Toward a realistic in silico abdominal phantom for QSM.

PURPOSE: QSM outside the brain has recently gained interest, particularly in the abdominal region. However, the absence of reliable ground truths makes difficult to assess reconstruction algorithms, whose quality is already compromised by additional signal contributions from fat, gases, and different kinds of motion. This work presents a realistic in silico phantom for the development, evaluation and comparison of abdominal QSM reconstruction algorithms. METHODS: Synthetic susceptibility and R 2 * $$ {R}_2^{\ast } $$ maps were generated by segmenting and postprocessing the abdominal 3T MRI data from a healthy volunteer. Susceptibility and R 2 * $$ {R}_2^{\ast } $$ values in different tissues/organs were assigned according to literature and experimental values and were also provided with realistic textures. The signal was simulated using as input the synthetic QSM and R 2 * $$ {R}_2^{\ast } $$ maps and fat contributions. Three susceptibility scenarios and two acquisition protocols were simulated to compare different reconstruction algorithms. RESULTS: QSM reconstructions show that the phantom allows to identify the main strengths and limitations of the acquisition approaches and reconstruction algorithms, such as in-phase acquisitions, water-fat separation methods, and QSM dipole inversion algorithms. CONCLUSION: The phantom showed its potential as a ground truth to evaluate and compare reconstruction pipelines and algorithms. The publicly available source code, designed in a modular framework, allows users to easily modify the susceptibility, R 2 * $$ {R}_2^{\ast } $$ and TEs, and thus creates different abdominal scenarios.

KomaMRI.jl: An open-source framework for general MRI simulations with GPU acceleration.

PURPOSE: To develop an open-source, high-performance, easy-to-use, extensible, cross-platform, and general MRI simulation framework (Koma). METHODS: Koma was developed using the Julia programming language. Like other MRI simulators, it solves the Bloch equations with CPU and GPU parallelization. The inputs are the scanner parameters, the phantom, and the pulse sequence that is Pulseq-compatible. The raw data is stored in the ISMRMRD format. For the reconstruction, MRIReco.jl is used. A graphical user interface utilizing web technologies was also designed. Two types of experiments were performed: one to compare the quality of the results and the execution speed, and the second to compare its usability. Finally, the use of Koma in quantitative imaging was demonstrated by simulating Magnetic Resonance Fingerprinting (MRF) acquisitions. RESULTS: Koma was compared to two well-known open-source MRI simulators, JEMRIS and MRiLab. Highly accurate results (with mean absolute differences below 0.1% compared to JEMRIS) and better GPU performance than MRiLab were demonstrated. In an experiment with students, Koma was proved to be easy to use, eight times faster on personal computers than JEMRIS, and 65% of test subjects recommended it. The potential for designing acquisition and reconstruction techniques was also shown through the simulation of MRF acquisitions, with conclusions that agree with the literature. CONCLUSIONS: Koma's speed and flexibility have the potential to make simulations more accessible for education and research. Koma is expected to be used for designing and testing novel pulse sequences before implementing them in the scanner with Pulseq files, and for creating synthetic data to train machine learning models.

Streaking artifact suppression of quantitative susceptibility mapping reconstructions via L1-norm data fidelity optimization (L1-QSM).

PURPOSE: The presence of dipole-inconsistent data due to substantial noise or artifacts causes streaking artifacts in quantitative susceptibility mapping (QSM) reconstructions. Often used Bayesian approaches rely on regularizers, which in turn yield reduced sharpness. To overcome this problem, we present a novel L1-norm data fidelity approach that is robust with respect to outliers, and therefore prevents streaking artifacts. METHODS: QSM functionals are solved with linear and nonlinear L1-norm data fidelity terms using functional augmentation, and are compared with equivalent L2-norm methods. Algorithms were tested on synthetic data, with phase inconsistencies added to mimic lesions, QSM Challenge 2.0 data, and in vivo brain images with hemorrhages. RESULTS: The nonlinear L1-norm-based approach achieved the best overall error metric scores and better streaking artifact suppression. Notably, L1-norm methods could reconstruct QSM images without using a brain mask, with similar regularization weights for different data fidelity weighting or masking setups. CONCLUSION: The proposed L1-approach provides a robust method to prevent streaking artifacts generated by dipole-inconsistent data, renders brain mask calculation unessential, and opens novel challenging clinical applications such asassessing brain hemorrhages and cortical layers.

