Estimation of pancreatic R2* for iron overload assessment in the presence of fat: a comparison of different approaches.

OBJECTIVES: To propose a method for estimating pancreatic relaxation rate, R2*, from conventional multi-echo MRI, based on the nonlinear fitting of the acquired magnitude signal decay to MR signal models that take into account both the signal oscillations induced by fat and the different R2* values of pancreatic parenchyma and fat. MATERIALS AND METHODS: Single-peak fat (SPF) and multi-peak fat (MPF) models were introduced. Single-R2* and dual-R2* assumptions were considered as well. Analyses were conducted on simulated data and 20 thalassemia major patients. RESULTS: Simulations revealed the ability of the MPF model to correctly estimate the R2* value in a large range of fat fractions and R2* values. From the comparison between the results obtained with a single R2* value for water and fat and the dual-R2* approach, the latter is more accurate in both water R2* and fat fraction estimation. In patient's data analysis, a strong concordance was found between SPF and MPF estimated data with measurements done with manual signal correction and from fat-saturated images. The MPF method showed better reproducibility. CONCLUSION: The MPF dual-R2* approach improves reproducibility and reduces image analysis time in the assessment of pancreatic R2* value in patients with iron overload.

Numerical evaluation of human exposure to WiMax patch antenna in tablet or laptop.

The use of wireless communication devices, such as tablets or laptops, is increasing among children. Only a few studies assess specific energy absorption rate (SAR) due to exposure from wireless-enabled tablets and laptops, in particular with Worldwide Interoperability for Microwave Access (WiMax) technology. This paper reports the estimation of the interaction between an E-shaped patch antenna (3.5 GHz) and human models, by means of finite-difference time-domain (FDTD) method. Specifically, four different human models (young adult male, young adult female, pre-teenager female, male child) in different exposure conditions (antenna at different distances from the human model, in different positions, and orientations) were considered and whole-body, 10 and 1 g local SAR and magnetic field value (Bmax) were evaluated. From our results, in some worst-case scenarios involving male and female children's exposure, the maximum radiofrequency energy absorption (hot spots) is located in more sensitive organs such as eye, genitals, and breast. Bioelectromagnetics. 39:414-422, 2018. © 2018 Wiley Periodicals, Inc.

Computational Fluid Dynamic Study for aTAA Hemodynamics: An Integrated Image-Based and Radial Basis Functions Mesh Morphing Approach.

We present a novel framework for the fluid dynamics analysis of healthy subjects and patients affected by ascending thoracic aorta aneurysm (aTAA). Our aim is to obtain indications about the effect of a bulge on the hemodynamic environment at different enlargements. Three-dimensional (3D) surface models defined from healthy subjects and patients with aTAA, selected for surgical repair, were generated. A representative shape model for both healthy and pathological groups has been identified. A morphing technique based on radial basis functions (RBF) was applied to mold the shape relative to healthy patient into the representative shape of aTAA dataset to enable the parametric simulation of the aTAA formation. Computational fluid dynamics (CFD) simulations were performed by means of a finite volume solver using the mean boundary conditions obtained from three-dimensional (PC-MRI) acquisition. Blood flow helicity and flow descriptors were assessed for all the investigated models. The feasibility of the proposed integrated approach pertaining the coupling between an RBF morphing technique and CFD simulation for aTAA was demonstrated. Significant hemodynamic changes appear at the 60% of the bulge progression. An impingement of the flow toward the bulge was observed by analyzing the normalized flow eccentricity (NFE) index.

Accelerating 4D flow MRI by exploiting low-rank matrix structure and hadamard sparsity.

PURPOSE: To develop accelerated 4D flow MRI by exploiting low-rank matrix structure and Hadamard sparsity. THEORY AND METHODS: 4D flow MRI data can be represented as the sum of a low-rank and a sparse component. To optimize the sparse representation of the data, it is proposed to incorporate a Hadamard transform of the velocity-encoding segments. Retrospectively and prospectively, undersampled data of the aorta of healthy subjects are used to assess the reconstruction accuracy of the proposed method relative to k-t SPARSE-SENSE reconstruction. Image reconstruction from eight-fold prospective undersampling is demonstrated and compared with conventional SENSE imaging. RESULTS: Simulation results revealed consistently lower errors in velocity estimation when compared with k-t SPARSE-SENSE. In vivo data yielded reduced error of peak flow with the proposed method relative to k-t SPARSE-SENSE when compared with two-fold SENSE ( 2.5±4.6% versus 10.2±8.5% in the ascending aorta, 3.6±8.4% versus 9.2±9.0% in the descending aorta). Streamline visualization showed more consistent flow fields with the proposed technique relative to the benchmark methods. CONCLUSION: Image reconstruction by exploiting low-rank structure and Hadamard sparsity of 4D flow MRI data improves the reconstruction accuracy relative to current state-of-the-art methods and holds promise to reduce the long scan times of 4D flow MRI. Magn Reson Med 78:1330-1341, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Measured PET Data Characterization with the Negative Binomial Distribution Model.

