Accelerated four-dimensional free-breathing whole-liver water-fat magnetic resonance imaging with deep dictionary learning and chemical shift modeling.

Background: Multi-echo chemical-shift-encoded magnetic resonance imaging (MRI) has been widely used for fat quantification and fat suppression in clinical liver examinations. Clinical liver water-fat imaging typically requires breath-hold acquisitions, with the free-breathing acquisition method being more desirable for patient comfort. However, the acquisition for free-breathing imaging could take up to several minutes. The purpose of this study is to accelerate four-dimensional free-breathing whole-liver water-fat MRI by jointly using high-dimensional deep dictionary learning and model-guided (MG) reconstruction. Methods: A high-dimensional model-guided deep dictionary learning (HMDDL) algorithm is proposed for the acceleration. The HMDDL combines the powers of the high-dimensional dictionary learning neural network (hdDLNN) and the chemical shift model. The neural network utilizes the prior information of the dynamic multi-echo data in spatial respiratory motion, and echo dimensions to exploit the features of images. The chemical shift model is used to guide the reconstruction of field maps, R2∗ maps, water images, and fat images. Data acquired from ten healthy subjects and ten subjects with clinically diagnosed nonalcoholic fatty liver disease (NAFLD) were selected for training. Data acquired from one healthy subject and two NAFLD subjects were selected for validation. Data acquired from five healthy subjects and five NAFLD subjects were selected for testing. A three-dimensional (3D) blipped golden-angle stack-of-stars multi-gradient-echo pulse sequence was designed to accelerate the data acquisition. The retrospectively undersampled data were used for training, and the prospectively undersampled data were used for testing. The performance of the HMDDL was evaluated in comparison with the compressed sensing-based water-fat separation (CS-WF) algorithm and a parallel non-Cartesian recurrent neural network (PNCRNN) algorithm. Results: Four-dimensional water-fat images with ten motion states for whole-liver are demonstrated at several R values. In comparison with the CS-WF and PNCRNN, the HMDDL improved the mean peak signal-to-noise ratio (PSNR) of images by 9.93 and 2.20 dB, respectively, and improved the mean structure similarity (SSIM) of images by 0.058 and 0.009, respectively, at R=10. The paired t-test shows that there was no significant difference between HMDDL and ground truth for proton-density fat fraction (PDFF) and R2∗ values at R up to 10. Conclusions: The proposed HMDDL enables features of water images and fat images from the highly undersampled multi-echo data along spatial, respiratory motion, and echo dimensions, to improve the performance of accelerated four-dimensional (4D) free-breathing water-fat imaging.

Accelerated liver water T1 mapping using single-shot continuous inversion-recovery spiral imaging.

PURPOSE: Liver T1 mapping techniques typically require long breath holds or long scan time in free-breathing, need correction for B 1 + inhomogeneities and process composite (water and fat) signals. The purpose of this work is to accelerate the multi-slice acquisition of liver water selective T1 (wT1) mapping in a single breath hold, improving the k-space sampling efficiency. METHODS: The proposed continuous inversion-recovery (IR) Look-Locker methodology combines a single-shot gradient echo spiral readout, Dixon processing and a dictionary-based analysis for liver wT1 mapping at 3 T. The sequence parameters were adapted to obtain short scan times. The influence of fat, B 1 + inhomogeneities and TE on the estimation of T1 was first assessed using simulations. The proposed method was then validated in a phantom and in 10 volunteers, comparing it with MRS and the modified Look-Locker inversion-recovery (MOLLI) method. Finally, the clinical feasibility was investigated by comparing wT1 maps with clinical scans in nine patients. RESULTS: The phantom results are in good agreement with MRS. The proposed method encodes the IR-curve for the liver wT1 estimation, is minimally sensitive to B 1 + inhomogeneities and acquires one slice in 1.2 s. The volunteer results confirmed the multi-slice capability of the proposed method, acquiring nine slices in a breath hold of 11 s. The present work shows robustness to B 1 + inhomogeneities ( wT 1 , No B 1 + = 1.07 wT 1 , B 1 + - 45.63 , R 2 = 0.99 ) , good repeatability ( wT 1 , 2 ° = 1 . 0 wT 1 , 1 ° - 2.14 , R 2 = 0.96 ) and is in better agreement with MRS ( wT 1 = 0.92 wT 1 MRS + 103.28 , R 2 = 0.38 ) than is MOLLI ( wT 1 MOLLI = 0.76 wT 1 MRS + 254.43 , R 2 = 0.44 ) . The wT1 maps in patients captured diverse lesions, thus showing their clinical feasibility. CONCLUSION: A single-shot spiral acquisition can be combined with a continuous IR Look-Locker method to perform rapid repeatable multi-slice liver water T1 mapping at a rate of 1.2 s per slice without a B 1 + map. The proposed method is suitable for nine-slice liver clinical applications acquired in a single breath hold of 11 s.

Real-time water/fat imaging at 0.55T with spiral out-in-out-in sampling.