3D Multiple Sound Source Localization by Proposed T-Shaped Circular Distributed Microphone Arrays in Combination with GEVD and Adaptive GCC-PHAT/ML Algorithms.

Multiple simultaneous sound source localization (SSL) is one of the most important applications in the speech signal processing. The one-step algorithms with the advantage of low computational complexity (and low accuracy), and the two-step methods with high accuracy (and high computational complexity) are proposed for multiple SSL. In this article, a combination of one-step-based method based on the generalized eigenvalue decomposition (GEVD), and a two-step-based method based on the adaptive generalized cross-correlation (GCC) by using the phase transform/maximum likelihood (PHAT/ML) filters along with a novel T-shaped circular distributed microphone array (TCDMA) is proposed for 3D multiple simultaneous SSL. In addition, the low computational complexity advantage of the GCC algorithm is considered in combination with the high accuracy of the GEVD method by using the distributed microphone array to eliminate spatial aliasing and thus obtain more appropriate information. The proposed T-shaped circular distributed microphone array-based adaptive GEVD and GCC-PHAT/ML algorithms (TCDMA-AGGPM) is compared with hierarchical grid refinement (HiGRID), temporal extension of multiple response model of sparse Bayesian learning with spherical harmonic (SH) extension (SH-TMSBL), sound field morphological component analysis (SF-MCA), and time-frequency mixture weight Bayesian nonparametric acoustical holography beamforming (TF-MW-BNP-AHB) methods based on the mean absolute estimation error (MAEE) criteria in noisy and reverberant environments on simulated and real data. The superiority of the proposed method is presented by showing the high accuracy and low computational complexity for 3D multiple simultaneous SSL.

Comparison of parameter optimization methods for quantitative susceptibility mapping.

PURPOSE: Quantitative Susceptibility Mapping (QSM) is usually performed by minimizing a functional with data fidelity and regularization terms. A weighting parameter controls the balance between these terms. There is a need for techniques to find the proper balance that avoids artifact propagation and loss of details. Finding the point of maximum curvature in the L-curve is a popular choice, although it is slow, often unreliable when using variational penalties, and has a tendency to yield overregularized results. METHODS: We propose 2 alternative approaches to control the balance between the data fidelity and regularization terms: 1) searching for an inflection point in the log-log domain of the L-curve, and 2) comparing frequency components of QSM reconstructions. We compare these methods against the conventional L-curve and U-curve approaches. RESULTS: Our methods achieve predicted parameters that are better correlated with RMS error, high-frequency error norm, and structural similarity metric-based parameter optimizations than those obtained with traditional methods. The inflection point yields less overregularization and lower errors than traditional alternatives. The frequency analysis yields more visually appealing results, although with larger RMS error. CONCLUSION: Our methods provide a robust parameter optimization framework for variational penalties in QSM reconstruction. The L-curve-based zero-curvature search produced almost optimal results for typical QSM acquisition settings. The frequency analysis method may use a 1.5 to 2.0 correction factor to apply it as a stand-alone method for a wider range of signal-to-noise-ratio settings. This approach may also benefit from fast search algorithms such as the binary search to speed up the process.

MAPL1: q-space reconstruction using ℓ1 -regularized mean apparent propagator.

PURPOSE: To improve the quality of mean apparent propagator (MAP) reconstruction from a limited number of q-space samples. METHODS: We implement an ℓ1 -regularised MAP (MAPL1) to consider higher order basis functions and to improve the fit without increasing the number of q-space samples. We compare MAPL1 with the least-squares optimization subject to non-negativity (MAP), and the Laplacian-regularized MAP (MAPL). We use simulations of crossing fibers and compute the normalized mean squared error (NMSE) and the Pearson's correlation coefficient to evaluate the reconstruction quality in q-space. We also compare coefficient-based diffusion indices in the simulations and in in vivo data. RESULTS: Results indicate that MAPL1 improves NMSE in 1 to 3% when compared to MAP or MAPL in a high undersampling regime. Additionally, MAPL1 produces more reproducible and accurate results for all sampling rates when there are enough basis functions to meet the sparsity criterion for the regularizer. These improved reconstructions also produce better coefficient-based diffusion indices for in vivo data. CONCLUSIONS: Adding an ℓ1 regularizer to MAP allows the use of more basis functions and a better fit without increasing the number of q-space samples. The impact of our research is that a complete diffusion spectrum can be reconstructed from an acquisition time very similar to a diffusion tensor imaging protocol.

