R2* estimation using "in-phase" echoes in the presence of fat: the effects of complex spectrum of fat

Multiparametric MR assessment of liver fat, iron, and fibrosis: a concise overview of the liver "Triple Screen"

Chronic liver disease (CLD) is a common source of morbidity and mortality worldwide. Non-alcoholic fatty liver disease (NAFLD) serves as a major cause of CLD with a rising annual prevalence. Additionally, iron overload can be both a cause and effect of CLD with a negative synergistic effect when combined with NAFLD. The development of state-of-the-art multiparametric MR solutions has led to a change in the diagnostic paradigm in CLD, shifting from traditional liver biopsy to innovative non-invasive methods for providing accurate and reliable detection and quantification of the disease burden. Novel imaging biomarkers such as MRI-PDFF for fat, R2 and R2* for iron, and liver stiffness for fibrosis provide important information for diagnosis, surveillance, risk stratification, and treatment. In this article, we provide a concise overview of the MR concepts and techniques involved in the detection and quantification of liver fat, iron, and fibrosis including their relative strengths and limitations and discuss a practical abbreviated MR protocol for clinical use that integrates these three MR biomarkers into a single simplified MR assessment. Multiparametric MR techniques provide accurate and reliable non-invasive detection and quantification of liver fat, iron, and fibrosis. These techniques can be combined in a single abbreviated MR "Triple Screen" assessment to offer a more complete metabolic imaging profile of CLD.

Quantification of Liver Iron Overload with MRI: Review and Guidelines from the ESGAR and SAR

Accumulation of excess iron in the body, or systemic iron overload, results from a variety of causes. The concentration of iron in the liver is linearly related to the total body iron stores and, for this reason, quantification of liver iron concentration (LIC) is widely regarded as the best surrogate to assess total body iron. Historically assessed using biopsy, there is a clear need for noninvasive quantitative imaging biomarkers of LIC. MRI is highly sensitive to the presence of tissue iron and has been increasingly adopted as a noninvasive alternative to biopsy for detection, severity grading, and treatment monitoring in patients with known or suspected iron overload. Multiple MRI strategies have been developed in the past 2 decades, based on both gradient-echo and spin-echo imaging, including signal intensity ratio and relaxometry strategies. However, there is a general lack of consensus regarding the appropriate use of these methods. The overall goal of this article is to summarize the current state of the art in the clinical use of MRI to quantify liver iron content and to assess the overall level of evidence of these various methods. Based on this summary, expert consensus panel recommendations on best practices for MRI-based quantification of liver iron are provided.

On the water-fat in-phase assumption for quantitative susceptibility mapping

PURPOSE

To (a) define multi-peak fat model-based effective in-phase echo times for quantitative susceptibility mapping (QSM) in water-fat regions, (b) analyze the relationship between fat fraction, field map quantification bias and susceptibility bias, and (c) evaluate the susceptibility mapping performance of the proposed effective in-phase echoes in comparison to single-peak in-phase echoes and water-fat separation for regions where both water and fat are present.

METHODS

Effective multipeak in-phase echo times for a bone marrow and a liver fat spectral model were derived from a single voxel simulation. A Monte Carlo simulation was performed to assess the field map estimation error as a function of fat fraction for the different in-phase echoes. Additionally, a phantom scan and in vivo scans in the liver, spine, and breast were performed and evaluated with respect to quantification accuracy.

RESULTS

The use of single-peak in-phase echoes can introduce a worst-case susceptibility bias of 0.43 $$ 0.43 $$  ppm. The use of effective multipeak in-phase echoes shows a similar quantitative performance in the numerical simulation, the phantom and in all in vivo anatomies when compared to water-fat separation-based QSM.

CONCLUSION

QSM based on the proposed effective multipeak in-phase echoes can alleviate the quantification bias present in QSM based on single-peak in-phase echoes. When compared to water-fat separation-based QSM the proposed effective in-phase echo times achieve a similar quantitative performance while drastically reducing the computational expense for field map estimation.

MAGORINO: Magnitude-only fat fraction and R* 2 estimation with Rician noise modeling

PURPOSE

Magnitude-based fitting of chemical shift-encoded data enables proton density fat fraction (PDFF) and R 2 * $$ {R}_2^{\ast } $$ estimation where complex-based methods fail or when phase data are inaccessible or unreliable. However, traditional magnitude-based fitting algorithms do not account for Rician noise, creating a source of bias. To address these issues, we propose an algorithm for magnitude-only PDFF and R 2 * $$ {R}_2^{\ast } $$ estimation with Rician noise modeling (MAGORINO).

METHODS

Simulations of multi-echo gradient-echo signal intensities are used to investigate the performance and behavior of MAGORINO over the space of clinically plausible PDFF, R 2 * $$ {R}_2^{\ast } $$ , and SNR values. Fitting performance is assessed through detailed simulation, including likelihood function visualization, and in a multisite, multivendor, and multi-field-strength phantom data set and in vivo.

RESULTS

Simulations show that Rician noise-based magnitude fitting outperforms existing Gaussian noise-based fitting and reveals two key mechanisms underpinning the observed improvement. First, the likelihood functions exhibit two local optima; Rician noise modeling increases the chance that the global optimum corresponds to the ground truth. Second, when the global optimum corresponds to ground truth for both noise models, the optimum from Rician noise modeling is closer to ground truth. Multisite phantom experiments show good agreement of MAGORINO PDFF with reference values, and in vivo experiments replicate the performance benefits observed in simulation.

CONCLUSION

The MAGORINO algorithm reduces Rician noise-related bias in PDFF and R 2 * $$ {R}_2^{\ast } $$ estimation, thus addressing a key limitation of existing magnitude-only fitting methods. Our results offer insight into the importance of the noise model for selecting the correct optimum when multiple plausible optima exist.