PURPOSE: To develop an efficient and flexible water/fat separated real-time MRI (RT-MRI) method using spiral out-in-out-in (OIOI) sampling and balanced SSFP (bSSFP) at 0.55T. METHODS: A bSSFP sequence with golden-angle spiral OIOI readout was developed, capturing three echoes to allow water/fat separation. A low-latency reconstruction that combines all echoes was available for online visualization. An offline reconstruction provided water and fat RT-MRI in two steps: (1) image reconstruction with spatiotemporally constrained reconstruction (STCR) and (2) water/fat separation with hierarchical iterative decomposition of water and fat with echo asymmetry and least-squares estimation (HIDEAL). In healthy volunteers, spiral OIOI was acquired in the wrist during a radial-to-ulnar deviation maneuver, in the heart without breath-hold and cardiac gating, and in the lower abdomen during free-breathing for visualizing small bowel motility. RESULTS: We demonstrate successful water/fat separated RT-MRI for all tested applications. In the wrist, resulting images provided clear depiction of ligament gaps and their interactions during the radial-to-ulnar deviation maneuver. In the heart, water/fat RT-MRI depicted epicardial fat, provided improved delineation of epicardial coronary arteries, and provided high blood-myocardial contrast for ventricular function assessment. In the abdomen, water-only RT-MRI captured small bowel mobility clearly with improved water-fat contrast. CONCLUSIONS: We have demonstrated a novel and flexible bSSFP spiral OIOI sequence at 0.55T that can provide water/fat separated RT-MRI with a variety of application-specific temporal resolution and spatial resolution requirements.

Diagnostic performance of 3.0 T unenhanced Dixon water-fat separation coronary MR angiography in patients with low-to-intermediate risk of coronary artery disease.

PURPOSE: To evaluate the diagnostic performance of 3.0 T unenhanced compressed-sensing sensitivity encoding (CS-SENSE) Dixon water-fat separation coronary MR angiography (CMRA) in patients with low-to-intermediate risk of coronary artery disease (CAD) and its ability to grade the severity of CAD based on Coronary Artery Disease Reporting and Data System (CAD-RADS). METHODS: A total of 55 patients who was clinically evaluated as low-to-intermediate risk of CAD were finally included to undergo both 3.0 T CS-SENSE water-fat separation CMRA and coronary computed tomography angiography (CCTA), and 11 of them also underwent X-ray coronary angiography (CAG). The severity of coronary artery disease was graded in patients who had completed both CCTA and CMRA examinations by the use of CAD-RADS reports for the patients with stable chest pain, and the diagnostic consistency between the two approaches was evaluated. Diagnostic performance of CMRA was assessed using the combination of CCTA and CAG as the reference standard for excluding or confirming CAD respectively. RESULTS: The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and diagnostic accuracy of 3.0 T unenhanced water-fat separation coronary MRA were 90.0%, 95.0%, 81.8%, 97.4% and 94.0% for a patient-based analysis respectively. In comparison with CCTA, 3.0 T Dixon water-fat separation CMRA demonstrated excellent consistency in grading the severity of coronary heart disease according to CAD-RADS (0.77 for kappa value). CONCLUSION: In the group of low-to-intermediate probability for CAD, 3.0 T unenhanced CS-SENSE Dixon water-fat separation CMRA can present satisfactory diagnostic performance for the exclusion of CAD with high sensitivity and negative predictive value as well as the evaluation of grading the severity of coronary artery disease.

3.0 T unenhanced Dixon water-fat separation whole-heart coronary magnetic resonance angiography: compressed-sensing sensitivity encoding imaging versus conventional 2D sensitivity encoding imaging.

This study was aimed to investigate 3.0 T unenhanced Dixon water-fat whole-heart CMRA (coronary magnetic resonance angiography) using compressed-sensing sensitivity encoding (CS-SENSE) and conventional sensitivity encoding (SENSE) in vitro and in vivo. The key parameters of CS-SENSE and conventional 1D/2D SENSE were compared in vitro phantom study. In vivo study, fifty patients with suspected coronary artery disease (CAD) completed unenhanced Dixon water-fat whole-heart CMRA at 3.0 T using both CS-SENSE and conventional 2D SENSE methods. We compared mean acquisition time, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and the diagnostic accuracy between two techniques. In vitro study, CS-SENSE achieved better effectiveness between higher SNR/CNR and shorter scan times using the appropriate acceleration factor compared with conventional 2D SENSE. In vivo study, CS-SENSE CMRA had better performance than 2D SENSE in terms of the mean acquisition time, SNR and CNR (7.4 ± 3.2 min vs. 8.3 ± 3.4 min, P = 0.001; SNR: 115.5 ± 35.4 vs. 103.3 ± 32.2; CNR: 101.1 ± 33.2 vs. 90.6 ± 30.1, P < 0.001 for both). The diagnostic accuracy between CS-SENSE and 2D SENSE had no significant difference on a patient-based analysis (sensitivity: 97.3% vs. 91.9%; specificity: 76.9% vs. 61.5%; accuracy: 92.0% vs. 84.0%; P > 0.05 for each). Unenhanced CS-SENSE Dixon water-fat separation whole-heart CMRA at 3.0 T can improve the SNR and CNR, shorten the acquisition time while providing equally satisfactory image quality and diagnostic accuracy compared with 2D SENSE CMRA.

