Differentiation of Vertebral Metastases From Focal Hematopoietic Marrow Depositions on MRI: Added Value of Proton Density Fat Fraction.

OBJECTIVE. The purpose of this study was to evaluate the added value of proton density fat fraction (PDFF) in differentiating vertebral metastases from focal hematopoietic marrow depositions. MATERIALS AND METHODS. The study included 44 patients with 30 vertebral metastases and 14 focal hematopoietic marrow depositions who underwent spinal MRI. The final diagnoses were based on histologic confirmation, follow-up MRI, or PET/CT. Two musculoskeletal radiologists with 1 and 15 years of experience independently interpreted both image sets (i.e., images from conventional MRI alone versus images from conventional MRI and PDFF combined). Using a 5-point scale, the readers scored their confidence in the malignancy of the vertebral lesions. The diagnostic performance (AUC) of the two image sets was assessed via ROC curve analyses. Sensitivities, specificities, and accuracies (for both image sets) were compared using the McNemar test. Kappa coefficients were calculated to assess interobserver agreement. RESULTS. Both readers showed improved diagnostic performance after PDFF was added (AUC, 0.840-0.912 and 0.805-0.895 for readers 1 and 2, respectively). However, adding PDFF did not significantly improve the sensitivity and specificity of either reader (p > .05). Interobserver agreement significantly improved from moderate (κ = 0.563) to excellent (κ = 0.947) after PDFF was added. CONCLUSION. The addition of PDFF to a conventional MRI protocol improved the diagnostic performance for differentiating vertebral metastases from focal hematopoietic marrow depositions but without resulting in significant improvement in sensitivity and specificity.

The Water-Fat Separation Method for Determining the Fat-free Component of Subcutaneous Adipose Tissue in Humans: A Brief Review.

Fat-free mass as well as lean soft tissue mass is a surrogate for skeletal muscle mass and is often used for the normalization of several physiological variables or for the diagnosing of low muscle mass in older adults. However, both fat-free mass and lean tissue mass include nonskeletal muscle components such as the fat-free component of adipose tissue fat cells. A technique known as water-fat MRI provides a noninvasive and radiation-free assessment of the fat-free component of adipose tissue in humans. However, if this method is impractical or unavailable, some authors suggest that a constant value for the fat-free component of adipose tissue can be used as an indirect estimate. The purpose of this review is to examine the fat fraction percentage of white (subcutaneous) adipose tissue in adolescents and young/middle-aged/older adults measured by water-fat MRI and provide discussion on how the fat-free adipose tissue values from the water-fat separation method compare with the constant value used in previous studies. Calculated mean values for the percentage of fat fraction in subcutaneous adipose tissue were 86.9% in the overall sample, 86.4% in adolescents (3 studies), and 87.1% in young, middle-aged and older adults (7 studies). This is similar to the 85% value proposed in the classical studies but in the majority of studies the 85% estimate was outside of the 95% confidence interval (CI) of the water-fat MRI estimate. There may be several factors to consider that may affect the fat fraction percentage (e.g. reliability of the MRI estimate, age, sex, obesity, etc.), however, at this time there is insufficient evidence to determine the effect of each of these variables. If the measurement is reliable, then this might suggest that the 85% constant may need to be altered to better reflect the water-fat MRI estimate.

Fully convolutional networks for automated segmentation of abdominal adipose tissue depots in multicenter water-fat MRI.

PURPOSE: An approach for the automated segmentation of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in multicenter water-fat MRI scans of the abdomen was investigated, using 2 different neural network architectures. METHODS: The 2 fully convolutional network architectures U-Net and V-Net were trained, evaluated, and compared using the water-fat MRI data. Data of the study Tellus with 90 scans from a single center was used for a 10-fold cross-validation in which the most successful configuration for both networks was determined. These configurations were then tested on 20 scans of the multicenter study beta-cell function in JUvenile Diabetes and Obesity (BetaJudo), which involved a different study population and scanning device. RESULTS: The U-Net outperformed the used implementation of the V-Net in both cross-validation and testing. In cross-validation, the U-Net reached average dice scores of 0.988 (VAT) and 0.992 (SAT). The average of the absolute quantification errors amount to 0.67% (VAT) and 0.39% (SAT). On the multicenter test data, the U-Net performs only slightly worse, with average dice scores of 0.970 (VAT) and 0.987 (SAT) and quantification errors of 2.80% (VAT) and 1.65% (SAT). CONCLUSION: The segmentations generated by the U-Net allow for reliable quantification and could therefore be viable for high-quality automated measurements of VAT and SAT in large-scale studies with minimal need for human intervention. The high performance on the multicenter test data furthermore shows the robustness of this approach for data of different patient demographics and imaging centers, as long as a consistent imaging protocol is used.

