On the confounding effect of temperature on chemical shift-encoded fat quantification

Parameter optimization for proton density fat fraction quantification in skeletal muscle tissue at 7 T

OBJECTIVE

To establish an image acquisition and post-processing workflow for the determination of the proton density fat fraction (PDFF) in calf muscle tissue at 7 T.

MATERIALS AND METHODS

Echo times (TEs) of the applied vendor-provided multi-echo gradient echo sequence were optimized based on simulations of the effective number of signal averages (NSA*). The resulting parameters were validated by measurements in phantom and in healthy calf muscle tissue (n = 12). Additionally, methods to reduce phase errors arising at 7 T were evaluated. Finally, PDFF values measured at 7 T in calf muscle tissue of healthy subjects (n = 9) and patients with fatty replacement of muscle tissue (n = 3) were compared to 3 T results.

RESULTS

Simulations, phantom and in vivo measurements showed the importance of using optimized TEs for the fat-water separation at 7 T. Fat-water swaps could be mitigated using a phase demodulation with an additional B0 map, or by shifting the TEs to longer values. Muscular PDFF values measured at 7 T were comparable to measurements at 3 T in both healthy subjects and patients with increased fatty replacement.

CONCLUSION

PDFF determination in calf muscle tissue is feasible at 7 T using a chemical shift-based approach with optimized acquisition and post-processing parameters.

Linearity and bias of proton density fat fraction across the full dynamic range of 0-100%: a multiplatform, multivendor phantom study using 1.5T and 3T MRI at two sites

OBJECTIVE

Performance assessments of quantitative determinations of proton density fat fraction (PDFF) have largely focused on the range between 0 and 50%. We evaluate PDFF in a two-site phantom study across the full 0-100% PDFF range.

MATERIALS AND METHODS

We used commercially available 3D chemical-shift-encoded water-fat MRI sequences from three MRI system vendors at 1.5T and 3T and conducted the study across two sites. A spherical phantom housing 18 vials spanning the full 0-100% PDFF range was used. Data at each site were acquired using default parameters to determine same-day and different-day intra-scanner repeatability, and inter-system and inter-site reproducibility, in addition to linear regression between reference and measured PDFF values.

RESULTS

Across all systems, results demonstrated strong linearity and minimal bias. For 1.5T systems, a pooled slope of 0.99 with a 95% confidence interval (CI) of 0.981-0.997 and a pooled intercept of 0.61% PDFF with a 95% CI of 0.17-1.04 were obtained. Results for pooled 3T data included a slope of 1.00 (95% CI 0.995-1.005) and an intercept of 0.69% PDFF (95% CI 0.39-0.97). Inter-site and inter-system reproducibility coefficients ranged from 2.9 to 6.2 (in units of PDFF), while intra-scanner same-day and different-day repeatability ranged from 0.6 to 7.8.

DISCUSSION

PDFF across the 0-100% range can be reliably estimated using current commercial offerings at 1.5T and 3T.

The effect of fat model variation on muscle fat fraction quantification in a cross-sectional cohort

Spectroscopic imaging, rooted in Dixon's two-echo spin sequence to distinguish water and fat, has evolved significantly in acquisition and processing. Yet precise fat quantification remains a persistent challenge in ongoing research. With adequate phase characterization and correction, the fat composition models will impact measurements of fatty tissue. However, the effect of the used fat model in low-fat regions such as healthy muscle is unknown. In this study, we investigate the effect of assumed fat composition, in terms of chain length and double bond count, on fat fraction quantification in healthy muscle, while addressing phase and relaxometry confounders. For this purpose, we acquired bilateral thigh datasets from 38 healthy volunteers. Fat fractions were estimated using the IDEAL algorithm employing three different fat models fitted with and without the initial phase constrained. After data processing and model fitting, we used a convolutional neural net to automatically segment all thigh muscles and subcutaneous fat to evaluate the fitted parameters. The fat composition was compared with those reported in the literature. Overall, all the observed estimated fat composition values fall within the range of previously reported fatty acid composition based on gas chromatography measurements. All methods and models revealed different estimates of the muscle fat fractions in various evaluated muscle groups. Lateral differences changed from 0.5% to 5.3% in the hamstring muscle groups depending on the chosen method. The lowest observed left-right differences in each muscle group were all for the fat model estimating the number of double bonds with the initial phase unconstrained. With this model, the left-right differences were 0.64% ± 0.31%, 0.50% ± 0.27%, and 0.50% ± 0.40% for the quadriceps, hamstrings, and adductors muscle groups, respectively. Our findings suggest that a fat model estimating double bond numbers while allowing separate phases for each chemical species, given some assumptions, yields the best fat fraction estimate for our dataset.

R2* Impact on Hepatic Fat Quantification With a Commercial Single Voxel Technique at 1.5 and 3.0 T

Rationale and Objectives: Fat quantification accuracy using a commercial single-voxel high speed T2-corrected multi-echo (HISTO) technique and its robustness to R2* variations at 3.0 T, such as those introduced by iron in liver, has not been fully established. This study evaluated HISTO at 3.0 T and sought to reproduce results at 1.5 T. Methods: Phantoms were prepared with a range of fat content and R2*. Data were acquired at 1.5 T and 3.0 T, using HISTO and a Dixon technique. Fat quantification accuracy was evaluated as a function of R2*. The patient study included 239 consecutive patients. Data were acquired at 1.5 T or 3.0 T, using HISTO and Dixon techniques. The techniques were compared using Bland-Altman plots. Bias significance was evaluated using a one-sample t-test. Results: In phantoms, HISTO was accurate within 10% up to a R2* of 100 s-1 at both field strengths, while Dixon was accurate within 10% where R2* was accurately quantified (up to 350 s-1 at 1.5 T, and 550 s-1 at 3.0 T). In patients, where R2* was <100 s-1, fat quantification from both techniques agreed at 1.5 T (P = .71), but not at 3.0 T (P = .007), with a bias <1%. Conclusion: Results suggest that HISTO is reliable when R2* is <100 s-1, corresponding to patients with at most mild liver iron overload, and that it should be used with caution when R2* is >100 s-1. Dixon should be preferred for hepatic fat quantification due to its robustness to R2* variations.

Comparative review of algorithms and methods for chemical-shift-encoded quantitative fat-water imaging

PURPOSE

To propose a standardized comparison between state-of-the-art open-source fat-water separation algorithms for proton density fat fraction (PDFF) andR 2 * $$ {R}_2^{\ast } $$ quantification using an open-source multi-language toolbox.

METHODS

Eight recent open-source fat-water separation algorithms were compared in silico, in vitro, and in vivo. Multi-echo data were synthesized with varying fat-fractions, B0 off-resonance, SNR and TEs. Experimental evaluation was conducted using calibrated fat-water phantoms acquired at 3T and multi-site open-source phantoms data. Algorithms' performances were observed on challenging in vivo datasets at 3T. Finally, reconstruction algorithms were investigated with different fat spectra to evaluate the importance of the fat model.

RESULTS

In silico and in vitro results proved most algorithms to be not sensitive to fat-water swaps andB 0 $$ {\mathrm{B}}_0 $$ offsets with five or more echoes. However, two methods remained inaccurate even with seven echoes and SNR = 50, and two other algorithms' precision depended on the echo spacing scheme (p < 0.05). The remaining four algorithms provided reliable performances with limits of agreement under 2% for PDFF and 6 s-1 forR 2 * $$ {R}_2^{\ast } $$ . The choice of fat spectrum model influenced quantification of PDFF mildly (<2% bias) and ofR 2 * $$ {R}_2^{\ast } $$ more severely, with errors up to 20 s-1 .

CONCLUSION

In promoting standardized comparisons of MRI-based fat and iron quantification using chemical-shift encoded multi-echo methods, this benchmark work has revealed some discrepancies between recent approaches for PDFF andR 2 * $$ {R}_2^{\ast } $$ mapping. Explicit choices and parameterization of the fat-water algorithm appear necessary for reproducibility. This open-source toolbox further enables the user to optimize acquisition parameters by predicting algorithms' margins of errors.

Multi-echo-based fat artifact correction for CEST MRI at 7 T

PURPOSE

CEST MRI is influenced by fat signal, which can reduce the apparent CEST contrast or lead to pseudo-CEST effects. Our goal was to develop a fat artifact correction based on multi-echo fat-water separation that functions stably for 7 T knee MRI data.

METHODS

Our proposed algorithm utilizes the full complex data and a phase demodulation with an off-resonance map estimation based on the Z-spectra prior to fat-water separation to achieve stable fat artifact correction. Our method was validated and compared to multi-echo-based methods originally proposed for 3 T by Bloch-McConnell simulations and phantom measurements. Moreover, the method was applied to in vivo 7 T knee MRI examinations and compared to Gaussian fat saturation and a published single-echo Z-spectrum-based fat artifact correction method.

RESULTS

Phase demodulation prior to fat-water separation reduced the occurrence of fat-water swaps. Utilizing the complex signal data led to more stable correction results than working with magnitude data, as was proposed for 3 T. Our approach reduced pseudo-nuclear Overhauser effects compared to the other correction methods. Thus, the mean asymmetry contrast at 3.5 ppm in cartilage over five volunteers increased from -9.2% (uncorrected) and -10.6% (Z-spectrum-based) to -1.5%. Results showed higher spatial stability than with the fat saturation pulse.

CONCLUSION

Our work demonstrates the feasibility of multi-echo-based fat-water separation with an adaptive fat model for fat artifact correction for CEST MRI at 7 T. Our approach provided better fat artifact correction throughout the entire spectrum and image than the fat saturation pulse or Z-spectrum-based correction method for both phantom and knee imaging results.

