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Background: Given that changes in brain water content are often correlated with disease, investigating water content non-invasively and in vivo could lead to a better understanding of the pathogenesis of several neurologic diseases., Purpose: To adapt a super-resolution-based technique, previously developed for humans, to the rat brain and report in vivo high-resolution (HR) water content maps in comparison with ex vivo wet/dry methods., Study Type: Prospective., Animal Model: Eight healthy male Wistar rats., Field Strength/sequence: 9.4-T, multi-echo gradient-echo (mGRE) sequence., Assessment: Using super-resolution reconstruction (SRR), a HR mGRE image (200 μm isotropic) was reconstructed from three low-resolution (LR) orthogonal whole-brain images in each animal, which was followed by water content mapping in vivo. The animals were subsequently sacrificed, the brains excised and divided into five regions (front left, front right, middle left, middle right, and cerebellum-brainstem regions), and the water content was measured ex vivo using wet/dry measurements as the reference standard. The water content values of the in vivo and ex vivo methods were then compared for the whole brain and also for the different regions separately., Statistical Tests: Friedman's non-parametric test was used to test difference between the five regions, and Pearson's correlation coefficient was used for correlation between in vivo and ex vivo measurements. A P-value <0.05 was considered statistically significant., Results: Water content values derived from in vivo MR measurements showed strong correlations with water content measured ex vivo at a regional level (r = 0.902). Different brain regions showed significantly different water content values. Water content values were highest in the frontal brain, followed by the midbrain, and lowest in the cerebellum and brainstem regions., Data Conclusion: An in vivo technique to achieve HR isotropic water content maps in the rat brain using SRR was adopted in this study. The MRI-derived water content values obtained using the technique showed strong correlations with water content values obtained using ex vivo wet/dry methods., Level of Evidence: 1 TECHNICAL EFFICACY: Stage 1., (© 2023 The Authors. Journal of Magnetic Resonance Imaging published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in Medicine.)

Background: Optimal fluid status is an important issue in hemodialysis. Clinical evaluation of volume status and different diagnostic tools are used to determine hydration status in these patients. However, there is still no accurate method for this assessment., Purpose: To propose and evaluate relative lean water signal (LWS rel ) as a water-fat MRI-based tissue hydration measurement., Study Type: Prospective., Population: A total of 16 healthy subjects (56 ± 6 years, 0 male) and 11 dialysis patients (60.3 ± 12.3 years, 9 male; dialysis time per week 15 ± 3.5 hours, dialysis duration 31.4 ± 27.9 months)., Field Strength/sequence: A 3 T; 3D spoiled gradient echo., Assessment: LWS rel , a measurement of the water concentration of tissue, was estimated from fat-referenced MR images. Segmentations of total adipose tissue as well as thigh and calf muscles were used to measure LWS rel and tissue volumes. LWS rel was compared between healthy subjects and dialysis patients, the latter before and after dialysis. Bioimpedance-based body composition monitor over hydration (BCM OH) was also measured., Statistical Tests: T-tests were used to compare differences between the healthy subjects and dialysis patients, as well as changes between before and after dialysis. Pearson correlation was calculated between MRI and non-MRI biomarkers. A P value <0.05 was considered statistically significant., Results: The LWS rel in adipose tissue was significantly higher in the dialysis cohort compared with the healthy cohort (246.8% ± 60.0% vs. 100.0% ± 10.8%) and decreased significantly after dialysis (246.8 ± 60.0% vs. 233.8 ± 63.4%). Thigh and calf muscle volumes also significantly decreased by 3.78% ± 1.73% and 2.02% ± 2.50% after dialysis. There was a significant correlation between changes in adipose tissue LWS rel and ultrafiltration volume (r = 87), as well as with BCM OH (r = 0.66)., Data Conclusion: MRI-based LWS rel and tissue volume measurements are sensitive to tissue hydration changes occurring during dialysis., Evidence Level: 2., Technical Efficacy: Stage 3., (© 2023 International Society for Magnetic Resonance in Medicine.)

Purpose: To determine the relationship between parameters measured from luminal water imaging (LWI), a new magnetic resonance imaging (MRI) T 2 mapping technique, and the corresponding tissue composition in prostate., Materials and Methods: In all, 17 patients with prostate cancer were examined with a 3D multiecho spin echo sequence at 3T prior to undergoing radical prostatectomy. Maps of seven MR parameters, called N, T 2-short , T 2-long , A short , A long , geometric mean T 2 time (gmT 2 ), and luminal water fraction (LWF), were generated using nonnegative least squares (NNLS) analysis of the T 2 decay curves. MR parametric maps were correlated to digitized whole-mount histology sections. Percentage area of tissue components, including luminal space, nuclei, and cytoplasm plus stroma, was measured on the histology sections by using color-based image segmentation. Spearman's rank correlation test was used to evaluate the correlation between MR parameters and the corresponding tissue components, with particular attention paid to the correlation between LWF and percentage area of luminal space., Results: N, T 2-short , A long , gmT 2 , and LWF showed significant correlation (P < 0.05) with percentage area of luminal space and stroma plus cytoplasm. T 2-short and gmT 2 also showed significant correlation (P < 0.05) with percentage area of nuclei. Overall, the strongest correlation was observed between LWF and luminal space (Spearman's coefficient of rank correlation = 0.75, P < 0.001)., Conclusion: Results of this study show that LWF measured with MRI is strongly correlated with the fractional amount of luminal space in prostatic tissue. This result suggests that LWI can potentially be applied for evaluation of prostatic diseases in which the extent of luminal space differs between normal and abnormal tissues., Level of Evidence: 1 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:861-869., (© 2017 International Society for Magnetic Resonance in Medicine.)

