Comparison of T1-weighted 2D TSE, 3D SPGR, and two-point 3D Dixon MRI for automated segmentation of visceral adipose tissue at 3 Tesla

MRI-Derived Radiomics Features of Hepatic Fat Predict Metabolic States in Individuals without Cardiovascular Disease

RATIONALE AND OBJECTIVES

To investigate radiomics features of hepatic fat as potential biomarkers of type 2 diabetes mellitus (T2DM) and metabolic syndrome (MetS) in individuals without overt cardiovascular disease, and benchmarking against hepatic proton density fat fraction (PDFF) and the body mass index (BMI).

MATERIALS AND METHODS

This study collected liver radiomics features of 310 individuals that were part of a case-controlled imaging substudy embedded in a prospective cohort. Individuals had known T2DM (n = 39; 12.6 %) and MetS (n = 107; 34.5 %) status, and were divided into stratified training (n = 232; 75 %) and validation (n = 78; 25 %) sets. Six hundred eighty-four MRI radiomics features were extracted for each liver volume of interest (VOI) on T₁-weighted dual-echo Dixon relative fat water content (rfwc) maps. Test-retest and inter-rater variance was simulated by additionally extracting radiomics features using noise augmented rfwc maps and deformed volume of interests. One hundred and seventy-one features with test-retest reliability (ICC(1,1)) and inter-rater agreement (ICC(3,k)) of ≥0.85 on the training set were considered stable. To construct predictive random forest (RF) models, stable features were filtered using univariate RF analysis followed by sequential forward aggregation. The predictive performance was evaluated on the independent validation set with area under the curve of the receiver operating characteristic (AUROC) and balanced accuracy (Accuracy_B).

RESULTS

On the validation set, the radiomics RF models predicted T2DM with AUROC of 0.835 and Accuracy_B of 0.822 and MetS with AUROC of 0.838 and Accuracy_B of 0.787, outperforming the RF models trained on the benchmark parameters PDFF and BMI.

CONCLUSION

Hepatic radiomics features may serve as potential imaging biomarkers for T2DM and MetS.

Effect of Bimagrumab vs Placebo on Body Fat Mass Among Adults With Type 2 Diabetes and Obesity: A Phase 2 Randomized Clinical Trial

IMPORTANCE

Antibody blockade of activin type II receptor (ActRII) signaling stimulates skeletal muscle growth. Previous clinical studies suggest that ActRII inhibition with the monoclonal antibody bimagrumab also promotes excess adipose tissue loss and improves insulin resistance.

OBJECTIVE

To evaluate the efficacy and safety of bimagrumab on body composition and glycemic control in adults with type 2 diabetes and overweight and obesity.

DESIGN, SETTING, AND PARTICIPANTS

This double-masked, placebo-controlled, 48-week, phase 2 randomized clinical trial was conducted among adults with type 2 diabetes, body mass index between 28 and 40, and glycated hemoglobin (HbA1c) levels between 6.5% and 10.0% at 9 US and UK sites. The trial was conducted from February 2017 to May 2019. Only participants who completed a full treatment regimen were included in analysis.

INTERVENTIONS

Patients were randomized to intravenous infusion of bimagrumab (10 mg/kg up to 1200 mg in 5% dextrose solution) or placebo (5% dextrose solution) treatment every 4 weeks for 48 weeks; both groups received diet and exercise counseling.

MAIN OUTCOMES AND MEASURES

The primary end point was least square mean change from baseline to week 48 in total body fat mass (FM); secondary and exploratory end points were lean mass (LM), waist circumference (WC), HbA1c level, and body weight (BW) changes from baseline to week 48.

RESULTS

A total of 75 patients were randomized to bimagrumab (n = 37; 23 [62.2%] women) or placebo (n = 38; 12 [31.6%] women); 58 (77.3%) completed the 48-week study. Patients at baseline had a mean (SD) age of 60.4 (7.7) years; mean (SD) BMI of 32.9 (3.4); mean (SD) BW of 93.6 (14.9) kg; mean (SD) FM of 35.4 (7.5) kg; and mean (SD) HbA1c level of 7.8% (1.0%). Changes at week 48 for bimagrumab vs placebo were as follows: FM, -20.5% (-7.5 kg [80% CI, -8.3 to -6.6 kg]) vs -0.5% (-0.18 kg [80% CI, -0.99 to 0.63 kg]) (P < .001); LM, 3.6% (1.70 kg [80% CI, 1.1 to 2.3 kg]) vs -0.8% (-0.4 kg [80% CI, -1.0 to 0.1 kg]) (P < .001); WC, -9.0 cm (80% CI, -10.3 to -7.7 cm) vs 0.5 cm (80% CI, -0.8 to 1.7 cm) (P < .001); HbA1c level, -0.76 percentage points (80% CI, -1.05 to -0.48 percentage points) vs -0.04 percentage points (80% CI, -0.23 to 0.31 percentage points) (P = .005); and BW, -6.5% (-5.9 kg [80% CI, -7.1 to -4.7 kg]) vs -0.8% (-0.8 kg [80% CI, -1.9 to 0.3 kg]) (P < .001). Bimagrumab's safety and tolerability profile was consistent with prior studies.

CONCLUSIONS AND RELEVANCE

In this phase 2 randomized clinical trial, ActRII blockade with bimagrumab led to significant loss of FM, gain in LM, and metabolic improvements during 48 weeks in patients with overweight or obesity who had type 2 diabetes. ActRII pathway inhibition may provide a novel approach for the pharmacologic management of excess adiposity and accompanying metabolic disturbances.

TRIAL REGISTRATION

ClinicalTrials.gov number: NCT03005288.

