Rapid water and lipid imaging with T2 mapping using a radial IDEAL-GRASE technique

Concurrent water T2 and fat fraction mapping of the breast using the radial gradient and spin echo (RADGRASE) pulse sequence

This work describes and evaluates an efficient radial gradient- and spin-echo (RADGRASE) pulse sequence and reconstruction algorithm for concurrent measurement of proton-density weighted fat fraction (FF) and water component T2 (T2w) within breast tissues. The ability to estimate T2w in breast tissues, where fat can be highly abundant, is demonstrated using oil/gel phantoms across a wide range of FF values (0.1-0.7). Successful T2w mapping of breast tissues is also demonstrated in vivo by comparison with fat suppressed T2 values. The sensitivity of RADGRASE to detect changes in the breast was assessed by tracking T2w in 3 healthy volunteers through their menstrual cycle, demonstrating T2w values in the late luteal phase to be 18-29 ms higher than in the follicular phase. The technique is also applied to a cohort of 68 patients taking tamoxifen for breast cancer risk reduction, where significant positive correlation between the FF parameter Frac50 and T2w (p = 0.035) was observed in premenopausal subjects (n = 20). Our findings demonstrate the ability and efficacy of RADGRASE for simultaneously mapping FF and T2w within breast tissues, and the potential utility of the technique in studying breast tissue changes in clinical applications.

Complex multi-dimensional integration for T2* and R2* mapping

A dual Multi-Dimensional Integration (dMDI) method was proposed and demonstrated for T2* and R2* mapping. By constructing and jointly using both the original MDI term and an inversed MDI term, T2* and R2* mapping can be performed independently with intrinsic background noise suppression and spike elimination, allowing for high quantitative accuracy and robustness over a wide range of T2*. dMDI was compared to original MDI and curve fitting methods in terms of quantitative specificity, accuracy, reliability and computational efficiency. All methods were tested and compared via simulation and in vivo data. With high signal-to-noise-ratio (SNR), the proposed dMDI method yielded T2*and R2* values similar to curve fitting methods. For low SNR and background noise signals, the dMDI yielded low T2* and R2* values, thus effectively suppressing all background noise. Virtually zero spikes were observed in dMDI T2* and R2* maps in all simulation and imaging results. The dMDI method has the potential to provide improved and reliable T2* and R2* mapping results in routine and SNR-challenging scenarios.

The relaxometry hype cycle

Relaxometry is a field with a glorious and controversial history, and no review will ever do it justice. It is full of egos and inventions, patents and lawsuits, high expectations and deep disillusionments. Rather than a paragraph dedicated to each of these, we want to give it an impressionistic overview, painted over with a coat of personal opinions and ruminations about the future of the field. For those unfamiliar with the Gartner hype cycle, here's a brief recap. The cycle starts with a technology trigger and goes through a phase of unrealistically inflated expectations. Eventually the hype dies down as implementations fail to deliver on their promise, and disillusionment sets in. Technologies that manage to live through the trough reach the slope of enlightenment, when there is a flurry of second and third generation products that make the initial promise feel feasible again. Finally, we reach the slope of productivity, where mainstream adoption takes off, and more incremental progress is made, eventually reaching steady state in terms of the technology's visibility. The entire interactive timeline can be viewed at https://qmrlab.org/relaxometry/.

The CALIPR framework for highly accelerated myelin water imaging with improved precision and sensitivity

Quantitative magnetic resonance imaging (MRI) techniques are powerful tools for the study of human tissue, but, in practice, their utility has been limited by lengthy acquisition times. Here, we introduce the Constrained, Adaptive, Low-dimensional, Intrinsically Precise Reconstruction (CALIPR) framework in the context of myelin water imaging (MWI); a quantitative MRI technique generally regarded as the most rigorous approach for noninvasive, in vivo measurement of myelin content. The CALIPR framework exploits data redundancy to recover high-quality images from a small fraction of an imaging dataset, which allowed MWI to be acquired with a previously unattainable sequence (fully sampled acquisition 2 hours:57 min:20 s) in 7 min:26 s (4.2% of the dataset, acceleration factor 23.9). CALIPR quantitative metrics had excellent precision (myelin water fraction mean coefficient of variation 3.2% for the brain and 3.0% for the spinal cord) and markedly increased sensitivity to demyelinating disease pathology compared to a current, widely used technique. The CALIPR framework facilitates drastically improved MWI and could be similarly transformative for other quantitative MRI applications.