The 2016 QSM Challenge: Lessons learned and considerations for a future challenge design.

PURPOSE: The 4th International Workshop on MRI Phase Contrast and QSM (2016, Graz, Austria) hosted the first QSM Challenge. A single-orientation gradient recalled echo acquisition was provided, along with COSMOS and the χ33 STI component as ground truths. The submitted solutions differed more than expected depending on the error metric used for optimization and were generally over-regularized. This raised (unanswered) questions about the ground truths and the metrics utilized. METHODS: We investigated the influence of background field remnants by applying additional filters. We also estimated the anisotropic contributions from the STI tensor to the apparent susceptibility to amend the χ33 ground truth and to investigate the impact on the reconstructions. Lastly, we used forward simulations from the COSMOS reconstruction to investigate the impact noise had on the metric scores. RESULTS: Reconstructions compared against the amended STI ground truth returned lower errors. We show that the background field remnants had a minor impact in the errors. In the absence of inconsistencies, all metrics converged to the same regularization weights, whereas structural similarity index metric was more insensitive to such inconsistencies. CONCLUSION: There was a mismatch between the provided data and the ground truths due to the presence of unaccounted anisotropic susceptibility contributions and noise. Given the lack of reliable ground truths when using in vivo acquisitions, simulations are suggested for future QSM Challenges.

Comparison of basis functions and q-space sampling schemes for robust compressed sensing reconstruction accelerating diffusion spectrum imaging.

Time constraints placed on magnetic resonance imaging often restrict the application of advanced diffusion MRI (dMRI) protocols in clinical practice and in high throughput research studies. Therefore, acquisition strategies for accelerated dMRI have been investigated to allow for the collection of versatile and high quality imaging data, even if stringent scan time limits are imposed. Diffusion spectrum imaging (DSI), an advanced acquisition strategy that allows for a high resolution of intra-voxel microstructure, can be sufficiently accelerated by means of compressed sensing (CS) theory. CS theory describes a framework for the efficient collection of fewer samples of a data set than conventionally required followed by robust reconstruction to recover the full data set from sparse measurements. For an accurate recovery of DSI data, a suitable acquisition scheme for sparse q-space sampling and the sensing and sparsifying bases for CS reconstruction need to be selected. In this work we explore three different types of q-space undersampling schemes and two frameworks for CS reconstruction based on either Fourier or SHORE basis functions. After CS recovery, diffusion and microstructural parameters and orientational information are estimated from the reconstructed data by means of state-of-the-art processing techniques for dMRI analysis. By means of simulation, diffusion phantom and in vivo DSI data, an isotropic distribution of q-space samples was found to be optimal for sparse DSI. The CS reconstruction results indicate superior performance of Fourier-based CS-DSI compared to the SHORE-based approach. Based on these findings we outline an experimental design for accelerated DSI and robust CS reconstruction of the sparse measurements that is suitable for the application within time-limited studies.

Variability of 4D flow parameters when subjected to changes in MRI acquisition parameters using a realistic thoracic aortic phantom.