SHIP-MR and Radiology: 12 Years of Whole-Body Magnetic Resonance Imaging in a Single Center

The Study of Health in Pomerania (SHIP), a population-based study from a rural state in northeastern Germany with a relatively poor life expectancy, supplemented its comprehensive examination program in 2008 with whole-body MR imaging at 1.5 T (SHIP-MR). We reviewed more than 100 publications that used the SHIP-MR data and analyzed which sequences already produced fruitful scientific outputs and which manuscripts have been referenced frequently. Upon reviewing the publications about imaging sequences, those that used T1-weighted structured imaging of the brain and a gradient-echo sequence for R2* mapping obtained the highest scientific output; regarding specific body parts examined, most scientific publications focused on MR sequences involving the brain and the (upper) abdomen. We conclude that population-based MR imaging in cohort studies should define more precise goals when allocating imaging time. In addition, quality control measures might include recording the number and impact of published work, preferably on a bi-annual basis and starting 2 years after initiation of the study. Structured teaching courses may enhance the desired output in areas that appear underrepresented.

Development, validation, qualification, and dissemination of quantitative MR methods: Overview and recommendations by the ISMRM quantitative MR study group

On behalf of the International Society for Magnetic Resonance in Medicine (ISMRM) Quantitative MR Study Group, this article provides an overview of considerations for the development, validation, qualification, and dissemination of quantitative MR (qMR) methods. This process is framed in terms of two central technical performance properties, i.e., bias and precision. Although qMR is confounded by undesired effects, methods with low bias and high precision can be iteratively developed and validated. For illustration, two distinct qMR methods are discussed throughout the manuscript: quantification of liver proton-density fat fraction, and cardiac T₁ . These examples demonstrate the expansion of qMR methods from research centers toward widespread clinical dissemination. The overall goal of this article is to provide trainees, researchers, and clinicians with essential guidelines for the development and validation of qMR methods, as well as an understanding of necessary steps and potential pitfalls for the dissemination of quantitative MR in research and in the clinic.

Hydration and glycogen affect T1 relaxation times of liver tissue

T₁ mapping is a useful tool for the assessment of patients with nonalcoholic fatty liver disease but still suffers from a large unexplained variance in healthy subjects. This study aims to characterize the potential effects of liver glycogen concentration and body hydration status on liver shortened modified Look-Locker inversion recovery (shMOLLI) T₁ measurements. Eleven glycogen phantoms and 12 healthy volunteers (mean age: 31 years, three females) were scanned at 3 T using inversion recovery spin echo, multiple contrast spin echo (in phantoms), shMOLLI T₁ mapping, multiple-echo spoiled gradient recalled echo and ¹³ C spectroscopy (in healthy volunteers). Phantom r₁ and r₂ relaxivities were determined from measured T₁ and T₂ values. Participants underwent a series of five metabolic experiments to vary their glycogen concentration and hydration levels: feeding, food fasting, exercising, underhydration, and rehydration. Descriptive statistics were calculated for shMOLLI T₁ , inferior vena cava to aorta cross-sectional area ratio (IVC/Ao) as a marker of body hydration status, glycogen concentration, T₂ * and proton density fat fraction values. A linear mixed model for shMOLLI R₁ was constructed to determine the effects of glycogen concentration and IVC/Ao ratio. The mean shMOLLI T₁ after fasting was 737 ± 67 ms. The mean within-subject change was 80 ± 45 ms. The linear mixed model revealed a glycogen r₁ relaxivity in volunteers (0.18 M^-1 s^-1 , p = 0.03) close to that determined in phantoms (0.28 M^-1 s^-1 ). A unit change in IVC/Ao ratio was associated with a drop of -0.113 s^-1 in R₁ (p < 0.001). This study demonstrated a dependence of liver shMOLLI T₁ values on liver glycogen concentration and overall body hydration status. Interparticipant variation of hydration status should be minimized in future liver MRI studies. Additionally, caution is advised when interpreting liver T1 measurements in participants with excess liver glycogen.

Quantitative magnetic resonance imaging for chronic liver disease

Chronic liver disease (CLD) has rapidly increased in prevalence over the past two decades, resulting in significant morbidity and mortality worldwide. Historically, the clinical gold standard for diagnosis, assessment of severity, and longitudinal monitoring of CLD has been liver biopsy with histological analysis, but this approach has limitations that may make it suboptimal for clinical and research settings. Magnetic resonance (MR)-based biomarkers can overcome the limitations by allowing accurate, precise, and quantitative assessment of key components of CLD without the risk of invasive procedures. This review briefly describes the limitations associated with liver biopsy and the need for non-invasive biomarkers. It then discusses the current state-of-the-art for MRI-based biomarkers of liver iron, fat, and fibrosis, and inflammation.

Quantification of 1.5 T T1 and T2 * Relaxation Times of Fetal Tissues in Uncomplicated Pregnancies

BACKGROUND

Despite its many advantages, experience with fetal magnetic resonance imaging (MRI) is limited, as is knowledge of how fetal tissue relaxation times change with gestational age (GA). Quantification of fetal tissue relaxation times as a function of GA provides insight into tissue changes during fetal development and facilitates comparison of images across time and subjects. This, therefore, can allow the determination of biophysical tissue parameters that may have clinical utility.

PURPOSE

To demonstrate the feasibility of quantifying previously unknown T₁ and T₂ ^* relaxation times of fetal tissues in uncomplicated pregnancies as a function of GA at 1.5 T.

STUDY TYPE

Pilot.

POPULATION

Nine women with singleton, uncomplicated pregnancies (28-38 weeks GA).

FIELD STRENGTH/SEQUENCE

All participants underwent two iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL-IQ) acquisitions at different flip angles (6° and 20°) at 1.5 T.

