MR properties of brown and white adipose tissues

Purpose:

To explore the MR signatures of brown adipose tissue (BAT) compared with white adipose tissue (WAT) using single‐voxel MR spectroscopy.

Materials and Methods:

¹H MR STEAM spectra were acquired from a 3 Tesla clinical whole body scanner from seven excised murine adipose tissue samples of BAT (n = 4) and WAT (n = 3). Spectra were acquired at multiple echo times (TEs) and inversion times (TIs) to measure the T1, T2, and T2‐corrected peak areas. A theoretical triglyceride model characterized the fat in terms of number of double bonds (ndb) and number of methylene‐interrupted double bonds (nmidb).

Results:

Negligible differences between WAT and BAT were seen in the T1 and T2 of fat and the T2 of water. However, the water fraction in BAT was higher (48.5%) compared with WAT (7.1%) and the T1 of water was lower in BAT (618 ms) compared with WAT (1053 ms). The fat spectrum also differed, indicating lower levels of unsaturated triglycerides in BAT (ndb = 2.7, nmidb = 0.7) compared with WAT (ndb = 3.3, nmidb = 1.0).

Conclusion:

We have demonstrated that there are several key MR‐based signatures of BAT and WAT that may allow differentiation on MR imaging. J. Magn. Reson. Imaging 2011;. © 2011 Wiley‐Liss, Inc.     

Evaluation of adipose tissue volume quantification with IDEAL fat-water separation

Purpose:

To validate i terative d ecomposition of water and fat with e cho a symmetry and l east‐squares estimation (IDEAL) for adipose tissue volume quantification. IDEAL allows MRI images to be produced only from adipose‐containing tissues; hence, quantifying adipose tissue should be simpler and more accurate than with current methods.

Materials and Methods:

Ten healthy controls were imaged with 1.5 Tesla (T) Spin Echo (SE), 3.0T T1‐weighted spoiled gradient echo (SPGR), and 3.0T IDEAL‐SPGR. Images were acquired from the abdomen, pelvis, mid‐thigh, and mid‐calf. Mean subcutaneous and visceral adipose tissue volumes were compared between the three acquisitions for each subject.

Results:

There were no significant differences (P > 0.05) between the three acquisitions for subcutaneous adipose tissue volumes. However, there was a significant difference (P = 0.0002) for visceral adipose tissue volumes in the abdomen. Post hoc analysis showed significantly lower visceral adipose tissue volumes measured by IDEAL versus 1.5T (P < 0.0001) and 3.0T SPGR (P < 0.002). The lower volumes given by IDEAL are due to its ability to differentiate true visceral adipose tissue from other bright structures like blood vessels and bowel content that are mistaken for adipose tissue in non‐fat suppressed images.

Conclusion:

IDEAL measurements of adipose tissue are equivalent to established 1.5T measurement techniques for subcutaneous depots and have improved accuracy for visceral depots, which are more metabolically relevant. J. Magn. Reson. Imaging 2011;. © 2011 Wiley‐Liss, Inc.     

Quantification of absolute fat mass using an adipose tissue reference signal model

Purpose

To develop a method for quantifying absolute fat mass, and to demonstrate its feasibility in phantoms and in ex vivo swine specimens at 3 Tesla.

Materials and Methods

Chemical‐shift‐based fat‐water decomposition was used to first reconstruct fat‐only images. Our proposed model used a reference signal from fat in pure adipose tissue to calibrate and normalize the fat signal intensities from the fat‐only images. Fat mass was subsequently computed on a voxel‐by‐voxel basis and summed across each sample. Feasibility of the model was tested in six ex vivo swine samples containing varying mixtures of fat (adipose) and lean tissues. The samples were imaged using 1.5‐mm isotropic voxels and a single‐channel birdcage head coil at 3 Tesla. Lipid assay was independently performed to determine fat mass, and served as the comparison standard.

Results

Absolute fat mass values (in grams) derived by our proposed model were in excellent agreement with lipid assay results, with a 5% to 7% difference (r > 0.99; P < 0.001).