Accurate statistical model of PET measurements is a prerequisite for a correct image reconstruction when using statistical image reconstruction algorithms, or when pre-filtering operations must be performed. Although radioactive decay follows a Poisson distribution, deviation from Poisson statistics occurs on projection data prior to reconstruction due to physical effects, measurement errors, correction of scatter and random coincidences. Modelling projection data can aid in understanding the statistical nature of the data in order to develop efficient processing methods and to reduce noise. This paper outlines the statistical behaviour of measured emission data evaluating the goodness of fit of the negative binomial (NB) distribution model to PET data for a wide range of emission activity values. An NB distribution model is characterized by the mean of the data and the dispersion parameter α that describes the deviation from Poisson statistics. Monte Carlo simulations were performed to evaluate: (a) the performances of the dispersion parameter α estimator, (b) the goodness of fit of the NB model for a wide range of activity values. We focused on the effect produced by correction for random and scatter events in the projection (sinogram) domain, due to their importance in quantitative analysis of PET data. The analysis developed herein allowed us to assess the accuracy of the NB distribution model to fit corrected sinogram data, and to evaluate the sensitivity of the dispersion parameter α to quantify deviation from Poisson statistics. By the sinogram ROI-based analysis, it was demonstrated that deviation on the measured data from Poisson statistics can be quantitatively characterized by the dispersion parameter α, in any noise conditions and corrections.

Variable density randomized stack of spirals (VDR-SoS) for compressive sensing MRI.

PURPOSE: To develop a 3D sampling strategy based on a stack of variable density spirals for compressive sensing MRI. METHODS: A random sampling pattern was obtained by rotating each spiral by a random angle and by delaying for few time steps the gradient waveforms of the different interleaves. A three-dimensional (3D) variable sampling density was obtained by designing different variable density spirals for each slice encoding. The proposed approach was tested with phantom simulations up to a five-fold undersampling factor. Fully sampled 3D dataset of a human knee, and of a human brain, were obtained from a healthy volunteer. The proposed approach was tested with off-line reconstructions of the knee dataset up to a four-fold acceleration and compared with other noncoherent trajectories. RESULTS: The proposed approach outperformed the standard stack of spirals for various undersampling factors. The level of coherence and the reconstruction quality of the proposed approach were similar to those of other trajectories that, however, require 3D gridding for the reconstruction. CONCLUSION: The variable density randomized stack of spirals (VDR-SoS) is an easily implementable trajectory that could represent a valid sampling strategy for 3D compressive sensing MRI. It guarantees low levels of coherence without requiring 3D gridding. Magn Reson Med 76:59-69, 2016. © 2015 Wiley Periodicals, Inc.

A Cross-Correlational Analysis between Electroencephalographic and End-Tidal Carbon Dioxide Signals: Methodological Issues in the Presence of Missing Data and Real Data Results.

Electroencephalographic (EEG) irreducible artifacts are common and the removal of corrupted segments from the analysis may be required. The present study aims at exploring the effects of different EEG Missing Data Segment (MDS) distributions on cross-correlation analysis, involving EEG and physiological signals. The reliability of cross-correlation analysis both at single subject and at group level as a function of missing data statistics was evaluated using dedicated simulations. Moreover, a Bayesian-based approach for combining the single subject results at group level by considering each subject's reliability was introduced. Starting from the above considerations, the cross-correlation function between EEG Global Field Power (GFP) in delta band and end-tidal CO2 (PETCO2) during rest and voluntary breath-hold was evaluated in six healthy subjects. The analysis of simulated data results at single subject level revealed a worsening of precision and accuracy in the cross-correlation analysis in the presence of MDS. At the group level, a large improvement in the results' reliability with respect to single subject analysis was observed. The proposed Bayesian approach showed a slight improvement with respect to simple average results. Real data results were discussed in light of the simulated data tests and of the current physiological findings.