PURPOSE: To assess the variability of peak flow, mean velocity, stroke volume, and wall shear stress measurements derived from 3D cine phase contrast (4D flow) sequences under different conditions of spatial and temporal resolutions. METHODS: We performed controlled experiments using a thoracic aortic phantom. The phantom was connected to a pulsatile flow pump, which simulated nine physiological conditions. For each condition, 4D flow data were acquired with different spatial and temporal resolutions. The 2D cine phase contrast and 4D flow data with the highest available spatio-temporal resolution were considered as a reference for comparison purposes. RESULTS: When comparing 4D flow acquisitions (spatial and temporal resolution of 2.0 × 2.0 × 2.0 mm3 and 40 ms, respectively) with 2D phase-contrast flow acquisitions, the underestimation of peak flow, mean velocity, and stroke volume were 10.5, 10 and 5%, respectively. However, the calculated wall shear stress showed an underestimation larger than 70% for the former acquisition, with respect to 4D flow, with spatial and temporal resolution of 1.0 × 1.0 × 1.0 mm3 and 20 ms, respectively. CONCLUSIONS: Peak flow, mean velocity, and stroke volume from 4D flow data are more sensitive to changes of temporal than spatial resolution, as opposed to wall shear stress, which is more sensitive to changes in spatial resolution. Magn Reson Med 79:1882-1892, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Three-dimensional quantification of vorticity and helicity from 3D cine PC-MRI using finite-element interpolations.

PURPOSE: We propose a 3D finite-element method for the quantification of vorticity and helicity density from 3D cine phase-contrast (PC) MRI. METHODS: By using a 3D finite-element method, we seamlessly estimate velocity gradients in 3D. The robustness and convergence were analyzed using a combined Poiseuille and Lamb-Ossen equation. A computational fluid dynamics simulation was used to compared our method with others available in the literature. Additionally, we computed 3D maps for different 3D cine PC-MRI data sets: phantom without and with coarctation (18 healthy volunteers and 3 patients). RESULTS: We found a good agreement between our method and both the analytical solution of the combined Poiseuille and Lamb-Ossen. The computational fluid dynamics results showed that our method outperforms current approaches to estimate vorticity and helicity values. In the in silico model, we observed that for a tetrahedral element of 2 mm of characteristic length, we underestimated the vorticity in less than 5% with respect to the analytical solution. In patients, we found higher values of helicity density in comparison to healthy volunteers, associated with vortices in the lumen of the vessels. CONCLUSIONS: We proposed a novel method that provides entire 3D vorticity and helicity density maps, avoiding the used of reformatted 2D planes from 3D cine PC-MRI. Magn Reson Med 79:541-553, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Total liver fat quantification using three-dimensional respiratory self-navigated MRI sequence.

PURPOSE: MRI can produce quantitative liver fat fraction (FF) maps noninvasively, which can help to improve diagnoses of fatty liver diseases. However, most sequences acquire several two-dimensional (2D) slices during one or more breath-holds, which may be difficult for patients with limited breath-holding capacity. A whole-liver 3D FF map could also be obtained in a single acquisition by applying a reliable breathing-motion correction method. Several correction techniques are available for 3D imaging, but they use external devices, interrupt acquisition, or jeopardize the spatial resolution. To overcome these issues, a proof-of-concept study introducing a self-navigated 3D three-point Dixon sequence is presented here. METHODS: A respiratory self-gating strategy acquiring a center k-space profile was integrated into a three-point Dixon sequence. We obtained 3D FF maps from a water-fat emulsions phantom and fifteen volunteers. This sequence was compared with multi-2D breath-hold and 3D free-breathing approaches. RESULTS: Our 3D three-point Dixon self-navigated sequence could correct for respiratory-motion artifacts and provided more precise FF measurements than breath-hold multi-2D and 3D free-breathing techniques. CONCLUSION: Our 3D respiratory self-gating fat quantification sequence could correct for respiratory motion artifacts and yield more-precise FF measurements. Magn Reson Med 76:1400-1409, 2016. © 2015 International Society for Magnetic Resonance in Medicine.

Realistic aortic phantom to study hemodynamics using MRI and cardiac catheterization in normal and aortic coarctation conditions.