ASSESSMENT

Segmentations of the lungs, liver, spleen, kidneys, muscle, and adipose tissue (AT) were conducted using water-only images and proton density fat fraction maps. Driven equilibrium single pulse observation of T₁ (DESPOT₁ ) was used to quantify the mean water T₁ of the lungs, intraabdominal organs, and muscle, and the mean water and lipid T₁ of AT. IDEAL T₂ ^* maps were used to quantify the T₂ ^* values of the lungs, intraabdominal organs, and muscle.

STATISTICAL TESTS

F-tests were performed to assess the T₁ and T₂ ^* changes of each analyzed tissue as a function of GA.

RESULTS

No tissue demonstrated a significant change in T₁ as a function of GA (lungs [P = 0.89]; liver [P = 0.14]; spleen [P = 0.59]; kidneys [P = 0.97]; muscle [P = 0.22]; AT: water [P = 0.36] and lipid [P = 0.14]). Only the spleen and muscle T₂ ^* showed a significant decrease as a function of GA (lungs [P = 0.67); liver [P = 0.05]; spleen [P < 0.05]; kidneys [P = 0.70]; muscle [P < 0.05]).

DATA CONCLUSION

These preliminary data suggest that the T₁ of the investigated tissues is relatively stable over 28-38 weeks GA, while the T₂ ^* change in spleen and muscle decreases significantly in that period.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2.

MR imaging assessment and quantification of liver iron

Iron overload is a common clinical problem resulting from hereditary hemochromatosis or secondary hemosiderosis (mainly associated with transfusion therapy), being also associated with chronic liver diseases and metabolic disorders. Excess of iron accumulates in organs like the liver, pancreas and heart. Without treatment, patients with iron overload disorders will develop liver cirrhosis, diabetes and cardiomyopathy. Iron quantification is therefore crucial not only for diagnosis of iron overload but also to monitor iron-reducing therapies. Liver iron concentration is considered the surrogate marker of total body iron stores. Because liver biopsy is invasive and prone to high variability and sampling bias, MR imaging has emerged as a non-invasive method and gained wide acceptance, now being considered the standard of care for assessing iron overload. Nevertheless, there are different MR techniques for iron quantification and there is still no consensus about the best technique or postprocessing tool for hepatic iron quantification, with the choice of imaging technique depending mainly on the local expertise as well on the available equipment and software. Because different methods should not be used interchangeably, it is important to choose one method and use the same one when following up patients over time.

Quantitative susceptibility mapping of the spine using in-phase echoes to initialize inhomogeneous field and R2* for the nonconvex optimization problem of fat-water separation

Quantitative susceptibility mapping (QSM) of human spinal vertebrae from a multi-echo gradient-echo (GRE) sequence is challenging, because comparable amounts of fat and water in the vertebrae make it difficult to solve the nonconvex optimization problem of fat-water separation (R2*-IDEAL) for estimating the magnetic field induced by tissue susceptibility. We present an in-phase (IP) echo initialization of R2*-IDEAL for QSM in the spinal vertebrae. Ten healthy human subjects were recruited for spine MRI. A 3D multi-echo GRE sequence was implemented to acquire out-phase and IP echoes. For the IP method, the R2* and field maps estimated by separately fitting the magnitude and phase of IP echoes were used to initialize gradient search R2*-IDEAL to obtain final R2*, field, water, and fat maps, and the final field map was used to generate QSM. The IP method was compared with the existing Zero method (initializing the field to zero), VARPRO-GC (variable projection using graphcuts but still initializing the field to zero), and SPURS (simultaneous phase unwrapping and removal of chemical shift using graphcuts for initialization) on both simulation and in vivo data. The single peak fat model was also compared with the multi-peak fat model. There was no substantial difference on QSM between the single peak and multi-peak fat models, but there were marked differences among different initialization methods. The simulations demonstrated that IP provided the lowest error in the field map. Compared to Zero, VARPRO-GC and SPURS, the proposed IP method provided substantially improved spine QSM in all 10 subjects.

Susceptibility based multiparametric quantification of liver disease: Non-invasive evaluation of steatosis and iron overload

PURPOSE

To evaluate if single-voxel MR spectroscopy (MRS) of iron and fat correlates with biopsy results of hepatic steatosis and iron overload, and to compare MR-measurements with room-temperature susceptometer (RTS), ultrasound, controlled attenuation parameter (CAP) and serum ferritin.

MATERIAL AND METHODS

In this prospective study, a set of 42 patients out of 47 screened patients with several chronic liver diseases underwent MRI-examination at 1.5 T including R2-measurements by single-voxel high-speed T2-corrected multiecho spectroscopy, additional liver biopsy, abdominal ultrasound, CAP, and RTS. Routine blood and serum parameters were determined, including ferritin. Atomic absorption spectroscopy (AAS) and histologically confirmed extent of hepatic steatosis from liver biopsy were used as reference standard. For correlation of R2, RTS, CAP, ferritin, and ultrasound with results of AAS and histologically determined fat fraction of liver biopsy specimen, Spearman's and Pearson's correlation as well as receiver operating characteristics curve (ROC) analysis with cut-off values determined by maximizing Youden index was used.

RESULTS

MRS iron assessment correlated best with AAS, with a Pearson correlation coefficient of 0.715 (p < 0.001), followed by RTS 0.520 (p < 0.001), and serum ferritin 0.213 (p = 0.088, not significant). MRS fat quantification correlated best with the histological confirmed extent of steatosis hepatis with a Spearman correlation coefficient of 0.836 (p < 0.001), followed by CAP 0.604 (p < 0.001) and sonographically diagnosed steatosis 0.358 (p = 0.013).

CONCLUSION

MRS by T2-corrected multiecho single-voxel spectroscopy correlated best with histological results of hepatic fat and iron content compared to RTS, CAP, abdominal ultrasound, and ferritin. Non-invasive methods to assess hepatic fat and iron are of clinical interest for follow-up examinations of patients with chronic liver diseases, where repeated biopsy is not indicated.