Comparison of modified two-point dixon and chemical shift encoded MRI water-fat separation methods for fetal fat quantification.

BACKGROUND: Fetal fat is indicative of the energy balance within the fetus, which may be disrupted in pregnancy complications such as fetal growth restriction, macrosomia, and gestational diabetes. Water-fat separated MRI is a technique sensitive to tissue lipid content, measured as fat fraction (FF), and can be used to accurately measure fat volumes. Modified two-point Dixon and chemical shift encoded MRI (CSE-MRI) are water-fat separated MRI techniques that could be applied to imaging of fetal fat. Modified two-point Dixon has biases present that are corrected in CSE-MRI which may contribute to differences in the fat measurements. PURPOSE: To compare the measurement of fetal fat volume and FF by modified two-point Dixon and CSE-MRI. STUDY TYPE: Cross-sectional study for comparison of two MRI pulse sequences. POPULATION: Twenty-one pregnant women with singleton pregnancies. FIELD STRENGTH/SEQUENCE: 1.5T, modified two-point Dixon and CSE-MRI. ASSESSMENT: Manual segmentation of total fetal fat volume and mean FF from modified 2-point Dixon and CSE-MRI FF images. STATISTICAL TESTS: Reliability was assessed by calculating the intraclass correlation coefficient (ICC). Agreement was assessed using a one-sample t-test on the fat measurements difference values (modified two-point Dixon - CSE-MRI). The difference scores were tested against a value of 0, which would indicate that the measurements were identical. RESULTS: The fat volume and FF measured by modified two-point Dixon and CSE-MRI had excellent reliability, demonstrated by ICCs of 0.93 (P < 0.001) and 0.90 (P < 0.001), respectively. They were not in agreement, with CSE-MRI giving mean fat volumes 180 mL greater and mean FF 3.0% smaller than modified two-point Dixon. DATA CONCLUSION: The reliability between modified two-point Dixon and CSE-MRI indicates that either technique can be used to compare fetal fat measurements in different participants, but they are not in agreement possibly due to uncorrected biases in modified two-point Dixon. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018.

Accelerating multi-echo water-fat MRI with a joint locally low-rank and spatial sparsity-promoting reconstruction.

OBJECTIVES: Our aim was to demonstrate the benefits of using locally low-rank (LLR) regularization for the compressed sensing reconstruction of highly-accelerated quantitative water-fat MRI, and to validate fat fraction (FF) and [Formula: see text] relaxation against reference parallel imaging in the abdomen. MATERIALS AND METHODS: Reconstructions using spatial sparsity regularization (SSR) were compared to reconstructions with LLR and the combination of both (LLR+SSR) for up to seven fold accelerated 3-D bipolar multi-echo GRE imaging. For ten volunteers, the agreement with the reference was assessed in FF and [Formula: see text] maps. RESULTS: LLR regularization showed superior noise and artifact suppression compared to reconstructions using SSR. Remaining residual artifacts were further reduced in combination with SSR. Correlation with the reference was excellent for FF with [Formula: see text] = 0.99 (all methods) and good for [Formula: see text] with [Formula: see text] = [0.93, 0.96, 0.95] for SSR, LLR and LLR+SSR. The linear regression gave slope and bias (%) of (0.99, 0.50), (1.01, 0.19) and (1.01, 0.10), and the hepatic FF/[Formula: see text] standard deviation was 3.5%/12.1 s[Formula: see text], 1.9%/6.4 s[Formula: see text] and 1.8%/6.3 s[Formula: see text] for SSR, LLR and LLR+SSR, indicating the least bias and highest SNR for LLR+SSR. CONCLUSION: A novel reconstruction using both spatial and spectral regularization allows obtaining accurate FF and [Formula: see text] maps for prospectively highly accelerated acquisitions.

