Improved reproducibility for myocardial ASL: Impact of physiological and acquisition parameters.

PURPOSE: To investigate and mitigate the influence of physiological and acquisition-related parameters on myocardial blood flow (MBF) measurements obtained with myocardial Arterial Spin Labeling (myoASL). METHODS: A Flow-sensitive Alternating Inversion Recovery (FAIR) myoASL sequence with bSSFP and spoiled GRE (spGRE) readout is investigated for MBF quantification. Bloch-equation simulations and phantom experiments were performed to evaluate how variations in acquisition flip angle (FA), acquisition matrix size (AMS), heart rate (HR) and blood T 1 $$ {\mathrm{T}}_1 $$ relaxation time ( T 1 , B $$ {\mathrm{T}}_{1,B} $$ ) affect quantification of myoASL-MBF. In vivo myoASL-images were acquired in nine healthy subjects. A corrected MBF quantification approach was proposed based on subject-specific T 1 , B $$ {\mathrm{T}}_{1,B} $$ values and, for spGRE imaging, subtracting an additional saturation-prepared baseline from the original baseline signal. RESULTS: Simulated and phantom experiments showed a strong dependence on AMS and FA ( R 2 $$ {R}^2 $$ >0.73), which was eliminated in simulations and alleviated in phantom experiments using the proposed saturation-baseline correction in spGRE. Only a very mild HR dependence ( R 2 $$ {R}^2 $$ >0.59) was observed which was reduced when calculating MBF with individual T 1 , B $$ {\mathrm{T}}_{1,B} $$ . For corrected spGRE, in vivo mean global spGRE-MBF ranged from 0.54 to 2.59 mL/g/min and was in agreement with previously reported values. Compared to uncorrected spGRE, the intra-subject variability within a measurement (0.60 mL/g/min), between measurements (0.45 mL/g/min), as well as the inter-subject variability (1.29 mL/g/min) were improved by up to 40% and were comparable with conventional bSSFP. CONCLUSION: Our results show that physiological and acquisition-related factors can lead to spurious changes in myoASL-MBF if not accounted for. Using individual T 1 , B $$ {\mathrm{T}}_{1,B} $$ and a saturation-baseline can reduce these variations in spGRE and improve reproducibility of FAIR-myoASL against acquisition parameters.

The future of cardiovascular magnetic resonance: All-in-one vs. real-time (Part 1).

Cardiovascular magnetic resonance (CMR) protocols can be lengthy and complex, which has driven the research community to develop new technologies to make these protocols more efficient and patient-friendly. Two different approaches to improving CMR have been proposed, specifically "all-in-one" CMR, where several contrasts and/or motion states are acquired simultaneously, and "real-time" CMR, in which the examination is accelerated to avoid the need for breathholding and/or cardiac gating. The goal of this two-part manuscript is to describe these two different types of emerging rapid CMR. To this end, the vision of each is described, along with techniques which have been devised and tested along the pathway of clinical implementation. The pros and cons of the different methods are presented, and the remaining open needs of each are detailed. Part 1 will tackle the "all-in-one" approaches, and Part 2 the "real-time" approaches along with an overall summary of these emerging methods.

Signal intensity informed multi-coil encoding operator for physics-guided deep learning reconstruction of highly accelerated myocardial perfusion CMR.