Effects of inner volume field-of-view reduction on myocardial T2 mapping.

BACKGROUND: Inner volume (IV) excitation was explored with respect to scan time reduction of cardiac gated double inversion recovery multi-echo fast spin echo (MEFSE) to measure the transverse relaxation time (T2 ) in the myocardium. METHODS: The IV imaging was achieved by applying orthogonal slice selection for the excitation and refocusing pulses. The T2 map accuracy was investigated using different excitation and refocusing pulses. The performance of IV-MEFSE was compared with MEFSE on phantoms and eight healthy volunteers, acquiring eight echo times in a single breath-hold. RESULTS: Compared with MEFSE, IV-MEFSE allowed a scan time reduction from 26 s to 16 s, but caused a T2 overestimation of approximately 10% due to stimulated echoes. CONCLUSION: IV successfully reduced the scan time to a single breath-hold feasible for many patients and remarkably facilitated the scan prescription, because there was no image aliasing concern. Care should be taken in using IV for T2 mapping because of T2 relaxation time overestimation.

Free-breathing, zero-TE MR lung imaging.

OBJECT: The investigation of three-dimensional radial, zero-echo time (TE) imaging for high-resolution, free-breathing magnetic resonance (MR) lung imaging using prospective and retrospective motion correction. MATERIALS AND METHODS: Zero-TE was implemented similarly to the rotating-ultra-fast-imaging-sequence, providing 3D, isotropic, radial imaging with proton density contrast. Respiratory motion was addressed using prospective triggering (PT), prospective gating (PG) and retrospective gating (RG) with physiological signals obtained from a respiratory belt and interleaved pencil beam and DC navigators. The methods were demonstrated on four healthy volunteers at 3T. RESULTS: 3D, radial zero-TE imaging with high imaging bandwidth and nominally zero echo-time enables efficient capture of short-lived signals from the lung parenchyma and the vessels. Compared to Cartesian encoding, unaccounted for free-breathing respiration resulted in only benign blurring artifacts confined to the origin of motion. Breath holding froze respiration but achieved only limited image resolution (~1.8 mm, 30 s). PT and PG obtained similar quality expiratory-phase images at 1.2 mm resolution in ~6 min scan time. RG allowed multi-phase imaging in ~15 min, derived from eight individually stored averages. CONCLUSION: Zero-TE appears to be an attractive pulse sequence for 3D isotropic lung imaging. Prospective and retrospective approaches provide high-quality, free-breathing MR lung imaging within reasonable scan time.

Modified cine inversion recovery pulse sequence for the quantification of myocardial T1 and gadolinium partition coefficient.

PURPOSE: To optimize and validate a modified cine inversion recovery sequence (MCine-IR) for myocardial T1 quantification and gadolinium partition coefficient (λ(Gd)) estimation at 1.5 T. MATERIALS AND METHODS: The original version of the cine inversion recovery sequence was modified to allow fully transverse magnetization recovery between two successive inversion pulses. Sixty heart phases were acquired from a number of heart cycles determined on a patient heart rate basis. Phantom studies were carried out to find the optimal effective TR for myocardial and blood pool T1 quantifications in pre- and postcontrast studies. Four patients with myocardial infarct (MI) and 22 dilated cardiomyopathy (DCM) were investigated, as well as 11 healthy subjects used as controls. RESULTS: Effective TR was identified to be 5000 msec and 2000 msec, respectively, for pre- and postcontrast studies. A longer precontrast (948 ± 102 msec) and shorter postcontrast (348 ± 27 msec) T1 in ischemic patients relative to DCM (815 ± 98 msec, P = 0.03 and 409 ± 42 msec, P = 0.001) were noted in delayed enhancement (DE) areas. In MI patients λ(Gd) resulted higher than in DCM in DE areas (609 ± 167 vs. 422 ± 52, P = 0.01) but lower in segments not exhibiting DE (355 ± 100 vs. 398 ± 54, P = 0.02). CONCLUSION: It was feasible to measure T1 and λ(Gd) with MCine-IR and the results were in good agreement with the literature.

Automatic 2D registration of renal perfusion image sequences by mutual information and adaptive prediction.