[Value of mDIXON-Quant sequence, diffusion-weighted imaging in quantitatively diagnosing the sacroiliitis stages].

Objective: To evaluate the value of mDIXON-Quant sequence, diffusion-weighted imaging (DWI) in quantitative diagnosing of the sacroiliitis stages in patients with ankylosing spondylitis (AS). Methods: Based on the Bath Ankylosing Spondylitis Activity Index (BASDAI) and laboratory parameters, a total of 51 patients were diagnosed with AS. They were divided into two groups as early active group (n=20) and chronic active group (n=31), and at the same time, 25 healthy people from Tianjin were included as control group. The regular MRI sequences and mDIXON-Quant sequence, DWI were obtained. The apparent diffusion coefficient (ADC) and fat-signal fraction (FF) value of bone marrow with edema of the sacroiliac joints in early active group and chronic active group and of subchondral bone marrow of sacroiliac joint in control group all were measured by ADC maps and FF maps. Mean (FF, ADC) values were compared between groups. Results: The ADC value of the early active group, chronic active group and the control group is (1.07±0.20)×10(-3)mm(2)/s, (1.00±0.22)×10(-3)mm(2)/s, (0.25±0.07)×10(-3)mm(2)/s, respectively, and the differences of ADC value between early active group and control group, chronic active group and control group were significant (P<0.01), but the difference of the ADC value between early active group and chronic active group was not significant (P=0.394). That is to say, the ADC value can't distinguish the early active group and chronic active group. The differences of FF value between groups was significant (P<0.01), and the FF value of bone marrow with edema in chronic active group were higher than that in early active group. Conclusions: The mDIXON-Quant sequence can quantitatively diagnose early active group and chronic active group, and the diagnostic value is better than DWI. Thus, it can provide guidance for clinical treatment and prognosis.

Characterization of brown adipose tissue by water-fat separated magnetic resonance imaging.

BACKGROUND: To evaluate the possibility of quantifying brown adipose tissue (BAT) volume and fat concentration with a high resolution, long echo time, dual-echo Dixon imaging protocol. METHODS: A 0.42 mm isotropic resolution water-fat separated MRI protocol was implemented by using the second opposite-phase echo and third in-phase echo. Fat images were calibrated with regard to the intensity of nearby white adipose tissue (WAT) to form relative fat content (RFC) images. To evaluate the ability to measure BAT volume and RFC contrast dynamics, rats were divided into two groups that were kept at 4° or 22°C for 5 days. The rats were then scanned in a 70 cm bore 3.0 Tesla MRI scanner and a human dual energy CT. Interscapular, paraaortal, and perirenal BAT (i/pa/pr-BAT) depots as well as WAT and muscle were segmented in the MRI and CT images. Biopsies were collected from the identified BAT depots. RESULTS: The biopsies confirmed that the three depots identified with the RFC images consisted of BAT. There was a significant linear correlation (P < 0.001) between the measured RFC and the Hounsfield units from DECT. Significantly lower iBAT RFC (P = 0.0064) and significantly larger iBAT and prBAT volumes (P = 0.0017) were observed in the cold stimulated rats. CONCLUSION: The calibrated Dixon images with RFC scaling can depict BAT and be used to measure differences in volume, and fat concentration, induced by cold stimulation. The high correlation between RFC and HU suggests that the fat concentration is the main RFC image contrast mechanism.

Thresholding approaches for estimating paraspinal muscle fat infiltration using T1- and T2-weighted MRI: Comparative analysis using water-fat MRI.