PURPOSE: To develop a physics-guided deep learning (PG-DL) reconstruction strategy based on a signal intensity informed multi-coil (SIIM) encoding operator for highly-accelerated simultaneous multislice (SMS) myocardial perfusion cardiac MRI (CMR). METHODS: First-pass perfusion CMR acquires highly-accelerated images with dynamically varying signal intensity/SNR following the administration of a gadolinium-based contrast agent. Thus, using PG-DL reconstruction with a conventional multi-coil encoding operator leads to analogous signal intensity variations across different time-frames at the network output, creating difficulties in generalization for varying SNR levels. We propose to use a SIIM encoding operator to capture the signal intensity/SNR variations across time-frames in a reformulated encoding operator. This leads to a more uniform/flat contrast at the output of the PG-DL network, facilitating generalizability across time-frames. PG-DL reconstruction with the proposed SIIM encoding operator is compared to PG-DL with conventional encoding operator, split slice-GRAPPA, locally low-rank (LLR) regularized reconstruction, low-rank plus sparse (L + S) reconstruction, and regularized ROCK-SPIRiT. RESULTS: Results on highly accelerated free-breathing first pass myocardial perfusion CMR at three-fold SMS and four-fold in-plane acceleration show that the proposed method improves upon the reconstruction methods use for comparison. Substantial noise reduction is achieved compared to split slice-GRAPPA, and aliasing artifacts reduction compared to LLR regularized reconstruction, L + S reconstruction and PG-DL with conventional encoding. Furthermore, a qualitative reader study indicated that proposed method outperformed all methods. CONCLUSION: PG-DL reconstruction with the proposed SIIM encoding operator improves generalization across different time-frames /SNRs in highly accelerated perfusion CMR.

Robust cardiac T 1 ρ $$ {\mathrm{T}}_{1_{\boldsymbol{\rho}}} $$ mapping at 3T using adiabatic spin-lock preparations.

PURPOSE: The aim of this study is to develop and optimize an adiabatic T 1 ρ $$ {\mathrm{T}}_{1\uprho} $$ ( T 1 ρ , adiab $$ {\mathrm{T}}_{1\uprho, \mathrm{adiab}} $$ ) mapping method for robust quantification of spin-lock (SL) relaxation in the myocardium at 3T. METHODS: Adiabatic SL (aSL) preparations were optimized for resilience against B 0 $$ {\mathrm{B}}_0 $$ and B 1 + $$ {\mathrm{B}}_1^{+} $$ inhomogeneities using Bloch simulations. Optimized B 0 $$ {\mathrm{B}}_0 $$ -aSL, Bal-aSL and B 1 $$ {\mathrm{B}}_1 $$ -aSL modules, each compensating for different inhomogeneities, were first validated in phantom and human calf. Myocardial T 1 ρ $$ {\mathrm{T}}_{1\uprho} $$ mapping was performed using a single breath-hold cardiac-triggered bSSFP-based sequence. Then, optimized T 1 ρ , adiab $$ {\mathrm{T}}_{1\uprho, \mathrm{adiab}} $$ preparations were compared to each other and to conventional SL-prepared T 1 ρ $$ {\mathrm{T}}_{1\uprho} $$ maps (RefSL) in phantoms to assess repeatability, and in 13 healthy subjects to investigate image quality, precision, reproducibility and intersubject variability. Finally, aSL and RefSL sequences were tested on six patients with known or suspected cardiovascular disease and compared with LGE, T 1 $$ {\mathrm{T}}_1 $$ , and ECV mapping. RESULTS: The highest T 1 ρ , adiab $$ {\mathrm{T}}_{1\uprho, \mathrm{adiab}} $$ preparation efficiency was obtained in simulations for modules comprising 2 HS pulses of 30 ms each. In vivo T 1 ρ , adiab $$ {\mathrm{T}}_{1\uprho, \mathrm{adiab}} $$ maps yielded significantly higher quality than RefSL maps. Average myocardial T 1 ρ , adiab $$ {\mathrm{T}}_{1\uprho, \mathrm{adiab}} $$ values were 183.28 ± $$ \pm $$ 25.53 ms, compared with 38.21 ± $$ \pm $$ 14.37 ms RefSL-prepared T 1 ρ $$ {\mathrm{T}}_{1\uprho} $$ . T 1 ρ , adiab $$ {\mathrm{T}}_{1\uprho, \mathrm{adiab}} $$ maps showed a significant improvement in precision (avg. 14.47 ± $$ \pm $$ 3.71% aSL, 37.61 ± $$ \pm $$ 19.42% RefSL, p < 0.01) and reproducibility (avg. 4.64 ± $$ \pm $$ 2.18% aSL, 47.39 ± $$ \pm $$ 12.06% RefSL, p < 0.0001), with decreased inter-subject variability (avg. 8.76 ± $$ \pm $$ 3.65% aSL, 51.90 ± $$ \pm $$ 15.27% RefSL, p < 0.0001). Among aSL preparations, B 0 $$ {\mathrm{B}}_0 $$ -aSL achieved the better inter-subject variability. In patients, B 1 $$ {\mathrm{B}}_1 $$ -aSL preparations showed the best artifact resilience among the adiabatic preparations. T 1 ρ , adiab $$ {\mathrm{T}}_{1\uprho, \mathrm{adiab}} $$ times show focal alteration colocalized with areas of hyper-enhancement in the LGE images. CONCLUSION: Adiabatic preparations enable robust in vivo quantification of myocardial SL relaxation times at 3T.

