fMRI at ultra-high field strengths.

A non-balanced (nb) SSFP-based fMRI method based on CE-FAST is presented to alleviate some shortcomings of high spatial-specificity techniques commonly used in high static magnetic fields. The proposed sequence does not suffer from the banding artifacts inherent to balanced (b) SSFP, has low geometrical distortions and SAR compared to spin-echo EPI, and in contrast to previous nbSSFP implementations, is applied at a TR, theoretically prescribed for the optimum contrast. Its non-balanced gradient was chosen to just dephase the unwanted signal component (2π dephasing per TR per voxel). 3D data were acquired from nine healthy subjects, who performed a visual-motor task on a 7 Tesla scanner. For comparison, experiments were accompanied by similar bSSFP and spin-echo acquisitions. Consistent activation was achieved in all subjects with theoretically optimal TR, in contrast to previous nbSSFP techniques. The signal stability as well as relative and absolute functional signal changes, were found to be comparable with bSSFP and spin-echo techniques. The results suggest that with suitable modifications, CE-FAST can be regarded as a robust SSFP-based method for high spatial specificity fMRI techniques.

Efficient radial tagging CMR exam: A coherent k-space reading and image reconstruction approach.

PURPOSE: Cardiac MR tagging techniques, which facilitate the strain evaluation, have not yet been widely adopted in clinics due to inefficiencies in acquisition and postprocessing. This problem may be alleviated by exploiting the coherency in the three steps of tagging: preparation, acquisition, and reconstruction. Herein, we propose a fully polar-based tagging approach that may lead to real-time strain mapping. METHODS: Radial readout trajectories were used to acquire radial tagging images and a Hankel-based algorithm, referred to as Polar Fourier Transform (PFT), has been adapted for reconstruction of the acquired raw data. In both phantom and human subjects, the overall performance of the method was investigated against radial undersampling and compared with the conventional reconstruction methods. RESULTS: Radially tagged images were reconstructed by the proposed PFT method from as few as 24 spokes with normalized root-mean-square-error of less than 3%. The reconstructed images showed a central focusing behavior, where the undersampling effects were pushed to the peripheral areas out of the central region of interest. Comparing the results with the re-gridding reconstruction technique, superior image quality and high robustness of the method were further established. In addition, a relative increase of 68 ± 2.5% in tagline sharpness was achieved for the PFT images and also higher tagging contrast (72 ± 5.6%), resulted from the well-tolerated undersampling artifacts, was observed in all reconstructions. CONCLUSION: The proposed approach led to the acceleration of the acquisition process, which was evaluated for up to eight-fold retrospectively from the fully sampled data. This is promising toward real-time imaging, and in contrast to iterative techniques, the method is consistent with online reconstruction. Magn Reson Med 77:1459-1472, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Investigating the spatial specificity of S2-SSFP fMRI: A Monte Carlo simulation approach.

The desirable spatial specificity of spin echo (SE) fMRI cannot be efficiently utilized in high fields due to specific absorption rate (SAR) and B1 inhomogeneity problems. Consequently, S2-SSFP fMRI has been suggested as an alternative to mitigate these problems. Nevertheless, no accurate analysis has been performed thus far to evaluate spatial specificity of this technique. To study spatial specificity, we performed Monte Carlo simulations for evaluating the micro-vasculature contribution in functional contrast along with vessel size sensitivity estimations for a range of relevant imaging parameters. Results showed a spatial specificity at the level of SE fMRI. Simulations further revealed that similar to SE fMRI, an effective echo time (TE) close to the tissue T2 maximizes the micro-vasculature contribution in the obtained contrast. The amount of this contribution, however, showed a slight decrease at ultra-high fields compared to SE fMRI. As for vessel size sensitivity, simulations presented a pattern for S2-SSFP similar to SE fMRI but with a minor shift toward larger vessels. These results are in general agreement with reported experimental studies. Our findings also suggest that the effect of older pathways, rather than primary SE pathway, might be responsible for the observed discrepancies between S2 and SE. Based on this study, provided that optimum experimental parameters are used, S2, with its desirable micro-vasculature contribution and high sensitivity to small vessels, is a promising low SAR approach to replace SE fMRI in high field.