Free-breathing simultaneous water-fat separation and T1 mapping of the whole liver (SWALI) with isotropic resolution using 3D golden-angle radial trajectory.

Background: Conventional liver T1 mapping techniques are typically performed under breath-holding conditions; they have limited slice coverage and often rely on multiple acquisitions. Furthermore, liver fat affects the accuracy of T1 quantification. Therefore, we aim to propose a free-breathing technique for simultaneous water-fat separation and T1 mapping of the whole liver (SWALI) in a single scan. Methods: The proposed SWALI sequence included an inversion recovery (IR) preparation pulse followed by a series of multiecho three-dimensional (3D) golden-angle radial acquisitions. For each echo time (TE), a series of images containing a mix of water and fat were reconstructed using a sliding window method. For each inversion time (TI), water and fat were separated, and then water and fat T1 estimation was conducted. The fat fraction (FF) was calculated based on the last TI image. The FF and water T1 quantification accuracy were compared with the gold standard sequences in the phantom. The in vivo feasibility was tested in 9 healthy volunteers, 2 patients with fatty liver, and 3 patients with hepatocellular carcinoma (HCC). The reproducibility was evaluated in the patients with fatty liver and in the healthy volunteers. Results: The mean FF and the mean water T1 values obtained by the SWALI sequence showed good agreements with chemical shift-encoded magnetic resonance imaging (CSE-MRI; r=0.998; P<0.001) and fat-suppressed (FS) IR-spin echo (SE; r=0.997; P<0.001) in the phantom. For the patients with fatty liver and the healthy volunteers, the SWALI sequence showed no significant difference with CSE-MRI in FF quantification (P=0.53). In T1 quantification, comparable T1 values were obtained with the SWALI sequence and modified Look-Locker inversion recovery (MOLLI; P=0.10) in healthy volunteers, while the water T1 estimated by the SWALI sequence was significantly lower than the water-fat compound T1 estimated by MOLLI (P<0.001) in patients with fatty liver. In the reproducibility study, the intraclass correlation coefficients (ICCs) for the estimated FF and water T1 were 0.997 and 0.943, respectively. Water T1 of the patients with HCC calculated using the SWALI sequence showed a significant reduction after the contrast administration (P<0.001). Conclusions: Free-breathing water-fat separation and T1 mapping of the whole liver with 2.5 mm isotropic spatial resolution were achieved simultaneously using the SWALI sequence in a 5-min scan.

Multi-echo MR thermometry in the upper leg at 7 T using near-harmonic 2D reconstruction for initialization.

PURPOSE: The aim of this work is the development of a thermometry method to measure temperature increases in vivo, with a precision and accuracy sufficient for validation against thermal simulations. Such an MR thermometry model would be a valuable tool to get an indication on one of the major safety concerns in MR imaging: the tissue heating occurring due to radiofrequency (RF) exposure. To prevent excessive temperature rise, RF power deposition, expressed as specific absorption rate, cannot exceed predefined thresholds. Using these thresholds, MRI has demonstrated an extensive history of safe usage. Nevertheless, MR thermometry would be a valuable tool to address some of the unmet needs in the area of RF safety assessment, such as validation of specific absorption rate and thermal simulations, investigation of local peak temperatures during scanning, or temperature-based safety guidelines. METHODS: The harmonic initialized model-based multi-echo approach is proposed. The method combines a previously published model-based multi-echo water/fat separated approach with an also previously published near-harmonic 2D reconstruction method. The method is tested on the human thigh with a multi-transmit array at 7 T, in three volunteers, and for several RF shims. RESULTS: Precision and accuracy are improved considerably compared to a previous fat-referenced method (precision: 0.09 vs. 0.19°C). Comparison of measured temperature rise distributions to subject-specific simulated counterparts show good relative agreement for multiple RF shim settings. CONCLUSION: The high precision shows promising potential for validation purposes and other RF safety applications.

Toward a realistic in silico abdominal phantom for QSM.

PURPOSE: QSM outside the brain has recently gained interest, particularly in the abdominal region. However, the absence of reliable ground truths makes difficult to assess reconstruction algorithms, whose quality is already compromised by additional signal contributions from fat, gases, and different kinds of motion. This work presents a realistic in silico phantom for the development, evaluation and comparison of abdominal QSM reconstruction algorithms. METHODS: Synthetic susceptibility and R 2 * $$ {R}_2^{\ast } $$ maps were generated by segmenting and postprocessing the abdominal 3T MRI data from a healthy volunteer. Susceptibility and R 2 * $$ {R}_2^{\ast } $$ values in different tissues/organs were assigned according to literature and experimental values and were also provided with realistic textures. The signal was simulated using as input the synthetic QSM and R 2 * $$ {R}_2^{\ast } $$ maps and fat contributions. Three susceptibility scenarios and two acquisition protocols were simulated to compare different reconstruction algorithms. RESULTS: QSM reconstructions show that the phantom allows to identify the main strengths and limitations of the acquisition approaches and reconstruction algorithms, such as in-phase acquisitions, water-fat separation methods, and QSM dipole inversion algorithms. CONCLUSION: The phantom showed its potential as a ground truth to evaluate and compare reconstruction pipelines and algorithms. The publicly available source code, designed in a modular framework, allows users to easily modify the susceptibility, R 2 * $$ {R}_2^{\ast } $$ and TEs, and thus creates different abdominal scenarios.