Practical guide to quantification of hepatic iron with MRI

Abstract

Our intention is to demystify the MR quantification of hepatic iron (i.e., the liver iron concentration) and give you a step-by-step approach by answering the most pertinent questions. The following article should be more of a manual or guide for every radiologist than a classic review article, which just summarizes the literature. Furthermore, we provide important background information for professional communication with clinicians. The information regarding the physical background is reduced to a minimum. After reading this article, you should be able to perform adequate MR measurements of the LIC with 1.5-T or 3.0-T scanners.

Key Points

• MRI is widely accepted as the primary approach to non-invasively determine liver iron concentration (LIC).

• This article is a guide for every radiologist to perform adequate MR measurements of the LIC.

• When using R2* relaxometry, some points have to be considered to obtain correct measurements—all explained in this article.

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.

Mapping tissue water T1 in the liver using the MOLLI T1 method in the presence of fat, iron and B0 inhomogeneity

Modified Look-Locker inversion recovery (MOLLI) T1 mapping sequences can be useful in cardiac and liver tissue characterization, but determining underlying water T1 is confounded by iron, fat and frequency offsets. This article proposes an algorithm that provides an independent water MOLLI T1 (referred to as on-resonance water T1 ) that would have been measured if a subject had no fat and normal iron, and imaging had been done on resonance. Fifteen NiCl2 -doped agar phantoms with different peanut oil concentrations and 30 adults with various liver diseases, nineteen (63.3%) with liver steatosis, were scanned at 3 T using the shortened MOLLI (shMOLLI) T1 mapping, multiple-echo spoiled gradient-recalled echo and 1 H MR spectroscopy sequences. An algorithm based on Bloch equations was built in MATLAB, and water shMOLLI T1 values of both phantoms and human participants were determined. The quality of the algorithm's result was assessed by Pearson's correlation coefficient between shMOLLI T1 values and spectroscopically determined T1 values of the water, and by linear regression analysis. Correlation between shMOLLI and spectroscopy-based T1 values increased, from r = 0.910 (P < 0.001) to r = 0.998 (P < 0.001) in phantoms and from r = 0.493 (for iron-only correction; P = 0.005) to r = 0.771 (for iron, fat and off-resonance correction; P < 0.001) in patients. Linear regression analysis revealed that the determined water shMOLLI T1 values in patients were independent of fat and iron. It can be concluded that determination of on-resonance water (sh)MOLLI T1 independent of fat, iron and macroscopic field inhomogeneities was possible in phantoms and human subjects.

Reliability of measuring the fat content of the lumbar vertebral marrow and paraspinal muscles using MRI mDIXON-Quant sequence

PURPOSE

We aimed to assess the reliability of measuring the fat content of the lumbar vertebral marrow and the paraspinal muscles using magnetic resonance imaging (MRI) mDIXON-Quant sequence.

METHODS

Thirty-one healthy volunteers were included. All participants underwent liver mDIXON-Quant imaging on a 3.0 T Philips MRI scanner by observer A. Within two weeks, observer B repeated the scan. After the examination, each observer independently measured the fat content of the third lumbar vertebra (L3), and the psoas (PS), erector spinae (ES), and multifidus (MF) muscles on central L3 axial images. After two weeks, each observer repeated the same measurements. They were blinded to their previous results. Reliability was estimated by evaluating the repeatability and reproducibility.

RESULTS

The repeatability of the fat content measurements of L3, PS, ES, and MF was high. The intraclass correlation coefficients of the fat content of L3, PS, ES, and MF were 0.997, 0.984, 0.997, and 0.995 for observer A and 0.948, 0.974, 0.963, and 0.995 for observer B, respectively. The reproducibility of the measurement of the fat content of L3, PS, ES, and MF was high, and the interclass correlation coefficients were 0.984, 0.981, 0.977, and 0.998, respectively.

CONCLUSION

Using mDIXON-Quant imaging to measure the fat content of the lumbar vertebral marrow and paraspinal muscles shows high reliability and is suitable for use in clinical practice.

Estimation of pancreatic R2* for iron overload assessment in the presence of fat: a comparison of different approaches

OBJECTIVES

To propose a method for estimating pancreatic relaxation rate, R2*, from conventional multi-echo MRI, based on the nonlinear fitting of the acquired magnitude signal decay to MR signal models that take into account both the signal oscillations induced by fat and the different R2* values of pancreatic parenchyma and fat.

MATERIALS AND METHODS

Single-peak fat (SPF) and multi-peak fat (MPF) models were introduced. Single-R2* and dual-R2* assumptions were considered as well. Analyses were conducted on simulated data and 20 thalassemia major patients.

RESULTS

Simulations revealed the ability of the MPF model to correctly estimate the R2* value in a large range of fat fractions and R2* values. From the comparison between the results obtained with a single R2* value for water and fat and the dual-R2* approach, the latter is more accurate in both water R2* and fat fraction estimation. In patient's data analysis, a strong concordance was found between SPF and MPF estimated data with measurements done with manual signal correction and from fat-saturated images. The MPF method showed better reproducibility.

CONCLUSION

The MPF dual-R2* approach improves reproducibility and reduces image analysis time in the assessment of pancreatic R2* value in patients with iron overload.

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.

Brown adipose tissue in young adults who were born preterm or small for gestational age

BACKGROUND

Brown adipose tissue (BAT) is present and functions to dissipate energy as heat in young adults and can be assessed using magnetic resonance imaging (MRI) to estimate the voxel fat fraction, i.e. proton density fat fraction (PDFF). It is hypothesized that subjects born preterm or small for gestational age (SGA) may exhibit disrupted BAT formation coupled to metabolic factors. Our purpose was to assess the presence of BAT in young adults born extremely preterm or SGA in comparison with controls.