Background: Paraspinal muscle fat infiltration is associated with spinal degeneration and low back pain, however, quantifying muscle fat using clinical magnetic resonance imaging (MRI) techniques continues to be a challenge. Advanced MRI techniques, including chemical-shift encoding (CSE) based water-fat MRI, enable accurate measurement of muscle fat, but such techniques are not widely available in routine clinical practice. Methods: To facilitate assessment of paraspinal muscle fat using clinical imaging, we compared four thresholding approaches for estimating muscle fat fraction (FF) using T1- and T2-weighted images, with measurements from water-fat MRI as the ground truth: Gaussian thresholding, Otsu's method, K-mean clustering, and quadratic discriminant analysis. Pearson's correlation coefficients (r), mean absolute errors, and mean bias errors were calculated for FF estimates from T1- and T2-weighted MRI with water-fat MRI for the lumbar multifidus (MF), erector spinae (ES), quadratus lumborum (QL), and psoas (PS), and for all muscles combined. Results: We found that for all muscles combined, FF measurements from T1- and T2-weighted images were strongly positively correlated with measurements from the water-fat images for all thresholding techniques (r = 0.70-0.86, p < 0.0001) and that variations in inter-muscle correlation strength were much greater than variations in inter-method correlation strength. Conclusion: We conclude that muscle FF can be quantified using thresholded T1- and T2-weighted MRI images with relatively low bias and absolute error in relation to water-fat MRI, particularly in the MF and ES, and the choice of thresholding technique should depend on the muscle and clinical MRI sequence of interest.

Brown adipose tissue mapping in rats with combined intermolecular double-quantum coherence and Dixon water-fat MRI.

Brown adipose tissue (BAT) is a promising therapeutic target in obesity studies. Recently, MRI has been proposed for the mapping of BAT. However, because of the limitation of spatial resolution, similar to the existing positron emission tomography and computed tomography techniques for BAT detection, it fails to distinguish BAT cells when they are mixed with other cells. In this work, a new MRI method is proposed, combining intermolecular double-quantum coherence and the chemical shift-encoded Dixon method. Its contrast depends on the water to fat ratio at the cellular scale, which is smaller than the imaging voxel size. The feasibility of this MRI method was shown with computer simulations and phantoms, and preliminary imaging of BAT of rats at 7 T. Both computer simulations and experimental results are consistent with theoretical predictions. The method provides a novel contrast mechanism and can map BAT distribution exclusively. In particular, a mixture of BAT cells and white adipose tissue cells was detected in an older rat, which was undetectable by other noninvasive methods. This method may be applicable to a wide range of uses in BAT-related studies, including the formation and variation of BAT.

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.

Comparison of brown and white adipose tissues in infants and children with chemical-shift-encoded water-fat MRI.

PURPOSE: To compare fat-signal fractions (FFs) and T2* values between brown (BAT) and white (WAT) adipose tissue located within the supraclavicular fossa and subcutaneous depots, respectively. MATERIALS AND METHODS: Twelve infants and 39 children were studied. Children were divided into lean and overweight/obese subgroups. Chemical-shift-encoded water-fat magnetic resonance imaging (MRI) was used to quantify FFs and T2* metrics in the supraclavicular and adjacent subcutaneous adipose tissue depots. Linear regression and t-tests were performed. RESULTS: Infants had lower supraclavicular FFs than children (P < 0.01) but T2* values were similar (P = 0.5). Lean children exhibited lower supraclavicular FFs and T2* values than overweight children (P < 0.01). In each individual infant and child, supraclavicular FFs were consistently lower than adjacent subcutaneous FFs. Supraclavicular T2* values were consistently lower than subcutaneous T2* values in children, but not in infants. FFs in both depots were positively correlated with age and weight in infants (P < 0.01). In children, they were correlated with weight and body mass index (BMI) (P < 0.01), but not age. Correlations between T2* and anthropometric variables existed in children (P < 0.01), but were absent in infants. CONCLUSION: Cross-sectional comparisons suggest variations in FF and T2* values in the supraclavicular and subcutaneous depots of infants and children, which are potentially indicative of physiological differences in adipose tissue fat content, amount, and metabolic activity.

Measurement of interscapular brown adipose tissue of mice in differentially housed temperatures by chemical-shift-encoded water-fat MRI.