Conclusion

Preliminary results in ex vivo swine samples demonstrated the feasibility of computing absolute fat mass as a quantitative endpoint using chemical‐shift fat‐water MRI with a signal model based on reference fat from pure adipose tissue. J. Magn. Reson. Imaging 2008;28:1483–1491. © 2008 Wiley‐Liss, Inc.     

Topography mapping of whole body adipose tissue using A fully automated and standardized procedure

Purpose:

To obtain quantitative measures of human body fat compartments from whole body MR datasets for the risk estimation in subjects prone to metabolic diseases without the need of any user interaction or expert knowledge.

Materials and Methods:

Sets of axial T1‐weighted spin‐echo images of the whole body were acquired. The images were segmented using a modified fuzzy c‐means algorithm. A separation of the body into anatomic regions along the body axis was performed to define regions with visceral adipose tissue present, and to standardize the results. In abdominal image slices, the adipose tissue compartments were divided into subcutaneous and visceral compartments using an extended snake algorithm. The slice‐wise areas of different tissues were plotted along the slice position to obtain topographic fat tissue distributions.

Results:

Results from automatic segmentation were compared with manual segmentation. Relatively low mean deviations were obtained for the class of total tissue (4.48%) and visceral adipose tissue (3.26%). The deviation of total adipose tissue was slightly higher (8.71%).

Conclusion:

The proposed algorithm enables the reliable and completely automatic creation of adipose tissue distribution profiles of the whole body from multislice MR datasets, reducing whole examination and analysis time to less than half an hour. J. Magn. Reson. Imaging 2010; 31: 430–439. © 2010 Wiley‐Liss, Inc.     

Automatic intra‐subject registration‐based segmentation of abdominal fat from water–fat MRI

Purpose:

To develop an automatic registration‐based segmentation algorithm for measuring abdominal adipose tissue depot volumes and organ fat fraction content from three‐dimensional (3D) water–fat MRI data, and to evaluate its performance against manual segmentation.

Materials and Methods:

Data were obtained from 11 subjects at two time points with intermediate repositioning, and from four subjects before and after a meal with repositioning. Imaging was performed on a 3 Tesla MRI, using the IDEAL chemical‐shift water–fat pulse sequence. Adipose tissue (subcutaneous—SAT, visceral—VAT) and organs (liver, pancreas) were manually segmented twice for each scan by a single trained observer. Automated segmentations of each subject's second scan were generated using a nonrigid volume registration algorithm for water–fat MRI images that used a b‐spline basis for deformation and minimized image dissimilarity after the deformation. Manual and automated segmentations were compared using Dice coefficients and linear regression of SAT and VAT volumes, organ volumes, and hepatic and pancreatic fat fractions (HFF, PFF).

Results:

Manual segmentations from the 11 repositioned subjects exhibited strong repeatability and set performance benchmarks. The average Dice coefficients were 0.9747 (SAT), 0.9424 (VAT), 0.9404 (liver), and 0.8205 (pancreas); the linear correlation coefficients were 0.9994 (SAT volume), 0.9974 (VAT volume), 0.9885 (liver volume), 0.9782 (pancreas volume), 0.9996 (HFF), and 0.9660 (PFF). When comparing manual and automated segmentations, the average Dice coefficients were 0.9043 (SAT volume), 0.8235 (VAT), 0.8942 (liver), and 0.7168 (pancreas); the linear correlation coefficients were 0.9493 (SAT volume), 0.9982 (VAT volume), 0.9326 (liver volume), 0.8876 (pancreas volume), 0.9972 (HFF), and 0.8617 (PFF). In the four pre‐ and post‐prandial subjects, the Dice coefficients were 0.9024 (SAT), 0.7781 (VAT), 0.8799 (liver), and 0.5179 (pancreas); the linear correlation coefficients were 0.9889, 0.9902 (SAT, and VAT volume), 0.9523 (liver volume), 0.8760 (pancreas volume), 0.9991 (HFF), and 0.6338 (PFF).