Purpose: To quantitatively compare diffusion metrics for human brain estimated with diffusional kurtosis imaging (DKI) at applied field strengths of 1.5 and 3T., Materials and Methods: DKI data for brain were acquired at both 1.5 and 3T from each of six healthy volunteers using a twice-refocused diffusion-weighted imaging sequence. From these data, parametric maps of mean diffusivity (MD), axial diffusivity (D ‖ ), radial diffusivity (D ⊥ ), fractional anisotropy (FA), mean diffusional kurtosis (MK), axial kurtosis (K ‖ ), radial kurtosis (K ⊥ ), and kurtosis fractional anisotropy (KFA) were estimated. Comparisons of the results from the two field strengths were made for each metric using both Bland-Altman plots and linear regression to calculate coefficients of determination (R 2 ) and best fit lines., Results: Diffusion metrics measured at 1.5 and 3T were observed to be similar. Linear regression of the full datasets had coefficients of determination varying from a low of R 2 = 0.86 for KFA to a high of R 2 = 0.97 for FA. The slopes of the 3T vs. 1.5T best linear fits varied from 0.881 ± 0.009 for KFA to 1.038 ± 0.010 for D ‖ . From a Bland-Altman analysis of selected regions of interest, the mean differences of the metrics for the two field strengths were all found to be less than 6%, except for KFA, which showed the largest relative discrepancy of 10%., Conclusion: Diffusion metrics measured with DKI at 1.5 and 3T are strongly correlated and typically differ by only a few percent. The somewhat higher discrepancy for the KFA is argued to mainly reflect the effects of signal noise. This supports the robustness DKI results with respect to field strength., Level of Evidence: 3 J. Magn. Reson. Imaging 2017;45:673-680., (© 2016 International Society for Magnetic Resonance in Medicine.)

Restriction spectrum imaging (RSI) is a novel diffusion-weighted MRI technique that uses the mathematically distinct behavior of water diffusion in separable microscopic tissue compartments to highlight key aspects of the tissue microarchitecture with high conspicuity. RSI can be acquired in less than 5 min on modern scanners using a surface coil. Multiple field gradients and high b-values in combination with postprocessing techniques allow the simultaneous resolution of length-scale and geometric information, as well as compartmental and nuclear volume fraction filtering. RSI also uses a distortion correction technique and can thus be fused to high resolution T2-weighted images for detailed localization, which improves delineation of disease extension into critical anatomic structures. In this review, we discuss the acquisition, postprocessing, and interpretation of RSI for prostate MRI. We also summarize existing data demonstrating the applicability of RSI for prostate cancer detection, in vivo characterization, localization, and targeting., Level of Evidence: 5 J. Magn. Reson. Imaging 2017;45:323-336., (© 2016 International Society for Magnetic Resonance in Medicine.)

Purpose: To validate a chemical shift-encoded (CSE) water-fat imaging for quantifying marrow fat fraction (FF), using proton magnetic resonance spectroscopy (MRS) as reference., Materials and Methods: Multiecho T 2 -corrected MRS and CSE imaging with eight-echo gradient-echo acquisitions at 3T were performed to calculate marrow FF in 83 subjects, including 41 with normal bone mineral density (BMD), 26 with osteopenia, and 16 with osteoporosis (based on DXA). Eight participants were scanned three times with repositioning to assess the repeatability of CSE FF map measurements. Pearson correlation coefficient, Bland-Altman 95% limit of agreement, and Lin's concordance correlation coefficient were calculated., Results: The Pearson correlation coefficient was 0.979 and Lin's concordance correlation coefficient was 0.962 between CSE-based FF and MRS-based FF. All data points, calculated using the Bland-Altman method, were within the limits of agreement. The intra- and interrater agreement for average CSE-based FF was excellent (intrarater, intraclass correlation coefficient [ICC] = 0.993; interrater, ICC = 0.976-0.982 for different BMD groups). In the subgroups of varying BMD, inverse correlations were observed to be very similar between BMD (r = -0.560 to -0.710), T-score (r = -0.526 to -0.747), and CSE-based FF, and between BMD (r = -0.539 to -0.706), T-score (r = -0.501 to -0.742), and MRS-based FF even controlling for age, years since menopause, and body mass index. The repeatability for CSE FF map measurements expressed as absolute precision error was 1.45%., Conclusion: CSE imaging is equally accurate in characterizing marrow fat content as MRS. Given its excellent correlation and concordance with MRS, the CSE sequence could be used as a potential replacement technique for marrow fat quantification., Level of Evidence: 1 J. Magn. Reson. Imaging 2017;45:66-73., (© 2016 International Society for Magnetic Resonance in Medicine.)