Clinical Application of Quantitative MR Imaging in Nonalcoholic Fatty Liver Disease

Viral hepatitis was previously the most common cause of chronic liver disease. However, in recent years, nonalcoholic fatty liver disease (NAFLD) cases have been increasing, especially in developed countries. NAFLD is histologically characterized by fat, fibrosis, and inflammation in the liver, eventually leading to cirrhosis and hepatocellular carcinoma. Although biopsy is the gold standard for the assessment of the liver parenchyma, quantitative evaluation methods, such as ultrasound, CT, and MRI, have been reported to have good diagnostic performances. The quantification of liver fat, fibrosis, and inflammation is expected to be clinically useful in terms of the prognosis, early intervention, and treatment response for the management of NAFLD. The aim of this review was to discuss the basics and prospects of MRI-based tissue quantifications of the liver, mainly focusing on proton density fat fraction for the quantification of fat deposition, MR elastography for the quantification of fibrosis, and multifrequency MR elastography for the evaluation of inflammation.

Quantitative MRI of diffuse liver diseases: techniques and tissue-mimicking phantoms

Quantitative magnetic resonance imaging (MRI) techniques are emerging as non-invasive alternatives to biopsy for assessment of diffuse liver diseases of iron overload, steatosis and fibrosis. For testing and validating the accuracy of these techniques, phantoms are often used as stand-ins to human tissue to mimic diffuse liver pathologies. However, currently, there is no standardization in the preparation of MRI-based liver phantoms for mimicking iron overload, steatosis, fibrosis or a combination of these pathologies as various sizes and types of materials are used to mimic the same liver disease. Liver phantoms that mimic specific MR features of diffuse liver diseases observed in vivo are important for testing and calibrating new MRI techniques and for evaluating signal models to accurately quantify these features. In this study, we review the liver morphology associated with these diffuse diseases, discuss the quantitative MR techniques for assessing these liver pathologies, and comprehensively examine published liver phantom studies and discuss their benefits and limitations.

Interval walking training in type 2 diabetes: A pilot study to evaluate the applicability as exercise therapy

There are few established easy-to-perform exercise protocols with evidence-based effects for individuals with type 2 diabetes (T2D). A unique exercise regimen, interval walking training (IWT), has been reported to be beneficial for improving metabolic function, physical fitness and muscle strength in adults of overall health. This pilot study aims to demonstrate descriptive statistics of IWT adherence and changes in various data before and after the intervention of IWT in adults with T2D, perform statistical hypothesis testing, and calculate effect sizes. We performed a single-arm interventional pilot study with IWT for 20 weeks. We enrolled 51 participants with T2D aged 20-80 years with glycohemoglobin (HbA1c) levels of 6.5-10.0% (48-86 mmol/mol) and a body mass index of 20-34 kg/m2, respectively. The target was 60 min/week of fast walking for 20 weeks. The participants visited the hospital and were examined at 4-week intervals during this period. Between the start of IWT and after 20 weeks, we measured and evaluated changes in glucose and lipid metabolism data, body composition, physical fitness, muscle strength, dietary calorie intake, and daily exercise calories. All included participants completed IWT, with 39% of them reaching the target length of fast walking over 1,200 minutes in 20 weeks. In the primary outcome, HbA1c levels, and in the secondary, lipid metabolism and body composition, no significant changes were observed except for high-density lipoprotein cholesterol (HDL-C) (from 1.4 mmol/L to 1.5 mmol/L, p = 0.0093, t-test). However, in the target achievement group, a significant increase in VO2 peak by 10% (from 1,682 mL/min to 1,827 mL/min, p = 0.037, t-test) was observed. Effect sizes were Cohen's d = 0.25 of HDL-C, -0.55 of triglyceride, and 0.24 of VO2 peak in the target achievement group, which were considered to be of small to medium clinical significance. These results could be solely attributed to IWT since there were no significant differences in dietary intake and daily life energy consumption before and after the study. IWT could be highly versatile and was suggested to have a positive effect on lipid metabolism and physical fitness. In future randomized controlled trial (RCT) studies, the detailed effects of IWT, focusing on these parameters, will be examined. Trial registration: This trial was registered with the Japanese University Hospital Medical Information Network Clinical Trials Registry (UMIN-CTR: Usefulness on interval walking training in patients with type 2 diabetes. 000037303).

Fast multi-parametric imaging in abdomen by B 1 + corrected dual-flip angle sequence with interleaved echo acquisition

PURPOSE

To achieve simultaneous T_{1, w} /proton density fat fraction (PDFF)/ R 2 ∗ mapping in abdomen within a single breadth-hold, and validate the accuracy using state-of-art measurement.

THEORY AND METHODS

An optimized multiple echo gradient echo (GRE) sequence with dual flip-angle acquisition was used to realize simultaneous water T₁ (T_{1, w} )/PDFF/ R 2 ∗ quantification. A new method, referred to as "solving the fat-water ambiguity based on their T₁ difference" (SORT), was proposed to address the fat-water separation problem. This method was based on the finding that compared to the true solution, the wrong (or aliased) solution to fat-water separation problem showed extra dependency on the applied flip angle due to the T₁ difference between fat and water. The B 1 + measurement sequence was applied to correct the B 1 + inhomogeneity for T_{1, w} relaxometry. The 2D parallel imaging was incorporated to enable the acquisition within a single breath-hold in abdomen.

RESULTS

The multi-parametric quantification results of the proposed method were consistent with the results of reference methods in phantom experiments (PDFF quantification: R²  = 0.993, mean error 0.73%; T_{1, w} quantification: R²  = 0.999, mean error 4.3%; R 2 ∗ quantification: R²  = 0.949, mean error 4.07 s^-1 ). For volunteer studies, robust fat-water separation was achieved without evident fat-water swaps. Based on the accurate fat-water separation, simultaneous T_{1, w} /PDFF/ R 2 ∗ quantification was realized for whole liver within a single breath-hold.

CONCLUSION

The proposed method accurately quantified T_{1, w} /PDFF/ R 2 ∗ for the whole liver within a single breath-hold. This technique serves as a quantitative tool for disease management in patients with hepatic steatosis.

Noninvasive assessment of steatosis and viability of cold-stored human liver grafts by MRI

PURPOSE

A shortage of suitable donor livers is driving increased use of higher risk livers for transplantation. However, current biomarkers are not sensitive and specific enough to predict posttransplant liver function. This is limiting the expansion of the donor pool. Therefore, better noninvasive tests are required to determine which livers will function following implantation and hence can be safely transplanted. This study assesses the temperature sensitivity of proton density fat fraction and relaxometry parameters and examines their potential for assessment of liver function ex vivo.

METHODS

Six ex vivo human livers were scanned during static cold storage following normothermic machine perfusion. Proton density fat fraction, T1 , T2 , and T 2 ∗ were measured repeatedly during cooling on ice. Temperature corrections were derived from these measurements for the parameters that showed significant variation with temperature.

RESULTS

Strong linear temperature sensitivities were observed for proton density fat fraction (R2 = 0.61, P < .001) and T1 (R2 = 0.78, P < .001). Temperature correction according to a linear model reduced the coefficient of repeatability in these measurements by 41% and 36%, respectively. No temperature dependence was observed in T2 or T 2 ∗ measurements. Comparing livers deemed functional and nonfunctional during normothermic machine perfusion by hemodynamic and biochemical criteria, T1 differed significantly: 516 ± 50 ms for functional versus 679 ± 60 ms for nonfunctional, P = .02.

CONCLUSION

Temperature correction is essential for robust measurement of proton density fat fraction and T1 in cold-stored human livers. These parameters may provide a noninvasive measure of viability for transplantation.

Proton density water fraction as a reproducible MR-based measurement of breast density

PURPOSE

To introduce proton density water fraction (PDWF) as a confounder-corrected (CC) MR-based biomarker of mammographic breast density, a known risk factor for breast cancer.

METHODS

Chemical shift encoded (CSE) MR images were acquired using a low flip angle to provide proton density contrast from multiple echo times. Fat and water images, corrected for known biases, were produced by a six-echo CC CSE-MRI algorithm. Fibroglandular tissue (FGT) volume was calculated from whole-breast segmented PDWF maps at 1.5T and 3T. The method was evaluated in (1) a physical fat-water phantom and (2) normal volunteers. Results from two- and three-echo CSE-MRI methods were included for comparison.

RESULTS

Six-echo CC-CSE-MRI produced unbiased estimates of the total water volume in the phantom (mean bias 3.3%) and was reproducible across protocol changes (repeatability coefficient [RC] = 14.8 cm³ and 13.97 cm³ at 1.5T and 3.0T, respectively) and field strengths (RC = 51.7 cm³ ) in volunteers, while the two- and three-echo CSE-MRI approaches produced biased results in phantoms (mean bias 30.7% and 10.4%) that was less reproducible across field strengths in volunteers (RC = 82.3 cm³ and 126.3 cm³ ). Significant differences in measured FGT volume were found between the six-echo CC-CSE-MRI and the two- and three-echo CSE-MRI approaches (p = 0.002 and p = 0.001, respectively).

CONCLUSION

The use of six-echo CC-CSE-MRI to create unbiased PDWF maps that reproducibly quantify FGT in the breast is demonstrated. Further studies are needed to correlate this quantitative MR biomarker for breast density with mammography and overall risk for breast cancer.