Velocity Measurement in Carotid Artery: Quantitative Comparison of Time-Resolved 3D Phase-Contrast MRI and Image-based Computational Fluid Dynamics.

BACKGROUND: Understanding hemodynamic environment in vessels is important for realizing the mechanisms leading to vascular pathologies. OBJECTIVES: Three-dimensional velocity vector field in carotid bifurcation is visualized using TR 3D phase-contrast magnetic resonance imaging (TR 3D PC MRI) and computational fluid dynamics (CFD). This study aimed to present a qualitative and quantitative comparison of the velocity vector field obtained by each technique. SUBJECTS AND METHODS: MR imaging was performed on a 30-year old male normal subject. TR 3D PC MRI was performed on a 3 T scanner to measure velocity in carotid bifurcation. 3D anatomical model for CFD was created using images obtained from time-of-flight MR angiography. Velocity vector field in carotid bifurcation was predicted using CFD and PC MRI techniques. A statistical analysis was performed to assess the agreement between the two methods. RESULTS: Although the main flow patterns were the same for the both techniques, CFD showed a greater resolution in mapping the secondary and circulating flows. Overall root mean square (RMS) errors for all the corresponding data points in PC MRI and CFD were 14.27% in peak systole and 12.91% in end diastole relative to maximum velocity measured at each cardiac phase. Bland-Altman plots showed a very good agreement between the two techniques. However, this study was not aimed to validate any of methods, instead, the consistency was assessed to accentuate the similarities and differences between Time-resolved PC MRI and CFD. CONCLUSION: Both techniques provided quantitatively consistent results of in vivo velocity vector fields in right internal carotid artery (RCA). PC MRI represented a good estimation of main flow patterns inside the vasculature, which seems to be acceptable for clinical use. However, limitations of each technique should be considered while interpreting results.

Complementary radial tagging for improved myocardial tagging contrast.

PURPOSE: To develop and evaluate complementary radial tagging (CRT) for improved myocardial tagging contrast. METHODS: We sought to develop and evaluate CRT, which aims to preserve the radial tag contrast throughout the cardiac cycle. Similar to complementary spatial modulation of magnetization, CRT acquires two sets of images with a phase shift in the tag pattern. The combination of a ramped imaging flip angle and image subtraction enhances tag contrast throughout the cardiac cycle. The proposed CRT technique uses a small table shift away from the isocenter to improve the uniformity of the radial tag pattern. We provide a mathematical solution for the optimal table shift and validate the solution in using a retrospective analysis of images from 500 patients in the Cardiac Atlas Project database. RESULTS: CRT simulations, phantom experiments, and in vivo images all demonstrate the improved tag contrast of CRT compared to RT. The retrospective evaluation demonstrated that acceptable CRT images could be acquired in over 98% of the clinical exams. CONCLUSION: The CRT technique improves radial tag contrast throughout the cardiac cycle and should produce high quality tag patterns in nearly all patients.

Tagging of cardiac magnetic resonance images in the polar coordinate system: physical principles and practical implementation.

PURPOSE: In current magnetic resonance practice, myocardial tagging is implemented by laying down a rectilinear presaturation grid over the heart. Although both the geometry and the deformation of the heart are better described in the polar coordinate system, practical methods for laying down polar grids have been elusive. The theory and implementation of high-density tagging in the polar coordinate system is described in this study. METHODS: Tagging sequences for generating high-density tagging patterns in both radial and circular directions have been developed. The approach, theoretical basis, and experimental results of the suggested sequences for efficient polar tagging are described in this article. RESULTS: A 10-ms preparation tagging sequence was tested for generating compact radial and circular tag patterns in a magnetization preparation time comparable to binomial rectilinear grid tagging. The sequence was successfully tested on both phantoms and human subjects. CONCLUSION: Direct myocardial tagging in the polar coordinate system is practical in acquisition times similar to Cartesian tagging. The deformation patterns of radial and circular tag lines can be used to isolate and analyze the circumferential and radial components of myocardial motion. Further work remains to establish the reliability and robustness of the techniques for a variety of clinical applications.