UNLABELLED: The objective of this study was to develop an automatic image registration technique capable of compensating for kidney motion in renal perfusion MRI, to assess the effect of renal artery stenosis on the kidney parenchyma. MATERIALS AND METHODS: Images from 20 patients scheduled for a renal perfusion study were acquired using a 1.5 T scanner. A free-breathing 3D-FSPGR sequence was used to acquire coronal views encompassing both kidneys following the infusion of Gd-BOPTA. A two-step registration algorithm was developed, including a preliminary registration minimising the quadratic difference and a fine registration maximising the mutual information (MI) between consecutive image frames. The starting point for the MI-based registration procedure was provided by an adaptive predictor that was able to predict kidney motion using a respiratory movement model. The algorithm was validated against manual registration performed by an expert user. RESULTS: The mean distance between the automatically and manually defined contours was 2.95 ± 0.81 mm, which was not significantly different from the interobserver variability of the manual registration procedure (2.86 ± 0.80 mm, P = 0.80). The perfusion indices evaluated on the manually and automatically extracted perfusion curves were not significantly different. CONCLUSIONS: The developed method is able to automatically compensate for kidney motion in perfusion studies, which prevents the need for time-consuming manual image registration.

The dynamics of EEG gamma responses to unpleasant visual stimuli: from local activity to functional connectivity.

Many electroencephalographic (EEG) studies on the cortical dynamics induced by unpleasant picture viewing demonstrated the modulation of event-related potentials (ERPs) components as a function of valence and the increase of gamma band responses to emotional stimuli; while only a few studies investigated phase synchronization phenomena such as inter-trial or between regions phase locking of gamma responses to emotional stimulation. The aim of this study was to provide a complete description of the cortical dynamics induced by unpleasant and neutral pictures viewing, from the ERP averages to gamma rhythm modulation, and its phase synchronization. Gamma rhythm modulation was estimated by the event-related synchronization (ERS) approach, and phase synchrony between trials and between cortical regions was studied by extending the phase-locking statistics (PLS) approach. Consistent with previous literature, an increase in P300 and late positive potential and an increase in gamma activity during viewing of unpleasant pictures as compared to neutral ones were found. No inter-trial synchronization was evoked by the stimuli, whereas widespread phase locking between sites was identified. In particular, differences in gamma synchronization between unpleasant and neutral stimuli were found. Specifically, at early (0-250 ms) lags from stimulus onset, in the 38-45 Hz gamma interval, stronger inter-site synchronizations for the unpleasant stimuli, even though quite widespread across the scalp, mainly involved the interhemispheric synchronization between temporal and frontal regions. In contrast, in the 30-37 Hz gamma interval, stronger synchronizations for the responses to neutral trials were found in the 500-750 time interval, mainly involving the temporo-parietal regions. These findings suggest that the full elaboration of unpleasant stimuli requires a tight interhemispheric communication between temporal and frontal regions that is realized by means of phase synchronization at about 40 Hz. In addition, in contrast with the idea of a broadband modulation of high-frequency activity by cognitive/emotional stimuli, the present findings i.e. stronger BRS responses to either emotional or neutral trials at specific frequency and time range, indicate that specific intervals of gamma activity could be each primarily involved in a specific aspect of stimulus processing.

How the signal-to-noise ratio influences hyperpolarized 13C dynamic MRS data fitting and parameter estimation.

MRS of hyperpolarized (13) C-labeled compounds represents a promising technique for in vivo metabolic studies. However, robust quantification and metabolic modeling are still important areas of investigation. In particular, time and spatial resolution constraints may lead to the analysis of MRS signals with low signal-to-noise ratio (SNR). The relationship between SNR and the precision of quantitative analysis for the evaluation of the in vivo kinetic behavior of metabolites is unknown. In this article, this topic is addressed by Monte Carlo simulations, covering the problem of MRS signal model parameter estimation, with strong emphasis on the peak amplitude and kinetic model parameters. The results of Monte Carlo simulation were confirmed by in vivo experiments on medium-sized animals injected with hyperpolarized [1-(13) C]pyruvate. The results of this study may be useful for the establishment of experimental planning and for the optimization of kinetic model estimation as a function of the SNR value.

Automatic PET-CT image registration method based on mutual information and genetic algorithms.