PURPOSE: To design and characterize a magnetic resonance imaging (MRI)-compatible aortic phantom simulating normal and aortic coarctation (AoCo) conditions and to compare its hemodynamics with healthy volunteers and AoCo patients. MATERIALS AND METHODS: The phantom is composed of an MRI-compatible pump, control unit, aortic model, compliance chamber, nonreturn, and shutoff valves. The phantom without and with AoCo (13, 11, and 9 mm) was studied using 2D and 3D phase-contrast data and with a catheterization unit to measure pressures. The phantom data were compared with the mean values of 10 healthy volunteers and two AoCo patients. RESULTS: Hemodynamic parameters in the normal phantom and healthy volunteers were: heart rate: 68/61 bpm, cardiac output: 3.5/4.5 L/min, peak flow and peak velocity (Vpeak) in the ascending aorta (AAo): 270/357 mL/s (significantly, P < 0.05) and 97/107 cm/s (not significantly, P = 0.16), and pressure in the AAo of the normal phantom of 131/58 mmHg. Hemodynamic parameters in the 13, 11, and 9 mm coarctation phantoms and Patients 1 and 2 were: heart rate: 75/75/75/97/78 bpm, cardiac output: 3.3/3.0/2.9/4.0/5.8 L/min, peak flow in the AAo: 245/265/215/244/376 mL/s, Vpeak in the AAo: 96/95/81/196/187 cm/s, Vpeak after the AoCo: 123/187/282/247/165 cm/s, pressure in the AAo: 124/56, 127/51, 133/50, 120/51 and 87/39 mmHg, and a trans-coarctation systolic pressure gradient: 7, 10, 30, 20, and 11 mmHg. CONCLUSION: We propose and characterize a normal and an AoCo phantom, whose hemodynamics, including velocity, flow, and pressure data are within the range of healthy volunteers and patients with AoCo. J. Magn. Reson. Imaging 2016;44:683-697.

High prevalence of undiagnosed liver cirrhosis and advanced fibrosis in type 2 diabetic patients.

UNLABELLED:  Background. Patients with type 2 diabetes mellitus (T2DM) are at risk for developing end-stage liver disease due to nonalcoholic steatohepatitis (NASH), the aggressive form of non-alcoholic fatty liver disease (NAFLD). Data on prevalence of advanced fibrosis among T2DM patients is scarce. AIM: To evaluate prevalence of steatosis, advanced fibrosis and cirrhosis using non-invasive methods in T2DM patients. MATERIAL AND METHODS: 145 consecutive T2DM patients (> 55 years-old) were prospectively recruited. Presence of cirrhosis and advanced fibrosis was evaluated by magnetic resonance imaging (MRI) and NAFLD fibrosis score (NFS) respectively. Exclusion criteria included significant alcohol consumption, markers of viral hepatitis infection or other liver diseases. Results are expressed in percentage or median (interquartile range). RESULTS: 52.6% of patients were women, the median age was 60 years old (57-64), mean BMI was 29.6 ± 4.7 kg/m2 and diabetes duration was 7.6 ± 6.9 years. A high prevalence of liver steatosis (63.9%), advanced fibrosis assessed by NFS (12.8%) and evidence of liver cirrhosis in MRI (6.0%) was observed. In a multivariate analysis GGT > 82 IU/L (P = 0.004) and no alcohol intake (P = 0.032) were independently associated to advanced fibrosis. CONCLUSION: A high frequency of undiagnosed advanced fibrosis and cirrhosis was observed in non-selected T2DM patients. Screening of these conditions may be warranted in this patient population.

Quantitative hepatic perfusion modeling using DCE-MRI with sequential breathholds.

PURPOSE: To develop and demonstrate the feasibility of a new formulation for quantitative perfusion modeling in the liver using interrupted DCE-MRI data acquired during multiple sequential breathholds. MATERIALS AND METHODS: A new mathematical formulation to estimate quantitative perfusion parameters using interrupted data was developed. Using this method, we investigated whether a second degree-of-freedom in the tissue residue function (TRF) improves quality-of-fit criteria when applied to a dual-input single-compartment perfusion model. We subsequently estimated hepatic perfusion parameters using DCE-MRI data from 12 healthy volunteers and 9 cirrhotic patients with a history of hepatocellular carcinoma (HCC); and examined the utility of these estimates in differentiating between healthy liver, cirrhotic liver, and HCC. RESULTS: Quality-of-fit criteria in all groups were improved using a Weibull TRF (2 degrees-of-freedom) versus an exponential TRF (1 degree-of-freedom), indicating nearer concordance of source DCE-MRI data with the Weibull model. Using the Weibull TRF, arterial fraction was greater in cirrhotic versus normal liver (39 ± 23% versus 15 ± 14%, P = 0.07). Mean transit time (20.6 ± 4.1 s versus 9.8 ± 3.5 s, P = 0.01) and arterial fraction (39 ± 23% versus 73 ± 14%, P = 0.04) were both significantly different between cirrhotic liver and HCC, while differences in total perfusion approached significance. CONCLUSION: This work demonstrates the feasibility of estimating hepatic perfusion parameters using interrupted data acquired during sequential breathholds.