Development, validation, qualification, and dissemination of quantitative MR methods: Overview and recommendations by the ISMRM quantitative MR study group.

On behalf of the International Society for Magnetic Resonance in Medicine (ISMRM) Quantitative MR Study Group, this article provides an overview of considerations for the development, validation, qualification, and dissemination of quantitative MR (qMR) methods. This process is framed in terms of two central technical performance properties, i.e., bias and precision. Although qMR is confounded by undesired effects, methods with low bias and high precision can be iteratively developed and validated. For illustration, two distinct qMR methods are discussed throughout the manuscript: quantification of liver proton-density fat fraction, and cardiac T1 . These examples demonstrate the expansion of qMR methods from research centers toward widespread clinical dissemination. The overall goal of this article is to provide trainees, researchers, and clinicians with essential guidelines for the development and validation of qMR methods, as well as an understanding of necessary steps and potential pitfalls for the dissemination of quantitative MR in research and in the clinic.

Emerging Techniques in Cardiac Magnetic Resonance Imaging.

Cardiovascular disease is the leading cause of death and a significant contributor of health care costs. Noninvasive imaging plays an essential role in the management of patients with cardiovascular disease. Cardiac magnetic resonance (MR) can noninvasively assess heart and vascular abnormalities, including biventricular structure/function, blood hemodynamics, myocardial tissue composition, microstructure, perfusion, metabolism, coronary microvascular function, and aortic distensibility/stiffness. Its ability to characterize myocardial tissue composition is unique among alternative imaging modalities in cardiovascular disease. Significant growth in cardiac MR utilization, particularly in Europe in the last decade, has laid the necessary clinical groundwork to position cardiac MR as an important imaging modality in the workup of patients with cardiovascular disease. Although lack of availability, limited training, physician hesitation, and reimbursement issues have hampered widespread clinical adoption of cardiac MR in the United States, growing clinical evidence will ultimately overcome these challenges. Advances in cardiac MR techniques, particularly faster image acquisition, quantitative myocardial tissue characterization, and image analysis have been critical to its growth. In this review article, we discuss recent advances in established and emerging cardiac MR techniques that are expected to strengthen its capability in managing patients with cardiovascular disease. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 1.

Saturation-pulse prepared heart-rate independent inversion-recovery (SAPPHIRE) biventricular T1 mapping: inter-field strength, head-to-head comparison of diastolic, systolic and dark-blood measurements.