Analytical method to measure three-dimensional strain patterns in the left ventricle from single slice displacement data.

BACKGROUND: Displacement encoded Cardiovascular MR (CMR) can provide high spatial resolution measurements of three-dimensional (3D) Lagrangian displacement. Spatial gradients of the Lagrangian displacement field are used to measure regional myocardial strain. In general, adjacent parallel slices are needed in order to calculate the spatial gradient in the through-slice direction. This necessitates the acquisition of additional data and prolongs the scan time. The goal of this study is to define an analytic solution that supports the reconstruction of the out-of-plane components of the Lagrangian strain tensor in addition to the in-plane components from a single-slice displacement CMR dataset with high spatio-temporal resolution. The technique assumes incompressibility of the myocardium as a physical constraint. RESULTS: The feasibility of the method is demonstrated in a healthy human subject and the results are compared to those of other studies. The proposed method was validated with simulated data and strain estimates from experimentally measured DENSE data, which were compared to the strain calculation from a conventional two-slice acquisition. CONCLUSION: This analytical method reduces the need to acquire data from adjacent slices when calculating regional Lagrangian strains and can effectively reduce the long scan time by a factor of two.

Evidence for the existence of a functional helical myocardial band.

Characterization of local and global contractile activities in the myocardium is essential for a better understanding of cardiac form and function. The spatial distribution of regions that contribute the most to cardiac function plays an important role in defining the pumping parameters of the myocardium like ejection fraction and dynamic aspects such as twisting and untwisting. In general, myocardium shortening, tangent to the wall, and ventricular wall thickening are important parameters that characterize the regional contribution within the myocardium to the global function of the heart. We have calculated these parameters using myocardium displacement fields, which were captured through the displacement-encoding with stimulated echoes (DENSE) MRI technique in three volunteers. High spatial resolution of the acquired data revealed transmural changes of thickening and tangential shortening with high fidelity in beating hearts. By filtering myocardium regions that showed a tangential shortening index of <0.23, we were able to identify the complete or a portion of a macrostructure composed of connected regions in the form of a helical bundle within the left ventricle mass. In this study, we present a representative case that shows the complete morphology of a helical myocardial band as well as two other cases that present ascending and descending portions of the helical myocardial band. Our observation of a helical functional band based on dynamics is in agreement with diffusion tensor MRI observations and gross dissection studies in the arrested heart.

The embryonic vertebrate heart tube is a dynamic suction pump.

The embryonic vertebrate heart begins pumping blood long before the development of discernable chambers and valves. At these early stages, the heart tube has been described as a peristaltic pump. Recent advances in confocal laser scanning microscopy and four-dimensional visualization have warranted another look at early cardiac structure and function. We examined the movement of cells in the embryonic zebrafish heart tube and the flow of blood through the heart and obtained results that contradict peristalsis as a pumping mechanism in the embryonic heart. We propose a more likely explanation of early cardiac dynamics in which the pumping action results from suction due to elastic wave propagation in the heart tube.

Factors affecting the accuracy of pressure measurements in vascular stenoses from phase-contrast MRI.

In this work the effects of noise, resolution, and velocity (flow) on the measurement of intravascular pressure from phase-contrast (PC) MRI are discussed. To elucidate these effects, we employed an axisymmetric geometry that enabled us to calculate pressures in <2 min on a Sun Ultra SPARC 10 workstation. To determine the effects of vascular stenoses, we fabricated several stenotic phantom geometries (with 50%, 75%, and 90% area stenoses), and performed both MRI and computational fluid dynamics (CFD) simulations for various flow rates for these phantom geometries. Noise with Gaussian statistics was added to the velocity field obtained from the CFD simulations. The pressure maps obtained directly from CFD simulations for our phantom geometries were compared with pressure maps derived by our algorithm when 1) the input was noise-corrupted velocity data from CFD, and 2) the input was PC-MRI data collected from the phantoms. The quantitative effects of noise, resolution, and flow rate on the accuracy of pressure measurements were determined. We found that for flow rates below the Reynolds number for turbulent flow, resolution is a more significant determinant of accuracy than SNR. Furthermore, if other parameters remain constant, increased flow rates may result in decreased accuracy.