Fast and accessible T2 mapping using off-resonance corrected DESPOT2 with application to 3D prostate.

PURPOSE: Most T1 and T2 mapping take long acquisitions or needs specialized sequences not widely accessible on clinical scanners. An available solution is DESPOT1/T2 (Driven equilibrium single pulse observation of T1/T2). DESPOT1/T2 uses Spoiled gradient-echo (SPGR) and balanced Steady-State Free Precession (bSSFP) sequences, offering an accessible and reliable way for 3D accelerated T1/T2 mapping. However, bSSFP is prone to off-resonance artifacts, limiting the application of DESPOT2 in regions with high susceptibility contrasts, like the prostate. Our proposal, DESPO+, employs the full bSSFP and SPGR models with a dictionary-based method to reconstruct 3D T1/T2 maps in the prostate region without off-resonance banding. METHODS: DESPO+ modifies the bSSFP acquisition of the original variable flip angle DESPOT2. DESPO+ uses variable repetition and echo times, employing a dictionary-based method of the full bSSFP and SPGR models to reconstruct T1, T2, and Proton Density (PD) simultaneously. The proposed DESPO+ method underwent testing through simulations, T1/T2 phantoms, and on fourteen healthy subjects. RESULTS: The results reveal a significant reduction in T2 map banding artifacts compared to the original DESPOT2 method. DESPO+ approach reduced T2 errors by up to seven times compared to DESPOT2 in simulations and phantom experiments. We also synthesized in-vivo T1-weighted/T2-weighted images from the acquired maps using a spin-echo model to verify the map's quality when lacking a reference. For in-vivo imaging, the synthesized images closely resemble those from the clinical MRI protocol, reducing scan time by around 50% compared to traditional spin-echo T1-weighted/T2-weighted acquisitions. CONCLUSION: DESPO+ provides an off-resonance insensitive and clinically available solution, enabling high-resolution 3D T1/T2 mapping and synthesized T1-weighted/T2-weighted images for the entire prostate, all achieved within a short scan time of 3.6 min, similar to DESPOT1/T2.

Calcium (Ca2+) waves data calibration and analysis using image processing techniques.

BACKGROUND: Calcium (Ca2+) propagates within tissues serving as an important information carrier. In particular, cilia beat frequency in oviduct cells is partially regulated by Ca2+ changes. Thus, measuring the calcium density and characterizing the traveling wave plays a key role in understanding biological phenomena. However, current methods to measure propagation velocities and other wave characteristics involve several manual or time-consuming procedures. This limits the amount of information that can be extracted, and the statistical quality of the analysis. RESULTS: Our work provides a framework based on image processing procedures that enables a fast, automatic and robust characterization of data from two-filter fluorescence Ca2+ experiments. We calculate the mean velocity of the wave-front, and use theoretical models to extract meaningful parameters like wave amplitude, decay rate and time of excitation. CONCLUSIONS: Measurements done by different operators showed a high degree of reproducibility. This framework is also extended to a single filter fluorescence experiments, allowing higher sampling rates, and thus an increased accuracy in velocity measurements.

Caval blood flow distribution in patients with Fontan circulation: quantification by using particle traces from 4D flow MR imaging.