BACKGROUND: To assess the feasibility of biventricular SAPPHIRE T1 mapping in vivo across field strengths using diastolic, systolic and dark-blood (DB) approaches. METHODS: 10 healthy volunteers underwent same-day non-contrast cardiovascular magnetic resonance at 1.5 Tesla (T) and 3 T. Left and right ventricular (LV, RV) T1 mapping was performed in the basal, mid and apical short axis using 4-variants of SAPPHIRE: diastolic, systolic, 0th and 2nd order motion-sensitized DB and conventional modified Look-Locker inversion recovery (MOLLI). RESULTS: LV global myocardial T1 times (1.5 T then 3 T results) were significantly longer by diastolic SAPPHIRE (1283 ± 11|1600 ± 17 ms) than any of the other SAPPHIRE variants: systolic (1239 ± 9|1595 ± 13 ms), 0th order DB (1241 ± 10|1596 ± 12) and 2nd order DB (1251 ± 11|1560 ± 20 ms, all p < 0.05). In the mid septum MOLLI and diastolic SAPPHIRE exhibited significant T1 signal contamination (longer T1) at the blood-myocardial interface not seen with the other 3 SAPPHIRE variants (all p < 0.025). Additionally, systolic, 0th order and 2nd order DB SAPPHIRE showed narrower dispersion of myocardial T1 times across the mid septum when compared to diastolic SAPPHIRE (interquartile ranges respectively: 25 ms, 71 ms, 73 ms vs 143 ms, all p < 0.05). RV T1 mapping was achievable using systolic, 0th and 2nd order DB SAPPHIRE but not with MOLLI or diastolic SAPPHIRE. All 4 SAPPHIRE variants showed excellent re-read reproducibility (intraclass correlation coefficients 0.953 to 0.996). CONCLUSION: These small-scale preliminary healthy volunteer data suggest that DB SAPPHIRE has the potential to reduce partial volume effects at the blood-myocardial interface, and that systolic SAPPHIRE could be a feasible solution for right ventricular T1 mapping. Further work is needed to understand the robustness of these sequences and their potential clinical utility.

Improved simultaneous multislice cardiac MRI using readout concatenated k-space SPIRiT (ROCK-SPIRiT).

PURPOSE: To develop and evaluate a simultaneous multislice (SMS) reconstruction technique that provides noise reduction and leakage blocking for highly accelerated cardiac MRI. METHODS: ReadOut Concatenated k-space SPIRiT (ROCK-SPIRiT) uses the concept of readout concatenation in image domain to represent SMS encoding, and performs coil self-consistency as in SPIRiT-type reconstruction in an extended k-space, while allowing regularization for further denoising. The proposed method is implemented with and without regularization, and validated on retrospectively SMS-accelerated cine imaging with three-fold SMS and two-fold in-plane acceleration. ROCK-SPIRiT is compared with two leakage-blocking SMS reconstruction methods: readout-SENSE-GRAPPA and split slice-GRAPPA. Further evaluation and comparisons are performed using prospectively SMS-accelerated cine imaging. RESULTS: Results on retrospectively three-fold SMS and two-fold in-plane accelerated cine imaging show that ROCK-SPIRiT without regularization significantly improves on existing methods in terms of PSNR (readout-SENSE-GRAPPA: 33.5 ± 3.2, split slice-GRAPPA: 34.1 ± 3.8, ROCK-SPIRiT: 35.0 ± 3.3) and SSIM (readout-SENSE-GRAPPA: 84.4 ± 8.9, split slice-GRAPPA: 85.0 ± 8.9, ROCK-SPIRiT: 88.2 ± 6.6 [in percentage]). Regularized ROCK-SPIRiT significantly outperforms all methods, as characterized by these quantitative metrics (PSNR: 37.6 ± 3.8, SSIM: 94.2 ± 4.1 [in percentage]). The prospectively five-fold SMS and two-fold in-plane accelerated data show that ROCK-SPIRiT and regularized ROCK-SPIRiT have visually improved image quality compared with existing methods. CONCLUSION: The proposed ROCK-SPIRiT technique reduces noise and interslice leakage in accelerated SMS cardiac cine MRI, improving on existing methods both quantitatively and qualitatively.

Free-breathing simultaneous T1 , T2 , and T2∗ quantification in the myocardium.