Assessment of MRF for simultaneous T1 and T2 quantification and water-fat separation in the liver at 0.55 T.

OBJECTIVE: The goal of this work was to assess the feasibility of performing MRF in the liver on a 0.55 T scanner and to examine the feasibility of water-fat separation using rosette MRF at 0.55 T. MATERIALS AND METHODS: Spiral and rosette MRF sequences were implemented on a commercial 0.55 T scanner. The accuracy of both sequences in T1 and T2 quantification was validated in the ISMRM/NIST system phantom. The efficacy of rosette MRF in water-fat separation was evaluated in simulations and water/oil phantoms. Both spiral and rosette MRF were performed in the liver of healthy subjects. RESULTS: In the ISMRM/NIST phantom, both spiral and rosette MRF achieved good agreement with reference values in T1 and T2 measurements. In addition, rosette MRF enables water-fat separation and can generate water- and fat- specific T1 maps, T2 maps, and proton density images from the same dataset for a spatial resolution of 1.56 × 1.56 × 5mm3 within the acquisition time of 15 s. CONCLUSION: It is feasible to measure T1 and T2 simultaneously in the liver using MRF on a 0.55 T system with lower performance gradients compared to state-of-the-art 1.5 T and 3 T systems within an acquisition time of 15 s. In addition, rosette MRF enables water-fat separation along with T1 and T2 quantification with no time penalty.

MR Multitasking-based multi-dimensional assessment of cardiovascular system (MT-MACS) with extended spatial coverage and water-fat separation.

PURPOSE: To extend the MR MultiTasking-based Multidimensional Assessment of Cardiovascular System (MT-MACS) technique with larger spatial coverage and water-fat separation for comprehensive aortocardiac assessment. METHODS: MT-MACS adopts a low-rank tensor image model for 7D imaging, with three spatial dimensions for volumetric imaging, one cardiac motion dimension for cine imaging, one respiratory motion dimension for free-breathing imaging, one T2-prepared inversion recovery time dimension for multi-contrast assessment, and one T2*-decay time dimension for water-fat separation. Nine healthy subjects were recruited for the 3T study. Overall image quality was scored on bright-blood (BB), dark-blood (DB), and gray-blood (GB) contrasts using a 4-point scale (0-poor to 3-excellent) by two independent readers, and their interreader agreement was evaluated. Myocardial wall thickness and left ventricular ejection fraction (LVEF) were quantified on DB and BB contrasts, respectively. The agreement in these metrics between MT-MACS and conventional breath-held, electrocardiography-triggered 2D sequences were evaluated. RESULTS: MT-MACS provides both water-only and fat-only images with excellent image quality (average score = 3.725/3.780/3.835/3.890 for BB/DB/GB/fat-only images) and moderate to high interreader agreement (weighted Cohen's kappa value = 0.727/0.668/1.000/1.000 for BB/DB/GB/fat-only images). There were good to excellent agreements in myocardial wall thickness measurements (intraclass correlation coefficients [ICC] = 0.781/0.929/0.680/0.878 for left atria/left ventricle/right atria/right ventricle) and LVEF quantification (ICC = 0.716) between MT-MACS and 2D references. All measurements were within the literature range of healthy subjects. CONCLUSION: The refined MT-MACS technique provides multi-contrast, phase-resolved, and water-fat imaging of the aortocardiac systems and allows evaluation of anatomy and function. Clinical validation is warranted.

Associations of incidental vertebral fractures and longitudinal changes of MR-based proton density fat fraction and T2* measurements of vertebral bone marrow.