Quantification of Liver Fat Content with CT and MRI: State of the Art

Hepatic steatosis is defined as pathologically elevated liver fat content and has many underlying causes. Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disease worldwide, with an increasing prevalence among adults and children. Abnormal liver fat accumulation has serious consequences, including cirrhosis, liver failure, and hepatocellular carcinoma. In addition, hepatic steatosis is increasingly recognized as an independent risk factor for the metabolic syndrome, type 2 diabetes, and, most important, cardiovascular mortality. During the past 2 decades, noninvasive imaging-based methods for the evaluation of hepatic steatosis have been developed and disseminated. Chemical shift-encoded MRI is now established as the most accurate and precise method for liver fat quantification. CT is important for the detection and quantification of incidental steatosis and may play an increasingly prominent role in risk stratification, particularly with the emergence of CT-based screening and artificial intelligence. Quantitative imaging methods are increasingly used for diagnostic work-up and management of steatosis, including treatment monitoring. The purpose of this state-of-the-art review is to provide an overview of recent progress and current state of the art for liver fat quantification using CT and MRI, as well as important practical considerations related to clinical implementation.

Adding marrow R2∗ to proton density fat fraction improves the discrimination of osteopenia and osteoporosis in postmenopausal women assessed with 3D FACT sequence

OBJECTIVE

To evaluate the role of three-dimensional Fat Analysis & Calculation Technique sequence in improving the diagnostic accuracy for the detection of osteopenia and osteoporosis by simultaneous quantification of proton density fat fraction (PDFF) and fat-corrected R2∗.

METHODS

Fat Analysis & Calculation Technique imaging of lumbar spine was obtained in 99 postmenopausal women including 52 normal bone mass, 29 osteopenia, and 18 osteoporosis. The diagnostic performance of PDFF and R2∗ in the differentiation of different bone-density groups was evaluated with the receiver operating characteristic curve.

RESULTS

The reproducibility of PDFF and R2∗ measures was satisfactory with the root mean square coefficient of variation, 2.16% and 2.70%, respectively. The intra- and interobserver agreements for the PDFF and R2∗ were excellent with the intraclass correlation coefficient > 0.9 for all. There were significant differences in PDFF and R2∗ among the three groups (P < 0.05). Bone density had a moderate inverse correlation with PDFF (r  = -0.659) but a positive association with R2∗ (r = 0.508, P < 0.001). Adjusted for age, years since menopause and body mass index, odds ratios (95% confidence interval) for osteopenia and osteoporosis per standard deviation higher marrow PDFF and R2∗ were 2.9 (1.4-5.8) and 0.4 (0.2-0.8), respectively. The areas under the curve were 0.821 for PDFF, 0.784 for R2∗, and 0.922 for both combined for the detection of osteoporosis (P < 0.05). Similar results were obtained in distinguishing osteopenia from healthy controls.

CONCLUSIONS

Simultaneous estimation of marrow R2∗ and PDFF improves the discrimination of osteopenia and osteoporosis in comparison with the PDFF or R2∗ alone.

Temperature-corrected proton density fat fraction estimation using chemical shift-encoded MRI in phantoms

PURPOSE

Chemical shift-encoded MRI (CSE-MRI) is well-established to quantify proton density fat fraction (PDFF) as a quantitative biomarker of hepatic steatosis. However, temperature is known to bias PDFF estimation in phantom studies. In this study, strategies were developed and evaluated to correct for the effects of temperature on PDFF estimation through simulations, temperature-controlled experiments, and a multi-center, multi-vendor phantom study.

THEORY AND METHODS

A technical solution that assumes and automatically estimates a uniform, global temperature throughout the phantom is proposed. Computer simulations modeled the effect of temperature on PDFF estimation using magnitude-, complex-, and hybrid-based CSE-MRI methods. Phantom experiments were performed to assess the temperature correction on PDFF estimation at controlled phantom temperatures. To assess the temperature correction method on a larger scale, the proposed method was applied to data acquired as part of a nine-site multi-vendor phantom study and compared to temperature-corrected PDFF estimation using an a priori guess for ambient room temperature.

RESULTS

Simulations and temperature-controlled experiments show that as temperature deviates further from the assumed temperature, PDFF bias increases. Using the proposed correction method and a reasonable a priori guess for ambient temperature, PDFF bias and variability were reduced using magnitude-based CSE-MRI, across MRI systems, field strengths, protocols, and varying phantom temperature. Complex and hybrid methods showed little PDFF bias and variability both before and after correction.

CONCLUSION

Correction for temperature reduces temperature-related PDFF bias and variability in phantoms across MRI vendors, sites, field strengths, and protocols for magnitude-based CSE-MRI, even without a priori information about the temperature.

Linearity and Bias of Proton Density Fat Fraction as a Quantitative Imaging Biomarker: A Multicenter, Multiplatform, Multivendor Phantom Study

Background Proton density fat fraction (PDFF) estimated by using chemical shift-encoded (CSE) MRI is an accepted imaging biomarker of hepatic steatosis. This work aims to promote standardized use of CSE MRI to estimate PDFF. Purpose To assess the accuracy of CSE MRI methods for estimating PDFF by determining the linearity and range of bias observed in a phantom. Materials and Methods In this prospective study, a commercial phantom with 12 vials of known PDFF values were shipped across nine U.S. centers. The phantom underwent 160 independent MRI examinations on 27 1.5-T and 3.0-T systems from three vendors. Two three-dimensional CSE MRI protocols with minimal T1 bias were included: vendor and standardized. Each vendor's confounder-corrected complex or hybrid magnitude-complex based reconstruction algorithm was used to generate PDFF maps in both protocols. The Siemens reconstruction required a configuration change to correct for water-fat swaps in the phantom. The MRI PDFF values were compared with the known PDFF values by using linear regression with mixed-effects modeling. The 95% CIs were calculated for the regression slope (ie, proportional bias) and intercept (ie, constant bias) and compared with the null hypothesis (slope = 1, intercept = 0). Results Pooled regression slope for estimated PDFF values versus phantom-derived reference PDFF values was 0.97 (95% CI: 0.96, 0.98) in the biologically relevant 0%-47.5% PDFF range. The corresponding pooled intercept was -0.27% (95% CI: -0.50%, -0.05%). Across vendors, slope ranges were 0.86-1.02 (vendor protocols) and 0.97-1.0 (standardized protocol) at 1.5 T and 0.91-1.01 (vendor protocols) and 0.87-1.01 (standardized protocol) at 3.0 T. The intercept ranges (absolute PDFF percentage) were -0.65% to 0.18% (vendor protocols) and -0.69% to -0.17% (standardized protocol) at 1.5 T and -0.48% to 0.10% (vendor protocols) and -0.78% to -0.21% (standardized protocol) at 3.0 T. Conclusion Proton density fat fraction estimation derived from three-dimensional chemical shift-encoded MRI in a commercial phantom was accurate across vendors, imaging centers, and field strengths, with use of the vendors' product acquisition and reconstruction software. © RSNA, 2021 See also the editorial by Dyke in this issue.

Evaluation of hepatic steatosis before liver transplantation in ex vivo by volumetric quantitative PDFF-MRI

PURPOSE

Over the last two decades, extended criteria have promoted an increased number of donor livers available for liver transplantation. But posttransplant graft loss is still a major concern. Macrovesicular hepatic steatosis (MHS) is recognized as the most significant prognostic histologic parameter in predicting posttransplant graft loss. We aimed to evaluate the utility of ex vivo volumetric quantitative MRI for quantifying MHS before liver transplantation using proton density fat-fraction (PDFF-MRI) histogram analysis.

METHODS

PDFF-MRI was performed at 3.0T in 40 livers. We obtained histogram parameters of whole-liver volume of interest, including the mean, median, 5th, 10th, 25th, 75th, 90th, and 95th percentile PDFF; skewness; kurtosis; entropy; and volume.

RESULTS

Livers from 40 cadaveric donors were included, and histologic ex vivo fat quantification was available for 33 livers. Ten livers had MHS and 23 had normal fat content. The MHS group had higher mean, median, 5th, 10th, 25th, 75th, 90th, and 95th percentile PDFF, and entropy than the group with normal fat content (P < .05). Median PDFF had greater area under the curve value than other parameters. Mean PDFF showed an excellent correlation with entropy and a moderate correlation with MHS quantification on histology.

CONCLUSIONS

Ex vivo volumetric quantitative PDFF-MRI histogram analysis is a very useful and noninvasive method to detect MHS before liver transplantation. Median PDFF was the best predictor of the presence of MHS. Entropy is a very promising parameter.

Liver fat quantification: where do we stand?

Excessive intracellular accumulation of triglycerides in the liver, or hepatic steatosis, is a highly prevalent condition affecting approximately one billion people worldwide. In the absence of secondary cause, the term nonalcoholic fatty liver disease (NAFLD) is used. Hepatic steatosis may progress into nonalcoholic steatohepatitis, the more aggressive form of NAFLD, associated with hepatic complications such as fibrosis, liver failure and hepatocellular carcinoma. Hepatic steatosis is associated with metabolic syndrome, cardiovascular disease and represents an independent risk factor for type 2 diabetes, cardiovascular disease and malignancy. Percutaneous liver biopsy is the current reference standard for NAFLD assessment; however, it is an invasive procedure associated with complications and suffers from high sampling variability, impractical for clinical routine and drug efficiency studies. Therefore, noninvasive imaging methods are increasingly used for the diagnosis and monitoring of NAFLD. Among the methods quantifying liver fat, chemical-shift-encoded MRI (CSE-MRI)-based proton density fat-fraction (PDFF) has shown the most promise. MRI-PDFF is increasingly accepted as quantitative imaging biomarker of liver fat that is transforming daily clinical practice and influencing the development of new treatments for NAFLD. Furthermore, CT is an important imaging method for detection of incidental steatosis, and the practical advantages of quantitative ultrasound hold great promise for the future. Understanding the disease burden of NAFLD and the role of imaging may initiate important interventions aimed at avoiding the hepatic and extrahepatic complications of NAFLD. This article reviews clinical burden of NAFLD, and the role of noninvasive imaging techniques for quantification of liver fat.