Conclusion:

Automated intra‐subject registration‐based segmentation is potentially suitable for the quantification of abdominal and organ fat and achieves comparable quantitative endpoints with respect to manual segmentation. J. Magn. Reson. Imaging 2013;37:423–430. © 2012 Wiley Periodicals, Inc.     

Automatic segmentation of intra‐abdominal and subcutaneous adipose tissue in 3D whole mouse MRI

Purpose

To fully automate intra‐abdominal (IAT) and total adipose tissue (TAT) segmentation in mice to replace tedious and subjective manual segmentation.

Materials and Methods

A novel transform codes each voxel with the radius of the narrowest passage on the widest possible three‐dimensional (3D) path to any voxel in the target object to select appropriate IAT seed points. Then competitive region growing is performed on a distance transform of the fat mask such that competing classes meet at narrow passages effectively segmenting the IAT and subcutaneous adipose compartments. Fully automatic segmentations were conducted on 32 3D mouse images independent to those used for algorithm development.

Results

Automatic processing worked on all 32 images and took 28 s on a 3.6 GHz Pentium computer with 2.0 GB RAM. Manual segmentation by an experienced operator typically took 1 h per 3D image. The correlation coefficients between manual and automated segmentation of TAT and IAT were 0.97 and 0.94, respectively.

Conclusion

The fully automatic method correlates well with manual segmentation and dramatically speeds up segmentation allowing MRI to be used in the anti‐obesity drug discovery pipeline. J. Magn. Reson. Imaging 2009;30:554–560. © 2009 Wiley‐Liss, Inc.     

Adipose tissue MRI for quantitative measurement of central obesity

Purpose:

To validate adipose tissue magnetic resonance imaging (atMRI) for rapid, quantitative volumetry of visceral adipose tissue (VAT) and total adipose tissue (TAT).

Materials and Methods:

Data were acquired on normal adults and clinically overweight girls with Institutional Review Board (IRB) approval/parental consent using sagittal 6‐echo 3D‐spoiled gradient‐echo (SPGR) (26‐sec single‐breath‐hold) at 3T. Fat‐fraction images were reconstructed with quantitative corrections, permitting measurement of a physiologically based fat‐fraction threshold in normals to identify adipose tissue, for automated measurement of TAT, and semiautomated measurement of VAT. TAT accuracy was validated using oil phantoms and in vivo TAT/VAT measurements validated with manual segmentation. Group comparisons were performed between normals and overweight girls using TAT, VAT, VAT‐TAT‐ratio (VTR), body‐mass‐index (BMI), waist circumference, and waist‐hip‐ratio (WHR).

Results:

Oil phantom measurements were highly accurate (<3% error). The measured adipose fat‐fraction threshold was 96% ± 2%. VAT and TAT correlated strongly with manual segmentation (normals r² ≥ 0.96, overweight girls r² ≥ 0.99). VAT segmentation required 30 ± 11 minutes/subject (14 ± 5 sec/slice) using atMRI, versus 216 ± 73 minutes/subject (99 ± 31 sec/slice) manually. Group discrimination was significant using WHR (P < 0.001) and VTR (P = 0.004).

Conclusion:

The atMRI technique permits rapid, accurate measurements of TAT, VAT, and VTR. J. Magn. Reson. Imaging 2013;37:707–716. © 2012 Wiley Periodicals, Inc.     

Automated unsupervised multi‐parametric classification of adipose tissue depots in skeletal muscle

Purpose:

To introduce and validate an automated unsupervised multi‐parametric method for segmentation of the subcutaneous fat and muscle regions to determine subcutaneous adipose tissue (SAT) and intermuscular adipose tissue (IMAT) areas based on data from a quantitative chemical shift‐based water‐fat separation approach.