METHODS

We studied 30 healthy subjects (median age, 21 years): 10 born extremely preterm, 10 full term but SGA and 10 full term with a normal birth weight (controls). We utilized an MRI technique combining multiple scans to enable smaller echo spacing and an advanced fat-water separation method applying graph cuts to estimate B0 inhomogeneity. We measured supraclavicular/cervical PDFF, R2*, fat volume, insulin-like growth factor 1, glucagon, thyroid stimulating hormone and the BAT-associated hormones fibroblast growth factor 21 and irisin.

RESULTS

The groups did not significantly differ in supraclavicular/cervical PDFF, R2*, fat volume or hormone levels. The mean supraclavicular/cervical PDFF was equivalent between the groups (range 75-77%).

CONCLUSIONS

Young adults born extremely preterm or SGA show BAT development similar to those born full term at a normal birth weight. Thus, the increased risk of cardiovascular and metabolic disorders in these groups is not due to the absence of BAT, although our results do not exclude possible BAT involvement in this scenario. Larger studies are needed to understand these relationships.

Iron deposition quantification: Applications in the brain and liver

Iron has long been implicated in many neurological and other organ diseases. It is known that over and above the normal increases in iron with age, in certain diseases there is an excessive iron accumulation in the brain and liver. MRI is a noninvasive means by which to image the various structures in the brain in three dimensions and quantify iron over the volume of the object of interest. The quantification of iron can provide information about the severity of iron-related diseases as well as quantify changes in iron for patient follow-up and treatment monitoring. This article provides an overview of current MRI-based methods for iron quantification, specifically for the brain and liver, including: signal intensity ratio, R₂ , R2*, R2', phase, susceptibility weighted imaging and quantitative susceptibility mapping (QSM). Although there are numerous approaches to measuring iron, R₂ and R2* are currently preferred methods in imaging the liver and QSM has become the preferred approach for imaging iron in the brain.

LEVEL OF EVIDENCE

5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2018. J. MAGN. RESON. IMAGING 2018;48:301-317.

Quantifying iron content in magnetic resonance imaging

Measuring iron content has practical clinical indications in the study of diseases such as Parkinson's disease, Huntington's disease, ferritinopathies and multiple sclerosis as well as in the quantification of iron content in microbleeds and oxygen saturation in veins. In this work, we review the basic concepts behind imaging iron using T2, T2*, T2', phase and quantitative susceptibility mapping in the human brain, liver and heart, followed by the applications of in vivo iron quantification in neurodegenerative diseases, iron tagged cells and ultra-small superparamagnetic iron oxide (USPIO) nanoparticles.

Prevalence of Fatty Liver Disease and Hepatic Iron Overload in a Northeastern German Population by Using Quantitative MR Imaging

Purpose To quantify liver fat and liver iron content by measurement of confounder-corrected proton density fat fraction (PDFF) and R2* and to identify clinical associations for fatty liver disease and liver iron overload and their prevalence in a large-scale population-based study. Materials and Methods From 2008 to 2013, 2561 white participants (1336 women; median age, 52 years; 25th and 75th quartiles, 42 and 62 years) were prospectively recruited to the Study of Health in Pomerania (SHIP). Complex chemical shift-encoded magnetic resonance (MR) examination of the liver was performed, from which PDFF and R2* were assessed. On the basis of previous histopathologic calibration, participants were stratified according to their liver fat and iron content as follows: none (PDFF, ≤5.1%; R2*, ≤41.0 sec^-1), mild (PDFF, >5.1%; R2*, >41 sec^-1), moderate (PDFF, >14.1%; R2*, >62.5 sec^-1), high (PDFF: >28.0%; R2*: >70.1 sec^-1). Prevalence of fatty liver diseases and iron overload was calculated (weighted by probability of participation). Clinical associations were identified by using boosting for generalized linear models. Results Median PDFF was 3.9% (range, 0.6%-41.5%). Prevalence of fatty liver diseases was 42.2% (1082 of 2561 participants); mild, 28.5% (730 participants); moderate, 12.0% (307 participants); high content, 1.8% (45 participants). Median R2* was 34.4 sec^-1 (range, 14.0-311.8 sec^-1). Iron overload was observed in 17.4% (447 of 2561 participants; mild, 14.7% [376 participants]; moderate, 0.8% [20 participants]; high content, 2.0% [50 participants]). Liver fat content correlated with waist-to-height ratio, alanine transaminase, uric acid, serum triglycerides, and blood pressure. Liver iron content correlated with mean serum corpuscular hemoglobin, male sex, and age. Conclusion In a white German population, the prevalence of fatty liver diseases and liver iron overload is 42.2% (1082 of 2561) and 17.4% (447 of 2561). Whereas liver fat is associated with predictors related to the metabolic syndrome, liver iron content is mainly associated with mean serum corpuscular hemoglobin. ^© RSNA, 2017 Online supplemental material is available for this article.

Preparation and In Vitro Characterization of Magnetized miR-modified Endothelial Cells

To date, the available surgical and pharmacological treatments for cardiovascular diseases (CVD) are limited and often palliative. At the same time, gene and cell therapies are highly promising alternative approaches for CVD treatment. However, the broad clinical application of gene therapy is greatly limited by the lack of suitable gene delivery systems. The development of appropriate gene delivery vectors can provide a solution to current challenges in cell therapy. In particular, existing drawbacks, such as limited efficiency and low cell retention in the injured organ, could be overcome by appropriate cell engineering (i.e., genetic) prior to transplantation. The presented protocol describes the efficient and safe transient modification of endothelial cells using a polyethyleneimine superparamagnetic magnetic nanoparticle (PEI/MNP)-based delivery vector. Also, the algorithm and methods for cell characterization are defined. The successful intracellular delivery of microRNA (miR) into human umbilical vein endothelial cells (HUVECs) has been achieved without affecting cell viability, functionality, or intercellular communication. Moreover, this approach was proven to cause a strong functional effect in introduced exogenous miR. Importantly, the application of this MNP-based vector ensures cell magnetization, with accompanying possibilities of magnetic targeting and non-invasive MRI tracing. This may provide a basis for magnetically guided, genetically engineered cell therapeutics that can be monitored non-invasively with MRI.

