Quantification of low fat contents: a comparison of MR imaging and spectroscopy methods at 1.5 and 3 T

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.

High-Resolution MR Imaging of Muscular Fat Fraction-Comparison of Three T2-Based Methods and Chemical Shift-Encoded Imaging

Chemical shift-encoded imaging (CSEI) is the most common magnetic resonance imaging fat–water separation method. However, when high spatial resolution fat fraction (FF) images are desired, CSEI might be challenging owing to the increased interecho spacing. Here, 3 T₂-based methods have been assessed as alternative methods for obtaining high-resolution FF images. Images from the calf of 10 healthy volunteers were acquired; FF maps were then estimated using 3 T₂-based methods (2- and 3-parameter nonlinear least squares fit and a Bayesian probability method) and CSEI for reference. In addition, simulations were conducted to characterize the performance of various methods. Here, all T₂-based methods resulted in qualitatively improved high-resolution FF images compared with high-resolution CSEI. The 2-parameter fit showed best quantitative agreement to low-resolution CSEI, even at low FF. The estimated T₂-values of fat and water, and the estimated muscle FF of the calf, agreed well with previously published data. In conclusion, T₂-based methods can provide improved high-resolution FF images of the calf compared with the CSEI method.

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.

Quantification of liver fat: A comprehensive review

Fat accumulation in the liver causes metabolic diseases such as obesity, hypertension, diabetes or dyslipidemia by affecting insulin resistance, and increasing the risk of cardiac complications and cardiovascular disease mortality. Fatty liver diseases are often reversible in their early stage; therefore, there is a recognized need to detect their presence and to assess its severity to recognize fat-related functional abnormalities in the liver. This is crucial in evaluating living liver donors prior to transplantation because fat content in the liver can change liver regeneration in the recipient and donor. There are several methods to diagnose fatty liver, measure the amount of fat, and to classify and stage liver diseases (e.g. hepatic steatosis, steatohepatitis, fibrosis and cirrhosis): biopsy (the gold-standard procedure), clinical (medical physics based) and image analysis (semi or fully automated approaches). Liver biopsy has many drawbacks: it is invasive, inappropriate for monitoring (i.e., repeated evaluation), and assessment of steatosis is somewhat subjective. Qualitative biomarkers are mostly insufficient for accurate detection since fat has to be quantified by a varying threshold to measure disease severity. Therefore, a quantitative biomarker is required for detection of steatosis, accurate measurement of severity of diseases, clinical decision-making, prognosis and longitudinal monitoring of therapy. This study presents a comprehensive review of both clinical and automated image analysis based approaches to quantify liver fat and evaluate fatty liver diseases from different medical imaging modalities.

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.

Magnetic resonance imaging reveals altered distribution of hepatic fat in children with type 1 diabetes compared to controls

INTRODUCTION

Children with type 1 diabetes have been identified as a risk group for non-alcoholic fatty liver disease (NAFLD). The aim was to compare total hepatic fat fraction and fat distribution across Couinaud segments in children with type 1 diabetes and controls and the relation of hepatic fat to plasma and anthropometric parameters.

METHODS

Hepatic fat fraction and fat distribution across Couinaud segments were measured with magnetic resonance imaging (MRI) in 22 children with type 1 diabetes and 32 controls. Blood tests and anthropometric data were collected.

RESULTS

No children had NAFLD. Children with type 1 diabetes had a slightly lower hepatic fat fraction (median 1.3%) than controls (median 1.8%), and their fat had a different segmental distribution. The fat fraction of segment V was the most representative of the liver as a whole. An incidental finding was that diabetes patients treated with multiple daily injections of insulin (MDI) had a fat distribution more similar to controls than patients with continuous subcutaneous insulin infusion (CSII).

CONCLUSIONS

In children with type 1 diabetes, NAFLD may be less common than recent studies have suggested. Children with type 1 diabetes may have a lower fat fraction and a different fat distribution in the liver than controls. Diabetes treatment with MDI or CSII may affect liver fat, but this needs to be confirmed in a larger sample of patients. The heterogeneity of hepatic fat infiltration may affect results when liver biopsy is used for diagnosing fatty liver.