PURPOSE: To implement a free-breathing sequence for simultaneous quantification of T1 , T2 , and T2∗ for comprehensive tissue characterization of the myocardium in a single scan using a multi-gradient-echo readout with saturation and T2 preparation pulses. METHODS: In the proposed Saturation And T2 -prepared Relaxometry with Navigator-gating (SATURN) technique, a series of multi-gradient-echo (GRE) images with different magnetization preparations was acquired during free breathing. A total of 35 images were acquired in 26.5 ± 14.9 seconds using multiple saturation times and T2 preparation durations and with imaging at 5 echo times. Bloch simulations and phantom experiments were used to validate a 5-parameter fit model for accurate relaxometry. Free-breathing simultaneous T1 , T2 , and T2∗ measurements were performed in 10 healthy volunteers and 2 patients using SATURN at 3T and quantitatively compared to conventional single-parameter methods such as SASHA for T1 , T2 -prepared bSSFP, and multi-GRE for T2∗ . RESULTS: Simulations confirmed accurate fitting with the 5-parameter model. Phantom measurements showed good agreement with the reference methods in the relevant range for in vivo measurements. Compared to single-parameter methods comparable accuracy was achieved. SATURN produced in vivo parameter maps that were visually comparable to single-parameter methods. No significant difference between T1 , T2 , and T2∗ times acquired with SATURN and single-parameter methods was shown in quantitative measurements (SATURN T1=1573±86ms , T2=33.2±3.6ms , T2∗=25.3±6.1ms ; conventional methods: T1=1544±107ms , T2=33.2±3.6ms , T2∗=23.8±5.5ms ; P>.2 ) CONCLUSION: SATURN enables simultaneous quantification of T1 , T2 , and T2∗ in the myocardium for comprehensive tissue characterization with co-registered maps, in a single scan with good agreement to single-parameter methods.

Accelerated white matter lesion analysis based on simultaneous T1 and T2∗ quantification using magnetic resonance fingerprinting and deep learning.

PURPOSE: To develop an accelerated postprocessing pipeline for reproducible and efficient assessment of white matter lesions using quantitative magnetic resonance fingerprinting (MRF) and deep learning. METHODS: MRF using echo-planar imaging (EPI) scans with varying repetition and echo times were acquired for whole brain quantification of T1 and T2∗ in 50 subjects with multiple sclerosis (MS) and 10 healthy volunteers along 2 centers. MRF T1 and T2∗ parametric maps were distortion corrected and denoised. A CNN was trained to reconstruct the T1 and T2∗ parametric maps, and the WM and GM probability maps. RESULTS: Deep learning-based postprocessing reduced reconstruction and image processing times from hours to a few seconds while maintaining high accuracy, reliability, and precision. Mean absolute error performed the best for T1 (deviations 5.6%) and the logarithmic hyperbolic cosinus loss the best for T2∗ (deviations 6.0%). CONCLUSIONS: MRF is a fast and robust tool for quantitative T1 and T2∗ mapping. Its long reconstruction and several postprocessing steps can be facilitated and accelerated using deep learning.

Magnetic resonance fingerprinting for simultaneous renal T1 and T2* mapping in a single breath-hold.

PURPOSE: To evaluate the use of magnetic resonance fingerprinting (MRF) for simultaneous quantification of T1 and T2∗ in a single breath-hold in the kidneys. METHODS: The proposed kidney MRF sequence was based on MRF echo-planar imaging. Thirty-five measurements per slice and overall 4 slices were measured in 15.4 seconds. Group matching was performed for in-line quantification of T1 and T2∗ . Images were acquired in a phantom and 8 healthy volunteers in coronal orientation. To evaluate our approach, region of interests were drawn in the kidneys to calculate mean values and standard deviations of the T1 and T2∗ times. Precision was calculated across multiple repeated MRF scans. Gaussian filtering is applied on baseline images to improve SNR and match stability. RESULTS: T1 and T2∗ times acquired with MRF in the phantom showed good agreement with reference measurements and conventional mapping methods with deviations of less than 5% for T1 and less than 10% for T2∗ . Baseline images in vivo were free of artifacts and relaxation times yielded good agreement with conventional methods and literature (deviation T1:7±4% , T2∗:6±3% ). CONCLUSIONS: In this feasibility study, the proposed renal MRF sequence resulted in accurate T1 and T2∗ quantification in a single breath-hold.

