Quantitative high-resolution renal perfusion imaging using 3-dimensional through-time radial generalized autocalibrating partially parallel acquisition. Invest Radiol. 2014;49:666-674. [PMID: 24879298 DOI: 10.1097/rli.0000000000000070]

In vivo methods and applications of xenon-129 magnetic resonance

Hyperpolarised gas lung MRI using xenon-129 can provide detailed 3D images of the ventilated lung airspaces, and can be applied to quantify lung microstructure and detailed aspects of lung function such as gas exchange. It is sensitive to functional and structural changes in early lung disease and can be used in longitudinal studies of disease progression and therapy response. The ability of ¹²⁹Xe to dissolve into the blood stream and its chemical shift sensitivity to its local environment allow monitoring of gas exchange in the lungs, perfusion of the brain and kidneys, and blood oxygenation. This article reviews the methods and applications of in vivo¹²⁹Xe MR in humans, with a focus on the physics of polarisation by optical pumping, radiofrequency coil and pulse sequence design, and the in vivo applications of ¹²⁹Xe MRI and MRS to examine lung ventilation, microstructure and gas exchange, blood oxygenation, and perfusion of the brain and kidneys.

Modeling dynamic radial contrast enhanced MRI with linear time invariant systems for motion correction in quantitative assessment of kidney function

Early identification of kidney function deterioration is essential to determine which newborn patients with congenital kidney disease should be considered for surgical intervention as opposed to observation. Kidney function can be measured by fitting a tracer kinetic (TK) model onto a series of Dynamic Contrast Enhanced (DCE) MR images and estimating the filtration rate parameter from the model. Unfortunately, breathing and large bulk motion events due to patient movement in the scanner create outliers and misalignments that introduce large errors in the TK model parameter estimates even when using a motion-robust dynamic radial VIBE sequence for DCE-MR imaging. The misalignments between the series of volumes are difficult to correct using standard registration due to 1) the large differences in geometry and contrast between volumes of the dynamic sequence and 2) the requirement of fast dynamic imaging to achieve high temporal resolution and motion deteriorates image quality. These difficulties reduce the accuracy and stability of registration over the dynamic sequence. An alternative registration approach is to generate noise and motion free templates of the original data from the TK model and use them to register each volume to its contrast-matched template. However, the TK models used to characterize DCE-MRI are tissue specific, non-linear and sensitive to the same motion and sampling artifacts that hinder registration in the first place. Hence, these can only be applied to register accurately pre-segmented regions of interest, such as kidneys, and might converge to local minima under the presence of large artifacts. Here we introduce a novel linear time invariant (LTI) model to characterize DCE-MR data for different tissue types within a volume. We approximate the LTI model as a sparse sum of first order LTI functions to introduce robustness to motion and sampling artifacts. Hence, this model is well suited for registration of the entire field of view of DCE-MR data with artifacts and outliers. We incorporate this LTI model into a registration framework and evaluate it on both synthetic data and data from 20 children. For each subject, we reconstructed the sequence of DCE-MR images, detected corrupted volumes acquired during motion, aligned the sequence of volumes and recovered the corrupted volumes using the LTI model. The results show that our approach correctly aligned the volumes, provided the most stable registration in time and improved the tracer kinetic model fit.

Quantifying Perfusion Properties with DCE-MRI Using a Dictionary Matching Approach

Perfusion properties can be estimated from pharmacokinetic models applied to DCE-MRI data using curve fitting algorithms; however, these suffer from drawbacks including the local minimum problem and substantial computational time. Here, a dictionary matching approach is proposed as an alternative. Curve fitting and dictionary matching were applied to simulated data using the dual-input single-compartment model with known perfusion property values and 5 in vivo DCE-MRI datasets. In simulation at SNR 60 dB, the dictionary estimate had a mean percent error of 0.4-1.0% for arterial fraction, 0.5-1.4% for distribution volume, and 0.0% for mean transit time. The curve fitting estimate had a mean percent error of 1.1-2.1% for arterial fraction, 0.5-1.3% for distribution volume, and 0.2-1.8% for mean transit time. In vivo, dictionary matching and curve fitting showed no statistically significant differences in any of the perfusion property measurements in any of the 10 ROIs between the methods. In vivo, the dictionary method performed over 140-fold faster than curve fitting, obtaining whole volume perfusion maps in just over 10 s. This study establishes the feasibility of using a dictionary matching approach as a new and faster way of estimating perfusion properties from pharmacokinetic models in DCE-MRI.