A multi-dimensional integration (MDI) strategy for MR T2 * mapping

MRI signals are intrinsically multi-dimensional, and signal behavior may be orthogonal among different dimensions. Such dimensional orthogonality can be utilized to eliminate unwanted effects and facilitate mathematical simplicity during image processing for improved outcomes. In this work, we will demonstrate and analyze the principles and performance of a newly developed multi-dimensional integration (MDI) strategy in MR T₂ * mapping. By constructing a complex signal function to extract the inter-echo signal changes, MDI solves an optimization problem by processing all signal dimensions (eg echoes, flip angles and coil channels) in one integrative step. MDI was compared with routine curve fitting methods on noise behavior, quantification accuracy and computational efficiency. All methods were tested and compared on simulation, phantom and knee data. Monte Carlo simulations were performed on simulation and all MRI data to investigate noise propagation from k space to T₂ * maps. For phantom tests, T₂ * values in regions of interest were extracted on a voxel-wise basis and analyzed using a paired t-test between scanning parameters and mapping methods, with p < 0.05 being significantly different. MDI facilitated a straightforward processing procedure, yielding homogeneous, high-signal-to-noise-ratio (SNR) and artifact-free T₂ * maps without explicit coil combination or additional measures. Compared with routine fitting methods, MDI offered significantly (p < 0.05) improved SNR and quantitative accuracy/robustness, with two to three orders higher computational efficiency. MDI also represented low-SNR signals with low T₂ * values, avoiding misinterpretation with long-T₂ * species.

Decreased water T2 in fatty infiltrated skeletal muscles of patients with neuromuscular diseases

Quantitative imaging techniques are emerging in the field of magnetic resonance imaging of neuromuscular diseases (NMD). T₂ of water (T_2w ) is considered an important imaging marker to assess acute and chronic alterations of the muscle fibers, being generally interpreted as an indicator for "disease activity" in the muscle tissue. To validate the accuracy and robustness of quantitative imaging methods, ¹ H magnetic resonance spectroscopy (MRS) can be used as a gold standard. The purpose of the present work was to investigate T_2w of remaining muscle tissue in regions of higher proton density fat fraction (PDFF) in 40 patients with defined NMD using multi-TE single-voxel ¹ H MRS. Patients underwent MR measurements on a 3 T system to perform a multi-TE single-voxel stimulated echo acquisition method (STEAM) MRS (TE = 11/15/20/25(/35) ms) in regions of healthy, edematous and fatty thigh muscle tissue. Muscle regions for MRS were selected based on T₂ -weighted water and fat images of a two-echo 2D Dixon TSE. MRS results were confined to regions with qualitatively defined remaining muscle tissue without edema and high fat content, based on visual grading of the imaging data. The results showed decreased T_2w values with increasing PDFF with R²  = 0.45 (p < 10^-3 ) (linear fit) and with R²  = 0.51 (exponential fit). The observed dependence of T_2w on PDFF should be considered when using T_2w as a marker in NMD imaging and when performing single-voxel MRS for T_2w in regions enclosing edematous, nonedematous and fatty infiltrated muscle tissue.

Reproducible automated breast density measure with no ionizing radiation using fat-water decomposition MRI

BACKGROUND

Increased breast density is a significant independent risk factor for breast cancer, and recent studies show that this risk is modifiable. Hence, breast density measures sensitive to small changes are desired.

PURPOSE

Utilizing fat-water decomposition MRI, we propose an automated, reproducible breast density measurement, which is nonionizing and directly comparable to mammographic density (MD).

STUDY TYPE

Retrospective study.

POPULATION

The study included two sample sets of breast cancer patients enrolled in a clinical trial, for concordance analysis with MD (40 patients) and reproducibility analysis (10 patients).

FIELD STRENGTH/SEQUENCE

The majority of MRI scans (59 scans) were performed with a 1.5T GE Signa scanner using radial IDEAL-GRASE sequence, while the remaining (seven scans) were performed with a 3T Siemens Skyra using 3D Cartesian 6-echo GRE sequence with a similar fat-water separation technique.

ASSESSMENT

After automated breast segmentation, breast density was calculated using FraGW, a new measure developed to reliably reflect the amount of fibroglandular tissue and total water content in the entire breast. Based on its concordance with MD, FraGW was calibrated to MR-based breast density (MRD) to be comparable to MD. A previous breast density measurement, Fra80-the ratio of breast voxels with <80% fat fraction-was also calculated for comparison with FraGW.

STATISTICAL TESTS

Pearson correlation was performed between MD (reference standard) and FraGW (and Fra80). Test-retest reproducibility of MRD was evaluated using the difference between test-retest measures (Δ_1-2 ) and intraclass correlation coefficient (ICC).