Scan-specific robust artificial-neural-networks for k-space interpolation (RAKI) reconstruction: Database-free deep learning for fast imaging.

PURPOSE: To develop an improved k-space reconstruction method using scan-specific deep learning that is trained on autocalibration signal (ACS) data. THEORY: Robust artificial-neural-networks for k-space interpolation (RAKI) reconstruction trains convolutional neural networks on ACS data. This enables nonlinear estimation of missing k-space lines from acquired k-space data with improved noise resilience, as opposed to conventional linear k-space interpolation-based methods, such as GRAPPA, which are based on linear convolutional kernels. METHODS: The training algorithm is implemented using a mean square error loss function over the target points in the ACS region, using a gradient descent algorithm. The neural network contains 3 layers of convolutional operators, with 2 of these including nonlinear activation functions. The noise performance and reconstruction quality of the RAKI method was compared with GRAPPA in phantom, as well as in neurological and cardiac in vivo data sets. RESULTS: Phantom imaging shows that the proposed RAKI method outperforms GRAPPA at high (≥4) acceleration rates, both visually and quantitatively. Quantitative cardiac imaging shows improved noise resilience at high acceleration rates (rate 4:23% and rate 5:48%) over GRAPPA. The same trend of improved noise resilience is also observed in high-resolution brain imaging at high acceleration rates. CONCLUSION: The RAKI method offers a training database-free deep learning approach for MRI reconstruction, with the potential to improve many existing reconstruction approaches, and is compatible with conventional data acquisition protocols.

Temporally resolved parametric assessment of Z-magnetization recovery (TOPAZ): Dynamic myocardial T1 mapping using a cine steady-state look-locker approach.

PURPOSE: To develop and evaluate a cardiac phase-resolved myocardial T1 mapping sequence. METHODS: The proposed method for temporally resolved parametric assessment of Z-magnetization recovery (TOPAZ) is based on contiguous fast low-angle shot imaging readout after magnetization inversion from the pulsed steady state. Thereby, segmented k-space data are acquired over multiple heartbeats, before reaching steady state. This results in sampling of the inversion-recovery curve for each heart phase at multiple points separated by an R-R interval. Joint T1 and B1+ estimation is performed for reconstruction of cardiac phase-resolved T1 and B1+ maps. Sequence parameters are optimized using numerical simulations. Phantom and in vivo imaging are performed to compare the proposed sequence to a spin-echo reference and saturation pulse prepared heart rate-independent inversion-recovery (SAPPHIRE) T1 mapping sequence in terms of accuracy and precision. RESULTS: In phantom, TOPAZ T1 values with integrated B1+ correction are in good agreement with spin-echo T1 values (normalized root mean square error = 4.2%) and consistent across the cardiac cycle (coefficient of variation = 1.4 ± 0.78%) and different heart rates (coefficient of variation = 1.2 ± 1.9%). In vivo imaging shows no significant difference in TOPAZ T1 times between the cardiac phases (analysis of variance: P = 0.14, coefficient of variation = 3.2 ± 0.8%), but underestimation compared with SAPPHIRE (T1 time ± precision: 1431 ± 56 ms versus 1569 ± 65 ms). In vivo precision is comparable to SAPPHIRE T1 mapping until middiastole (P > 0.07), but deteriorates in the later phases. CONCLUSIONS: The proposed sequence allows cardiac phase-resolved T1 mapping with integrated B1+ assessment at a temporal resolution of 40 ms. Magn Reson Med 79:2087-2100, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Oxygen extraction fraction mapping at 3 Tesla using an artificial neural network: A feasibility study.

