Correlations between quantitative fat-water magnetic resonance imaging and computed tomography in human subcutaneous white adipose tissue

Brown Adipose Tissue-A Translational Perspective

Brown adipose tissue (BAT) displays the unique capacity to generate heat through uncoupled oxidative phosphorylation that makes it a very attractive therapeutic target for cardiometabolic diseases. Here, we review BAT cellular metabolism, its regulation by the central nervous and endocrine systems and circulating metabolites, the plausible roles of this tissue in human thermoregulation, energy balance, and cardiometabolic disorders, and the current knowledge on its pharmacological stimulation in humans. The current definition and measurement of BAT in human studies relies almost exclusively on BAT glucose uptake from positron emission tomography with 18F-fluorodeoxiglucose, which can be dissociated from BAT thermogenic activity, as for example in insulin-resistant states. The most important energy substrate for BAT thermogenesis is its intracellular fatty acid content mobilized from sympathetic stimulation of intracellular triglyceride lipolysis. This lipolytic BAT response is intertwined with that of white adipose (WAT) and other metabolic tissues, and cannot be independently stimulated with the drugs tested thus far. BAT is an interesting and biologically plausible target that has yet to be fully and selectively activated to increase the body's thermogenic response and shift energy balance. The field of human BAT research is in need of methods able to directly, specifically, and reliably measure BAT thermogenic capacity while also tracking the related thermogenic responses in WAT and other tissues. Until this is achieved, uncertainty will remain about the role played by this fascinating tissue in human cardiometabolic diseases.

Robust water-fat separation based on deep learning model exploring multi-echo nature of mGRE

PURPOSE

To design a new deep learning network for fast and accurate water-fat separation by exploring the correlations between multiple echoes in multi-echo gradient-recalled echo (mGRE) sequence and evaluate the generalization capabilities of the network for different echo times, field inhomogeneities, and imaging regions.

METHODS

A new multi-echo bidirectional convolutional residual network (MEBCRN) was designed to separate water and fat images in a fast and accurate manner for the mGRE data. This new MEBCRN network contains 2 main modules, the first 1 is the feature extraction module, which learns the correlations between consecutive echoes, and the other one is the water-fat separation module that processes the feature information extracted from the feature extraction module. The multi-layer feature fusion (MLFF) mechanism and residual structure were adopted in the water-fat separation module to increase separation accuracy and robustness. Moreover, we trained the network using in vivo abdomen images and tested it on the abdomen, knee, and wrist images.

RESULTS

The results showed that the proposed network could separate water and fat images accurately. The comparison of the proposed network and other deep learning methods shows the advantage in both quantitative metrics and robustness for different TEs, field inhomogeneities, and images acquired for various imaging regions.

CONCLUSION

The proposed network could learn the correlations between consecutive echoes and separate water and fat images effectively. The deep learning method has certain generalization capabilities for TEs and field inhomogeneity. Although the network was trained only in vivo abdomen images, it could be applied for different imaging regions.

Visceral Adipose Tissue Radiodensity Is Linked to Prognosis in Hepatocellular Carcinoma Patients Treated with Selective Internal Radiation Therapy

Hepatocellular carcinoma (HCC) constitutes the fourth leading cause of cancer-related mortality. Various factors, such as tumor size, tumor multiplicity, and liver function, have been linked to the prognosis of HCC. The aim of this study was to explore the prognostic significance of muscle, subcutaneous and visceral adipose tissue (VAT) mass, and radiodensity, in a cohort of 101 HCC patients treated with selective internal radiation therapy (SIRT). Muscle and adipose tissue cross sectional area (cm²/m²) and radiodensity, reported as the Hounsfield Unit (HU), were determined using pre-SIRT computed tomography images. Cox proportional hazard models and exact logistic regression were conducted to assess associations between body composition and adverse outcomes. Majority of the patients were male (88%) with a mean VAT radiodensity of −85 ± 9 HU. VAT radiodensity was independently associated with mortality (HR 1.05; 95% CI: 1.01–1.08; p = 0.01), after adjusting for cirrhosis etiology, Barcelona Clinic Liver Cancer stage, previous HCC treatment, and portal hypertension markers. Patients with a high VAT radiodensity of ≥–85 HU had a two times higher risk of mortality (HR 2.01, 95% CI 1.14–3.54, p = 0.02), compared to their counterpart. Clinical features of portal hypertension were more prevalent in patients with high VAT radiodensity. High VAT radiodensity was associated with severe adverse events after adjusting for confounding factors. High VAT radiodensity is independently associated with both increased mortality and severe adverse events in patients treated with SIRT. VAT radiodensity measurement might serve as an objective approach to identify patients who will experience the most benefit from SIRT.

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

BACKGROUND

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

PURPOSE

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

STUDY TYPE

Prospective.

POPULATION/SUBJECTS/PHANTOM/SPECIMEN/ANIMAL MODEL

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

FIELD STRENGTH/SEQUENCE

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

ASSESSMENT

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

STATISTICAL TESTS

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

RESULTS

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

DATA CONCLUSION

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

LEVEL OF EVIDENCE

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

Lean body mass wasting and toxicity in early breast cancer patients receiving anthracyclines

Background

Sarcopenia refers to the reduction of both volume and number of skeletal muscle fibers. Lean body mass loss is associated with survival, quality of life and tolerance to treatment in cancer patients. The aim of our study is to analyse the association between toxicities and sarcopenia in early breast cancer patients receiving adjuvant treatment.

Materials and Methods

Breast cancer patients who have received anthracycline-based adjuvant treatment were retrospectively enrolled. CT scan images performed before, during and after adjuvant chemotherapy were used to evaluate lean body mass at third lumbar vertebra level with the software Slice Omatic V 5.0.

Results

21 stage I–III breast cancer patients were enrolled. According to the skeletal muscle index at third lumbar vertebra cut-off ≤38.5 cm²/m², 8 patients (38.1%) were classified as sarcopenic before starting treatment, while 10 patients (47.6%) were sarcopenic at the end of treatment. A lower baseline L3 skeletal muscle index is associated with G3-4 vs G0-2 toxicities (33.4 cm²/m² (31.1–39.9) vs 40.5 cm²/m² (33.4–52.0), p = 0.028). Similarly skeletal muscle cross sectional area was significantly lower in patients with G3-4 toxicities (86.7 cm² (82.6–104.7) vs 109.0 cm² (83.3–143.9), p = 0.017). L3 skeletal muscle index is an independent predictor of severe toxicity (p = 0.0282) in multivariate analysis.

Conclusion

Lean body mass loss is associated with higher grade of toxicity in early breast cancer patients receiving adjuvant chemotherapy.

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

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