Background: Quantitative magnetic resonance imaging (MRI) techniques such as chemical shift encoding-based water-fat separation techniques (CSE-MRI) are increasingly applied as noninvasive biomarkers to assess the biochemical composition of vertebrae. This study aims to investigate the longitudinal change of proton density fat fraction (PDFF) and T2* derived from CSE-MRI of the thoracolumbar vertebral bone marrow in patients that develop incidental vertebral compression fractures (VCFs), and whether PDFF and T2* enable the prediction of an incidental VCF. Methods: In this study we included 48 patients with CT-derived bone mineral density (BMD) measurements at baseline. Patients that presented an incidental VCF at follow up (N=12, mean age 70.5 ± 7.4 years, 5 female) were compared to controls without incidental VCF at follow up (N=36, mean age 71.1 ± 8.6 years, 15 females). All patients underwent 3T MRI, containing a significant part of the thoracolumbar spine (Th11-L4), at baseline, 6-month and 12 month follow up, including a gradient echo sequence for chemical shift encoding-based water-fat separation, from which PDFF and T2* maps were obtained. Associations between changes in PDFF, T2* and BMD measurements over 12 months and the group (incidental VCF vs. no VCF) were assessed using multivariable regression models. Mixed-effect regression models were used to test if there is a difference in the rate of change in PDFF, T2* and BMD between patients with and without incidental VCF. Results: Prior to the occurrence of an incidental VCF, PDFF in vertebrae increased in the VCF group (ΔPDFF=6.3 ± 3.1%) and was significantly higher than the change of PDFF in the group without VCF (ΔPDFF=2.1 ± 2.5%, P=0.03). There was no significant change in T2* (ΔT2*=1.7 ± 1.1ms vs. ΔT2*=1.1 ± 1.3ms, P=0.31) and BMD (ΔBMD=-1.2 ± 11.3mg/cm3 vs. ΔBMD=-11.4 ± 24.1mg/cm3, P= 0.37) between the two groups over 12 months. At baseline, no significant differences were detected in the average PDFF, T2* and BMD of all measured vertebrae (Th11-L4) between the VCF group and the group without VCF (P=0.66, P=0.35 and P= 0.21, respectively). When assessing the differences in rates of change, there was a significant change in slope for PDFF (2.32 per 6 months, 95% confidence interval (CI) 0.31-4.32; P=0.03) but not for T2* (0.02 per 6 months, CI -0.98-0.95; P=0.90) or BMD (-4.84 per 6 months, CI -23.4-13.7; P=0.60). Conclusions: In our study population, the average change of PDFF over 12 months is significantly higher in patients that develop incidental fractures at 12-month follow up compared to patients without incidental VCF, while T2* and BMD show no significant changes prior to the occurrence of the incidental vertebral fractures. Therefore, a longitudinal increase in bone marrow PDFF may be predictive for vertebral compression fractures.

Deep Learning-Based Water-Fat Separation from Dual-Echo Chemical Shift-Encoded Imaging.

Conventional water-fat separation approaches suffer long computational times and are prone to water/fat swaps. To solve these problems, we propose a deep learning-based dual-echo water-fat separation method. With IRB approval, raw data from 68 pediatric clinically indicated dual echo scans were analyzed, corresponding to 19382 contrast-enhanced images. A densely connected hierarchical convolutional network was constructed, in which dual-echo images and corresponding echo times were used as input and water/fat images obtained using the projected power method were regarded as references. Models were trained and tested using knee images with 8-fold cross validation and validated on out-of-distribution data from the ankle, foot, and arm. Using the proposed method, the average computational time for a volumetric dataset with ~400 slices was reduced from 10 min to under one minute. High fidelity was achieved (correlation coefficient of 0.9969, l1 error of 0.0381, SSIM of 0.9740, pSNR of 58.6876) and water/fat swaps were mitigated. I is of particular interest that metal artifacts were substantially reduced, even when the training set contained no images with metallic implants. Using the models trained with only contrast-enhanced images, water/fat images were predicted from non-contrast-enhanced images with high fidelity. The proposed water-fat separation method has been demonstrated to be fast, robust, and has the added capability to compensate for metal artifacts.

Accelerating multi-echo chemical shift encoded water-fat MRI using model-guided deep learning.

PURPOSE: To accelerate chemical shift encoded (CSE) water-fat imaging by applying a model-guided deep learning water-fat separation (MGDL-WF) framework to the undersampled k-space data. METHODS: A model-guided deep learning water-fat separation framework is proposed for the acceleration using Cartesian/radial undersampling data. The proposed MGDL-WF combines the power of CSE water-fat imaging model and data-driven deep learning by jointly using a multi-peak fat model and a modified residual U-net network. The model is used to guide the image reconstruction, and the network is used to capture the artifacts induced by the undersampling. A data consistency layer is used in MGDL-WF to ensure the output images to be consistent with the k-space measurements. A Gauss-Newton iteration algorithm is adapted for the gradient updating of the networks. RESULTS: Compared with the compressed sensing water-fat separation (CS-WF) algorithm/2-step procedure algorithm, the MGDL-WF increased peak signal-to-noise ratio (PSNR) by 5.31/5.23, 6.11/4.54, and 4.75 dB/1.88 dB with Cartesian sampling, and by 4.13/6.53, 2.90/4.68, and 1.68 dB/3.48 dB with radial sampling, at acceleration rates (R) of 4, 6, and 8, respectively. By using MGDL-WF, radial sampling increased the PSNR by 2.07 dB at R = 8, compared with Cartesian sampling. CONCLUSIONS: The proposed MGDL-WF enables exploiting features of the water images and fat images from the undersampled multi-echo data, leading to improved performance in the accelerated CSE water-fat imaging. By using MGDL-WF, radial sampling can further improve the image quality with comparable scan time in comparison with Cartesian sampling.