Quantitative 1 H MRI and MRS of fatty acid composition

Adipose tissue as well as other depots of fat (triglycerides) are increasingly being recognized as active contributors to the human function and metabolism. In addition to the fat concentration, also the fatty acid chemical composition (FAC) of the triglyceride molecules may play an important part in diseases such as obesity, insulin resistance, hepatic steatosis, osteoporosis, and cancer. MR spectroscopy and chemical-shift-encoded imaging (CSE-MRI) are established methods for non-invasive quantification of fat concentration in tissue. More recently, similar techniques have been developed for assessment also of the FAC in terms of the number of double bonds, the fraction of saturated, monounsaturated, and polyunsaturated fatty acids, or semi-quantitative unsaturation indices. The number of papers focusing on especially CSE-MRI-based techniques has steadily increased during the past few years, introducing a range of acquisition protocols and reconstruction algorithms. However, a number of potential sources of bias have also been identified. Furthermore, the measures used to characterize the FAC using both MRI and MRS differ, making comparisons between different techniques difficult. The aim of this paper is to review MRS- and MRI-based methods for in vivo quantification of the FAC. We describe the chemical composition of triglycerides and discuss various potential FAC measures. Furthermore, we review acquisition and reconstruction methodology and finally, some existing and potential applications are summarized. We conclude that both MRI and MRS provide feasible non-invasive alternatives to the gold standard gas chromatography for in vivo measurements of the FAC. Although both are associated with gas chromatography, future studies are warranted.

Design and evaluation of quantitative MRI phantoms to mimic the simultaneous presence of fat, iron, and fibrosis in the liver

PURPOSE

To design, construct, and evaluate quantitative MR phantoms that mimic MRI signals from the liver with simultaneous control of three parameters: proton-density fat fraction (PDFF), R 2 ∗ , and T₁ . These parameters are established biomarkers of hepatic steatosis, iron overload, and fibrosis/inflammation, respectively, which can occur simultaneously in the liver.

METHODS

Phantoms including multiple vials were constructed. Peanut oil was used to modulate PDFF, MnCl₂ and iron microspheres were used to modulate R 2 ∗ , and NiCl₂ was used to modulate the T₁ of water (T_1,water ). Phantoms were evaluated at both 1.5 T and 3 T using stimulated-echo acquisition-mode MRS and chemical shift-encoded MRI. Stimulated-echo acquisition-mode MRS data were processed to estimate T_1,water , T_1,fat , R 2 , water ∗ , and R 2 , fat ∗ for each vial. Chemical shift-encoded MRI data were processed to generate PDFF and R 2 ∗ maps, and measurements were obtained in each vial. Measurements were evaluated using linear regression and Bland-Altman analysis.

RESULTS

High-quality PDFF and R 2 ∗ maps were obtained with homogeneous values throughout each vial. High correlation was observed between imaging PDFF with target PDFF (slope = 0.94-0.97, R² = 0.994-0.997) and imaging R 2 ∗ with target R 2 ∗ (slope = 0.84-0.88, R² = 0.935-0.943) at both 1.5 T and 3 T. The values of R 2 , fat ∗ and R 2 , water ∗ were highly correlated with slope close to 1.0 at both 1.5 T (slope = 0.90, R² = 0.988) and 3 T (slope = 0.99, R² = 0.959), similar to the behavior observed in vivo. The value of T_1,water (500-1200 ms) was controlled with varying NiCl₂ concentration, while T_1,fat (300 ms) was independent of NiCl₂ concentration.

CONCLUSION

Novel quantitative MRI phantoms that mimic the simultaneous presence of fat, iron, and fibrosis in the liver were successfully developed and validated.

Motion-robust, high-SNR liver fat quantification using a 2D sequential acquisition with a variable flip angle approach

PURPOSE

Chemical shift encoded (CSE)-MRI enables quantification of proton-density fat fraction (PDFF) as a biomarker of liver fat content. However, conventional 3D Cartesian CSE-MRI methods require breath-holding. A motion-robust 2D Cartesian sequential method addresses this limitation but suffers from low SNR. In this work, a novel free breathing 2D Cartesian sequential CSE-MRI method using a variable flip angle approach with centric phase encoding (VFA-centric) is developed to achieve fat quantification with low T 1 bias, high SNR, and minimal blurring.

METHODS

Numerical simulation was performed for variable flip angle schedule design and preliminary evaluation of VFA-centric method, along with several alternative flip angle designs. Phantom, adults (n = 8), and children (n = 27) were imaged at 3T. Multi-echo images were acquired and PDFF maps were estimated. PDFF standard deviation was used as a surrogate for SNR.

RESULTS

In both simulation and phantom experiments, the VFA-centric method enabled higher SNR imaging with minimal T 1 bias and blurring artifacts. High correlation (slope = 1.00, intercept = 0.04, R 2 = 0.998) was observed in vivo between the proposed VFA-centric method obtained PDFF and reference PDFF (free breathing low-flip angle 2D sequential acquisition). Further, the proposed VFA-centric method (PDFF standard deviation = 1.5%) had a better SNR performance than the reference acquisition (PDFF standard deviation = 3.3%) with P < .001.

CONCLUSIONS

The proposed free breathing 2D Cartesian sequential CSE-MRI method with variable flip angle approach and centric-ordered phase encoding achieved motion robustness, low T 1 bias, high SNR compared to previous 2D sequential methods, and low blurring in liver fat quantification.

Practical Approaches to Bone Marrow Fat Fraction Quantification Across Magnetic Resonance Imaging Platforms

BACKGROUND

Quantification of fat by proton density fat fraction (PDFF) measurements may be valuable for the quantification and follow-up of pathology in multicenter clinical trials and routine practice. However, many centers do not have access to specialist methods (such as chemical shift imaging) for PDFF measurement. This is a barrier to more widespread trial implementation.

PURPOSE/HYPOTHESIS

To determine the agreement between fat fraction (FF) measurements derived from 1) basic vendor-supplied sequences, 2) basic sequences with offline correction, and 3) specialist vendor-supplied methods.

STUDY TYPE

Prospective.

POPULATION

Two substudies with ten and five healthy volunteers.

FIELD STRENGTH/SEQUENCE

Site A: mDixon Quant (Philips 3T Ingenia); Site B: IDEAL and FLEX (GE 1.5T Optima MR450W); Site C: DIXON, with additional 5-echo gradient echo acquisition for offline correction (Siemens 3T Skyra); Site D: DIXON, with additional VIBE acquisitions for offline correction (Siemens 1.5T Avanto). The specialist method at site A was used as a standard to compare to the basic methods at sites B, C, and D.

ASSESSMENT

Regions of interest were placed on areas of subchondral bone on FF maps from the various methods in each volunteer.

STATISTICAL TESTS

Relationships between FF measurements from the various sites and Dixon methods were assessed using Bland-Altman analysis and linear regression.

RESULTS

Basic methods consisting of IDEAL, LAVA FLEX, and DIXON produced FF values that were linearly related to reference FF values (P < 0.0001), but produced mean biases of up to 10%. Offline correction produced a significant reduction in bias in both substudies (P < 0.001).

DATA CONCLUSION

FF measurements derived using basic vendor-supplied methods are strongly linearly related with those derived using specialist methods but produce a bias of up to 10%. A simple offline correction that is accessible even when the scanner has only basic sequence options can significantly reduce bias.

LEVEL OF EVIDENCE

2 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;52:298-306.

Magnetic Resonance Imaging Techniques for Brown Adipose Tissue Detection

Magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) methods can non-invasively assess brown adipose tissue (BAT) structure and function. Recently, MRI and MRS have been proposed as a means to differentiate BAT from white adipose tissue (WAT) and to extract morphological and functional information on BAT inaccessible by other means. Specifically, proton MR (¹H) techniques, such as proton density fat fraction mapping, diffusion imaging, and intermolecular multiple quantum coherence imaging, have been employed to access BAT microstructure; MR thermometry, relaxometry, and MRI and MRS with ³¹P, ²H, ¹³C, and ¹²⁹Xe have shown to provide complementary information on BAT function. The purpose of the present review is to provide a comprehensive overview of MR imaging and spectroscopy techniques used to detect BAT in rodents and in humans. The present work discusses common challenges of current methods and provides an outlook on possible future directions of using MRI and MRS in BAT studies.

Characterizing a short T2 * signal component in the liver using ultrashort TE chemical shift-encoded MRI at 1.5T and 3.0T

PURPOSE

Recent studies have suggested the presence of short-T₂ * signals in the liver, which may confound chemical shift-encoded (CSE) fat quantification when using short echo times (TEs). The purpose of this study was to characterize the liver signal at short echo times and to determine its impact on liver fat quantification.

METHODS

An ultrashort echo time (UTE) chemical shift-encoded MRI (CSE-MRI) technique and a multicomponent reconstruction were developed to characterize short-T₂ * liver signals. Subsequently, liver fat fraction was quantified using a short-TE (first TE = 0.7 ms) and UTE CSE-MRI acquisitions and compared with a standard CSE-MRI (first TE = 1.2 ms).