Feasibility of pulmonary MRI for nodule detection in comparison to computed tomography

Background

To assess the feasibility of various magnetic resonance imaging (MRI) sequences for the detection of pulmonary nodules by comparing the detection rate of computed tomography (CT).

Methods

Forty-two patients with pulmonary nodules detected by multi-slice CT (MSCT) were prospectively enrolled in the present study between November 2016 and February 2017. Chest MRI was acquired within 24 h of CT. The MRI protocol included free-breathing radial VIBE (r-VIBE) and a conventional breathhold T1-weighted VIBE (C-VIBE) were analyzed by two independent radiologists. Both detection and morphology results of each MRI image were recorded. Subjective image evaluation in terms of overall nodule morphology on the MRI images was carried out using the 4-point scoring criteria. The MRI results were compared with those from CT, with the results of MSCT serving as the reference standard.

Results

Two hundred and fifty-eight solid pulmonary nodules in 42 patients were detected by CT. The r-VIBE correctly detected 94% of the pulmonary nodules as compared with CT. The detection rate increased to 100% for lesions ≥6 mm. The C-VIBE had a lower overall detection rate (64.3%) of pulmonary nodules. The difference in the subjective image evaluation scores between the two sequences was statistically significant (p < 0.001).

Conclusion

Significantly increased detection rates were obtained with free-breathing r-VIBE as compared with C-VIBE for the detection of pulmonary nodules and also provided more information when evaluating the nodules as compared with C-VIBE.

Self-calibrated interpolation of non-Cartesian data with GRAPPA in parallel imaging

PURPOSE

To develop a non-Cartesian k-space reconstruction method using self-calibrated region-specific interpolation kernels for highly accelerated acquisitions.

METHODS

In conventional non-Cartesian GRAPPA with through-time GRAPPA (TT-GRAPPA), the use of region-specific interpolation kernels has demonstrated improved reconstruction quality in dynamic imaging for highly accelerated acquisitions. However, TT-GRAPPA requires the acquisition of a large number of separate calibration scans. To reduce the overall imaging time, we propose Self-calibrated Interpolation of Non-Cartesian data with GRAPPA (SING) to self-calibrate region-specific interpolation kernels from dynamic undersampled measurements. The SING method synthesizes calibration data to adapt to the distinct shape of each region-specific interpolation kernel geometry, and uses a novel local k-space regularization through an extension of TT-GRAPPA. This calibration approach is used to reconstruct non-Cartesian images at high acceleration rates while mitigating noise amplification. The reconstruction quality of SING is compared with conjugate-gradient SENSE and TT-GRAPPA in numerical phantoms and in vivo cine data sets.

RESULTS

In both numerical phantom and in vivo cine data sets, SING offers visually and quantitatively similar reconstruction quality to TT-GRAPPA, and provides improved reconstruction quality over conjugate-gradient SENSE. Furthermore, temporal fidelity in SING and TT-GRAPPA is similar for the same acceleration rates. G-factor evaluation over the heart shows that SING and TT-GRAPPA provide similar noise amplification at moderate and high rates.

CONCLUSION

The proposed SING reconstruction enables significant improvement of acquisition efficiency for calibration data, while matching the reconstruction performance of TT-GRAPPA.