MR Quantification of the Fatty Fraction from T2*-corrected Dixon Fat/Water Separation Volume-interpolated Breathhold Examination (VIBE) in the Assessment of Muscle Atrophy in Rotator Cuff Tears

RATIONALE AND OBJECTIVES

To assess the usefulness of T2*-corrected fat fraction (FF) map from volume-interpolated breathhold examination (VIBE) magnetic resonance (MR) sequence in patients with the rotator cuff pathology.

MATERIALS AND METHODS

The phantom study was performed to validate the FF maps. Eighty-nine shoulder MR arthrographies were analyzed: (1) divided into three groups namely tendinopathy/normal tendons, partial-thickness tears, and full-thickness tears, and (2) occupation ratio (OR) was measured for muscular atrophy. Uncorrected and T2*-corrected FF maps were reconstructed from the VIBE images. The Pearson correlation test was used to correlate the FFs with ORs. The FF and the OR were compared between groups using the Student t test.

RESULTS

T2*-corrected FF maps could provide a higher correlation than uncorrected FF maps. There were significantly negative correlations between the ORs and the FFs (P < .01). In the normal and the partial-thickness tear group, the OR did not show a significant difference, although the FF maps showed a significant difference (P < .01).

CONCLUSIONS

This quantitative assessment of the T2*-corrected FF in the rotator cuff muscles was found to be reliable and correlated well with the ORs. The T2*-corrected FF maps could be used for more sophisticated assessments of the fat even in the partial-thickness tear.

Relaxation effects in MRI-based quantification of fat content and fatty acid composition

PURPOSE

To investigate various sources of bias in MRI-based quantification of fat fraction (FF) and fatty acid composition (FAC) using chemical shift-encoded techniques.

METHODS

Signals from various FFs and FACs and individual relaxation rates of all signal components were simulated. From these signals, FF and FAC parameters were estimated with and without correction for differences in individual relaxation rates. In addition, phantom experiments were conducted with various flip angles and number of echoes to validate the simulations.

RESULTS

As expected, T(1) weighting resulted in an overestimation of the FF, but had much smaller impact on the FAC parameters. Differences in T(2) values of the signal components resulted in overestimation of the FAC parameters in fat/water mixtures, whereas the estimation in pure oil was largely unaffected. This bias was corrected using a simplified signal model with different T(2) values of water and fat, where the accuracy of the modeled T(2) of water was critical. The results of the phantom experiment were in agreement with simulations.

CONCLUSION

T(1) weighting has only a minor effect on FAC quantification in both fat/water mixtures and pure oils. T(2) weighting is mainly a concern in fat/water mixtures but may be corrected using a simplified model.

Quantitative proton MR techniques for measuring fat

Accurate, precise and reliable techniques for the quantification of body and organ fat distributions are important tools in physiology research. They are critically needed in studies of obesity and diseases involving excess fat accumulation. Proton MR methods address this need by providing an array of relaxometry-based (T1, T2) and chemical shift-based approaches. These techniques can generate informative visualizations of regional and whole-body fat distributions, yield measurements of fat volumes within specific body depots and quantify fat accumulation in abdominal organs and muscles. MR methods are commonly used to investigate the role of fat in nutrition and metabolism, to measure the efficacy of short- and long-term dietary and exercise interventions, to study the implications of fat in organ steatosis and muscular dystrophies and to elucidate pathophysiological mechanisms in the context of obesity and its comorbidities. The purpose of this review is to provide a summary of mainstream MR strategies for fat quantification. The article succinctly describes the principles that differentiate water and fat proton signals, summarizes the advantages and limitations of various techniques and offers a few illustrative examples. The article also highlights recent efforts in the MR of brown adipose tissue and concludes by briefly discussing some future research directions.