RESULTS

Short-T₂ * signals were consistently observed in the liver of all healthy volunteers imaged at both 1.5T and 3.0T. At 3.0T, short-T₂ * signal fractions of 9.6 ± 1.5%, 7.0 ± 1.7%, and 7.4 ± 1.7% with T₂ * of 0.23 ± 0.05 ms, 0.20 ± 0.05 ms, and 0.10 ± 0.02 ms were measured in healthy volunteers, patients with liver cirrhotic disease, and patients with hepatic steatosis (but no cirrhosis), respectively. For proton density fat fraction (PDFF) estimation, 1.7% (P < .01) and 3.4% (P < .01) biases were observed in subjects imaged using short-TE CSE-MRI and using UTE CSE-MRI at 1.5T, respectively. The biases were reduced to 0.4% and -0.7%, respectively, by excluding short echoes less than 1 ms. A 3.2% bias (P < .01) was observed in subjects imaged using UTE CSE-MRI at 3.0T, which was reduced to 0.1% by excluding short echoes <1 ms.

CONCLUSIONS

A liver short-T₂ * signal component was consistently observed and was shown to confound liver fat quantification when short echo times were used with CSE-MRI.

Hierarchical iterative linear-fitting algorithm (HILA) for phase correction in fat quantification by bipolar multi-echo sequence

Background

Multi-echo gradient echo (GRE) sequence with bipolar readout gradients can reduce achievable echo spacing and thus have higher acquisition efficiency compared to unipolar readout gradients for fat fraction (FF) quantification. However, the eddy current induced phase (EC-phase) in a bipolar sequence corrupts the phase consistency between echoes and can lead to inaccurate fat quantification.

Methods

A hierarchical iterative linear-fitting algorithm (HILA) was proposed for EC-phase correction. In each iteration, image blocks were divided into sub-blocks. The EC-phase was fitted to a linear model in each sub-block. The estimated linear phase in each sub-block was then used as a starting value for the next iteration. Finally, a weighted average over all levels was calculated to obtain the final EC-phase map. Monte Carlo simulations were adopted to evaluate how the residual EC-phase would affect FF quantification accuracy. The performance of the proposed HILA method was then compared to the well-established unipolar acquisition method in phantom and in vivo experiments on 3T.

Results

The simulations showed that certain ΔTE values, such as ΔTE =~0.80/1.50/1.95 ms, allowed for FF estimation that were relatively robust to the residual EC-phase ranging from -2π/15 to 2π/15 for a 6-echo bipolar acquisition on 3T. The phantom study showed that the maximum mean FF error, after EC-phase correction with the proposed HILA method, was smaller than 2%, implying that HILA can approximate the high-order term of the EC-phase through step-wise linear fitting. There was no significant difference between the FFs from bipolar and unipolar acquisitions on the two MR systems in the in vivo experiments.

Conclusions

The proposed HILA method provides a simple and efficient EC-phase correction method for bipolar acquisition without acquiring additional data. The appropriate choice of TEs may further reduce the effect of the residual EC-phase on accurate FF quantification with bipolar readout sequence.

Lipid nanocapsules as in vivo oxygen sensors using magnetic resonance imaging

Hypoxia is common occurrence of the tumour microenvironment, wherein heterogeneous gradients of O₂ give rise to tumoural cells which are highly malignant, metastatic, and resistant to therapeutic efforts. Thus, the assessment and imaging of hypoxia is essential for tumour diagnosis and treatment. Magnetic resonance imaging and, more specifically, the quantitative assessment of longitudinal relaxation time enhancement, was shown to enable the mapping of oxygen in tumours with increased sensitivity for lipids as compared to water signal. Unfortunately, this can only be applied to tumours with high lipid content. To overcome this issue, we propose the use of lipid nanocapsules (LNCs). LNCs have been demonstrated as excellent core-shell nanocarriers, wherein the lipidic-core is used for lipophilic drug encapsulation, enabling treatment of highly malignant tumours. Herein, however, we exploited the lipidic-core of the LNCs to develop a simple but effective technique to increase the lipidic content within tissues to enable the assessment and mapping of pO₂. LNCs were prepared using the phase-inversion technique to produce 60 nm sized nanoparticles, and in vitro studies demonstrated the permeability and responsiveness of LNCs to O₂. To evaluate the ability of LNCs to respond to changes in pO₂in vivo, after a hyperoxic challenge, three animal models, namely a normal tissue model (gastrocnemius muscle tissue) and two tumour tissue models (subcutaneous fibrosarcoma and intracerebral glioblastoma) were explored. LNCs were found to be responsive to variation of O₂in vivo. Moreover, the use of MRI enabled the mapping of oxygen gradients and heterogeneity within tumours.

Magnitude-intrinsic water-fat ambiguity can be resolved with multipeak fat modeling and a multipoint search method

Purpose

To develop a postprocessing algorithm for multiecho chemical‐shift encoded water–fat separation that estimates proton density fat fraction (PDFF) maps over the full dynamic range (0‐100%) using multipeak fat modeling and multipoint search optimization. To assess its accuracy, reproducibility, and agreement with state‐of‐the‐art complex‐based methods, and to evaluate its robustness to artefacts in abdominal PDFF maps.

Methods

We introduce MAGO (MAGnitude‐Only), a magnitude‐based reconstruction that embodies multipeak liver fat spectral modeling and multipoint optimization, and which is compatible with asymmetric echo acquisitions. MAGO is assessed first for accuracy and reproducibility on publicly available phantom data. Then, MAGO is applied to N = 178 UK Biobank cases, in which its liver PDFF measures are compared using Bland‐Altman analysis with those from a version of the hybrid iterative decomposition of water and fat with echo asymmetry and least squares estimation (IDEAL) algorithm, LiverMultiScan IDEAL (LMS IDEAL, Perspectum Diagnostics Ltd, Oxford, UK). Finally, MAGO is tested on a succession of high field challenging cases for which LMS IDEAL generated artefacts in the PDFF maps.

Results

Phantom data showed accurate, reproducible MAGO PDFF values across manufacturers, field strengths, and acquisition protocols. Moreover, we report excellent agreement between MAGO and LMS IDEAL for 6‐echo, 1.5 tesla human acquisitions (bias = −0.02% PDFF, 95% confidence interval = ±0.13% PDFF). When tested on 12‐echo, 3 tesla cases from different manufacturers, MAGO was shown to be more robust to artefacts compared to LMS IDEAL.

Conclusion

MAGO resolves the water–fat ambiguity over the entire fat fraction dynamic range without compromising accuracy, therefore enabling robust PDFF estimation where phase data is inaccessible or unreliable and complex‐based and hybrid methods fail.

Techniques and Applications of Magnetic Resonance Imaging for Studying Brown Adipose Tissue Morphometry and Function

The present review reports on the current knowledge and recent findings in magnetic resonance imaging (MRI) and spectroscopy (MRS) of brown adipose tissue (BAT). The work summarizes the features and mechanisms that allow MRI to differentiate BAT from white adipose tissue (WAT) by making use of their distinct morphological appearance and the functional characteristics of BAT. MR is a versatile imaging modality with multiple contrast mechanisms as potential candidates in the study of BAT, targeting properties of ¹H, ¹³C, or ¹²⁹Xe nuclei. Techniques for assessing BAT morphometry based on fat fraction and markers of BAT microstructure, including intermolecular quantum coherence and diffusion imaging, are first described. Techniques for assessing BAT function based on the measurement of BAT metabolic activity, perfusion, oxygenation, and temperature are then presented. The application of the above methods in studies of BAT in animals and humans is described, and future directions in MR study of BAT are finally discussed.

Accuracy and precision of proton density fat fraction measurement across field strengths and scan intervals: A phantom and human study

BACKGROUND

Complex-based chemical shift imaging-based magnetic resonance imaging (CSE-MRI) is emerging as a preferred method for noninvasively quantifying proton density fat fraction (PDFF), a promising quantitative imaging biomarker (QIB) for longitudinal hepatic steatosis measurement.

PURPOSE

To determine linearity, bias, repeatability, and reproducibility of the PDFF measurement using CSE-MRI (CSE-PDFF) across scan intervals, MR field strengths, and readers in phantom and nonalcoholic fatty liver disease (NAFLD) patients.

STUDY TYPE

Institutional Review Board (IRB)-approved prospective.

SUBJECTS

Fat-water phantom and 20 adult patients.

FIELD STRENGTH/SEQUENCE

1.5 T and 3.0 T MR systems and a commercially available CSE-MRI sequence (IDEAL-IQ).

ASSESSMENT

Two independent readers measured CSE-PDFF of fat-water phantom and NAFLD patients across two field strengths and scan intervals (same-day and 2-week) each and in a combination of both. MR spectroscopy-based PDFF (MRS-PDFF) was used as the reference standard for phantom PDFF.

STATISTICAL TESTS

Linearity and bias of measurement were evaluated by linear regression analysis and Bland-Altman plots, respectively. Repeatability and reproducibility were assessed by coefficient of variance and repeatability / reproducibility coefficients (RC). The intraclass correlation coefficient was used to validate intra- and interobserver agreements.

RESULTS

CSE-PDFF showed high linearity and small bias (-0.6-0.4 PDFF%) with 95% limits of agreement within ±2.9 PDFF% across field strengths, 2-week interscan period, and readers in the clinical scans. CSE-PDFF was highly repeatable and reproducible both in phantom and clinical scans, with the largest observed RC across field strengths and 2-week interscan period being 3 PDFF%.

DATA CONCLUSION

CSE-PDFF is a robust QIB with high linearity, small bias, and excellent repeatability/reproducibility. A change of more than 3 PDFF% across field strengths within 2 weeks of scan interval likely reflects a true change, which is well within the clinically acceptable range.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:305-314.

Effect of microscopic susceptibility gradients on chemical-shift-based fat fraction quantification in supraclavicular fat

BACKGROUND

Susceptibility differences between fat and water can cause changes in the water-fat frequency separation that can negatively affect the accuracy of fat fraction techniques. This may be especially relevant for brown adipose tissue, as MRI fat fraction techniques have been proposed for its detection.