PURPOSE: To determine differences in fat-signal fraction (FF) from chemical-shift-encoded water-fat MRI of interscapular BAT in mice housed at different ambient temperatures (Ta ). MATERIALS AND METHODS: C57BL/6J male mice (8 weeks old) were singly housed at 16°C, 23°C, or 30°C (n = 16/group) for 4 weeks. Measures included food intake, body weight (both measured weekly) and body composition (at baseline, 2, and 4 weeks post-thermal exposure); chemical-shift-encoded water-fat MRI was performed on a 9.4 Tesla Bruker magnet with respiratory gating and anesthesia at 4 weeks post-thermal exposure. RESULTS: A significant inverse relationship between food intake and Ta was evidenced (P < 0.0001). Lean mass was similar among groups, while total fat mass was significantly different among groups ([mean ± SE]: 30°C = 5.10 ± 0.19 g; 23°C = 4.18 ± 0.16 g; 16°C = 3.48 ± 0.54 g; P < 0.0001). Mean BAT-FF was positively related to Ta (means: 30°C = 79.4%; 23°C = 61.8%; 16°C = 50.9%; P < 0.0001). CONCLUSION: These cross-sectional results demonstrate that MRI measurement of FF within the interscapular BAT in mice reflects recent functional status of the tissue, with a lower Ta leading to a significantly reduced BAT-FF, indicative of the tissue's involvement in thermogenesis.

A fully convolutional neural network for comprehensive compartmentalization of abdominal adipose tissue compartments in MRI.

BACKGROUND: Existing literature has highlighted structural, physiological, and pathological disparities among abdominal adipose tissue (AAT) sub-depots. Accurate separation and quantification of these sub-depots are crucial for advancing our understanding of obesity and its comorbidities. However, the absence of clear boundaries between the sub-depots in medical imaging data has challenged their separation, particularly for internal adipose tissue (IAT) sub-depots. To date, the quantification of AAT sub-depots remains challenging, marked by a time-consuming, costly, and complex process. PURPOSE: To implement and evaluate a convolutional neural network to enable granular assessment of AAT by compartmentalization of subcutaneous adipose tissue (SAT) into superficial subcutaneous (SSAT) and deep subcutaneous (DSAT) adipose tissue, and IAT into intraperitoneal (IPAT), retroperitoneal (RPAT), and paraspinal (PSAT) adipose tissue. MATERIAL AND METHODS: MRI datasets were retrospectively collected from Singapore Preconception Study for Long-Term Maternal and Child Outcomes (S-PRESTO: 389 women aged 31.4 ± 3.9 years) and Singapore Adult Metabolism Study (SAMS: 50 men aged 28.7 ± 5.7 years). For all datasets, ground truth segmentation masks were created through manual segmentation. A Res-Net based 3D-UNet was trained and evaluated via 5-fold cross-validation on S-PRESTO data (N = 300). The model's final performance was assessed on a hold-out (N = 89) and an external test set (N = 50, SAMS). RESULTS: The proposed method enabled reliable segmentation of individual AAT sub-depots in 3D MRI volumes with high mean Dice similarity scores of 98.3%, 97.2%, 96.5%, 96.3%, and 95.9% for SSAT, DSAT, IPAT, RPAT, and PSAT respectively. CONCLUSION: Convolutional neural networks can accurately sub-divide abdominal SAT into SSAT and DSAT, and abdominal IAT into IPAT, RPAT, and PSAT with high accuracy. The presented method has the potential to significantly contribute to advancements in the field of obesity imaging and precision medicine.

Quantitative Muscle MRI in Patients with Neuromuscular Diseases-Association of Muscle Proton Density Fat Fraction with Semi-Quantitative Grading of Fatty Infiltration and Muscle Strength at the Thigh Region.