Image registration in dynamic renal MRI-current status and prospects

Magnetic resonance imaging (MRI) modalities have achieved an increasingly important role in the clinical work-up of chronic kidney diseases (CKD). This comprises among others assessment of hemodynamic parameters by arterial spin labeling (ASL) or dynamic contrast-enhanced (DCE-) MRI. Especially in the latter, images or volumes of the kidney are acquired over time for up to several minutes. Therefore, they are hampered by motion, e.g., by pulsation, peristaltic, or breathing motion. This motion can hinder subsequent image analysis to estimate hemodynamic parameters like renal blood flow or glomerular filtration rate (GFR). To overcome motion artifacts in time-resolved renal MRI, a wide range of strategies have been proposed. Renal image registration approaches could be grouped into (1) image acquisition techniques, (2) post-processing methods, or (3) a combination of image acquisition and post-processing approaches. Despite decades of progress, the translation in clinical practice is still missing. The aim of the present article is to discuss the existing literature on renal image registration techniques and show today’s limitations of the proposed techniques that hinder clinical translation. This paper includes transformation, criterion function, and search types as traditional components and emerging registration technologies based on deep learning. The current trend points towards faster registrations and more accurate results. However, a standardized evaluation of image registration in renal MRI is still missing.

Renal perfusion imaging by MRI

Renal perfusion can be quantitatively assessed by multiple magnetic resonance imaging (MRI) methods, including dynamic contrast enhanced (DCE), arterial spin labeling (ASL), and diffusion-weighted imaging with intravoxel incoherent motion (IVIM) analysis. In this review we summarize the advances in the field of renal-perfusion MRI over the past 5 years. The review starts with a brief introduction of relevant MRI methods, followed by a discussion of recent technical developments. In the main section of the review, we examine the clinical and preclinical applications for three disease populations: chronic kidney disease, renal transplant, and renal tumors. The DCE method has been routinely used for assessing renal tumors but not other renal diseases. As a noncontrast alternative, ASL was extensively explored in both preclinical and clinical applications and showed much promise. Protocol standardization for the methods is desperately needed, and then large-scale clinical trials for the methods can be initiated prior to their broad clinical use. Level of Evidence: 5 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019. J. Magn. Reson. Imaging 2020;52:369-379.

A modified two-compartment model for measurement of renal function using dynamic contrast-enhanced computed tomography

Objectives

To validate and adapt a modified two-compartment model, originally developed for magnetic resonance imaging, for measuring human single-kidney glomerular filtration rate (GFR) and perfusion using dynamic contrast-enhanced computed tomography (DCE-CT).

Methods

This prospective study was approved by the institutional review board, and written informed consent was obtained from all patients. Thirty-eight patients with essential hypertension (EH, n = 13) or atherosclerotic renal artery stenosis (ARAS, n = 25) underwent renal DCE-CT for GFR and perfusion measurement using a modified two-compartment model. Iothalamate clearance was used to measure reference total GFR, which was apportioned into single-kidney GFR by renal blood flow. Renal perfusion was also calculated using a conventional deconvolution algorithm. Validation of GFR and perfusion and inter-observer reproducibility, were conducted by using the Pearson correlation and Bland-Altman analysis.

Results

Both the two-compartment model and iothalamate clearance detected in ARAS patients lower GFR in the stenotic compared to the contralateral and EH kidneys. GFRs measured by DCE-CT and iothalamate clearance showed a close match (r = 0.94, P<0.001, and mean difference 2.5±12.2mL/min). Inter-observer bias and variation in model-derived GFR (r = 0.97, P<0.001; mean difference, 0.3±7.7mL/min) were minimal. Renal perfusion by deconvolution agreed well with that by the compartment model when the blood transit delay from abdominal aorta to kidney was negligible.

Conclusion

The proposed two-compartment model faithfully depicts contrast dynamics using DCE-CT and may provide a reliable tool for measuring human single-kidney GFR and perfusion.