Materials and Methods:

Unsupervised standard k‐means clustering was used to define sets of similar features (k = 2) within the whole multi‐modal image after the water‐fat separation. The automated image processing chain was composed of three primary stages: tissue, muscle, and bone region segmentation. The algorithm was applied on calf and thigh datasets to compute SAT and IMAT areas and was compared with a manual segmentation.

Results:

The IMAT area using the automatic segmentation had excellent agreement with the IMAT area using the manual segmentation for all the cases in the thigh (R²: 0.96) and for cases with up to moderate IMAT area in the calf (R²: 0.92). The group with the highest grade of muscle fat infiltration in the calf had the highest error in the inner SAT contour calculation.

Conclusion:

The proposed multi‐parametric segmentation approach combined with quantitative water‐fat imaging provides an accurate and reliable method for an automated calculation of the SAT and IMAT areas reducing considerably the total postprocessing time. J. Magn. Reson. Imaging 2013;37:917–927. © 2012 Wiley Periodicals, Inc.     

Water-fat separation with IDEAL gradient-echo imaging

Purpose

To combine gradient‐echo (GRE) imaging with a multipoint water–fat separation method known as “iterative decomposition of water and fat with echo asymmetry and least squares estimation” (IDEAL) for uniform water–fat separation. Robust fat suppression is necessary for many GRE imaging applications; unfortunately, uniform fat suppression is challenging in the presence of B₀ inhomogeneities. These challenges are addressed with the IDEAL technique.

Materials and Methods

Echo shifts for three‐point IDEAL were chosen to optimize noise performance of the water–fat estimation, which is dependent on the relative proportion of water and fat within a voxel. Phantom experiments were performed to validate theoretical SNR predictions. Theoretical echo combinations that maximize noise performance are discussed, and examples of clinical applications at 1.5T and 3.0T are shown.

Results

The measured SNR performance validated theoretical predictions and demonstrated improved image quality compared to unoptimized echo combinations. Clinical examples of the liver, breast, heart, knee, and ankle are shown, including the combination of IDEAL with parallel imaging. Excellent water–fat separation was achieved in all cases. The utility of recombining water and fat images into “in‐phase,” “out‐of‐phase,” and “fat signal fraction” images is also discussed.

Conclusion

IDEAL‐SPGR provides robust water–fat separation with optimized SNR performance at both 1.5T and 3.0T with multicoil acquisitions and parallel imaging in multiple regions of the body. J. Magn. Reson. Imaging 2007;25:644–652. © 2007 Wiley‐Liss, Inc.     

Automatic quantification of subcutaneous and visceral adipose tissue from whole‐body magnetic resonance images suitable for large cohort studies

Purpose:

To develop an automated method with which to distinguish metabolically different adipose tissues in a large number of subjects using whole‐body magnetic resonance imaging (MRI) datasets for improving the understanding of chronic disease risk predictions associated with distinct adipose tissue compartments.

Materials and Methods:

In all, 314 participants were scanned using a 1.5T MRI‐scanner with a 2‐point Dixon whole‐body sequence. Image segmentation was automated using standard image processing techniques and knowledge‐based methods. Abdominal adipose tissue was separated into subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) by statistical shape models. Bone marrow was removed to provide a more accurate measurement of adipose tissue. To assess segmentation accuracy, ground‐truth segmentations in 52 images were performed manually by one operator. Due to the high effort of manual delineation, manual segmentation was limited to seven slices per volume.

Results:

Volumetric differences were 3.30 ± 2.97% and 6.22 ± 5.28% for SAT and VAT, respectively. The systematic error shows an overestimation of 4.22 ± 7.01% for VAT and 0.37 ± 4.45% for SAT. Coefficients‐of‐variation from repeated measurements were: 3.50 ± 2.93% for VAT and 0.35 ± 0.26% for SAT. The approach of removing bone marrow worked well in most body regions. Only occasionally the method failed for knees and/or shinbone, which resulted in an overestimation of SAT by 3.14 ± 1.45%.