PURPOSE

To assess the effect of microscopic magnetic susceptibility gradients on the water-fat frequency separation and its impact on chemical-shift-based fat fraction quantification techniques in the supraclavicular fat, where brown adipose tissue is commonly found in humans.

STUDY TYPE

Prospective.

POPULATION/SUBJECTS/PHANTOM/SPECIMEN/ANIMAL MODEL

Subjects: 11 healthy volunteers, mean age of 26 and mean BMI of 23, three overweight volunteers, mean age of 38 and mean BMI of 33. Phantoms: bovine phantom and intralipid fat emulsion. Simulations: various water-fat distributions.

FIELD STRENGTH/SEQUENCE

Six-echo gradient echo chemical-shift-encoded sequence at 3T.

ASSESSMENT

Fat fraction values as obtained from a water-fat spectral model accounting for susceptibility-induced water-fat frequency variations were directly compared to traditional spectral models that assume constant water-fat frequency separation.

STATISTICAL TESTS

Two-tail t-tests were used for significance testing (p < 0.05.) A Bayesian Information Criterion difference of 6 between fits was taken as strong evidence of an improved model.

RESULTS

Phantom experiments and simulation results showed variations of the water-fat frequency separation up to 0.4 ppm and 0.6 ppm, respectively. In the supraclavicular area, the water-fat frequency separation produced by magnetic susceptibility gradients varied by as much as ±0.4 ppm, with a mean of 0.08 ± 0.14 ppm, producing a mean difference in fat fraction of -1.26 ± 5.26%.

DATA CONCLUSION

In the supraclavicular fat depot, microscopic susceptibility gradients that exist within a voxel between water and fat compartments can produce variations in the water-fat frequency separation. These variations may produce fat fraction quantification errors of 5% when a spectral model with a fixed water-fat frequency separation is applied, which could impact MR brown fat techniques.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2019;49:141-151.

Dual-step iterative temperature estimation method for accurate and precise fat-referenced PRFS temperature imaging

PURPOSE

The aim of this study was to propose dual-step iterative temperature estimation (DITE) of a fat-referenced proton resonance frequency shift (PRFS) method to improve both the accuracy and precision of temperature estimations in fat-containing tissues.

METHODS

A fat-water signal model with multiple fat peaks was used to simultaneously estimate the temperature, fat/water intensity and <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msubsup><mml:mtext>T</mml:mtext> <mml:mrow><mml:mn>2</mml:mn></mml:mrow> <mml:mrow><mml:mrow/> <mml:mo>∗</mml:mo></mml:mrow> </mml:msubsup> </mml:math> , and field offset. In DITE, model fitting was implemented with alternating 2-step minimizations. The estimated temperature map was smoothed between the 2-step minimizations, which is considered to be the most important step for improving the temperature precision. The performance of DITE was evaluated with a Monte Carlo simulation, fat/water phantoms, and ex vivo brown adipose tissue experiments and then compared with the performance of previous fat-referenced proton resonance frequency shift methods.

RESULTS

In fat/water phantom experiment with a smooth temperature profile, the temperatures estimated by DITE are consistent with the thermometer results and present a better accuracy and precision than those of previous fat-referenced proton resonance frequency shift methods. In the brown adipose tissue heating experiment, the average mean error, SD, and RMS error were -0.08ºC, 0.46ºC, and 0.56ºC, respectively, over all of the measurements within the region of interest.

CONCLUSION

Our proposed DITE method improves both the accuracy and precision of temperature measurements in tissues with fat fractions between 20% and 80% under smooth distribution of the temperature profile and represents a simple fat-referenced thermometry method.

Calibration of methylene-referenced lipid-dissolved xenon frequency for absolute MR temperature measurements

PURPOSE

Absolute MR temperature measurements are currently difficult because they require precalibration procedures specific for tissue types and conditions. Reference of the lipid-dissolved ¹²⁹ Xe resonance frequency to temperature-insensitive methylene protons (rLDX) has been proposed to remove the effect of macro- and microscopic susceptibility gradients to obtain absolute temperature information. The scope of this work is to evaluate the rLDX chemical shift (CS) dependence on lipid composition to estimate the precision of absolute temperature measurements in lipids.

METHODS

Neat triglycerides, vegetable oils, and samples of freshly excised human and rodent adipose tissue (AT) are prepared under ¹²⁹ Xe atmosphere and studied using high-resolution NMR. The rLDX CS is measured as a function of temperature. ¹ H spectra are also acquired and the consistency of methylene-referenced water proton and rLDX CS values are compared in human AT.

RESULTS

Although rLDX CS shows a dependence on lipid composition, in human and rodent AT samples the rLDX shows consistent CS values with a similar temperature dependence (-0.2058 ± 0.0010) ppm/°C × T (°C) + (200.15 ± 0.03) ppm, enabling absolute temperature measurements with an accuracy of 0.3°C. Methylene-referenced water CS values present variations of up to 4°C, even under well-controlled conditions.

CONCLUSIONS

The rLDX can be used to obtain accurate absolute temperature measurements in AT, opening new opportunities for hyperpolarized ¹²⁹ Xe MR to measure tissue absolute temperature.

Water-fat magnetic resonance imaging quantifies relative proportions of brown and white adipose tissues: ex-vivo experiments

Quantifying the amount of brown adipose tissue (BAT) within white adipose tissue (WAT) in human depots may serve as a target to combat obesity. We aimed to quantify proton density fat fraction (PDFF) of BAT and WAT in relatively pure and in mixed preparation using water–fat imaging. Three ex-vivo experiments were performed at 3 T using excised interscapular BAT and inguinal/subcutaneous WAT from mice. The first two experiments consisted of BAT and WAT in separate tubes, and the third used mixed preparation with graded quantities of BAT and WAT. To investigate the influence of partial volume on PDFF metrics, low (2.66  mm3) and high spatial resolution (0.55  mm3 acquired voxels) in two orthogonal three-dimensional sections were compared. The low-resolution acquisitions are corrected for T2* and multipeak lipid spectrum, thus considered “quantitative,” whereas the high-resolution acquisitions are not corrected but were performed to better spatially segment BAT from WAT zones. As potential BAT metrics, we quantified the average PDFF and the volume of tissue having PDFF ≤50% (VOLPDFF≤50%) based on the PDFF histogram. In the first experiment, the average PDFF of BAT was 23±6% and 21±7.6% and the average PDFF of WAT was 76±7% and 87±7% using high- and low-resolution techniques, respectively. A similar trend with excellent reproducibility in average PDFF of BAT and WAT was observed in the second experiment. In the third experiment over the four acquisitions, the BAT-dominant tube demonstrated lower PDFF (mean ± SD) of 55±2% than WAT-dominant (69±4%) and WAT-only tubes (88±4%). Estimating VOLPDFF≤50%, the BAT-dominant tube demonstrated higher volume of 0.26  cm3 than WAT-dominant (0.16  cm3) and WAT-only tubes (0.01  cm3). The presence of BAT exhibits a lower PDFF relative to WAT, thus allowing segmentation of low PDFF tissue for quantification of volume representative of BAT. Future studies will determine the clinical relevance of BAT volume within human depots.

Longitudinal assessment of marrow fat content using three-point Dixon technique in osteoporotic rabbits

OBJECTIVE

In this longitudinal pilot study, we aimed to investigate the intra-, interobserver, and scan-rescan reproducibility of marrow fat fraction (FF) measurements using three-point Dixon imaging in osteoporotic rabbits: comparison with histopathology.

METHODS

Twenty female rabbits were randomly assigned to sham-operation and ovariectomy in combination with daily methylprednisolone hemisuccinate groups (n = 10 per group). Marrow FF by three-point Dixon technique and bone density by dual-energy x-ray absorptiometry were assessed at baseline, 6 and 12 weeks after operation. Intra-, inter-reader, and scan-rescan reliability of FF measurements were evaluated using intraclass correlation coefficient (ICC) and Bland-Altman 95% limit of agreement. Histomorphometry was performed to quantify marrow adipocyte parameters.

RESULTS

Intra- and inter-reader reproducibility of FF measurements was "substantial" (ICC = 0.984 and 0.978, respectively). Although the ICC for scan-rescan reliability was excellent (ICC = 0.962), increased measurement variability was observed using Bland-Altman plot. Relative to the sham-operated rabbits, the adipocytes mean diameter, density, and percent adipocytes area in the osteoporotic rabbits increased by 23.4%, 68.9%, and 117.0%, respectively. Marrow FF was positively correlated with the quantitative parameters of adipocytes, particularly with percent adipocyte area, but inversely associated with bone density. At the relatively early stage, the percentage of bone loss was similar to that of elevated fatty marrow in the osteoporotic rabbits; at the later stage, the change for the latter outweighed that of the former.

CONCLUSIONS

Results of three-point Dixon technique demonstrated a very reproducible manner within and between observers and acceptable scan-rescan performance in the assessment of marrow fat in rabbits.

