Rapid simultaneous acquisition of T1 and T2 mapping images using multishot double spin-echo EPI and automated variations of TR and TE (ms-DSEPI-T12).
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ABSTRACT:
SUBMITTER: Liu X
PROVIDER: S-EPMC3541052 | biostudies-other | 2010 Jan
REPOSITORIES: biostudies-other
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Project description:The knowledge of relaxation times is essential for understanding the biophysical mechanisms underlying contrast in magnetic resonance imaging. Quantitative experiments, while offering major advantages in terms of reproducibility, may benefit from simultaneous acquisitions. In this work, we demonstrate the possibility of simultaneously recording relaxation-time and susceptibility maps with a prototype Multi-Echo (ME) Magnetization-Prepared 2 RApid Gradient Echoes (MP2RAGE) sequence. T1 maps can be obtained using the MP2RAGE sequence, which is relatively insensitive to inhomogeneities of the radio-frequency transmit field, [Formula: see text]. As an extension, multiple gradient echoes can be acquired in each of the MP2RAGE readout blocks, which permits the calculation of [Formula: see text] and susceptibility maps. We used computer simulations to explore the effects of the parameters on the precision and accuracy of the mapping. In vivo parameter maps up to 0.6 mm nominal resolution were acquired at 7 T in 19 healthy volunteers. Voxel-by-voxel correlations and the test-retest reproducibility were used to assess the reliability of the results. When using optimized paramenters, T1 maps obtained with ME-MP2RAGE and standard MP2RAGE showed excellent agreement for the whole range of values found in brain tissues. Simultaneously obtained [Formula: see text] and susceptibility maps were of comparable quality as Fast Low-Angle SHot (FLASH) results. The acquisition times were more favorable for the ME-MP2RAGE (? 19 min) sequence as opposed to the sum of MP2RAGE (? 12 min) and FLASH (? 10 min) acquisitions. Without relevant sacrifice in accuracy, precision or flexibility, the multi-echo version may yield advantages in terms of reduced acquisition time and intrinsic co-registration, provided that an appropriate optimization of the acquisition parameters is performed.
| S-EPMC5230783 | biostudies-literature
Project description:PurposeIn this study, we sought to develop a self-navigation strategy for improving the reconstruction of diffusion weighted 3D multishot echo planar imaging (EPI). We propose a method for extracting the phase correction information from the acquisition itself, eliminating the need for a 2D navigator, further accelerating the acquisition.MethodsIn-vivo acquisitions at 3T with 0.9 mm and 1.5 mm isotropic resolutions were used to evaluate the performance of the self-navigation strategy. Sensitivity to motion was tested using a large difference in pitch position of the head. Using a multishell diffusion weighted acquisition, tractography results were obtained at (0.9 mm)3 to validate the quality with conventional acquisition.ResultsThe use of 3D multislab EPI with self-navigation enables 3D diffusion-weighted spin echo EPI acquisitions that have the same efficiency as 2D single-shot acquisition. For matched acquisition time the image signal-to-noise ratio (SNR) between 3D and 2D acquisition is shown to be comparable for whole-brain coverage with (1.5 mm)3 resolution and for (0.9 mm)3 resolution the 3D acquisition has higher SNR than what can be obtained with 2D acquisitions using current state-of-art multiband techniques. The self-navigation technique was shown to be stable under inter-volume motion. In tractography analysis, the higher resolution afforded by our technique enabled clear delineation of the tapetum and posterior corona radiata.ConclusionThe proposed self-navigation approach utilized a self-consistent phase in 3D diffusion weighted acquisitions. Its efficiency and stability were demonstrated for a plurality of common acquisitions. The proposed self-navigation approach allows for faster acquisition of 3D multishot EPI desirable for large field of view and/or higher resolution.