Single breath-hold 3D cardiac T1 mapping using through-time spiral GRAPPA

The quantification of cardiac T1 relaxation time holds great potential for the detection of various cardiac diseases. However, as a result of both cardiac and respiratory motion, only one two-dimensional T1 map can be acquired in one breath-hold with most current techniques, which limits its application for whole heart evaluation in routine clinical practice. In this study, an electrocardiogram (ECG)-triggered three-dimensional Look-Locker method was developed for cardiac T1 measurement. Fast three-dimensional data acquisition was achieved with a spoiled gradient-echo sequence in combination with a stack-of-spirals trajectory and through-time non-Cartesian generalized autocalibrating partially parallel acquisition (GRAPPA) acceleration. The effects of different magnetic resonance parameters on T1 quantification with the proposed technique were first examined by simulating data acquisition and T1 map reconstruction using Bloch equation simulations. Accuracy was evaluated in studies with both phantoms and healthy subjects. These results showed that there was close agreement between the proposed technique and the reference method for a large range of T1 values in phantom experiments. In vivo studies further demonstrated that rapid cardiac T1 mapping for 12 three-dimensional partitions (spatial resolution, 2 × 2 × 8 mm3 ) could be achieved in a single breath-hold of ~12 s. The mean T1 values of myocardial tissue and blood obtained from normal volunteers at 3 T were 1311 ± 66 and 1890 ± 159 ms, respectively. In conclusion, a three-dimensional T1 mapping technique was developed using a non-Cartesian parallel imaging method, which enables fast and accurate T1 mapping of cardiac tissues in a single short breath-hold.

Functional Magnetic Resonance Imaging of the Kidneys-With and Without Gadolinium-Based Contrast

Assessment of renal function with magnetic resonance imaging (MRI) has been actively explored in the past decade. In this review, we introduce the principle of MRI and review recent progress of MRI methods (contrast enhanced and noncontrast) in assessing renal function. Contrast-enhanced MRI using ultra-low dose of gadolinium-based agent has been validated for measuring single-kidney glomerular filtration rate and renal plasma flow accurately. For routine functional test, contrast-enhanced MRI may not replace the simple serum-creatinine method. However, for patients with renal diseases, it is often worthy to perform MRI to accurately monitor renal function, particularly for the diseased kidney. As contrast-enhanced MRI is already an established clinical tool for characterizing renal structural abnormalities, including renal mass and ureteral obstruction, it is possible to adapt the clinical MRI protocol to measure single-kidney glomerular filtration rate and renal plasma flow, as demonstrated by recent studies. What makes MRI unique is the promise of its noncontrast methods. These methods include arterial spin labeling for tissue perfusion, blood oxygen-level dependent for blood and tissue oxygenation, and diffusion-weighted imaging for water diffusion. For each method, we reviewed recent findings and summarized challenges.

Multiresolution imaging using golden angle stack-of-stars and compressed sensing for dynamic MR urography

PURPOSE

To develop a novel multiresolution MRI methodology for accurate estimation of glomerular filtration rate (GFR) in vivo.

MATERIALS AND METHODS

A three-dimensional golden-angle radial stack-of-stars (SoS) trajectory was used for data acquisition on a 3 Tesla MRI scanner. Multiresolution reconstruction and analysis was performed using arterial input function reconstructed at 1-s. temporal resolution and renal dynamic data reconstructed using compressed sensing (CS) with 4-s temporal resolution. The method was first validated using simulations and the clinical utility of the technique was evaluated by comparing the GFR estimates from the proposed method to the estimated GFR (eGFR) obtained from serum creatinine for 10 subjects.

RESULTS

The 4-s temporal resolution CS images minimized streaking artifacts and noise while the 1-s temporal resolution AIF minimized errors in GFR estimates. A paired t-test showed that there was no statistically significant difference between MRI based total GFR values and serum creatinine based eGFR estimates (P = 0.92).

CONCLUSION

We have demonstrated the feasibility of multiresolution MRI using a golden angle radial stack-of-stars scheme to accurately estimate GFR as well as produce diagnostic quality dynamic images in vivo.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 3 J. MAGN. RESON. IMAGING 2017;46:303-311.