PURPOSE: To validate the use of particle traces derived from four-dimensional (4D) flow magnetic resonance (MR) imaging to quantify in vivo the caval flow contribution to the pulmonary arteries (PAs) in patients who had been treated with the Fontan procedure. MATERIALS AND METHODS: The institutional review boards approved this study, and informed consent was obtained. Twelve healthy volunteers and 10 patients with Fontan circulation were evaluated. The particle trace method consists of creating a region of interest (ROI) on a blood vessel, which is used to emit particles with a temporal resolution of approximately 40 msec. The flow distribution, as a percentage, is then estimated by counting the particles arriving to different ROIs. To validate this method, two independent observers used particle traces to calculate the flow contribution of the PA to its branches in volunteers and compared it with the contribution estimated by measuring net forward flow volume (reference method). After the method was validated, caval flow contributions were quantified in patients. Statistical analysis was performed with nonparametric tests and Bland-Altman plots. P < .05 was considered to indicate a significant difference. RESULTS: Estimation of flow contributions by using particle traces was equivalent to estimation by using the reference method. Mean flow contribution of the PA to the right PA in volunteers was 54% ± 3 (standard deviation) with the reference method versus 54% ± 3 with the particle trace method for observer 1 (P = .4) and 54% ± 4 versus 54% ± 4 for observer 2 (P = .6). In patients with Fontan circulation, 87% ± 13 of the superior vena cava blood flowed to the right PA (range, 63%-100%), whereas 55% ± 19 of the inferior vena cava blood flowed to the left PA (range, 22%-82%). CONCLUSION: Particle traces derived from 4D flow MR imaging enable in vivo quantification of the caval flow distribution to the PAs in patients with Fontan circulation. This method might allow the identification of patients at risk of developing complications secondary to uneven flow distribution. SUPPLEMENTAL MATERIAL: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12120778/-/DC1.

Adipose tissue MRI for quantitative measurement of central obesity.

PURPOSE: To validate adipose tissue magnetic resonance imaging (atMRI) for rapid, quantitative volumetry of visceral adipose tissue (VAT) and total adipose tissue (TAT). MATERIALS AND METHODS: Data were acquired on normal adults and clinically overweight girls with Institutional Review Board (IRB) approval/parental consent using sagittal 6-echo 3D-spoiled gradient-echo (SPGR) (26-sec single-breath-hold) at 3T. Fat-fraction images were reconstructed with quantitative corrections, permitting measurement of a physiologically based fat-fraction threshold in normals to identify adipose tissue, for automated measurement of TAT, and semiautomated measurement of VAT. TAT accuracy was validated using oil phantoms and in vivo TAT/VAT measurements validated with manual segmentation. Group comparisons were performed between normals and overweight girls using TAT, VAT, VAT-TAT-ratio (VTR), body-mass-index (BMI), waist circumference, and waist-hip-ratio (WHR). RESULTS: Oil phantom measurements were highly accurate (<3% error). The measured adipose fat-fraction threshold was 96% ± 2%. VAT and TAT correlated strongly with manual segmentation (normals r(2) ≥ 0.96, overweight girls r(2) ≥ 0.99). VAT segmentation required 30 ± 11 minutes/subject (14 ± 5 sec/slice) using atMRI, versus 216 ± 73 minutes/subject (99 ± 31 sec/slice) manually. Group discrimination was significant using WHR (P < 0.001) and VTR (P = 0.004). CONCLUSION: The atMRI technique permits rapid, accurate measurements of TAT, VAT, and VTR.

Hemodynamic assessment in patients with one-and-a-half ventricle repair revealed by four-dimensional flow magnetic resonance imaging.

We report hemodynamic findings in two patients with pulmonary atresia and intact ventricular septum (PAIVS) after "one-and-a-half ventricle repair" and placement of a bidirectional Glenn shunt using four-dimensional (4D) flow magnetic resonance imaging. Quantification of flow and analysis of flow patterns revealed the hemodynamic "battle" between the right ventricle (RV) and the Glenn shunt. Moreover, with a novel approach we calculated during Glenn anastomosis the flow distribution from the superior vena cava (SVC) to the pulmonary arteries. Our results showed a highly asymmetric flow distribution, with most of the flow from the SVC toward the RV and not to the lungs. The evidence provided by 4D flow demonstrates poor efficiency of this system and suggests that both patients might benefit from adding an artificial pulmonary valve to avoid right heart failure.