RESULTS

Both FraGW and Fra80 were strongly correlated with MD (Pearson ρ: 0.96 vs. 0.90, both P < 0.0001). MRD converted from FraGW showed higher test-retest reproducibility (Δ_1-2 variation: 1.1% ± 1.2%; ICC: 0.99) compared to MD itself (literature intrareader ICC ≤0.96) and Fra80.

DATA CONCLUSION

The proposed MRD is directly comparable with MD and highly reproducible, which enables the early detection of small breast density changes and treatment response.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;48:971-981.

A flexible fast spin echo triple-echo Dixon technique

PURPOSE

To develop a flexible fast spin echo (FSE) triple-echo Dixon (FTED) technique.

METHODS

An FSE pulse sequence was modified by replacing each readout gradient with three fast-switching bipolar readout gradients with minimal interecho dead time. The corresponding three echoes were used to generate three raw images with relative phase shifts of -θ, 0, and θ between water and fat signals. A region growing-based two-point Dixon phase correction algorithm was used to joint process two separate pairs of the three raw images, yielding a final set of water-only and fat-only images. The flexible FTED technique was implemented on 1.5T and 3.0T scanners and evaluated in five subjects for fat-suppressed T2-weighted imaging and in one subject for post-contrast fat-suppressed T1-weighted imaging.

RESULTS

The flexible FTED technique achieved a high data acquisition efficiency, comparable to that of FSE, and was flexible in scan protocols. The joint two-point Dixon phase correction algorithm helped to ensure consistency in the processing of the two separate pairs of raw images. Reliable and uniform separation of water and fat was achieved in all of the test cases.

CONCLUSION

The flexible FTED technique incorporates the benefits of both FSE and Dixon imaging and provided more flexibility than the original FTED in applications such as fat-suppressed T2-weighted and T1-weighted imaging. Magn Reson Med 77:1049-1057, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Segmentation and quantification of adipose tissue by magnetic resonance imaging

In this brief review, introductory concepts in animal and human adipose tissue segmentation using proton magnetic resonance imaging (MRI) and computed tomography are summarized in the context of obesity research. Adipose tissue segmentation and quantification using spin relaxation-based (e.g., T1-weighted, T2-weighted), relaxometry-based (e.g., T1-, T2-, T2*-mapping), chemical-shift selective, and chemical-shift encoded water-fat MRI pulse sequences are briefly discussed. The continuing interest to classify subcutaneous and visceral adipose tissue depots into smaller sub-depot compartments is mentioned. The use of a single slice, a stack of slices across a limited anatomical region, or a whole body protocol is considered. Common image post-processing steps and emerging atlas-based automated segmentation techniques are noted. Finally, the article identifies some directions of future research, including a discussion on the growing topic of brown adipose tissue and related segmentation considerations.

Measurement of liver fat fraction and iron with MRI and MR spectroscopy techniques

Diffuse liver disease is a widespread global healthcare burden, and the abnormal accumulation of lipid and/or iron is common to important disease processes. Developing the improved methods for detecting and quantifying liver lipid and iron is an important clinical need. The inherent risk, invasiveness, and sampling error of liver biopsy have prompted the development of noninvasive imaging methods for lipid and iron assessment. Ultrasonography and computed tomography have the ability to detect diffuse liver disease, but with limited accuracy. The purpose of this review is to describe the current state-of-the-art methods for quantifying liver lipid and iron using magnetic resonance imaging and spectroscopy, including their implementation, benefits, and potential pitfalls. Imaging- and spectroscopy-based methods are naturally suited for lipid and iron quantification. Lipid can be detected and decomposed from the inherent chemical shift between lipid and water signals, whereas iron imparts significant paramagnetic susceptibility to tissue, which accelerates proton relaxation. However, measurements of these biomarkers are confounded by technical and biological effects. Current methods must address these factors to allow a precise correlation between the lipid fraction and iron concentration. Although this correlation becomes increasingly challenging in the presence of combined lipid and iron accumulation, advanced techniques show promise for delineating these quantities through multi-lipid peak analysis, T2 water mapping, and fast single-voxel water-lipid spectroscopy.

Automated breast segmentation of fat and water MR images using dynamic programming

RATIONALE AND OBJECTIVES

To develop and test an algorithm that outlines the breast boundaries using information from fat and water magnetic resonance images.