PURPOSE: The oxygen extraction fraction (OEF) is an important biomarker for tissue-viability. MRI enables noninvasive estimation of the OEF based on the blood-oxygenation-level-dependent (BOLD) effect. Quantitative OEF-mapping is commonly applied using least-squares regression (LSR) to an analytical tissue model. However, the LSR method has not yet become clinically established due to the necessity for long acquisition times. Artificial neural networks (ANNs) recently have received increasing interest for robust curve-fitting and might pose an alternative to the conventional LSR method for reduced acquisition times. This study presents in vivo OEF mapping results using the conventional LSR and the proposed ANN method. METHODS: In vivo data of five healthy volunteers and one patient with a primary brain tumor were acquired at 3T using a gradient-echo sampled spin-echo (GESSE) sequence. The ANN was trained with simulated BOLD data. RESULTS: In healthy subjects, the mean OEF was 36 ± 2% (LSR) and 40 ± 1% (ANN). The OEF variance within subjects was reduced from 8% to 6% using the ANN method. In the patient, both methods revealed a distinct OEF hotspot in the tumor area, whereas ANN showed less apparent artifacts in surrounding tissue. CONCLUSION: In clinical scan times, the ANN analysis enables OEF mapping with reduced variance, which could facilitate its integration into clinical protocols. Magn Reson Med 79:890-899, 2018. © 2017 International Society for Magnetic Resonance in Medicine.

Gaussian signal relaxation around spin echoes: Implications for precise reversible transverse relaxation quantification of pulmonary tissue at 1.5 and 3 Tesla.

PURPOSE: To characterize the reversible transverse relaxation in pulmonary tissue and to study the benefit of a quadratic exponential (Gaussian) model over the commonly used linear exponential model for increased quantification precision. METHODS: A point-resolved spectroscopy sequence was used for comprehensive sampling of the relaxation around spin echoes. Measurements were performed in an ex vivo tissue sample and in healthy volunteers at 1.5 Tesla (T) and 3 T. The goodness of fit using χred2 and the precision of the fitted relaxation time by means of its confidence interval were compared between the two relaxation models. RESULTS: The Gaussian model provides enhanced descriptions of pulmonary relaxation with lower χred2 by average factors of 4 ex vivo and 3 in volunteers. The Gaussian model indicates higher sensitivity to tissue structure alteration with increased precision of reversible transverse relaxation time measurements also by average factors of 4 ex vivo and 3 in volunteers. The mean relaxation times of the Gaussian model in volunteers are T2,G' = (1.97 ± 0.27) msec at 1.5 T and T2,G' = (0.83 ± 0.21) msec at 3 T. CONCLUSION: Pulmonary signal relaxation was found to be accurately modeled as Gaussian, providing a potential biomarker T2,G' with high sensitivity. Magn Reson Med 77:1938-1945, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Magnetic resonance fingerprinting using echo-planar imaging: Joint quantification of T1 and T2∗ relaxation times.

PURPOSE: To develop an implementation of the magnetic resonance fingerprinting (MRF) paradigm for quantitative imaging using echo-planar imaging (EPI) for simultaneous assessment of T1 and T2∗. METHODS: The proposed MRF method (MRF-EPI) is based on the acquisition of 160 gradient-spoiled EPI images with rapid, parallel-imaging accelerated, Cartesian readout and a measurement time of 10 s per slice. Contrast variation is induced using an initial inversion pulse, and varying the flip angles, echo times, and repetition times throughout the sequence. Joint quantification of T1 and T2∗ is performed using dictionary matching with integrated B1+ correction. The quantification accuracy of the method was validated in phantom scans and in vivo in 6 healthy subjects. RESULTS: Joint T1 and T2∗ parameter maps acquired with MRF-EPI in phantoms are in good agreement with reference measurements, showing deviations under 5% and 4% for T1 and T2∗, respectively. In vivo baseline images were visually free of artifacts. In vivo relaxation times are in good agreement with gold-standard techniques (deviation T1 : 4 ± 2%, T2∗: 4 ± 5%). The visual quality was comparable to the in vivo gold standard, despite substantially shortened scan times. CONCLUSION: The proposed MRF-EPI method provides fast and accurate T1 and T2∗ quantification. This approach offers a rapid supplement to the non-Cartesian MRF portfolio, with potentially increased usability and robustness. Magn Reson Med 78:1724-1733, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Simultaneous multislice imaging for native myocardial T1 mapping: Improved spatial coverage in a single breath-hold.