(1) Background and Purpose: The skeletal muscles of patients suffering from neuromuscular diseases (NMD) are affected by atrophy, hypertrophy, fatty infiltration, and edematous changes. Magnetic resonance imaging (MRI) is an important tool for diagnosis and monitoring. Concerning fatty infiltration, T1-weighted or T2-weighted DIXON turbo spin echo (TSE) sequences enable a qualitative assessment of muscle involvement. To achieve higher comparability, semi-quantitative grading scales, such as the four-point Mercuri scale, are commonly applied. However, the evaluation remains investigator-dependent. Therefore, effort is being invested to develop quantitative MRI techniques for determination of imaging markers such as the proton density fat fraction (PDFF). The present work aims to assess the diagnostic value of PDFF in correlation to Mercuri grading and clinically determined muscle strength in patients with myotonic dystrophy type 2 (DM2), limb girdle muscular dystrophy type 2A (LGMD2A), and adult Pompe disease. (2) Methods: T2-weighted two-dimensional (2D) DIXON TSE and chemical shift encoding-based water-fat MRI were acquired in 13 patients (DM2: n = 5; LGMD2A: n = 5; Pompe disease: n = 3). Nine different thigh muscles were rated in all patients according to the Mercuri grading and segmented to extract PDFF values. Muscle strength was assessed according to the British Medical Research Council (BMRC) scale. For correlation analyses between Mercuri grading, muscle strength, and PDFF, the Spearman correlation coefficient (rs) was computed. (3) Results: Mean PDFF values ranged from 7% to 37% in adults with Pompe disease and DM2 and up to 79% in LGMD2A patients. In all three groups, a strong correlation of the Mercuri grading and PDFF values was observed for almost all muscles (rs > 0.70, p < 0.05). PDFF values correlated significantly to muscle strength for muscle groups responsible for knee flexion (rs = -0.80, p < 0.01). (4) Conclusion: In the small, investigated patient cohort, PDFF offers similar diagnostic precision as the clinically established Mercuri grading. Based on these preliminary data, PDFF could be further considered as an MRI-based biomarker in the assessment of fatty infiltration of muscle tissue in NMD. Further studies with larger patient cohorts are needed to advance PDFF as an MRI-based biomarker in NMD, with advantages such as its greater dynamic range, enabling the assessment of subtler changes, the amplified objectivity, and the potential of direct correlation to muscle function for selected muscles.

Automated Segmentation of Visceral, Deep Subcutaneous, and Superficial Subcutaneous Adipose Tissue Volumes in MRI of Neonates and Young Children.

PURPOSE: To develop and evaluate an automated segmentation method for accurate quantification of abdominal adipose tissue (AAT) depots (superficial subcutaneous adipose tissue [SSAT], deep subcutaneous adipose tissue [DSAT], and visceral adipose tissue [VAT]) in neonates and young children. MATERIALS AND METHODS: This was a secondary analysis of prospectively collected data, which used abdominal MRI data from Growing Up in Singapore Towards healthy Outcomes, or GUSTO, a longitudinal mother-offspring cohort, to train and evaluate a convolutional neural network for volumetric AAT segmentation. The data comprised imaging volumes of 333 neonates obtained at early infancy (age ≤2 weeks, 180 male neonates) and 755 children aged either 4.5 years (n = 316, 150 male children) or 6 years (n = 439, 219 male children). The network was trained on images of 761 randomly selected volumes (neonates and children combined) and evaluated on 100 neonatal volumes and 227 child volumes by using 10-fold validation. Automated segmentations were compared with expert-generated manual segmentation. Segmentation performance was assessed using Dice scores. RESULTS: When the model was tested on the test datasets across the 10 folds, the model had strong agreement with the ground truth for all testing sets, with mean Dice similarity scores for SSAT, DSAT, and VAT, respectively, of 0.960, 0.909, and 0.872 in neonates and 0.944, 0.851, and 0.960 in children. The model generalized well to different body sizes and ages and to all abdominal levels. CONCLUSION: The proposed segmentation approach provided accurate automated volumetric assessment of AAT compartments on MR images of neonates and children.Keywords Pediatrics, Deep Learning, Convolutional Neural Networks, Water-Fat MRI, Image Segmentation, Deep and Superficial Subcutaneous Adipose Tissue, Visceral Adipose TissueClinical trial registration no. NCT01174875 Supplemental material is available for this article. © RSNA, 2021.

Regional variation of thigh muscle fat infiltration in patients with neuromuscular diseases compared to healthy controls.