MATERIALS AND METHODS

Three algorithms were implemented and tested using registered fat and water magnetic resonance images. Two of the segmentation algorithms are simple extensions of the techniques used for contrast-enhanced images: one algorithm uses clustering and local gradient (CLG) analysis and the other algorithm uses a Hessian-based sheetness filter (HSF). The third segmentation algorithm uses k-means++ and dynamic programming (KDP) for finding the breast pixels. All three algorithms separate the left and right breasts using either a fixed region or a morphological method. The performance is quantified using a mutual overlap (Dice) metric and a pectoral muscle boundary error. The algorithms are evaluated against three manual tracers using 266 breast images from 14 female subjects.

RESULTS

The KDP algorithm has a mean overlap percentage improvement that is statistically significant relative to the HSF and CLG algorithms. When using a fixed region to remove the tissue between breasts with tracer 1 as a reference, the KDP algorithm has a mean overlap of 0.922 compared to 0.864 (P < .01) for HSF and 0.843 (P < .01) for CLG. The performance of KDP is very similar to tracers 2 (0.926 overlap) and 3 (0.929 overlap). The performance analysis in terms of pectoral muscle boundary error showed that the fraction of the muscle boundary within three pixels of reference tracer 1 is 0.87 using KDP compared to 0.578 for HSF and 0.617 for CLG. Our results show that the performance of the KDP algorithm is independent of breast density.

CONCLUSIONS

We developed a new automated segmentation algorithm (KDP) to isolate breast tissue from magnetic resonance fat and water images. KDP outperforms the other techniques that focus on local analysis (CLG and HSF) and yields a performance similar to human tracers.

High-resolution 3D radial bSSFP with IDEAL

Radial trajectories facilitate high-resolution balanced steady state free precession (bSSFP) because the efficient gradients provide more time to extend the trajectory in k-space. A number of radial bSSFP methods that support fat-water separation have been developed; however, most of these methods require an environment with limited B0 inhomogeneity. In this work, high-resolution bSSFP with fat-water separation is achieved in more challenging B0 environments by combining a 3D radial trajectory with the IDEAL chemical species separation method. A method to maintain very high resolution within the timing constraints of bSSFP and IDEAL is described using a dual-pass pulse sequence. The sampling of a unique set of radial lines at each echo time is investigated as a means to circumvent the longer scan time that IDEAL incurs as a multiecho acquisition. The manifestation of undersampling artifacts in this trajectory and their effect on chemical species separation are investigated in comparison to the case in which each echo samples the same set of radial lines. This new bSSFP method achieves 0.63 mm isotropic resolution in a 5-min scan and is demonstrated in difficult in vivo imaging environments, including the breast and a knee with ACL reconstruction hardware at 1.5 T.

Fat-corrected T2 measurement as a marker of active muscle disease in inflammatory myopathy

OBJECTIVE

We sought to improve the utility of T2 measurement as a marker of active muscle disease in patients with idiopathic inflammatory myopathy by correcting for T2 prolongations caused by fatty replacement of muscle that accompnaies chronic muscle damage.

SUBJECTS AND METHODS

Twenty-one patients with idiopathic inflammatory myopathy underwent a standardized MRI evaluation of the thighs. Fat fraction maps were calculated from dual-echo gradient-echo images. Fat-corrected T2 maps were generated from multiecho spin-echo images on the basis of a biexponential model that incorporated voxelwise fat fraction estimates. Semiautomated summaries of conventional and fat-corrected muscle T2 values were compared with one another and with standardized visual scores of muscle disease based on T1-weighted spin-echo and STIR images.

RESULTS

Fat-corrected muscle T2 maps showed lower mean values and greater histogram entropy than conventional T2 maps, as analyzed over a standardized portion of the thigh muscles. Conventional and fat-corrected T2 values correlated with visual scores of active muscle disease on STIR images and with the varying intensity of disease depicted with STIR in focal muscle regions.

CONCLUSION

MRI T2 maps of muscle can be corrected for varying fat content by combining the information from chemical shift-sensitive gradient-echo and multiecho spin-echo images. Use of this strategy may prove useful in the study of idiopathic inflammatory myopathy and other diseases characterized by both muscle inflammation and atrophy.