Free-breathing radial volumetric interpolated breath-hold examination vs breath-hold cartesian volumetric interpolated breath-hold examination magnetic resonance imaging of the liver at 1.5T

AIM: To compare breath-hold cartesian volumetric interpolated breath-hold examination (cVIBE) and free-breathing radial VIBE (rVIBE) and determine whether rVIBE could replace cVIBE in routine liver magnetic resonance imaging (MRI).

METHODS: In this prospective study, 15 consecutive patients scheduled for routine MRI of the abdomen underwent pre- and post-contrast breath-hold cVIBE imaging (19 s acquisition time) and free-breathing rVIBE imaging (111 s acquisition time) on a 1.5T Siemens scanner. Three radiologists with 2, 4, and 8 years post-fellowship experience in abdominal imaging evaluated all images. The radiologists were blinded to the sequence types, which were presented in a random order for each patient. For each sequence, the radiologists scored the cVIBE and rVIBE images for liver edge sharpness, hepatic vessel clarity, presence of artifacts, lesion conspicuity, fat saturation, and overall image quality using a five-point scale.

RESULTS: Compared to rVIBE, cVIBE yielded significantly (P < 0.001) higher scores for liver edge sharpness (mean score, 3.87 vs 3.37), hepatic-vessel clarity (3.71 vs 3.18), artifacts (3.74 vs 3.06), lesion conspicuity (3.81 vs 3.2), and overall image quality (3.91 vs 3.24). cVIBE and rVIBE did not significantly differ in quality of fat saturation (4.12 vs 4.03, P = 0.17). The inter-observer variability with respect to differences between rVIBE and cVIBE scores was close to zero compared to random error and inter-patient variation. Quality of rVIBE images was rated as acceptable for all parameters.

CONCLUSION: rVIBE cannot replace cVIBE in routine liver MRI. At 1.5T, free-breathing rVIBE yields acceptable, although slightly inferior image quality compared to breath-hold cVIBE.

Sparse Reconstruction Techniques in Magnetic Resonance Imaging: Methods, Applications, and Challenges to Clinical Adoption

The family of sparse reconstruction techniques, including the recently introduced compressed sensing framework, has been extensively explored to reduce scan times in magnetic resonance imaging (MRI). While there are many different methods that fall under the general umbrella of sparse reconstructions, they all rely on the idea that a priori information about the sparsity of MR images can be used to reconstruct full images from undersampled data. This review describes the basic ideas behind sparse reconstruction techniques, how they could be applied to improve MRI, and the open challenges to their general adoption in a clinical setting. The fundamental principles underlying different classes of sparse reconstructions techniques are examined, and the requirements that each make on the undersampled data outlined. Applications that could potentially benefit from the accelerations that sparse reconstructions could provide are described, and clinical studies using sparse reconstructions reviewed. Lastly, technical and clinical challenges to widespread implementation of sparse reconstruction techniques, including optimization, reconstruction times, artifact appearance, and comparison with current gold standards, are discussed.

Measurement of glomerular filtration rate by dynamic contrast-enhanced magnetic resonance imaging using a subject-specific two-compartment model