BACKGROUND: Chemical shift encoding-based water-fat magnetic resonance imaging (CSE-MRI) measures a quantitative biomarker: the proton density fat fraction (PDFF). The aim was to assess regional and proximo-distal PDFF variations at the thigh in patients with myotonic dystrophy type 2 (DM2), limb-girdle muscular dystrophy type 2A (LGMD2A), and late-onset Pompe disease (LOPD) as compared to healthy controls. METHODS: Seven patients (n=2 DM2, n=2 LGMD2A, n=3 LOPD) and 20 controls were recruited. A 3D-spoiled gradient echo sequence was used to scan the thigh musculature. Muscles were manually segmented to generate mean muscle PDFF. RESULTS: In all three disease entities, there was an increase in muscle fat replacement compared to healthy controls. However, within each disease group, there were patients with a shorter time since symptom onset that only showed mild PDFF elevation (range, 10% to 20%) compared to controls (P≤0.05), whereas patients with a longer period since symptom onset showed a more severe grade of fat replacement with a range of 50% to 70% (P<0.01). Increased PDFF of around 5% was observed for vastus medialis, semimembranosus and gracilis muscles in advanced compared to early DM2. LGMD2A_1 showed an early disease stage with predominantly mild PDFF elevations over all muscles and levels (10.9%±7.1%) compared to controls. The quadriceps, gracilis and biceps femoris muscles showed the highest difference between LGMD2A_1 with 5 years since symptom onset (average PDFF 11.1%±6.9%) compared to LGMD2A_2 with 32 years since symptom onset (average PDFF 66.3%±6.3%). For LOPD patients, overall PDFF elevations were observed in all major hip flexors and extensors (range, 25.8% to 30.8%) compared to controls (range, 1.7% to 2.3%, P<0.05). Proximal-to-distal PDFF highly varied within and between diseases and within controls. The intra-reader reliability was high (reproducibility coefficient ≤2.19%). CONCLUSIONS: By quantitatively measuring muscle fat infiltration at the thigh, we identified candidate muscles for disease monitoring due to their gradual PDFF elevation with longer disease duration. Regional variation between proximal, central, and distal muscle PDFF was high and is important to consider when performing longitudinal MRI follow-ups in the clinical setting or in longitudinal studies.

Measuring fetal adipose tissue using 3D water-fat magnetic resonance imaging: a feasibility study.

Purpose: Analysis of fetal adipose tissue volumes may provide useful insight towards assessment of overall fetal health, especially in cases with abnormal fetal growth. Here, we assess whether fetal adipose tissue volume can be reliably measured using 3D water-fat MRI, using a quantitative assessment of the lipid content of tissues.Materials and methods: Seventeen women with singleton pregnancies underwent a fetal MRI and water-only and fat-only images were acquired (modified 2-point Dixon technique). Water and fat images were used to generate a fat signal fraction (fat/(water + fat)) from which subcutaneous adipose tissue was segmented along the fetal trunk. Inter-rater (three readers) and intrarater reliability was assessed using intraclass-correlation coefficients (ICC) for 10 image sets. Relationships between adipose tissue measurements and gestational age and estimated fetal weight percentiles were examined.Results: The ICC of the inter-rater reliability was 0.936 (p < .001), and the ICC of the intrarater reliability was 0.992 (p < .001). Strong positive correlations were found between adipose tissue measurements (lipid volume, lipid volume/total fetal volume, mean fat signal fraction) and gestational age.Conclusions: 3D water-fat MRI can reliably measure volume and quantify lipid content of fetal subcutaneous adipose tissues.

Validation of marrow fat assessment using noninvasive imaging with histologic examination of human bone samples.