Unenhanced Whole-Heart Coronary MRA: Prospective Intraindividual Comparison of 1.5-T SSFP and 3-T Dixon Water-Fat Separation GRE Methods Using Coronary Angiography as Reference.

BACKGROUND. Coronary MRA is commonly performed at 1.5 T using SSFP acquisitions. Coronary MRA performed at 3 T using SSFP is limited due to impaired fat suppression and has been typically investigated using contrast-enhanced techniques. A Dixon fat-water separation gradient-recalled echo (GRE) method may enable high-quality unenhanced 3-T coronary MRA. OBJECTIVE. The purpose of this study was to compare 1.5-T SSFP and 3-T Dixon water-fat separation GRE methods for unenhanced whole-heart coronary MRA in patients with suspected coronary artery disease (CAD). METHODS. This prospective study included 44 patients (27 men and 17 women; mean age, 59 ± 8 [SD] years) with an intermediate to high risk of CAD who underwent both 1.5-T SSFP and 3-T Dixon GRE coronary MRA examinations before undergoing coronary angiography (CAG). Two radiologists independently assessed coronary arteries in terms of subjective image quality (on a scale of 1-5, with 5 denoting the highest image quality), number of visible segments, apparent contrast-to-noise ratio (CNR; vs myocardium), and presence of significant stenoses. Methods were compared using the mean of the readers' values for apparent CNR and using consensus interpretations for other measures. CAG served as the reference standard for detecting the presence of stenoses. RESULTS. Expressed as a kappa coefficient, interobserver agreement was 0.85 for image quality, 0.85 for segment visibility, and 0.83 for stenosis, and expressed as an intraclass correlation coefficient, interobserver agreement was 0.92 for apparent CNR. The mean overall image quality score was 4.0 ± 1.1 for 3-T Dixon GRE versus 3.0 ± 1.2 for 1.5-T SSFP. The percentage of visible segments for 3-T Dixon GRE versus 1.5-T SSFP was 96.7% versus 88.9% for all segments, 96.9% versus 90.1% for distal segments, and 93.1% versus 77.2% for branch segments. The mean overall apparent CNR was 93.2 ± 29.2 for 3-T Dixon GRE versus 80.8 ± 27.9 for 1.5-T SSFP. The 3-T Dixon GRE method, compared with the 1.5-T SSFP method, showed higher sensitivity and specificity in per-vessel analysis (87.9% vs 77.3% and 83.3% vs 60.6%, respectively), per-segment analysis (84.6% vs 74.8% and 90.9% vs 79.6%, respectively), and per-segment analysis of distal and branch segments (89.7% vs 75.9% and 89.7% vs 73.7%, respectively). CONCLUSION. For unenhanced coronary MRA, 3-T unenhanced Dixon GRE had better image quality and diagnostic performance than 1.5-T SSFP, particularly for distal and branch segments. CLINICAL IMPACT. The 3-T Dixon GRE technique may be preferred to the current clinical standard of the 1.5-T SSFP technique for unenhanced coronary MRA.

[Application of MRI Water-Fat Separation Technology in Patients with Multiple Myeloma].

OBJECTIVE: To explore the clinical significance of magnetic resonance imaging water-fat separation (Dixon) technique in patients with multiple myeloma. METHODS: A total of 41 newly diagnosed patients with multiple myeloma who underwent Dixon in The Affiliated Hospital of Qingdao University from April 2019 to April 2021 were included in this study. Patients were divided into observation group and control group according to whether Dixon performance was normal or not. The differences of clinical data and fat fraction (FF) between the two groups were compared. The correlation between FF and clinical data, disease stages and differences before and after treatment were also compared. The receiver operator characteristic curve of patients was drawn to analyze the diagnostic value of FF combined with serum alkaline phosphatase for bone destruction in patients with multiple myeloma. RESULTS: Among the 41 patients, there were 12 cases in the control group and 29 cases in the observation group. There was no significant difference in age and sex between the two groups. In the observation group, ß2-microglobulin concentration and M protein were significantly higher than those in the control group, while serum alkaline phosphatase and FF were lower (P<0.05). In all 41 patients included in the study, there was a significant negative correlation between FF value and ß2-microglobulin concentration (r=-0.57), and a significant positive correlation between FF value and serum alkaline phosphatase (r=0.31). After treatment, FF value increased, while myeloma cell percentage, ß2-microglobulin concentration and M protein decreased in 11 patients who completed 4 cycles of chemotherapy, and the differences before and after treatment were statistically significant (P<0.05). The value of serum alkaline phosphatase combined with FF value in predicting bone destruction is higher than that of FF value or serum alkaline phosphatase alone. CONCLUSION: Dixon's different imaging manifestations can reflect the severity of the disease. FF value is correlated with clinical examination results and R-ISS staging, and there is a significant difference before and after treatment. Serum alkaline phosphatase combined with FF value is better than two indicators alone in predicting bone destruction.

Ultrafast water-fat separation using deep learning-based single-shot MRI.