Conclusion:

We developed a fully automatic process to assess SAT and VAT in whole‐body MRI data. The method can support epidemiological studies investigating the relationship between excess body fat and chronic diseases. J. Magn. Reson. Imaging 2012; 36:1421–1434. © 2012 Wiley Periodicals, Inc.     

Unequivocal identification of brown adipose tissue in a human infant

We report the unique depiction of brown adipose tissue (BAT) by magnetic resonance imaging (MRI) and computed tomography (CT) in a human 3-month-old infant. Based on cellular differences between BAT and more lipid-rich white adipose tissue (WAT), chemical-shift MRI and CT were both capable of generating distinct signal contrasts between the two tissues and against surrounding anatomy, utilizing fat-signal fraction metrics in the former and x-ray attenuation values in the latter. While numerous BAT imaging experiments have been performed previously in rodents, the identification of BAT in humans has only recently been described with fusion positron emission and computed tomography in adults. The imaging of BAT in children has not been widely reported and, furthermore, MRI of human BAT in general has not been demonstrated. In the present work, large bilateral supraclavicular BAT depots were clearly visualized with MRI and CT. Tissue identity was subsequently confirmed by histology. BAT has important implications in regulating energy metabolism and nonshivering thermogenesis and has the potential to combat the onset of weight gain and the development of obesity. Current findings suggest that BAT is present in significant amounts in children and that MRI and CT can differentiate BAT from WAT based on intrinsic tissue properties.     

Body composition analysis of obesity and hepatic steatosis in mice by relaxation compensated fat fraction (RCFF) MRI

Purpose:

To develop and validate a quantitative magnetic resonance imaging (MRI) methodology for phenotyping animal models of obesity and fatty liver disease on 7T small animal MRI scanners.

Materials and Methods:

A new MRI acquisition and image analysis technique, relaxation‐compensated fat fraction (RCFF), was developed and validated by both magnetic resonance spectroscopy and histology. This new RCFF technique was then used to assess lipid biodistribution in two groups of mice on either a high‐fat (HFD) or low‐fat (LFD) diet.

Results:

RCFF demonstrated excellent correlation in phantom studies (R² = 0.99) and in vivo compared to histological evaluation of hepatic triglycerides (R² = 0.90). RCFF images provided robust fat fraction maps with consistent adipose tissue values (82% ± 3%). HFD mice exhibited significant increases in peritoneal and subcutaneous adipose tissue volumes in comparison to LFD controls (peritoneal: 6.4 ± 0.4 cm³ vs. 0.7 ± 0.2, P < 0.001; subcutaneous: 14.7 ± 2.0 cm³ vs. 1.2 ± 0.3 cm³, P < 0.001). Hepatic fat fractions were also significantly different between HFD and LFD mice (3.1% ± 1.7% LFD vs. 27.2% ± 5.4% HFD, P = 0.002).

Conclusion:

RCFF can be used to quantitatively assess adipose tissue volumes and hepatic fat fractions in rodent models at 7T. J. Magn. Reson. Imaging 2012;35:837–843. © 2011 Wiley Periodicals, Inc.     

Novel segmentation method for abdominal fat quantification by MRI

Purpose:

To introduce and describe the feasibility of a novel method for abdominal fat segmentation on both water‐saturated and non–water‐saturated MR images with improved absolute fat tissue quantification.

Materials and Methods:

A general fat distribution model which fits both water‐saturated (WS) and non–water‐saturated (NWS) MR images based on image gray‐level histogram is first proposed. Next, a novel fuzzy c‐means clustering step followed by a simple thresholding is proposed to achieve automated and accurate abdominal quantification taking into consideration the partial‐volume effects (PVE) in abdominal MR images. Eleven subjects were scanned at central abdomen levels with both WS and NWS MRI techniques. Synthesized “noisy” NWS (nNWS) images were also generated to study the impact of reduced SNR on fat quantification using the novel approach. The visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) amounts of the WS MR images were quantified with a traditional intensity thresholding method as a reference to evaluate the performance of the novel method on WS, NWS, and nNWS MR images.