Purpose: To assess the feasibility of measuring the fat fraction, T1 and T2 * relaxation times of water and fat signals in vertebral bone marrow using breath-hold magnetic resonance imaging (MRI) gradient echo images of the spine., Materials and Methods: MRI experiments were performed at 1.5T on eight healthy volunteers (35.1 ± 15.7 years, five men and three women) using two sagittal four-echo 3D gradient echo volumetric interpolated breath-hold examination (VIBE Dixon) sequences acquired at two different flip angles (5° and 15°). The water/fat decomposition was performed in the vertebral bodies of L1 to L5 by fitting the signal to a function that depends on the echo time and the flip angle to calculate the fat fraction (FF) and T1 and T2 * relaxation times of water and fat signals. Repeatability was assessed by scanning one volunteer six times., Results: The mean fat fraction over L1 to L5 was 33 ± 8%. The mean T1 and T2 * of water and fat signals were respectively T1w = 701 ± 151 msec, T2 *w = 13.7 ± 2.9 msec, T1f = 334 ± 113 msec, and T2 *f = 11.4 ± 2.7 msec. When considering each vertebra separately, the fat fraction increased from L1 to L5 and the T1w decreased from L1 to L5. The mean coefficients of variation obtained from the repeatability study were 8% (FF), 11% (T1w ), 17% (T1f ), 8% (T2 *w ), and 27% (T2 *f )., Conclusion: The method introduced in the current study allows for the measurement of the fat fraction and water and fat relaxation times, with a total acquisition time of less than 40 seconds. J. Magn. Reson. Imaging 2016;44:549-555., (© 2016 International Society for Magnetic Resonance in Medicine.)

Purpose: To determine whether differences in hydration state, which could arise from routine clinical procedures such as overnight fasting, affect brain total water content (TWC) and brain volume measured with magnetic resonance imaging (MRI)., Materials and Methods: Twenty healthy volunteers were scanned with a 3T MR scanner four times: day 1, baseline scan; day 2, hydrated scan after consuming 3L of water over 12 hours; day 3, dehydrated scan after overnight fasting of 9 hours, followed by another scan 1 hour later for reproducibility. The following MRI data were collected: T2 relaxation (for TWC measurement), inversion recovery (for T1 measurement), and 3D T1 -weighted (for brain volumes). Body weight and urine specific gravity were also measured. TWC was calculated by fitting the T2 relaxation data with a nonnegative least-squares algorithm, with corrections for T1 relaxation and image signal inhomogeneity and normalization to ventricular cerebrospinal fluid. Brain volume changes were measured using SIENA. TWC means were calculated within 14 tissue regions., Results: Despite indications of dehydration as demonstrated by increases in urine specific gravity (P = 0.03) and decreases in body weight (P = 0.001) between hydrated and dehydrated scans, there was no measurable change in TWC (within any brain region) or brain volume between hydration states., Conclusion: We demonstrate that within a range of physiologic conditions commonly encountered in routine clinical scans (no pretreatment with hydration, well hydrated before MRI, and overnight fasting), brain TWC and brain volumes are not substantially affected in a healthy control cohort. J. Magn. Reson. Imaging 2016;44:296-304., (© 2016 Wiley Periodicals, Inc.)

Purpose: To propose and assess a method to improve the reliability of phase-sensitive fat-water separation for phased-array balanced steady-state free precession (bSSFP) acquisitions. Phase-sensitive steady-state free precession (PS-SSFP) is an efficient fat-water separation technique that detects the phase difference between neighboring bands in the bSSFP magnetization profile. However, large spatial variations in the sensitivity profiles of phased-array coils can lead to noisy phase estimates away from the coil centers, compromising tissue classification., Materials and Methods: We first perform region-growing phase correction in individual coil images via unsupervised selection of a fat-voxel seed near the peak of each coil's sensitivity profile. We then use an optimal linear combination of phase-corrected images to segregate fat and water signals. The proposed method was demonstrated on noncontrast-enhanced SSFP angiograms of the thigh, lower leg, and foot acquired at 1.5T using an 8-channel coil. Individual coil PS-SSFP with a common seed selection for all coils, individual coil PS-SSFP with coil-wise seed selection, PS-SSFP after coil combination, and IDEAL reconstructions were also performed. Water images reconstructed via PS-SSFP methods were compared in terms of the level of fat suppression and the similarity to reference IDEAL images (signed-rank test)., Results: While tissue misclassification was broadly evident across regular PS-SSFP images, the proposed method achieved significantly higher levels of fat suppression (P < 0.005) and increased similarity to reference IDEAL images (P < 0.005)., Conclusion: The proposed method enhances fat-water separation in phased-array acquisitions by producing improved phase estimates across the imaging volume. J. Magn. Reson. Imaging 2016;44:148-157., (© 2015 Wiley Periodicals, Inc.)