Hybrid PET/CT scanners can simultaneously visualize coronary artery disease as revealed by computed tomography (CT) and myocardial perfusion as measured by positron emission tomography (PET). Manual registration is usually required in clinical practice to compensate spatial mismatch between datasets. In this paper, we present a registration algorithm that is able to automatically align PET/CT cardiac images. The algorithm bases on mutual information (MI) as registration metric and on genetic algorithm as optimization method. A multiresolution approach was used to optimize the processing time. The algorithm was tested on computerized models of volumetric PET/CT cardiac data and on real PET/CT datasets. The proposed automatic registration algorithm smoothes the pattern of the MI and allows it to reach the global maximum of the similarity function. The implemented method also allows the definition of the correct spatial transformation that matches both synthetic and real PET and CT volumetric datasets.

Analysis, comparison and representation of occupational exposure to a static magnetic field in a 3-T MRI site.

The purpose of this study is to analyze exposure to the time-varying magnetic field caused by worker movements in a 3-T clinical magnetic resonance imaging (MRI) scanner. Measurements of the static magnetic field (B) in the proximity of the MRI scanner were performed to create a detailed map of the spatial gradient of B, in order to indicate the areas at high risk of exposure. Moreover, a personal exposure recording system was used in order to analyze and compare exposure to the static magnetic field during different routine procedures in MRI. We found that for all of the performed work activities, exposure was compliant with International Commission on Non-Ionizing Radiation Protection levels. However, our findings confirm that there is great variability of exposure between different workers and suggest the importance of performing personal exposure measurements and of detailed knowledge of the magnetic field spatial distribution.

Occupational exposure to electromagnetic fields in magnetic resonance environment: an update on regulation, exposure assessment techniques, health risk evaluation, and surveillance.

Magnetic resonance imaging (MRI) is one of the most-used diagnostic imaging methods worldwide. There are ∼50,000 MRI scanners worldwide each of which involves a minimum of five workers from different disciplines who spend their working days around MRI scanners. This review analyzes the state of the art of literature about the several aspects of the occupational exposure to electromagnetic fields (EMF) in MRI: regulations, literature studies on biological effects, and health surveillance are addressed here in detail, along with a summary of the main approaches for exposure assessment. The original research papers published from 2013 to 2021 in international peer-reviewed journals, in the English language, are analyzed, together with documents published by legislative bodies. The key points for each topic are identified and described together with useful tips for precise safeguarding of MRI operators, in terms of exposure assessment, studies on biological effects, and health surveillance.

A novel tool for estimation of magnetic resonance occupational exposure to spatially varying magnetic fields.

OBJECT: Staff operating in the environment of magnetic resonance imaging (MRI) scanners are exposed daily to static magnetic fields (MFs). To protect workers several guidelines are present in literature reporting exposure limits values expressed in terms of magnetic flux density or induced current density. We present here a novel tool for estimating the induced current density due to worker movement in the MR environment. MATERIALS AND METHODS: A Matlab script was created to estimate the induced current density J due to operator movements along a chosen walking path. RESULTS: The induced current density associated with any worker's movements during MR procedures is dependent on the walking speed and on the spatial gradient fields associated with a specific path. Some examples of possible worker paths were considered here for a 3 T MR scanner and a maximum value of 160 cm/s walking speed. CONCLUSION: This tool permits one to find exposure level for specific worker walking path and speed; it can be used as assessment tool in any MRI centre and for workers safety education. It is valid for any kind of commercial scanner because it requires only the knowledge of the MR scanner room map with isogauss lines.

Deep-learning-based cardiac amyloidosis classification from early acquired pet images.

The objective of the present work was to evaluate the potential of deep learning tools for characterizing the presence of cardiac amyloidosis from early acquired PET images, i.e. 15 min after [18F]-Florbetaben tracer injection. 47 subjects were included in the study: 13 patients with transthyretin-related amyloidosis cardiac amyloidosis (ATTR-CA), 15 patients with immunoglobulin light-chain amyloidosis (AL-CA), and 19 control-patients (CTRL). [18F]-Florbetaben PET/CT images were acquired in list mode and data was sorted into a sinogram, covering a time interval of 5 min starting 15 min after the injection. The resulting sinogram was reconstructed using OSEM iterative algorithm. A deep convolutional neural network (CAclassNet) was designed and implemented, consisting of five 2D convolutional layers, three fully connected layers and a final classifier returning AL, ATTR and CTRL scores. A total of 1107 2D images (375 from AL-subtype patients, 312 from ATTR-subtype, and 420 from Controls) have been considered in the study and used to train, validate and test the proposed network. CAclassNet cross-validation resulted with train error mean ± sd of 2.001% ± 0.96%, validation error of 4.5% ± 2.26%, and net accuracy of 95.49% ± 2.26%. Network test error resulted in a mean ± sd values of 10.73% ± 0.76%. Sensitivity, specificity, and accuracy evaluated on the test dataset were respectively for AL-CA sub-type: 1, 0.912, 0.936; for ATTR-CA: 0.935, 0.897, 0.972; for control subjects: 0.809, 0.971, 0.909. In conclusion, the proposed CAclassNet model seems very promising as an aid for the clinician in the diagnosis of CA from cardiac [18F]-Florbetaben PET images acquired a few minutes after the injection.