Results:

The novel approach resulted in consistent SAT and VAT amounts for WS, NWS, and nNWS images. Automatic segmentation and incorporation of spatial information during segmentation improved speed and accuracy. These results were in good agreement with those from the WS images quantified with a traditional intensity thresholding method and accounted for PVE contributions.

Conclusion:

The proposed method using a novel fuzzy c‐means clustering method followed by thresholding can achieve consistent quantitative results on both WS and NWS abdominal MR images while accounting for PVE contributing inaccuracies. J. Magn. Reson. Imaging 2011;. © 2011 Wiley‐Liss, Inc.     

Quantification of hepatic macrosteatosis in living,related liver donors using T1‐independent,T2*‐corrected chemical shift MRI

Purpose:

To evaluate the diagnostic implications of the iterative decomposition of water and fat using echo‐asymmetry and the least‐squares estimation (IDEAL) technique to detect hepatic steatosis (HS) in potential liver donors using histopathology as the reference standard.

Materials and Methods:

Forty‐nine potential liver donors (32 male, 17 female; mean age, 31.7 years) were included. All patients were imaged using the in‐ and out‐of‐phase (IOP) gradient‐echo (GRE) and IDEAL techniques on a 1.5 T MR scanner. To estimate the hepatic fat fraction (FF), two reviewers performed regions‐of‐interest measurement in 15 areas of the liver seen on the IOP images and on the IDEAL‐FF images. The magnetic resonance imaging (MRI) and pathology values of macrosteatosis were correlated using the Pearson correlation coefficient. We analyzed the diagnostic performance of IOP imaging and IDEAL for detecting HS.

Results:

The results of the hepatic‐FF estimated on IDEAL were well correlated with the histologic degree of macrosteatosis (γ = 0.902, P < 0.001). IDEAL showed 100% sensitivity and 91% specificity for detecting HS, and IOP imaging showed 87.5% sensitivity and 97% specificity, respectively.

Conclusion:

IDEAL is a useful tool for the preoperative diagnosis of HS in potential living liver donors; it can also help to avoid unnecessary biopsies in these patients. J. Magn. Reson. Imaging 2012;36:1124–1130. © 2012 Wiley Periodicals, Inc.     

Software for automated MRI‐based quantification of abdominal fat and preliminary evaluation in morbidly obese patients

Purpose:

To present software for supervised automatic quantification of visceral and subcutaneous adipose tissue (VAT, SAT) and evaluates its performance in terms of reliability, interobserver variation, and processing time, since fully automatic segmentation of fat‐fraction magnetic resonance imaging (MRI) is fast but susceptible to anatomical variations and artifacts, particularly for advanced stages of obesity.

Materials and Methods:

Twenty morbidly obese patients (average BMI 44 kg/m²) underwent 1.5‐T MRI using a double‐echo gradient‐echo sequence. Fully automatic analysis (FAA) required no user interaction, while supervised automatic analysis (SAA) involved review and manual correction of the FAA results by two observers. Standard of reference was provided by manual segmentation analysis (MSA).

Results:

Average processing times per patient were 6, 6+4, and 21 minutes for FAA, SAA, and MSA (P < 0.001), respectively. For VAT/SAT assessment, Pearson correlation coefficients, mean (bias), and standard deviations of the differences were R = 0.950, +0.003, and 0.043 between FAA and MSA and R = 0.981, +0.009, and 0.027 between SAA and MSA. Interobserver variation and intraclass correlation were 3.1% and 0.996 for SAA, and 6.6% and 0.986 for MSA, respectively.

Conclusion:

The presented supervised automatic approach provides a reliable option for MRI‐based fat quantification in morbidly obese patients and was much faster than manual analysis. J. Magn. Reson. Imaging 2013;37:1144–1150. © 2012 Wiley Periodicals, Inc.     

Improved time‐of‐flight magnetic resonance angiography with IDEAL water‐fat separation

Purpose

To implement IDEAL (iterative decomposition of water and fat using echo asymmetry and least squares estimation) water‐fat separation with 3D time‐of‐flight (TOF) magnetic resonance angiography (MRA) of intracranial vessels for improved background suppression by providing uniform and robust separation of fat signal that appears bright on conventional TOF‐MRA.