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Project description:PURPOSE:Most clinical MR examinations require acquisition of different image contrasts. For abdominal exams, the scans are conventionally performed as separate acquisitions using respiratory gating or repeated breath holding, which can be time-inefficient and challenging for patients. Here, a hybrid imaging approach is described that creates T2 - and T1 -weighted images from a single scan and allows for free-breathing acquisition. THEORY AND METHODS:T2 -weighted data is collected using 3D fast spin-echo (FSE) acquisition with motion-robust radial stack-of-stars sampling. The wait time between the FSE trains is used to acquire T1 -weighted gradient-echo (GRE) data. Improved robustness is achieved by extracting a respiratory signal from the GRE data and using it for motion-weighted reconstruction. RESULTS:As validated in simulations and phantom scans, GRE acquisition in the wait time has minor effect on the signal strength and contrast. Volunteer scans at 1.5T showed that T2 - and T1 -weighted hybrid imaging is feasible during free-breathing. Furthermore, it has been demonstrated in a patient that hybrid imaging with T1 -weighted Dixon acquisition is possible. CONCLUSION:The described hybrid sequence enables comprehensive T2 - and T1 -weighted imaging in a single scan. In addition to free-breathing abdominal examination, it promises value for clinical applications that are frequently affected by motion artifacts.
| S-EPMC6107373 | biostudies-literature
Project description:This study sought to determine whether the classification of human coronary atherosclerotic plaques with T1, T2, and ultrashort echo time (UTE) cardiac magnetic resonance (CMR) would correlate well with atherosclerotic plaque classification by histology.CMR has been extensively used to classify carotid plaque, but its ability to characterize coronary plaque remains unknown. In addition, the detection of plaque calcification by CMR remains challenging. Here, we used T1, T2, and UTE CMR to evaluate atherosclerotic plaques in fixed post-mortem human coronary arteries. We hypothesized that the combination of T1, T2, and UTE CMR would allow both calcified and lipid-rich coronary plaques to be accurately detected.Twenty-eight plaques from human donor hearts with proven coronary artery disease were imaged at 9.4-T with a T1-weighted 3-dimensional fast low-angle shot (FLASH) sequence (250-?m resolution), a T2-weighted rapid acquisition with refocused echoes (RARE) sequence (in-plane resolution 0.156 mm), and an UTE sequence (300-?m resolution). Plaques showing selective hypointensity on T2-weighted CMR were classified as lipid-rich. Areas of hypointensity on the T1-weighted images, but not the UTE images, were classified as calcified. Hyperintensity on the T1-weighted and UTE images was classified as hemorrhage. Following CMR, histological characterization of the plaques was performed with a pentachrome stain and established American Heart Association criteria.CMR showed high sensitivity and specificity for the detection of calcification (100% and 90%, respectively) and lipid-rich necrotic cores (90% and 75%, respectively). Only 2 lipid-rich foci were missed by CMR, both of which were extremely small. Overall, CMR-based classification of plaque was in complete agreement with the histological classification in 22 of 28 cases (weighted ? = 0.6945, p < 0.0001).The utilization of UTE CMR allows plaque calcification in the coronary arteries to be robustly detected. High-resolution CMR with T1, T2, and UTE contrast enables accurate classification of human coronary atherosclerotic plaque.
| S-EPMC3661771 | biostudies-literature
Project description:PURPOSE:To present a stimulated-echo based mapping (STEM) approach for simultaneous T1 , T2 , and ADC mapping. METHODS:Diffusion-weighted stimulated-echo images with various combinations of mixing time (TM), TE, and b-value were acquired to enable simultaneous mapping of T1 , T2 , and ADC. The proposed STEM method was performed by densely sampling the TM-TE-b space in a phantom and in brain and prostate of healthy volunteers. T1 , T2 , and ADC from STEM were compared to reference mapping methods. Additionally, protocol optimization was performed to enable rapid STEM acquisition within 2?min by sparsely sampling the TM-TE-b space. The T1 , T2 , and ADC measurements from rapid acquisitions were compared to the densely sampled STEM for evaluation. Finally, a patient with biopsy-proven high-risk prostate cancer was imaged to demonstrate the ability of STEM to differentiate cancer and healthy tissues. RESULTS:Relative to the reference measurements, densely sampled STEM provided accurate quantitative T1 , T2 , and ADC mapping in phantoms (R2 ?=?0.999, slope between 0.97-1.03), as well as in brain and prostate. Further, the T1 , T2 , and ADC measurements from the optimized rapid STEM acquisitions agreed closely with densely sampled STEM. Finally, STEM showed decreased T2 and ADC in prostate cancer compared to healthy prostate tissue. CONCLUSION:STEM provides accurate simultaneous mapping of T1 , T2 , and ADC. This method may enable rapid and accurate multi-parametric tissue characterization for clinical and research applications.