PURPOSE: The marrow composition throughout the body is heterogeneous and changes with age. Due to heterogeneity, invasive biopsies of the iliac crest do not truly represent the complete physiological status, impeding the clinical effectiveness of this method. Therefore, we aim to provide verification for an in vivo imaging technique using co-registered histologic examinations for assessment of marrow adiposity. METHODS: Five recently expired (i.e. <24h) human cadavers were scanned with a dual source CT (DECT) scanner in order to measure marrow fat in the lumbar vertebrae. These donors were also imaged using water-fat MRI (wfMRI) which was used to estimate the fraction of yellow marrow. After imaging, lumbar columns were excised and the superior and inferior aspects of 21 vertebrae were removed. The remaining center section was processed for histological examination to find the ratio of adipocyte volume per tissue volume (AV/TV). RESULTS: Results of DECT and wfMRI had a high correlation (r = 0.88). AV/TV ranged from 0.18 to 0.75 with a mean (SD) of 0.36 (0.18). Inter-evaluator reliability for AV/TV was r > 0.984. There were similar correlations between AV/TV and the imaging modalities, DECT-derived MF and wfMRI (r = 0.802 and 0.772, respectively). CONCLUSIONS: A high MF variation was seen among the 25 vertebrae imaged. Both DECT and wfMRI have a good correlation with the histologic adipocyte proportion and can be used to measure MF. This makes longitudinal studies possible without painful, less-effective, invasive biopsies.

A phase I feasibility study of multi-modality imaging assessing rapid expansion of marrow fat and decreased bone mineral density in cancer patients.

PURPOSE: Cancer survivors are at an increased risk for fractures, but lack of effective and economical biomarkers limits quantitative assessments of marrow fat (MF), bone mineral density (BMD) and their relation in response to cytotoxic cancer treatment. We report dual energy CT (DECT) imaging, commonly used for cancer diagnosis, treatment and surveillance, as a novel biomarker of MF and BMD. METHODS: We validated DECT in pre-clinical and phase I clinical trials and verified with water-fat MRI (WF-MRI), quantitative CT (QCT) and dual-energy X-ray absorptiometry (DXA). Basis material composition framework was validated using water and small-chain alcohols simulating different components of bone marrow. Histologic validation was achieved by measuring percent adipocyte in the cadaver vertebrae and compared with DECT and WF-MRI. For a phase I trial, sixteen patients with gynecologic malignancies (treated with oophorectomy, radiotherapy or chemotherapy) underwent DECT, QCT, WF-MRI and DXA before and 12months after treatment. BMD and MF percent and distribution were quantified in the lumbar vertebrae and the right femoral neck. RESULTS: Measured precision (3mg/cm(3)) was sufficient to distinguish test solutions. Adiposity in cadaver bone histology was highly correlated with MF measured using DECT and WF-MRI (r=0.80 and 0.77, respectively). In the clinical trial, DECT showed high overall correlation (r=0.77, 95% CI: 0.69, 0.83) with WF-MRI. MF increased significantly after treatment (p<0.002). Chemotherapy and radiation caused greater increases in MF than oophorectomy (p<0.032). L4 BMD decreased 14% by DECT, 20% by QCT, but only 5% by DXA (p<0.002 for all). At baseline, we observed a statistically significant inverse association between MF and BMD which was dramatically attenuated after treatment. CONCLUSION: Our study demonstrated that DECT, similar to WF-MRI, can accurately measure marrow adiposity. Both imaging modalities show rapid increase in MF following cancer treatment. Our results suggest that MF and BMD cannot be used interchangeably to monitor skeletal health following cancer therapy.

Heterogeneity of muscle fat infiltration in children with spina bifida.

Children with spina bifida have well recognized functional deficits of muscle, but little is known about the associated changes in muscle anatomy and composition. This study used water-fat magnetic resonance imaging (MRI) to measure fat infiltration in the lower extremity muscles of 11 children with myelomeningocele, the most severe form of spina bifida. MRI measurements of muscle fat fraction (FF) were compared against manual muscle test (MMT) scores for muscle strength. The FF measurements were objective and reliable with mean inter-rater differences of <2% and intraclass correlation coefficients>0.98. There was a significant inverse relationship between muscle FF and MMT scores (P ≤ 0.001). Surprisingly, however, muscles with negligible strength (MMT 0-1) exhibited a bimodal distribution of FF with one group having FF>70% and another group having FF<20%. The MRI also revealed striking heterogeneity amongst individual muscles in the same muscle group (e.g., 4% fat in one participant's lateral gastrocnemius vs. 88% in her medial gastrocnemius), as well as significant asymmetry in FF in one participant with asymmetric strength and sensation. These results suggest that quantitative water-fat MRI may serve as a biomarker for muscle degeneration which may reveal subclinical changes useful for predicting functional potential and prognosis.