PURPOSE: To develop a saturation recovery myocardial T1 mapping method for the simultaneous multislice acquisition of three slices. METHODS: Saturation pulse-prepared heart rate independent inversion recovery (SAPPHIRE) T1 mapping was implemented with simultaneous multislice imaging using FLASH readouts for faster coverage of the myocardium. Controlled aliasing in parallel imaging (CAIPI) was used to achieve minimal noise amplification in three slices. Multiband reconstruction was performed using three linear reconstruction methods: Slice- and in-plane GRAPPA, CG-SENSE, and Tikhonov-regularized CG-SENSE. Accuracy, spatial variability, and interslice leakage were compared with single-band T1 mapping in a phantom and in six healthy subjects. RESULTS: Multiband phantom T1 times showed good agreement with single-band T1 mapping for all three reconstruction methods (normalized root mean square error <1.0%). The increase in spatial variability compared with single-band imaging was lowest for GRAPPA (1.29-fold), with higher penalties for Tikhonov-regularized CG-SENSE (1.47-fold) and CG-SENSE (1.52-fold). In vivo multiband T1 times showed no significant difference compared with single-band (T1 time ± intersegmental variability: single-band, 1580 ± 119 ms; GRAPPA, 1572 ± 145 ms; CG-SENSE, 1579 ± 159 ms; Tikhonov, 1586 ± 150 ms [analysis of variance; P = 0.86]). Interslice leakage was smallest for GRAPPA (5.4%) and higher for CG-SENSE (6.2%) and Tikhonov-regularized CG-SENSE (7.9%). CONCLUSION: Multiband accelerated myocardial T1 mapping demonstrated the potential for single-breath-hold T1 quantification in 16 American Heart Association segments over three slices. A 1.2- to 1.4-fold higher in vivo spatial variability was observed, where GRAPPA-based reconstruction showed the highest homogeneity and the least interslice leakage. Magn Reson Med 78:462-471, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Black-blood native T1 mapping: Blood signal suppression for reduced partial voluming in the myocardium.

PURPOSE: To study the feasibility of black-blood contrast in native T1 mapping for reduction of partial voluming at the blood-myocardium interface. METHODS: A saturation pulse prepared heart-rate-independent inversion recovery (SAPPHIRE) T1 mapping sequence was combined with motion-sensitized driven-equilibrium (MSDE) blood suppression for black-blood T1 mapping at 3 Tesla. Phantom scans were performed to assess the T1 time accuracy. In vivo black-blood and conventional SAPPHIRE T1 mapping was performed in eight healthy subjects and analyzed for T1 times, precision, and inter- and intraobserver variability. Furthermore, manually drawn regions of interest (ROIs) in all T1 maps were dilated and eroded to analyze the dependence of septal T1 times on the ROI thickness. RESULTS: Phantom results and in vivo myocardial T1 times show comparable accuracy with black-blood compared to conventional SAPPHIRE (in vivo: black-blood: 1562 ± 56 ms vs. conventional: 1583 ± 58 ms, P = 0.20); Using black-blood SAPPHIRE precision was significantly lower (standard deviation: 133.9 ± 24.6 ms vs. 63.1 ± 6.4 ms, P < .0001), and blood T1 time measurement was not possible. Significantly increased interobserver interclass correlation coefficient (ICC) (0.996 vs. 0.967, P = 0.011) and similar intraobserver ICC (0.979 vs. 0.939, P = 0.11) was obtained with the black-blood sequence. Conventional SAPPHIRE showed strong dependence on the ROI thickness (R2 = 0.99). No such trend was observed using the black-blood approach (R2 = 0.29). CONCLUSION: Black-blood SAPPHIRE successfully eliminates partial voluming at the blood pool in native myocardial T1 mapping while providing accurate T1 times, albeit at a reduced precision. Magn Reson Med 78:484-493, 2017. © 2016 International Society for Magnetic Resonance in Medicine.