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Project description:BACKGROUND:Adipose tissue (AT) can be classified into white and brown/beige subtypes. Chemical shift encoding-based water-fat MRI-techniques allowing simultaneous mapping of proton density fat fraction (PDFF) and T2 * result in a lower PDFF and a shorter T2 * in brown compared with white AT. However, AT T2 * values vary widely in the literature and are primarily based on 6-echo data. Increasing the number of echoes in a multiecho gradient-echo acquisition is expected to increase the precision of AT T2 * mapping. PURPOSE:1) To mitigate issues of current T2 *-measurement techniques through experimental design, and 2) to investigate gluteal and supraclavicular AT T2 * and PDFF and their relationship using a 20-echo gradient-echo acquisition. STUDY TYPE:Prospective. SUBJECTS:Twenty-one healthy subjects. FIELD STRENGTH/SEQUENCE ASSESSMENT:First, a ground truth signal evolution was simulated from a single-T2 * water-fat model. Second, a time-interleaved 20-echo gradient-echo sequence with monopolar gradients of neck and abdomen/pelvis at 3 T was performed in vivo to determine supraclavicular and gluteal PDFF and T2 *. Complex-based water-fat separation was performed for the first 6 echoes and the full 20 echoes. AT depots were segmented. STATISTICAL TESTS:Mann-Whitney test, Wilcoxon signed-rank test and simple linear regression analysis. RESULTS:Both PDFF and T2 * differed significantly between supraclavicular and gluteal AT with 6 and 20 echoes (PDFF: P < 0.0001 each, T2 *: P = 0.03 / P < 0.0001 for 6/20 echoes). 6-echo T2 * demonstrated higher standard deviations and broader ranges than 20-echo T2 *. Regression analyses revealed a strong relationship between PDFF and T2 * values per AT compartment (R2 = 0.63 supraclavicular, R2 = 0.86 gluteal, P < 0.0001 each). DATA CONCLUSION:The present findings suggest that an increase in the number of sampled echoes beyond 6 does not affect AT PDFF quantification, whereas AT T2 * is considerably affected. Thus, a 20-echo gradient-echo acquisition enables a multiparametric analysis of both AT PDFF and T2 * and may therefore improve MR-based differentiation between white and brown fat. LEVEL OF EVIDENCE:2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:424-434.
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Project description:The purpose of this study was to develop a self-navigation strategy to improve scan efficiency and image quality of water/fat-separated, diffusion-weighted multishot echo-planar imaging (ms-EPI). This is accomplished by acquiring chemical shift-encoded diffusion-weighted data and using an appropriate water-fat and diffusion-encoded signal model to enable reconstruction directly from k-space data. Multishot EPI provides reduced geometric distortion and improved signal-to-noise ratio in diffusion-weighted imaging compared with single-shot approaches. Multishot acquisitions require corrections for physiological motion-induced shot-to-shot phase errors using either extra navigators or self-navigation principles. In addition, proper fat suppression is important, especially in regions with large B0 inhomogeneity. This makes the use of chemical shift encoding attractive. However, when combined with ms-EPI, shot-to-shot phase navigation can be challenging because of the spatial displacement of fat signals along the phase-encoding direction. In this work, a new model-based, self-navigated water/fat separation reconstruction algorithm is proposed. Experiments in legs and in the head-neck region of 10 subjects were performed to validate the algorithm. The results are compared with an image-based, two-dimensional (2D) navigated water/fat separation approach for ms-EPI and with a conventional fat saturation approach. Compared with the 2D navigated method, the use of self-navigation reduced the shot duration time by 30%-35%. The proposed algorithm provided improved diffusion-weighted water images in both leg and head-neck regions compared with the 2D navigator-based approach. The proposed algorithm also produced better fat suppression compared with the conventional fat saturation technique in the B0 inhomogeneous regions. In conclusion, the proposed self-navigated reconstruction algorithm can produce superior water-only diffusion-weighted EPI images with less artefacts compared with the existing methods.