A data-oriented self-calibration and robust chemical-shift encoding by using clusterization (OSCAR): Theory, optimization and clinical validation in neuromuscular disorders

Multi-echo Chemical Shift-Encoded (CSE) methods for Fat-Water quantification are growing in clinical use due to their ability to estimate and correct some confounding effects. State of the art CSE water/fat separation approaches rely on a multi-peak fat spectrum with peak frequencies and relative amplitudes kept constant over the entire MRI dataset. However, the latter approximation introduces a systematic error in fat percentage quantification in patients where the differences in lipid chemical composition are significant (such as for neuromuscular disorders) because of the spatial dependence of the peak amplitudes. The present work aims to overcome this limitation by taking advantage of an unsupervised clusterization-based approach offering a reliable criterion to carry out a data-driven segmentation of the input MRI dataset into multiple regions. Results established that the presented algorithm is able to identify at least 4 different partitions from MRI dataset under which to perform independent self-calibration routines and was found robust in NMD imaging studies (as evaluated on a cohort of 24 subjects) against latest CSE techniques with either calibrated or non-calibrated approaches. Particularly, the PDFF of the thigh was more reproducible for the quantitative estimation of pathological muscular fat infiltrations, which may be promising to evaluate disease progression in clinical practice.

Simultaneous Quantification of Bone Edema/Adiposity and Structure in Inflamed Bone Using Chemical Shift-Encoded MRI in Spondyloarthritis

Purpose

To evaluate proton density fat fraction (PDFF) and R2* as markers of bone marrow composition and structure in inflamed bone in patients with spondyloarthritis.

Methods

Phantoms containing fat, water, and trabecular bone were constructed with proton density fat fraction (PDFF) and bone mineral density (BMD) values matching those expected in healthy bone marrow and disease states, and scanned using chemical shift‐encoded MRI (CSE‐MRI) at 3T. Measured PDFF and R2* values in phantoms were compared with reference FF and BMD values. Eight spondyloarthritis patients and 10 controls underwent CSE‐MRI of the sacroiliac joints. PDFF and R2* in areas of inflamed bone and fat metaplasia in patients were compared with normal bone marrow in controls.

Results

In phantoms, PDFF measurements were accurate over the full range of PDFF and BMD values. R2* measurements were positively associated with BMD but also were influenced by variations in PDFF. In patients, PDFF was reduced in areas of inflammation and increased in fat metaplasia compared to normal marrow. R2* measurements were significantly reduced in areas of fat metaplasia.

Conclusion

PDFF measurements reflect changes in marrow composition in areas of active inflammation and structural damage and could be used for disease monitoring in spondyloarthritis. R2* measurements may provide additional information bone mineral density but also are influenced by fat content. Magn Reson Med 79:1031–1042, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Quantitative MRI and spectroscopy of bone marrow

Bone marrow is one of the largest organs in the human body, enclosing adipocytes, hematopoietic stem cells, which are responsible for blood cell production, and mesenchymal stem cells, which are responsible for the production of adipocytes and bone cells. Magnetic resonance imaging (MRI) is the ideal imaging modality to monitor bone marrow changes in healthy and pathological states, thanks to its inherent rich soft‐tissue contrast. Quantitative bone marrow MRI and magnetic resonance spectroscopy (MRS) techniques have been also developed in order to quantify changes in bone marrow water–fat composition, cellularity and perfusion in different pathologies, and to assist in understanding the role of bone marrow in the pathophysiology of systemic diseases (e.g. osteoporosis). The present review summarizes a large selection of studies published until March 2017 in proton‐based quantitative MRI and MRS of bone marrow. Some basic knowledge about bone marrow anatomy and physiology is first reviewed. The most important technical aspects of quantitative MR methods measuring bone marrow water–fat composition, fatty acid composition, perfusion, and diffusion are then described. Finally, previous MR studies are reviewed on the application of quantitative MR techniques in both healthy aging and diseased bone marrow affected by osteoporosis, fractures, metabolic diseases, multiple myeloma, and bone metastases.

Level of Evidence: 3

Technical Efficacy: Stage 2

J. Magn. Reson. Imaging 2018;47:332–353.

Measurement of vertebral bone marrow proton density fat fraction in children using quantitative water-fat MRI

OBJECTIVES

To investigate the feasibility of employing a 3D time-interleaved multi-echo gradient-echo (TIMGRE) sequence to measure the proton density fat fraction (PDFF) in the vertebral bone marrow (VBM) of children and to examine cross-sectional changes with age and intra-individual variations from the lumbar to the cervical region in the first two decades of life.

MATERIALS AND METHODS

Quantitative water-fat imaging of the spine was performed in 93 patients (49 girls; 44 boys; age median 4.5 years; range 0.1-17.6 years). For data acquisition, a six-echo 3D TIMGRE sequence was used with phase correction and complex-based water-fat separation. Additionally, single-voxel MR spectroscopy (MRS) was performed in the L4 vertebrae of 37 patients. VBM was manually segmented in the midsagittal slice of each vertebra. Univariable and multivariable linear regression models were calculated between averaged lumbar, thoracic and cervical bone marrow PDFF and age with adjustments for sex, height, weight, and body mass index percentile.

RESULTS

Measured VBM PDFF correlated strongly between imaging and MRS (R ² = 0.92, slope = 0.94, intercept = -0.72%). Lumbar, thoracic and cervical VBM PDFF correlated significantly (all p < 0.001) with the natural logarithm of age. Differences between female and male patients were not significant (p > 0.05).

CONCLUSION

VBM development in children showed a sex-independent cross-sectional increase of PDFF correlating with the natural logarithm of age and an intra-individual decrease of PDFF from the lumbar to the cervical region in all age groups. The present results demonstrate the feasibility of using a 3D TIMGRE sequence for PDFF assessment in VBM of children.

High SNR Acquisitions Improve the Repeatability of Liver Fat Quantification Using Confounder-corrected Chemical Shift-encoded MR Imaging

PURPOSE

To determine whether high signal-to-noise ratio (SNR) acquisitions improve the repeatability of liver proton density fat fraction (PDFF) measurements using confounder-corrected chemical shift-encoded magnetic resonance (MR) imaging (CSE-MRI).

MATERIALS AND METHODS

Eleven fat-water phantoms were scanned with 8 different protocols with varying SNR. After repositioning the phantoms, the same scans were repeated to evaluate the test-retest repeatability. Next, an in vivo study was performed with 20 volunteers and 28 patients scheduled for liver magnetic resonance imaging (MRI). Two CSE-MRI protocols with standard- and high-SNR were repeated to assess test-retest repeatability. MR spectroscopy (MRS)-based PDFF was acquired as a standard of reference. The standard deviation (SD) of the difference (Δ) of PDFF measured in the two repeated scans was defined to ascertain repeatability. The correlation between PDFF of CSE-MRI and MRS was calculated to assess accuracy. The SD of Δ and correlation coefficients of the two protocols (standard- and high-SNR) were compared using F-test and t-test, respectively. Two reconstruction algorithms (complex-based and magnitude-based) were used for both the phantom and in vivo experiments.

RESULTS

The phantom study demonstrated that higher SNR improved the repeatability for both complex- and magnitude-based reconstruction. Similarly, the in vivo study demonstrated that the repeatability of the high-SNR protocol (SD of Δ = 0.53 for complex- and = 0.85 for magnitude-based fit) was significantly higher than using the standard-SNR protocol (0.77 for complex, P < 0.001; and 0.94 for magnitude-based fit, P = 0.003). No significant difference was observed in the accuracy between standard- and high-SNR protocols.

CONCLUSION

Higher SNR improves the repeatability of fat quantification using confounder-corrected CSE-MRI.

A pilot study on the correlation between fat fraction values and glucose uptake values in supraclavicular fat by simultaneous PET/MRI

PURPOSE

To assess the spatial correlation between MRI and 18F-fludeoxyglucose positron emission tomography (FDG-PET) maps of human brown adipose tissue (BAT) and to measure differences in fat fraction (FF) between glucose avid and non-avid regions of the supraclavicular fat depot using a hybrid FDG-PET/MR scanner.

METHODS

In 16 healthy volunteers, mean age of 30 and body mass index of 26, FF, R2*, and FDG uptake maps were acquired simultaneously using a hybrid PET/MR system while employing an individualized cooling protocol to maximally stimulate BAT.

RESULTS

Fourteen of the 16 volunteers reported BAT-positive FDG-PET scans. MR FF maps of BAT correlate well with combined FDG-PET/MR maps of BAT only in subjects with intense glucose uptake. The results indicate that the extent of the spatial correlation positively correlates with maximum FDG uptake in the supraclavicular fat depot. No consistent, significant differences were found in FF or R2* between FDG avid and non-avid supraclavicular fat regions. In a few FDG-positive subjects, a small but significant linear decrease in BAT FF was observed during BAT stimulation.

CONCLUSION

MR FF, when used in conjunction with FDG uptake maps, can be seen as a valuable, radiation-free alternative to CT and can be used to measure tissue hydration and lipid consumption in some subjects. Magn Reson Med 78:1922-1932, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Correction of phase errors in quantitative water-fat imaging using a monopolar time-interleaved multi-echo gradient echo sequence

PURPOSE

To propose a phase error correction scheme for monopolar time-interleaved multi-echo gradient echo water-fat imaging that allows accurate and robust complex-based quantification of the proton density fat fraction (PDFF).

METHODS

A three-step phase correction scheme is proposed to address a) a phase term induced by echo misalignments that can be measured with a reference scan using reversed readout polarity, b) a phase term induced by the concomitant gradient field that can be predicted from the gradient waveforms, and c) a phase offset between time-interleaved echo trains. Simulations were carried out to characterize the concomitant gradient field-induced PDFF bias and the performance estimating the phase offset between time-interleaved echo trains. Phantom experiments and in vivo liver and thigh imaging were performed to study the relevance of each of the three phase correction steps on PDFF accuracy and robustness.

RESULTS

The simulation, phantom, and in vivo results showed in agreement with the theory an echo time-dependent PDFF bias introduced by the three phase error sources. The proposed phase correction scheme was found to provide accurate PDFF estimation independent of the employed echo time combination.