On the R2⁎ relaxometry in complex multi-peak multi-Echo chemical shift-based water-fat quantification: Applications to the neuromuscular diseases

PURPOSE

Investigation of the feasibility of the R₂^⁎ mapping techniques by using latest theoretical models corrected for confounding factors and optimized for signal to noise ratio.

THEORY AND METHODS

The improvement of the performance of state of the art magnetic resonance imaging (MRI) relaxometry algorithms is challenging because of a non-negligible bias and still unresolved numerical instabilities. Here, R₂^⁎ mapping reconstructions, including complex fitting with multi-spectral fat-correction by using single-decay and double-decay formulation, are deeply studied in order to investigate and identify optimal configuration parameters and minimize the occurrence of numerical artifacts. The effects of echo number, echo spacing, and fat/water relaxation model type are evaluated through both simulated and in-vivo data. We also explore the stability and feasibility of the fat/water relaxation model by analyzing the impact of high percentage of fat infiltrations and local transverse relaxation differences among biological species.

RESULTS

The main limits of the MRI relaxometry are the presence of bias and the occurrence of artifacts, which significantly affect its accuracy. Chemical-shift complex R₂^⁎-correct single-decay reconstructions exhibit a large bias in presence of a significant difference in the relaxation rates of fat and water and with fat concentration larger than 30%. We find that for fat-dominated tissues or in patients affected by extensive iron deposition, MRI reconstructions accounting for multi-exponential relaxation time provide accurate R₂^⁎ measurements and are less prone to numerical artifacts.

CONCLUSIONS

Complex fitting and fat-correction with multi-exponential decay formulation outperforms the conventional single-decay approximation in various diagnostic scenarios. Although it still lacks of numerical stability, which requires model enhancement and support from spectroscopy, it offers promising perspectives for the development of relaxometry as a reliable tool to improve tissue characterization and monitoring of neuromuscular disorders.

Does fat suppression via chemically selective saturation affect R2*-MRI for transfusional iron overload assessment? A clinical evaluation at 1.5T and 3T

PURPOSE

Fat suppression (FS) via chemically selective saturation (CHESS) eliminates fat-water oscillations in multiecho gradient echo (mGRE) R2*-MRI. However, for increasing R2* values as seen with increasing liver iron content (LIC), the water signal spectrally overlaps with the CHESS band, which may alter R2*. We investigated the effect of CHESS on R2* and developed a heuristic correction for the observed CHESS-induced R2* changes.

METHODS

Eighty patients [female, n = 49; male, n = 31; mean age (± standard deviation), 18.3 ± 11.7 y] with iron overload were scanned with a non-FS and a CHESS-FS mGRE sequence at 1.5T and 3T. Mean liver R2* values were evaluated using three published fitting approaches. Measured and model-corrected R2* values were compared and statistically analyzed.

RESULTS

At 1.5T, CHESS led to a systematic R2* reduction (P < 0.001 for all fitting algorithms) especially toward higher R2*. Our model described the observed changes well and reduced the CHESS-induced R2* bias after correction (linear regression slopes: 1.032/0.927/0.981). No CHESS-induced R2* reductions were found at 3T.

CONCLUSION

The CHESS-induced R2* bias at 1.5T needs to be considered when applying R2*-LIC biopsy calibrations for clinical LIC assessment, which were established without FS at 1.5T. The proposed model corrects the R2* bias and could therefore improve clinical iron overload assessment based on linear R2*-LIC calibrations. Magn Reson Med 76:591-601, 2016. © 2015 Wiley Periodicals, Inc.

Liver enzyme levels and hepatic iron content in Fatty liver: a noninvasive assessment in general population by T2* mapping

RATIONALE AND OBJECTIVES

Existing evidence suggests potential contribution of iron in pathogenesis of nonalcoholic fatty liver disease (NAFLD). We aimed to investigate whether hepatic iron content correlates with liver enzyme levels in NAFLD using a noninvasive magnetic resonance imaging (MRI) technique.

MATERIALS AND METHODS

Subjects from Golestan Cohort Study were randomly selected. Diagnosis of NAFLD was made by combination of ultrasound and MRI. Subjects with NAFLD were divided into two groups with high (H-NAFLD) and low (L-NAFLD) enzyme level according to 95th percentile of alanine aminotransferase (ALT) value in normal population. Quantitative T2* maps of entire cross-sectional area of liver were calculated on pixel-by-pixel basis using a semiautomated software.

RESULTS

A total of 207 subjects were enrolled. Mean T2* values were significantly lower in NAFLD group than controls (P < .001) indicating higher iron content. Male subjects with H-NAFLD had statistically lower T2* values than those with L-NAFLD in multivariate analysis (odds ratio, 0.74; 95% confidence interval [CI], 0.58-0.95), whereas this was not observed in women. Unlike women, there was significant negative correlation between ALT levels and T2* values in men with H-NAFLD (r = -0.66, P = .01). Every 1-millisecond decrement in T2* value was associated with 6.37 IU/L increase in ALT level (95% CI, 1.8-10.9, P = .01) in men with H-NAFLD.

CONCLUSIONS

Higher hepatic iron in men with H-NAFLD, estimated by T2* mapping, may support the role of iron in possible progression of simple steatosis to nonalcoholic steatohepatitis. Lack of such correlation in women could be attributed to relatively lower iron storage or other mechanisms rather than iron.