| S-EPMC10078174 | biostudies-literature
Project description:ObjectivesTo apply the MB (multiband) excitation and blipped-CAIPI (blipped-controlled aliasing in parallel imaging) techniques in a spin and gradient-echo (SAGE) EPI sequence to improve the slice coverage for vessel architecture imaging (VAI).Materials and methodsBoth MB excitation and blipped-CAIPI with in-plane parallel imaging were incorporated into a gradient-echo (GE)/spin-echo (SE) EPI sequence for simultaneous tracking of the dynamic MR signal changes in both GE and SE contrasts after the injection of contrast agent. MB and singleband (SB) excitation were compared using a 20-channel head coil at 3 Tesla, and high-resolution MB VAI could be performed in 32 glioma patients.ResultsWhole-brain covered high resolution VAI can be achieved after applying multiband excitation with a factor of 2 and in-plane parallel imaging with a factor of 3. The quality of the images resulting from MB acceleration was comparable to those from the SB method: images were reconstructed without any loss of spatial resolution or severe distortions. In addition, MB and SB signal-to-noise ratios (SNR) were similar. A relative low g-factor induced from the MB acceleration method was achieved after using a blipped-CAIPI technique (1.35 for GE and 1.33 for SE imaging). Performing quantitative VAI, we found that, among all VAI parametric maps, microvessel type indicator (MTI), distance map (I) and vascular-induced bolus peak-time shift (VIPS) were highly correlated. Likewise, VAI parametric maps of slope, slope length and short axis were highly correlated.ConclusionsMultiband accelerated SAGE successfully doubles the number of readout slices in the same measurement time when compared to conventional readout sequences. The corresponding VAI parametric maps provide insights into the complexity and heterogeneity of vascular changes in glioma.
| S-EPMC6688807 | biostudies-literature
Project description:Transverse relaxation time (T(2)) is a basic but very informative MRI parameter, widely used in imaging to examine a host of diseases, including multiple sclerosis, stroke, and tumor. However, short repetition time (TR) is often used to minimize scan time, which may introduce non-negligible errors in T(2) measurement. Specifically, due to the use of refocusing pulse, the steady state magnetization depends not only on TR but also on the TE. Hence, if the TE dependence is not properly accounted for, it may be mistaken as T(2)-induced signal attenuation, leading to non-negligible T(2) underestimation. Our study proposed a fast radio-frequency enforced steady state (FRESS) spin echo (SE) MRI sequence, which saturates the magnetization after the echo and ensures a TE-independent steady state. The proposed FRESS-SE MRI was evaluated with numerical simulation, implemented with echo planar imaging readout, and validated by both phantom and in vivo experiments. In summary, FRESS-SE T(2) MRI technique was developed for fast and accurate T(2) imaging, suitable for in vivo applications.
| S-EPMC3712835 | biostudies-other
Project description:PurposeTo introduce a combined machine learning (ML)- and physics-based image reconstruction framework that enables navigator-free, highly accelerated multishot echo planar imaging (msEPI) and demonstrate its application in high-resolution structural and diffusion imaging.MethodsSingle-shot EPI is an efficient encoding technique, but does not lend itself well to high-resolution imaging because of severe distortion artifacts and blurring. Although msEPI can mitigate these artifacts, high-quality msEPI has been elusive because of phase mismatch arising from shot-to-shot variations which preclude the combination of the multiple-shot data into a single image. We utilize deep learning to obtain an interim image with minimal artifacts, which permits estimation of image phase variations attributed to shot-to-shot changes. These variations are then included in a joint virtual coil sensitivity encoding (JVC-SENSE) reconstruction to utilize data from all shots and improve upon the ML solution.ResultsOur combined ML + physics approach enabled Rinplane × multiband (MB) = 8- × 2-fold acceleration using 2 EPI shots for multiecho imaging, so that whole-brain T2 and T2 * parameter maps could be derived from an 8.3-second acquisition at 1 × 1 × 3-mm3 resolution. This has also allowed high-resolution diffusion imaging with high geometrical fidelity using 5 shots at Rinplane × MB = 9- × 2-fold acceleration. To make these possible, we extended the state-of-the-art MUSSELS reconstruction technique to simultaneous multislice encoding and used it as an input to our ML network.ConclusionCombination of ML and JVC-SENSE enabled navigator-free msEPI at higher accelerations than previously possible while using fewer shots, with reduced vulnerability to poor generalizability and poor acceptance of end-to-end ML approaches.
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