CONCLUSION

Complex-based time-interleaved water-fat imaging was found to give accurate and robust PDFF measurements after applying the proposed phase error correction scheme. Magn Reson Med 78:984-996, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Characterizing active and inactive brown adipose tissue in adult humans using PET-CT and MR imaging

Activated brown adipose tissue (BAT) plays an important role in thermogenesis and whole body metabolism in mammals. Positron emission tomography (PET)-computed tomography (CT) imaging has identified depots of BAT in adult humans, igniting scientific interest. The purpose of this study is to characterize both active and inactive supraclavicular BAT in adults and compare the values to those of subcutaneous white adipose tissue (WAT). We obtained [(18)F]fluorodeoxyglucose ([(18)F]FDG) PET-CT and magnetic resonance imaging (MRI) scans of 25 healthy adults. Unlike [(18)F]FDG PET, which can detect only active BAT, MRI is capable of detecting both active and inactive BAT. The MRI-derived fat signal fraction (FSF) of active BAT was significantly lower than that of inactive BAT (means ± SD; 60.2 ± 7.6 vs. 62.4 ± 6.8%, respectively). This change in tissue morphology was also reflected as a significant increase in Hounsfield units (HU; -69.4 ± 11.5 vs. -74.5 ± 9.7 HU, respectively). Additionally, the CT HU, MRI FSF, and MRI R2* values are significantly different between BAT and WAT, regardless of the activation status of BAT. To the best of our knowledge, this is the first study to quantify PET-CT and MRI FSF measurements and utilize a semiautomated algorithm to identify inactive and active BAT in the same adult subjects. Our findings support the use of these metrics to characterize and distinguish between BAT and WAT and lay the foundation for future MRI analysis with the hope that some day MRI-based delineation of BAT can stand on its own.

Multisite, multivendor validation of the accuracy and reproducibility of proton-density fat-fraction quantification at 1.5T and 3T using a fat-water phantom

PURPOSE

To evaluate the accuracy and reproducibility of quantitative chemical shift-encoded (CSE) MRI to quantify proton-density fat-fraction (PDFF) in a fat-water phantom across sites, vendors, field strengths, and protocols.

METHODS

Six sites (Philips, Siemens, and GE Healthcare) participated in this study. A phantom containing multiple vials with various oil/water suspensions (PDFF:0%-100%) was built, shipped to each site, and scanned at 1.5T and 3T using two CSE protocols per field strength. Confounder-corrected PDFF maps were reconstructed using a common algorithm. To assess accuracy, PDFF bias and linear regression with the known PDFF were calculated. To assess reproducibility, measurements were compared across sites, vendors, field strengths, and protocols using analysis of covariance (ANCOVA), Bland-Altman analysis, and the intraclass correlation coefficient (ICC).

RESULTS

PDFF measurements revealed an overall absolute bias (across sites, field strengths, and protocols) of 0.22% (95% confidence interval, 0.07%-0.38%) and R²  > 0.995 relative to the known PDFF at each site, field strength, and protocol, with a slope between 0.96 and 1.02 and an intercept between -0.56% and 1.13%. ANCOVA did not reveal effects of field strength (P = 0.36) or protocol (P = 0.19). There was a significant effect of vendor (F = 25.13, P = 1.07 × 10^-10 ) with a bias of -0.37% (Philips) and -1.22% (Siemens) relative to GE Healthcare. The overall ICC was 0.999.

CONCLUSION

CSE-based fat quantification is accurate and reproducible across sites, vendors, field strengths, and protocols. Magn Reson Med 77:1516-1524, 2017. © 2016 International Society for Magnetic Resonance in Medicine.

Modeling of T2* decay in vertebral bone marrow fat quantification

Bone marrow fat fraction mapping using chemical shift encoding-based water-fat separation is becoming a useful tool in investigating the association between bone marrow adiposity and bone health and in assessing cancer treatment-induced bone marrow damage. Vertebral bone marrow is characterized by short T2* relaxation times, which are in general different for the water and fat components and can confound fat quantification. The purpose of the present study is to compare different approaches to T2* correction in chemical shift encoding-based water-fat imaging of vertebral bone marrow using single-voxel MRS as reference. Eight-echo gradient-echo imaging and single-voxel MRS measurements were made on the spine (L3-L5) of 25 healthy volunteers. Different approaches were evaluated for correction of T2* effects: (a) single-T2* correction, (b) dual-T2* correction, (c) T2' correction using the a priori-known T2 from the MRS at each vertebral body and (d) T2' correction using the a priori-known T2 equal to previously measured average values. Dual-T2* correction resulted in noisier imaging fat fraction maps than single-T2* correction or T2' correction using a priori-known T2. Linear regression analysis between imaging and MRS fat fraction showed a slope significantly different from 1 when using single-T2* correction (R(2) = 0.96) or dual-T2* correction (R(2) = 0.87). T2' correction using the a priori-known T2 resulted in a slope not significantly different from 1, an intercept significantly different from 0 (between 2.4% and 3%) and R(2) = 0.96. Therefore, a T2' correction using a priori-known T2 can remove the fat fraction bias induced by the difference in T2* between water and fat components without degrading noise performance in fat fraction mapping of vertebral bone marrow.

Quantitative magnetic resonance imaging of hepatic steatosis: Validation in ex vivo human livers

Emerging magnetic resonance imaging (MRI) biomarkers of hepatic steatosis have demonstrated tremendous promise for accurate quantification of hepatic triglyceride concentration. These methods quantify the proton density fat-fraction (PDFF), which reflects the concentration of triglycerides in tissue. Previous in vivo studies have compared MRI-PDFF with histologic steatosis grading for assessment of hepatic steatosis. However, the correlation of MRI-PDFF with the underlying hepatic triglyceride content remained unknown. The aim of this ex vivo study was to validate the accuracy of MRI-PDFF as an imaging biomarker of hepatic steatosis. Using ex vivo human livers, we compared MRI-PDFF with magnetic resonance spectroscopy-PDFF (MRS-PDFF), biochemical triglyceride extraction, and histology as three independent reference standards. A secondary aim was to compare the precision of MRI-PDFF relative to biopsy for the quantification of hepatic steatosis. MRI-PDFF was prospectively performed at 1.5 Tesla in 13 explanted human livers. We performed colocalized paired evaluation of liver fat content in all nine Couinaud segments using single-voxel MRS-PDFF (n=117) and tissue wedges for biochemical triglyceride extraction (n=117), and five core biopsies performed in each segment for histologic grading (n=585). Accuracy of MRI-PDFF was assessed through linear regression with MRS-PDFF, triglyceride extraction, and histology. Intraobserver agreement, interobserver agreement, and repeatability of MRI-PDFF and histologic grading were assessed through Bland-Altman analyses. MRI-PDFF showed an excellent correlation with MRS-PDFF (r=0.984, confidence interval 0.978-0.989) and strong correlation with histology (r=0.850, confidence interval 0.791-0.894) and triglyceride extraction (r=0.871, confidence interval 0.818-0.909). Intraobserver agreement, interobserver agreement, and repeatability showed a significantly smaller variance for MRI-PDFF than for histologic steatosis grading (all P<0.001).

CONCLUSION

MRI-PDFF is an accurate, precise, and reader-independent noninvasive imaging biomarker of liver triglyceride content, capable of steatosis quantification over the entire liver.

Quantification of mass fat fraction in fish using water-fat separation MRI

Selection of fish with appropriate fat content and anatomic distribution is searched in fish industry. This necessitates fast and accurate measurements of mass fat fraction maps on a large number of fish. The objective of this work is to assess the relevance of MRI water-fat separation for this purpose. For the separation of the water and fat images we rely on a single T2(⁎) and a multiple peak fat spectrum model, the parameters of which are estimated using the "Varpro" method. The difference of proton density between fat and water and the lack of the signal from the macromolecules are taken into account to convert the obtained proton density fat fraction into mass fat fraction. We used 0.23T NMR to validate the method on 30 salmon steaks. The fat fraction values were in the range of 5% to 25%. Very good accordance was found between 1.5T MRI and NMR although MRI slightly overestimated the mass fat fraction. The R(2) of the linear regression was equal to 0.96 (P<10(-5)), the slope to 1.12 (CI.95=0.03). These results demonstrate that a good accuracy can be achieved. We also show that high throughput can be achieved since the measurements do not depend on the position and we conclude that, for example, it is feasible to quantify the mass fat fraction in fish steaks within about one minute per sample.

Characterization of the ultrashort-TE (UTE) MR collagen signal

Although current cardiovascular MR (CMR) techniques for the detection of myocardial fibrosis have shown promise, they nevertheless depend on gadolinium-based contrast agents and are not specific to collagen. In particular, the diagnosis of diffuse myocardial fibrosis, a precursor of heart failure, would benefit from a non-invasive imaging technique that can detect collagen directly. Such a method could potentially replace the need for endomyocardial biopsy, the gold standard for the diagnosis of the disease. The objective of this study was to measure the MR properties of collagen using ultrashort TE (UTE), a technique that can detect short T2* species. Experiments were performed in collagen solutions. Via a model of bi-exponential T2* with oscillation, a linear relationship (slope = 0.40 ± 0.01, R(2) = 0.99696) was determined between the UTE collagen signal fraction associated with these properties and the measured collagen concentration in solution. The UTE signal of protons in the collagen molecule was characterized as having a mean T2* of 0.75 ± 0.05 ms and a mean chemical shift of -3.56 ± 0.01 ppm relative to water at 7 T. The results indicated that collagen can be detected and quantified using UTE. A knowledge of the collagen signal properties could potentially be beneficial for the endogenous detection of myocardial fibrosis.