Effect of hepatocyte-specific gadolinium-based contrast agents on hepatic fat-fraction and R2(⁎)

The purpose of this work was to investigate the effect of a hepatocyte-specific gadolinium based contrast agent (GBCA) on quantitative hepatic fat-fraction (FF) and R2* measurements. Fifty patients were imaged at 1.5T, using chemical-shift encoded water-fat MRI with low (5°) and high (15°) flip angles (FA), both before and after administration of a hepatocyte-specific GBCA (gadoxetic acid). Low and high FA, pre- and post-contrast FF and R2* values were measured for each subject. Available serum laboratory studies related to liver disease were also recorded. Linear regression and Bland-Altman analysis were performed to compare measurements. Hepatic FF was unaffected by GBCA at low FA (slope=1.02±0.02, p=0.32). FF was overestimated at high FA pre-contrast (slope=1.33±0.03, p<10(-10)), but underestimated post-contrast (slope=0.81±0.02, p<10(-10)). Hepatic R2* was unaffected by FA (mean difference±95% CI pre-contrast:2.2±4.9s(-1), post-contrast:2.8±3.6s(-1)), but increased post-contrast in patients with total bilirubin <2.5mg/dL (ΔR2*=13.4±12.7s(-1)). Regression analysis of serum values demonstrated a correlation of post-contrast change in R2* with total bilirubin (p<0.01) and model for end-stage liver disease (MELD) score (p≈0.01). In conclusion, GBCA has no effect on hepatic FF at low FA due to a lack of T1-weighting, potentially allowing flexibility for FF imaging with hepatobiliary imaging protocols. Hepatic R2* increased significantly after GBCA administration, particularly in the biliary tree. Therefore, R2* maps should be obtained prior to contrast administration.

Comparative in vitro study on magnetic iron oxide nanoparticles for MRI tracking of adipose tissue-derived progenitor cells

Magnetic resonance imaging (MRI) using measurement of the transverse relaxation time (R2*) is to be considered as a promising approach for cell tracking experiments to evaluate the fate of transplanted progenitor cells and develop successful cell therapies for tissue engineering. While the relationship between core composition of nanoparticles and their MRI properties is well studied, little is known about possible effects on progenitor cells. This in vitro study aims at comparing two magnetic iron oxide nanoparticle types, single vs. multi-core nanoparticles, regarding their physico-chemical characteristics, effects on cellular behavior of adipose tissue-derived stem cells (ASC) like differentiation and proliferation as well as their detection and quantification by means of MRI. Quantification of both nanoparticle types revealed a linear correlation between labeling concentration and R2* values. However, according to core composition, different levels of labeling concentrations were needed to achieve comparable R2* values. Cell viability was not altered for all labeling concentrations, whereas the proliferation rate increased with increasing labeling concentrations. Likewise, deposition of lipid droplets as well as matrix calcification revealed to be highly dose-dependent particularly regarding multi-core nanoparticle-labeled cells. Synthesis of cartilage matrix proteins and mRNA expression of collagen type II was also highly dependent on nanoparticle labeling. In general, the differentiation potential was decreased with increasing labeling concentrations. This in vitro study provides the proof of principle for further in vivo tracking experiments of progenitor cells using nanoparticles with different core compositions but also provides striking evidence that combined testing of biological and MRI properties is advisable as improved MRI properties of multi-core nanoparticles may result in altered cell functions.

Quantification of liver iron with MRI: state of the art and remaining challenges

Liver iron overload is the histological hallmark of hereditary hemochromatosis and transfusional hemosiderosis, and can also occur in chronic hepatopathies. Iron overload can result in liver damage, with the eventual development of cirrhosis, liver failure, and hepatocellular carcinoma. Assessment of liver iron levels is necessary for detection and quantitative staging of iron overload and monitoring of iron-reducing treatments. This article discusses the need for noninvasive assessment of liver iron and reviews qualitative and quantitative methods with a particular emphasis on magnetic resonance imaging (MRI). Specific MRI methods for liver iron quantification include signal intensity ratio as well as R2 and R2* relaxometry techniques. Methods that are in clinical use, as well as their limitations, are described. Remaining challenges, unsolved problems, and emerging techniques to provide improved characterization of liver iron deposition are discussed.

Clinical implications of non-steatotic hepatic fat fractions on quantitative diffusion-weighted imaging of the liver

Diffusion-weighted imaging (DWI) is an important diagnostic tool in the assessment of focal liver lesions and diffuse liver diseases such as cirrhosis and fibrosis. Quantitative DWI parameters such as molecular diffusion, microperfusion and their fractions, are known to be affected when hepatic fat fractions (HFF) are higher than 5.5% (steatosis). However, less is known about the effect on DWI for HFF in the normal non-steatotic range below 5.5%, which can be found in a large part of the population. The aim of this study was therefore to evaluate the diagnostic implications of non-steatotic HFF on quantitative DWI parameters in eight liver segments. For this purpose, eleven healthy volunteers (2 men, mean-age 31.0) were prospectively examined with DWI and three series of in-/out-of-phase dual-echo spoiled gradient-recalled MRI sequences to obtain the HFF and T₂*. DWI data were analyzed using the intravoxel incoherent motion (IVIM) model. Four circular regions (ø22.3 mm) were drawn in each of eight liver segments and averaged. Measurements were divided in group 1 (HFF≤2.75%), group 2 (2.75< HFF ≤5.5%) and group 3 (HFF>5.5%). DWI parameters and T₂* were compared between the three groups and between the segments. It was observed that the molecular diffusion (0.85, 0.72 and 0.49 ×10⁻³ mm²/s) and T₂* (32.2, 27.2 and 21.0 ms) differed significantly between the three groups of increasing HFF (2.18, 3.50 and 19.91%). Microperfusion and its fraction remained similar for different HFF. Correlations with HFF were observed for the molecular diffusion (r = −0.514, p<0.001) and T₂* (−0.714, p<0.001). Similar results were obtained for the majority of individual liver segments. It was concluded that fat significantly decreases molecular diffusion in the liver, also in absence of steatosis (HFF≤5.5%). Also, it was confirmed that fat influences T₂*. Determination of HFF prior to quantitative DWI is therefore crucial.