PURPOSE: To present a deep learning-based reconstruction method for spatiotemporally encoded single-shot MRI to simultaneously obtain water and fat images. METHODS: Spatiotemporally encoded MRI is an ultrafast branch that can encode chemical shift information due to its special quadratic phase modulation. A deep learning approach using a 2D U-Net was proposed to reconstruct spatiotemporally encoded signal and obtain water and fat images simultaneously. The training data for U-Net were generated by MRiLab software (version 1.3) with various synthetic models. Numerical simulations and experiments on ex vivo pork and in vivo rats at a 7.0 T Varian MRI system (Agilent Technologies, Santa Clara, CA) were performed, and the deep learning results were compared with those obtained by state-of-the-art algorithms. The structural similarity index and signal-to-ghost ratio were used to evaluate the residual artifact of different reconstruction methods. RESULTS: With a well-trained neural network, the proposed deep learning approach can accomplish signal reconstruction within 0.46 s on a personal computer, which is comparable with the conjugate gradient method (0.41 s) and much faster than the state-of-the-art super-resolved water-fat image reconstruction method (30.31 s). The results of numerical simulations, ex vivo pork experiments, and in vivo rat experiments demonstrate that the deep learning approach can achieve better fidelity and higher spatial resolution compared to the other 2 methods. The deep learning approach also has a great advantage in artifact suppression, as indicated by the signal-to-ghost ratio results. CONCLUSION: Spatiotemporally encoded MRI with deep learning can provide ultrafast water-fat separation with better performance compared to the state-of-the-art methods.

Clinical Application of Non-Contrast-Enhanced Dixon Water-Fat Separation Compressed SENSE Whole-Heart Coronary MR Angiography at 3.0 T With and Without Nitroglycerin.

BACKGROUND: 3.0 T non-contrast-enhanced nitroglycerin (NTG)-assisted whole-heart coronary magnetic resonance angiography (MRA) employing Dixon water-fat separation and compressed SENSE (CS-SENSE) acceleration is a promising method for diagnosing coronary artery disease (CAD). PURPOSE: To evaluate the diagnostic performance of this technique for detecting clinically-relevant (≥50% diameter reducing) CAD and to evaluate the difference in NTG-induced coronary vasodilation between patients with and without clinically-relevant CAD. STUDY TYPE: Prospective. POPULATION: Sixty-six patients with suspected CAD. FIELD STRENGTH/SEQUENCE: 3.0 T; CSSENSE, Dixon water-fat separation, three-dimensional segmented turbo field gradient-echo sequence for whole-heart coronary MRA. ASSESSMENT: Overall image quality of coronary MRA was calculated on the basis of all visible coronary segments. The diagnostic performance of coronary MRA for detecting a ≥50% reduction in coronary artery diameter with and without NTG was compared using X-ray coronary angiography (CAG) as the reference. According to CAG, patients were divided into a non-clinically-relevant CAD group and clinically-relevant CAD group, and the difference in NTG-induced vasodilation between the groups was evaluated. STATISTICAL TESTS: Unpaired/paired Student's t-test, Mann-Whitney U test, paired Wilcoxon signed-rank test, χ2 test, McNemar test. A two-tailed P value <0.05 was considered significant. RESULTS: Overall image quality was increased significantly in the coronary MRA images after NTG. The diagnostic performance of the non-NTG vs. NTG-assisted coronary MRA was as follows on a per-patient basis: sensitivity 94.3% vs. 94.3%, specificity 64.5% vs. 83.9%, positive predictive value 75.0% vs. 86.8%, negative predictive value 90.9% vs. 92.9%, and accuracy 80.3% vs. 89.4%, respectively. NTG-induced vasodilation was significantly lower in the clinically-relevant CAD group than in the non-clinically-relevant CAD group (13.7 ± 8.1% vs. 24.1 ± 16.3%). DATA CONCLUSION: Non-contrast Dixon water-fat separation CS-SENSE coronary MRA at 3.0 T can noninvasively detect clinically-relevant CAD and sublingual NTG improved performance. Combining pre- and post-NTG coronary MRA may provide a simple noninvasive and nonionizing test to evaluate coronary vasodilation function. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 2.

Application of MRI Water-Fat Separation Technology in Patients with Multiple Myeloma / 中国实验血液学杂志