Materials and Methods

IDEAL TOF‐MRA and conventional TOF‐MRA were performed in volunteers and patients undergoing routine brain MRI/MRA on a 3T magnet. Images were reviewed by two radiologists and graded based on vessel visibility and image quality.

Results

IDEAL TOF‐MRA demonstrated statistically significant improvement in vessel visibility when compared to conventional TOF‐MRA in both volunteer and clinical patients using an image quality grading system. Overall image quality was 3.87 (out of 4) for IDEAL versus 3.55 for conventional TOF imaging (P = 0.02). Visualization of the ophthalmic artery was 3.53 for IDEAL versus 1.97 for conventional TOF imaging (P < 0.00005) and visualization of the superficial temporal artery was 3.92 for IDEAL imaging versus 1.97 for conventional TOF imaging (P < 0.00005).

Conclusion

By providing uniform suppression of fat, IDEAL TOF‐MRA provides improved background suppression with improved image quality when compared to conventional TOF‐MRA methods. J. Magn. Reson. Imaging 2009;29:1367–1374. © 2009 Wiley‐Liss, Inc.     

Impact of partial volume effects on visceral adipose tissue quantification using MRI

Purpose:

To quantitatively estimate the impact of partial volume effects on visceral adipose tissue (VAT) quantification using typical resolution magnetic resonance imaging (MRI).

Materials and Methods:

Nine normal or overweight subjects were scanned at central abdomen levels with a water‐saturated, balanced steady‐state free precession (b‐SSFP) sequence. The water‐saturation effectiveness was evaluated with region‐of‐interest analysis on fat, muscle, bowel, and noise areas. The number of full‐volume (FV) and partial‐volume (PV) fat pixels was estimated based on a gray‐level histogram model of water‐saturated images. Both FV and PV fat amounts were quantified.

Results:

High‐quality, fat‐only images were generated with the b‐SSFP imaging method. Fat SNR was 77.7 ± 25.6 and water‐saturation was effective, with the average fat‐to‐water signal intensity ratio = 20.7 ± 3.8. The average ratio of partial‐ to full‐volume fat amounts was 104.0%. The ratio was higher with lower body mass index (BMI) and PV fat amount only increased slightly when BMI increased.

Conclusion:

PV fat contributes a significant amount of fat to fat measurements on typical spatial resolution MRI on normal and overweight subjects. The relative PV fat contribution is markedly higher in slimmer patients. Inclusion of this portion of the adipose tissue will increase overall accuracy and decrease variability of VAT quantification using MRI. J. Magn. Reson. Imaging 2011;. © 2011 Wiley Periodicals, Inc.     

T2‐weighted 3D fast spin echo imaging with water–fat separation in a single acquisition

Purpose:

To develop a robust 3D fast spin echo (FSE) T₂‐weighted imaging method with uniform water and fat separation in a single acquisition, amenable to high‐quality multiplanar reformations.

Materials and Methods:

The Iterative Decomposition of water and fat with Echo Asymmetry and Least squares estimation (IDEAL) method was integrated with modulated refocusing flip angle 3D‐FSE. Echoes required for IDEAL processing were acquired by shifting the readout gradient with respect to the Carr‐Purcell‐Meiboom‐Gill echo. To reduce the scan time, an alternative data acquisition using two gradient echoes per repetition was implemented. Using the latter approach, a total of four gradient echoes were acquired in two repetitions and used in the modified IDEAL reconstruction.

Results:

3D‐FSE T₂‐weighted images with uniform water–fat separation were successfully acquired in various anatomies including breast, abdomen, knee, and ankle in clinically feasible scan times, ranging from 5:30–8:30 minutes. Using water‐only and fat‐only images, in‐phase and out‐of‐phase images were reconstructed.