Liver fat quantification using a multi-step adaptive fitting approach with multi-echo GRE imaging

PURPOSE

The purpose of this study was to develop a multi-step adaptive fitting approach for liver proton density fat fraction (PDFF) and R(2)* quantification, and to perform an initial validation on a broadly available hardware platform.

THEORY AND METHODS

The proposed method uses a multi-echo three-dimensional gradient echo acquisition, with initial guesses for the fat and water signal fractions based on a Dixon decomposition of two selected echoes. Based on magnitude signal equations with a multi-peak fat spectral model, a multi-step nonlinear fitting procedure is then performed to adaptively update the fat and water signal fractions and R(2)* values. The proposed method was validated using numeric phantoms as ground truth, followed by preliminary clinical validation of PDFF calculations against spectroscopy in 30 patients.

RESULTS

The results of the proposed method agreed well with the ground truth of numerical phantoms, and were relatively insensitive to changes in field strength, field homogeneity, monopolar/bipolar readout, signal to noise ratio, and echo time selections. The in vivo patient study showed excellent consistency between the PDFF values measured with the proposed approach compared with spectroscopy.

CONCLUSION

This multi-step adaptive fitting approach performed well in both simulated and initial clinical evaluation, and shows potential in the quantification of hepatic steatosis.

T1 bias in chemical shift-encoded liver fat-fraction: role of the flip angle

PURPOSE

To investigate flip angle (FA)-dependent T1 bias in chemical shift-encoded fat-fraction (FF) and to evaluate a strategy for correcting this bias to achieve accurate MRI-based estimates of liver fat with optimized signal-to-noise ratio (SNR).

MATERIALS AND METHODS

Thirty-three obese patients, 14 men/19 women, aged 57.3 ± 13.9 years underwent 3 Tesla (T) liver MRI including MR-spectroscopy and four three-echo-complex chemical shift-encoded MRI sequences using different FAs (1°/3°/10°/20°). FF was estimated with R2* correction and multi-peak fat spectral modeling. The FF for each FA with and without T1 correction was compared with spectroscopy as a reference standard, using linear regression. Relative SNR of the magnitude data were assessed for each flip angle.

RESULTS

The correlation between chemical shift-encoded MRI and spectroscopy was high (R(2) &asymp; 0.9). Without T1 correction, the agreement of both techniques showed no significant differences in slope (PFlipAngle1 °  = 0.385/PFlipAngle3 °  = 0.289) using low FA. High FA resulted in significant different slopes (PFlipAngle10 °  = 0.016/PFlipAngle20 °  = 0.014. T1 bias was successfully corrected using the T1 correction strategy (slope:PFlipAngle10 °  = 0.387/PFlipAngle20 °  = 0.440). Additionally, the use of high FA (near the Ernst angle) improved the SNR of the magnitude data (FA1 vs. FA3; respectively FA1 vs. FA10 P ≤ 0.001).

CONCLUSION

T1 bias is a strong confounder in the assessment of liver fat using chemical shift imaging with high FA. However, using a larger flip angle with T1 correction leads to higher SNR, and residual error after T1 correction is very small.

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

PURPOSE

To characterize the confounding effect of temperature on chemical shift-encoded (CSE) fat quantification.

METHODS

The proton resonance frequency of water, unlike triglycerides, depends on temperature. This leads to a temperature dependence of the spectral models of fat (relative to water) that are commonly used by CSE-MRI methods. Simulation analysis was performed for 1.5 Tesla CSE fat-water signals at various temperatures and echo time combinations. Oil-water phantoms were constructed and scanned at temperatures between 0 and 40°C using spectroscopy and CSE imaging at three echo time combinations. An explanted human liver, rejected for transplantation due to steatosis, was scanned using spectroscopy and CSE imaging. Fat-water reconstructions were performed using four different techniques: magnitude and complex fitting, with standard or temperature-corrected signal modeling.

RESULTS

In all experiments, magnitude fitting with standard signal modeling resulted in large fat quantification errors. Errors were largest for echo time combinations near TEinit ≈ 1.3 ms, ΔTE ≈ 2.2 ms. Errors in fat quantification caused by temperature-related frequency shifts were smaller with complex fitting, and were avoided using a temperature-corrected signal model.

CONCLUSION

Temperature is a confounding factor for fat quantification. If not accounted for, it can result in large errors in fat quantifications in phantom and ex vivo acquisitions.

Proton-density fat fraction and simultaneous R2* estimation as an MRI tool for assessment of osteoporosis

OBJECTIVE

To investigate multi-echo chemical shift-encoded MRI-based mapping of proton density fat fraction (PDFF) and fat-corrected R2* in bone marrow as biomarkers for osteoporosis assessment.

METHODS

Fifty-one patients (28 female; mean age 69.7 ± 9.0 years) underwent dual energy X-ray absorptiometry (DXA). On the basis of the t score, 173 valid vertebrae bodies were divided into three groups (healthy, osteopenic and osteoporotic). Three echo chemical shift-encoded MRI sequences were acquired at 3 T. PDFF and R2* with correction for multiple-peak fat (R2*MP) were measured for each vertebral body. Kruskal-Wallis test and post hoc analysis were performed to evaluate differences between groups. Further, the area under the curve (AUC) for each technique was calculated using logistic regression analysis.

RESULTS

On the basis of DXA, 92 samples were normal (53 %), 47 osteopenic (27 %) and 34 osteoporotic (20 %). PDFF was increased in osteoporosis compared with healthy (P = 0.007). R2*MP showed significant differences between normal and osteopenia (P = 0.004), and between normal and osteoporosis (P < 0.001). AUC to differentiate between normal and osteoporosis was 0.698 for R2*MP, 0.656 for PDFF and 0.74 for both combined.

CONCLUSION

PDFF and R2*MP are moderate biomarkers for osteoporosis. PDFF and R2*MP combination might improve the prediction in differentiating healthy subjects from those with osteoporosis.