Registration of myocardial PET and SPECT for viability assessment using mutual information.

PURPOSE: The combination of sequentially acquired cardiac PET and SPECT data integrating metabolic and perfusion information allows the assessment of myocardial viability, a relevant clinical parameter for the management of patients who have suffered myocardial infarction and are now candidates for complex and cost intensive therapies such as bypass surgery. However, registration of cardiac functional datasets acquired on different imaging systems is limited by the difficulty to define anatomical landmarks and by the relatively poor inherent spatial resolution. In this article, the authors sought to evaluate whether it is possible to automatically register FDG-PET and sestamibi-SPECT cardiac data. METHODS: Automatic rigid registration was implemented with the ITK framework using Mattes mutual information as the similarity measure and a quaternion to represent the rotational component. The goodness of the alignment was evaluated by computing the mean target registration error (mTRE) at the myocardial wall. The registration parameters were optimized for robustness and speed using the data from 11 cardiac patients undergoing both PET and SPECT examinations (training datasets). The optimized algorithm was applied on the PET and SPECT data from 11 further patients (evaluation datasets). Quantitative (mTRE calculation) and visual (scoring method) comparisons were performed between automatic and manual registrations. Moreover, the automatic registration was also compared to the registration implicitly defined in the standard clinical analysis. RESULTS: The registration parameters were successfully optimized and resulted in a mean mTRE of 1.13 mm and 1.2 s average runtime on standard computer hardware for the training datasets. Automatic registration in the 11 validation datasets resulted in an average mTRE of 2.3 mm, with 7.5 mm mTRE in the worst case and an average runtime of 1.6 s. Automatic registration outperformed manual registrations both for the mTRE and for the visual assessment. Automatic registration also resulted in higher accuracy and better visual assessment as compared to the registration implicitly performed in the standard clinical analysis. CONCLUSIONS: The results demonstrate the possibility to successfully perform mutual information based registration of PET and SPECT cardiac data, allowing an improved workflow for the sequentially acquired cardiac datasets, in general, and specifically for the assessment of myocardial viability.

Hyperpolarized 13C MRS surface coil: design and signal-to-noise ratio estimation.

PURPOSE: Hyperpolarized carbon-13 magnetic resonance spectroscopy is a novel and powerful tool for exploring the metabolic state of tissue, but a number of technological problems still limit this technology and need innovative solutions. In particular, the low molar concentration of derivate metabolites give rise to low signal-to-noise ratio (SNR), which makes the design and development of dedicated RF coils a task of fundamental importance. In this article, the authors describe the simulation and the design of a dedicated 13C surface coil for cardiac metabolism assessment in pig models. METHODS: A SNR model for a circular loop is presented and applied to the design of a 13C coil which guarantees the desired field-of-view and provides high SNR with a good penetration in deep sample regions. The coil resistance was calculated from Ohm's law and the magnetic field pattern was calculated using Biot-Savart law, while the sample induced resistance was calculated using a numerical finite-difference time-domain algorithm. Successively, a prototype of the coil was built and tested on the workbench and by acquisition of MR data. RESULTS: The comparison of SNR-vs-depth profiles between the theoretical SNR model and the experimental SNR extracted from the phantom chemical shift image (CSI) showed the accuracy of the authors' model. Moreover, the authors demonstrated the use of the coil for the acquisition of a CSI of a hyperpolarized [1-13C] pyruvate phantom. CONCLUSIONS: The results demonstrated the design trade-offs to successfully design a dedicated coil for cardiac imaging in the pig with hyperpolarized 13C by developing a SNR model which allows the prediction of the coil performance. This approach can be employed for deriving SNR formulations for coil with more complex geometries.