Conclusion:

3D‐FSE‐IDEAL provides volumetric T₂‐weighted images with uniform water and fat separation in a single acquisition. High‐resolution images with multiple contrasts can be reformatted to any orientation from a single acquisition. This could potentially replace 2D‐FSE acquisitions with and without fat suppression and in multiple planes, thus improving overall imaging efficiency. J. Magn. Reson. Imaging 2010;32:745–751. © 2010 Wiley‐Liss, Inc.     

Improved fat suppression using multipeak reconstruction for IDEAL chemical shift fat‐water separation: Application with fast spin echo imaging

Purpose

To evaluate and quantify improvements in the quality of fat suppression for fast spin‐echo imaging of the knee using multipeak fat spectral modeling and IDEAL fat‐water separation.

Materials and Methods

T₁‐weighted and T₂‐weighted fast spin‐echo sequences with IDEAL fat‐water separation and two frequency‐selective fat‐saturation methods (fat‐selective saturation and fat‐selective partial inversion) were performed on 10 knees of five asymptomatic volunteers. The IDEAL images were reconstructed using a conventional single‐peak method and precalibrated and self‐calibrated multipeak methods that more accurately model the NMR spectrum of fat. The signal‐to‐noise ratio (SNR) was measured in various tissues for all sequences. Student t‐tests were used to compare SNR values.

Results

Precalibrated and self‐calibrated multipeak IDEAL had significantly greater suppression of signal (P < 0.05) within subcutaneous fat and bone marrow than fat‐selective saturation, fat‐selective partial inversion, and single‐peak IDEAL for both T₁‐weighted and T₂‐weighted fast spin‐echo sequences. For T₁‐weighted fast spin‐echo sequences, the improvement in the suppression of signal within subcutaneous fat and bone marrow for multipeak IDEAL ranged between 65% when compared to fat‐selective partial inversion to 86% when compared to fat‐selectivesaturation. For T2‐weighted fast spin‐echo sequences, the improvement for multipeak IDEAL ranged between 21% when compared to fat‐selective partial inversion to 81% when compared to fat‐selective saturation.

Conclusion

Multipeak IDEAL fat‐water separation provides improved fat suppression for T₁‐weighted and T₂‐weighted fast spin‐echo imaging of the knee when compared to single‐peak IDEAL and two widely used frequency‐selected fat‐saturation methods. J. Magn. Reson. Imaging 2009;29:436–442. © 2009 Wiley‐Liss, Inc.     

Characterization of the regional distribution of skeletal muscle adipose tissue in type 2 diabetes using chemical shift-based water/fat separation

Purpose:

To show the feasibility of assessing the spatial distribution of skeletal muscle adipose tissue using chemical shift‐based water/fat separation and to characterize differences in calf intermuscular adipose tissue (IMAT) compartmentalization in patients with type 2 diabetes mellitus (T2DM) compared to healthy age‐matched controls.

Materials and Methods:

A chemical shift‐based water/fat separation approach using a multiecho 3D spoiled gradient echo sequence was applied in a study of 64 patients, including 35 healthy controls and 29 subjects with T2DM. Masks were defined based on manual segmentations to compute fat volume within different compartments, including regions of subcutaneous adipose tissue (SAT) and six muscular regions. IMAT was divided into two compartments representing fat within the muscular regions (intraMF) and fat between the muscular regions (interMF). Two‐sample Student's t‐tests were used to compare fat volumes between the two groups.

Results:

The subjects with T2DM had a lower volume of SAT compared to the healthy controls (P = 4 × 10^?5). There was no statistically significant difference in the IMAT volume between the two groups. However, the intraMF volume normalized by the IMAT volume was higher in the diabetics compared to the controls (P = 0.006).

Conclusion:

Chemical shift‐based water/fat separation enables the quantification of fat volume within localized muscle regions, showing that the IMAT regional distribution is significantly different in T2DM compared to normal controls. J. Magn. Reson. Imaging 2012;35:899–907. © 2011 Wiley Periodicals, Inc.