Measuring glomerular filtration rate (GFR) by dynamic contrast‐enhanced (DCE) magnetic resonance imaging (MRI) as part of standard of care clinical MRI exams (e.g., in pediatric solid tumor patients) has the potential to reduce diagnostic burden. However, enthusiasm for this relatively new GFR test may be curbed by the limited amount of cross‐calibration studies with reference GFR techniques and the vast variety of MR tracer model algorithms causing confusion on the choice of model. To advance MRI‐based GFR quantification via improved GFR modeling and comparison with associated ^99mTc‐DTPA‐GFR, 29 long‐term Wilms' tumor survivors (19.0–43.3 years, [median 32.0 ± 6.0 years]) treated with nephrectomy, nonnephrotoxic chemotherapy ± radiotherapy underwent MRI with Gd‐DTPA administration and a ^99mTc‐DTPA GFR test. For DCE‐MRI‐based GFR estimation, a subject‐specific two‐compartment (SS‐2C) model was developed that uses individual hematocrit values, automatically defines subject‐specific uptake intervals, and fits tracer‐uptake curves by incorporating these measures. The association between reference ^99mTc‐DTPA GFR and MR‐GFRs obtained by SS‐2C, three published 2C uptake, and inflow–outflow models was investigated via linear regression analysis. Uptake intervals varied from 64 sec to 141 sec [96 sec ± 21 sec] and hematocrit values ranged from 30% to 49% [41% ± 4%]; these parameters can therefore not be assumed as constants in 2C modeling. Our MR‐GFR estimates using the SS‐2C model showed accordingly the highest correlation with ^99mTc‐DTPA‐GFRs (R² = 0.76, P < 0.001) compared with other models (R²‐range: 0.36–0.66). In conclusion, SS‐2C modeling of DCE‐MRI data improved the association between GFR obtained by ^99mTc‐DTPA and Gd‐DTPA DCE‐MRI to such a degree that this approach could turn into a viable, diagnostic GFR assay without radiation exposure to the patient.

Real-time free-breathing cardiac imaging with self-calibrated through-time radial GRAPPA

PURPOSE

Real-time free-breathing cardiac imaging with highly undersampled radial trajectories has previously been successfully demonstrated using calibrated radial generalized autocalibrating partially parallel acquisition (rGRAPPA). A self-calibrated approach for rGRAPPA is proposed that removes the need for the calibration prescan.

METHODS

To investigate the effect of various parameters on image quality, a comprehensive imaging study on one normal swine was performed. Root mean squared errors (RMSEs) were computed with respect to gold standard acquisitions, and several acquisition/reconstruction strategies were compared. Additionally, the method was tested on 13 human subjects, and RMSEs relative to standard through-time radial GRAPPA were computed.

RESULTS

Real-time images with high spatiotemporal resolution were obtained. Image quality was comparable to calibrated through-time rGRAPPA with endocardial and epicardial borders clearly delineated. In the swine, the average RMSE between self-calibrated and gold-standard calibrated images was 5.18 ± 0.84%. In normal human subjects, the average RMSE between self-calibrated and calibrated through-time rGRAPPA was 3.79 ± 0.64%. For lower accelerations rates (R = 6-8) image quality was similar to comparable calibrated scans though RMSE increased for higher degrees of undersampling (R = 12-16).

CONCLUSION

Highly accelerated real-time imaging with undersampled radial trajectories without additional calibration data is feasible. Image quality was acceptable for real-time cardiac MRI applications demanding high speed. Magn Reson Med 77:250-264, 2017. © 2016 Wiley Periodicals, Inc.

Free-breathing liver perfusion imaging using 3-dimensional through-time spiral generalized autocalibrating partially parallel acquisition acceleration

OBJECTIVES

The goal of this study was to develop free-breathing high-spatiotemporal resolution dynamic contrast-enhanced liver magnetic resonance imaging using non-Cartesian parallel imaging acceleration, and quantitative liver perfusion mapping.

MATERIALS AND METHODS

This study was approved by the local institutional review board and written informed consent was obtained from all participants. Ten healthy subjects and 5 patients were scanned on a Siemens 3-T Skyra scanner. A stack-of-spirals trajectory was undersampled in-plane with a reduction factor of 6 and reconstructed using 3-dimensional (3D) through-time non-Cartesian generalized autocalibrating partially parallel acquisition. High-resolution 3D images were acquired with a true temporal resolution of 1.6 to 1.9 seconds while the subjects were breathing freely. A dual-input single-compartment model was used to retrieve liver perfusion parameters from dynamic contrast-enhanced magnetic resonance imaging data, which were coregistered using an algorithm designed to reduce the effects of dynamic contrast changes on registration. Image quality evaluation was performed on spiral images and conventional images from 5 healthy subjects.