Quantitative Assessment of Liver Fat with Magnetic Resonance Imaging and Spectroscopy

Hepatic steatosis is characterized by abnormal and excessive accumulation of lipids within hepatocytes. It is an important feature of diffuse liver disease, and the histological hallmark of non-alcoholic fatty liver disease (NAFLD). Other conditions associated with steatosis include alcoholic liver disease, viral hepatitis, HIV and genetic lipodystrophies, cystic fibrosis liver disease, and hepatotoxicity from various therapeutic agents. Liver biopsy, the current clinical gold standard for assessment of liver fat, is invasive and has sampling errors, and is not optimal for screening, monitoring, clinical decision making, or well-suited for many types of research studies. Non-invasive methods that accurately and objectively quantify liver fat are needed. Ultrasound (US) and computed tomography (CT) can be used to assess liver fat but have limited accuracy as well as other limitations. Magnetic resonance (MR) techniques can decompose the liver signal into its fat and water signal components and therefore assess liver fat more directly than CT or US. Most magnetic resonance (MR) techniques measure the signal fat-fraction (the fraction of the liver MR signal attributable to liver fat), which may be confounded by numerous technical and biological factors and may not reliably reflect fat content. By addressing the factors that confound the signal fat-fraction, advanced MR techniques measure the proton density fat-fraction (the fraction of the liver proton density attributable to liver fat), which is a fundamental tissue property and a direct measure of liver fat content. These advanced techniques show promise for accurate fat quantification and are likely to be commercially available soon.

Quantitative Assessment of Liver Fat with Magnetic Resonance Imaging and Spectroscopy

Hepatic steatosis is characterized by abnormal and excessive accumulation of lipids within hepatocytes. It is an important feature of diffuse liver disease, and the histological hallmark of non-alcoholic fatty liver disease (NAFLD). Other conditions associated with steatosis include alcoholic liver disease, viral hepatitis, HIV and genetic lipodystrophies, cystic fibrosis liver disease, and hepatotoxicity from various therapeutic agents. Liver biopsy, the current clinical gold standard for assessment of liver fat, is invasive and has sampling errors, and is not optimal for screening, monitoring, clinical decision making, or well-suited for many types of research studies. Non-invasive methods that accurately and objectively quantify liver fat are needed. Ultrasound (US) and computed tomography (CT) can be used to assess liver fat but have limited accuracy as well as other limitations. Magnetic resonance (MR) techniques can decompose the liver signal into its fat and water signal components and therefore assess liver fat more directly than CT or US. Most magnetic resonance (MR) techniques measure the signal fat-fraction (the fraction of the liver MR signal attributable to liver fat), which may be confounded by numerous technical and biological factors and may not reliably reflect fat content. By addressing the factors that confound the signal fat-fraction, advanced MR techniques measure the proton density fat-fraction (the fraction of the liver proton density attributable to liver fat), which is a fundamental tissue property and a direct measure of liver fat content. These advanced techniques show promise for accurate fat quantification and are likely to be commercially available soon.

T2 mapping from highly undersampled data by reconstruction of principal component coefficient maps using compressed sensing

Recently, there has been an increased interest in quantitative MR parameters to improve diagnosis and treatment. Parameter mapping requires multiple images acquired with different timings usually resulting in long acquisition times. While acquisition time can be reduced by acquiring undersampled data, obtaining accurate estimates of parameters from undersampled data is a challenging problem, in particular for structures with high spatial frequency content. In this work, principal component analysis is combined with a model-based algorithm to reconstruct maps of selected principal component coefficients from highly undersampled radial MRI data. This novel approach linearizes the cost function of the optimization problem yielding a more accurate and reliable estimation of MR parameter maps. The proposed algorithm--reconstruction of principal component coefficient maps using compressed sensing--is demonstrated in phantoms and in vivo and compared with two other algorithms previously developed for undersampled data.

A technique for rapid single-echo spin-echo T2 mapping

A rapid technique for mapping of T(2) relaxation times is presented. The method is based on the conventional single-echo spin echo approach but uses a much shorter pulse repetition time to accelerate data acquisition. The premise of the new method is the use of a constant difference between the echo time and pulse repetition time, which removes the conventional and restrictive requirement of pulse repetition time >> T(1). Theoretical and simulation investigations were performed to evaluate the criteria for accurate T(2) measurements. Measured T(2)s were shown to be within 1% error as long as the key criterion of pulse repetition time/T(2) > or =3 is met. Strictly, a second condition of echo time/T(1) << 1 is also required. However, violations of this condition were found to have minimal impact in most clinical scenarios. Validation was conducted in phantoms and in vivo T(2) mapping of healthy cartilage and brain. The proposed method offers all the advantages of single-echo spin echo imaging (e.g., immunity to stimulated echo effects, robustness to static field inhomogeneity, flexibility in the number and choice of echo times) in a considerably reduced amount of time and is readily implemented on any clinical scanner.