OBJECTIVE@#To explore the clinical significance of magnetic resonance imaging water-fat separation (Dixon) technique in patients with multiple myeloma.@*METHODS@#A total of 41 newly diagnosed patients with multiple myeloma who underwent Dixon in The Affiliated Hospital of Qingdao University from April 2019 to April 2021 were included in this study. Patients were divided into observation group and control group according to whether Dixon performance was normal or not. The differences of clinical data and fat fraction (FF) between the two groups were compared. The correlation between FF and clinical data, disease stages and differences before and after treatment were also compared. The receiver operator characteristic curve of patients was drawn to analyze the diagnostic value of FF combined with serum alkaline phosphatase for bone destruction in patients with multiple myeloma.@*RESULTS@#Among the 41 patients, there were 12 cases in the control group and 29 cases in the observation group. There was no significant difference in age and sex between the two groups. In the observation group, β2-microglobulin concentration and M protein were significantly higher than those in the control group, while serum alkaline phosphatase and FF were lower (P<0.05). In all 41 patients included in the study, there was a significant negative correlation between FF value and β2-microglobulin concentration (r=-0.57), and a significant positive correlation between FF value and serum alkaline phosphatase (r=0.31). After treatment, FF value increased, while myeloma cell percentage, β2-microglobulin concentration and M protein decreased in 11 patients who completed 4 cycles of chemotherapy, and the differences before and after treatment were statistically significant (P<0.05). The value of serum alkaline phosphatase combined with FF value in predicting bone destruction is higher than that of FF value or serum alkaline phosphatase alone.@*CONCLUSION@#Dixon's different imaging manifestations can reflect the severity of the disease. FF value is correlated with clinical examination results and R-ISS staging, and there is a significant difference before and after treatment. Serum alkaline phosphatase combined with FF value is better than two indicators alone in predicting bone destruction.

Vertebral bone marrow T2* mapping using chemical shift encoding-based water-fat separation in the quantitative analysis of lumbar osteoporosis and osteoporotic fractures.

BACKGROUND: Chemical shift encoding-based water-fat separation techniques have been used for fat quantification [proton density fat fraction (PDFF)], but they also enable the assessment of bone marrow T2*, which has previously been reported to be a potential biomarker for osteoporosis and may give insight into the cause of vertebral fractures (i.e., osteoporotic vs. traumatic) and the microstructure of the bone when applied to vertebral bone marrow. METHODS: The 32 patients (78.1% with low-energy osteopenic/osteoporotic fractures, mean age 72.3±9.8 years, 76% women; 21.9% with high-energy traumatic fractures, 47.3±12.8 years, no women) were frequency-matched for age and sex to subjects without vertebral fractures (n=20). All study patients underwent 3T-MRI of the lumbar spine including sagittally acquired spoiled gradient echo sequences for chemical shift encoding-based water-fat separation, from which T2* values were obtained. Volumetric trabecular bone mineral density (BMD) and trabecular bone parameters describing the three-dimensional structural integrity of trabecular bone were derived from quantitative CT. Associations between T2* measurements, fracture status and trabecular bone parameters were assessed using multivariable linear regression models. RESULTS: Mean T2* values of non fractured vertebrae in all patients showed a significant correlation with BMD (r=-0.65, P<0.001), trabecular number (TbN) (r=-0.56, P<0.001) and trabecular spacing (TbSp) (r=0.61, P<0.001); patients with low-energy osteoporotic vertebral fractures showed significantly higher mean T2* values than those with traumatic fractures (13.6±4.3 vs. 8.4±2.2 ms, P=0.01) as well as a significantly lower TbN (0.69±0.08 vs. 0.93±0.03 mm-1, P<0.01) and a significantly larger trabecular spacing (1.06±0.16 vs. 0.56±0.08 mm, P<0.01). Mean T2* values of osteoporotic patients with and without vertebral fracture showed no significant difference (13.5±3.4 vs. 15.6±3.5 ms, P=0.40). When comparing the mean T2* of the fractured vertebrae, no significant difference could be detected between low-energy osteoporotic fractures and high-energy traumatic fractures (12.6±5.4 vs. 8.1±2.4 ms, P=0.10). CONCLUSIONS: T2* mapping of vertebral bone marrow using using chemical shift encoding-based water-fat separation allows for assessing osteoporosis as well as the trabecular microstructure and enables a radiation-free differentiation between patients with low-energy osteoporotic and high-energy traumatic vertebral fractures, suggesting its potential as a biomarker for bone fragility.

Multiple-echo steady-state (MESS): Extending DESS for joint T2 mapping and chemical-shift corrected water-fat separation.

PURPOSE: To extend the double echo steady-state (DESS) sequence to enable chemical-shift corrected water-fat separation. METHODS: This study proposes multiple-echo steady-state (MESS), a sequence that modifies the readouts of the DESS sequence to acquire two echoes each with bipolar readout gradients with higher readout bandwidth. This enables water-fat separation and eliminates the need for water-selective excitation that is often used in combination with DESS, without increasing scan time. An iterative fitting approach was used to perform joint chemical-shift corrected water-fat separation and T2 estimation on all four MESS echoes simultaneously. MESS and water-selective DESS images were acquired for five volunteers, and were compared qualitatively as well as quantitatively on cartilage T2 and thickness measurements. Signal-to-noise ratio (SNR) and T2 quantification were evaluated numerically using pseudo-replications of the acquisition. RESULTS: The water-fat separation provided by MESS was robust and with quality comparable to water-selective DESS. MESS T2 estimation was similar to DESS, albeit with slightly higher variability. Noise analysis showed that SNR in MESS was comparable to DESS on average, but did exhibit local variations caused by uncertainty in the water-fat separation. CONCLUSION: In the same acquisition time as DESS, MESS provides water-fat separation with comparable SNR in the reconstructed water and fat images. By providing additional image contrasts in addition to the water-selective DESS images, MESS provides a promising alternative to DESS.