RESULTS

Images with a spatial resolution of 1.9 × 1.9 × 3 mm3 were obtained with whole-liver coverage. With an imaging speed of better than 2 s/vol, free-breathing scans were achieved and dynamic changes in enhancement were captured. The overall image quality of free-breathing spiral images was slightly lower than that of conventional long breath-hold Cartesian images, but it provided clinically acceptable or better image quality. The free-breathing 3D images were registered with almost no residual motion in liver tissue. After the registration, quantitative whole-liver 3D perfusion maps were obtained and the perfusion parameters are all in good agreement with the literature.

CONCLUSIONS

This high-spatiotemporal resolution free-breathing 3D liver imaging technique allows voxelwise quantification of liver perfusion.

Rapid volumetric T1 mapping of the abdomen using three-dimensional through-time spiral GRAPPA

PURPOSE

To develop an ultrafast T1 mapping method for high-resolution, volumetric T1 measurements in the abdomen.

METHODS

The Look-Locker method was combined with a stack-of-spirals acquisition accelerated using three-dimensional (3D) through-time spiral GRAPPA reconstruction for fast data acquisition. A segmented k-space acquisition scheme was proposed and the time delay between segments for the recovery of longitudinal magnetization was optimized using Bloch equation simulations. The accuracy of this method was validated in a phantom experiment and in vivo T1 measurements were performed with 35 asymptomatic subjects on both 1.5 Tesla (T) and 3T MRI systems.

RESULTS

Phantom experiments yielded close agreement between the proposed method and gold standard measurements for a large range of T1 values (200 to 1600 ms). The in vivo results further demonstrate that high-resolution T1 maps (2 × 2 × 4 mm(3)) for 32 slices can be achieved in a single clinically feasible breath-hold of approximately 20 s. The T1 values for multiple organs and tissues in the abdomen are in agreement with the published literature.

CONCLUSION

A high-resolution 3D abdominal T1 mapping technique was developed, which allows fast and accurate T1 mapping of multiple abdominal organs and tissues in a single breath-hold.

Quantification of left ventricular functional parameter values using 3D spiral bSSFP and through-time non-Cartesian GRAPPA

BACKGROUND

The standard clinical acquisition for left ventricular functional parameter analysis with cardiovascular magnetic resonance (CMR) uses a multi-breathhold multi-slice segmented balanced SSFP sequence. Performing multiple long breathholds in quick succession for ventricular coverage in the short-axis orientation can lead to fatigue and is challenging in patients with severe cardiac or respiratory disorders. This study combines the encoding efficiency of a six-fold undersampled 3D stack of spirals balanced SSFP sequence with 3D through-time spiral GRAPPA parallel imaging reconstruction. This 3D spiral method requires only one breathhold to collect the dynamic data.

METHODS

Ten healthy volunteers were recruited for imaging at 3 T. The 3D spiral technique was compared against 2D imaging in terms of systolic left ventricular functional parameter values (Bland-Altman plots), total scan time (Welch's t-test) and qualitative image rating scores (Wilcoxon signed-rank test).

RESULTS

Systolic left ventricular functional values were not significantly different (i.e. 3D-2D) between the methods. The 95% confidence interval for ejection fraction was -0.1 ± 1.6% (mean ± 1.96*SD). The total scan time for the 3D spiral technique was 48 s, which included one breathhold with an average duration of 14 s for the dynamic scan, plus 34 s to collect the calibration data under free-breathing conditions. The 2D method required an average of 5 min 40s for the same coverage of the left ventricle. The difference between 3D and 2D image rating scores was significantly different from zero (Wilcoxon signed-rank test, p < 0.05); however, the scores were at least 3 (i.e. average) or higher for 3D spiral imaging.

CONCLUSION

The 3D through-time spiral GRAPPA method demonstrated equivalent systolic left ventricular functional parameter values, required significantly less total scan time and yielded acceptable image quality with respect to the 2D segmented multi-breathhold standard in this study. Moreover, the 3D spiral technique used just one breathhold for dynamic imaging, which is anticipated to reduce patient fatigue as part of the complete cardiac examination in future studies that include patients.