Noninvasive, longitudinal imaging-based analysis of body adipose tissue and water composition in a melanoma mouse model and in immune checkpoint inhibitor-treated metastatic melanoma patients

Background

As cancer cachexia (CC) is associated with cancer progression, early identification would be beneficial. The aim of this study was to establish a workflow for automated MRI-based segmentation of visceral (VAT) and subcutaneous adipose tissue (SCAT) and lean tissue water (LTW) in a B16 melanoma animal model, monitor diseases progression and transfer the protocol to human melanoma patients for therapy assessment.

Methods

For in vivo monitoring of CC B16 melanoma-bearing and healthy mice underwent longitudinal three-point DIXON MRI (days 3, 12, 17 after subcutaneous tumor inoculation). In a prospective clinical study, 18 metastatic melanoma patients underwent MRI before, 2 and 12 weeks after onset of checkpoint inhibitor therapy (CIT; n = 16). We employed an in-house MATLAB script for automated whole-body segmentation for detection of VAT, SCAT and LTW.

Results

B16 mice exhibited a CC phenotype and developed a reduced VAT volume compared to baseline (B16 − 249.8 µl, − 25%; controls + 85.3 µl, + 10%, p = 0.003) and to healthy controls. LTW was increased in controls compared to melanoma mice. Five melanoma patients responded to CIT, 7 progressed, and 6 displayed a mixed response. Responding patients exhibited a very limited variability in VAT and SCAT in contrast to others. Interestingly, the LTW was decreased in CIT responding patients (− 3.02% ± 2.67%; p = 0.0034) but increased in patients with progressive disease (+ 1.97% ± 2.19%) and mixed response (+ 4.59% ± 3.71%).

Conclusion

MRI-based segmentation of fat and water contents adds essential additional information for monitoring the development of CC in mice and metastatic melanoma patients during CIT or other treatment approaches.

Normalized Indices Derived from Visceral Adipose Mass Assessed by Magnetic Resonance Imaging and Their Correlation with Markers for Insulin Resistance and Prediabetes

Visceral adipose tissue (VAT) plays an important role in the pathogenesis of insulin resistance (IR), prediabetes and type 2 diabetes. However, VAT volume alone might not be the best marker for insulin resistance and prediabetes or diabetes, as a given VAT volume may impact differently on these metabolic traits based on body height, gender, age and ethnicity. In a cohort of 1295 subjects from the Tübingen Diabetes Family Study (TDFS) and in 9978 subjects from the UK Biobank (UKBB) undergoing magnetic resonance imaging for quantification of VAT volume, total adipose tissue (TAT) in the TDFS, total abdominal adipose tissue (TAAT) in the UKBB, and total lean tissue (TLT), VAT volume and several VAT-indices were investigated for their relationships with insulin resistance and glycemic traits. VAT-related indices were calculated by correcting for body height (VAT/m:VAT/body height; VAT/m²:VAT/(body height)², and VAT/m³:VAT/(body height)³), TAT (%VAT), TLT (VAT/TLT) and weight (VAT/WEI), with closest equivalents used within the UKBB dataset. Prognostic values of VAT and VAT-related indices for insulin sensitivity, HbA1c levels and prediabetes/diabetes were analyzed for males and females. Males had higher VAT volume and VAT-related indices than females in both cohorts (p < 0.0001) and VAT volume has shown to be a stronger determinant for insulin sensitivity than anthropometric variables. Among the parameters uncorrected VAT and derived indices, VAT/m³ most strongly correlated negatively with insulin sensitivity and positively with HbA1c levels and prediabetes/diabetes in the TDFS (R² = 0.375/0.305 for females/males for insulin sensitivity, 0.178/0.148 for HbA1c levels vs., e.g., 0.355/0.293 and 0.144/0.133 for VAT, respectively) and positively with HbA1c (R² = 0.046/0.042) in the UKBB for females and males. Furthermore, VAT/m³ was found to be a significantly better determinant of insulin resistance or prediabetes than uncorrected VAT volume (p < 0.001/0.019 for females/males regarding insulin sensitivity, p < 0.001/< 0.001 for females/males regarding HbA1c). Evaluation of several indices derived from VAT volume identified VAT/m³ to correlate most strongly with insulin sensitivity and glucose metabolism. Thus, VAT/m³ appears to provide better indications of metabolic characteristics (insulin sensitivity and pre-diabetes/diabetes) than VAT volume alone.

Vertebral Bone Marrow Fat Is independently Associated to VAT but Not to SAT: KORA FF4-Whole-Body MR Imaging in a Population-Based Cohort

The objective of the current study was to assess the relationship of bone marrow adipose tissue (BMAT) content to abdominal fat depots, including visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT), as well as cardiovascular risk factors (CVRF) beyond physical activity in a population-based cohort study undergoing whole-body magnetic resonance (MR) imaging. Subjects of the Cooperative Health Research in the Augsburg Region (KORA) FF4 study without known cardiovascular disease underwent fat fraction quantification in vertebrae (BMAT_L1/L2) via a 2-point T1-weighted volumetric interpolated breath-hold examination (VIBE) Dixon sequence. The same MR sequence was applied to quantify VAT and SAT volume. Subjects’ characteristics, including physical activity, were determined through standardized exams and self-assessment questionnaires. Univariate and multivariate linear regression were applied. In the cohort of 378 subjects (56 ± 9.1years; 42.1% female), BMAT_L1/L2 was 54.3 ± 10.1%, VAT was 4.54 ± 2.71 L, and SAT was 8.10 ± 3.68 L. VAT differed significantly across BMAT_L1/L2 tertiles (3.60 ± 2.76 vs. 4.92 ± 2.66 vs. 5.11 ± 2.48; p < 0.001), there was no significant differences for SAT (p = 0.39). In the fully adjusted model, VAT remained positively associated with BMAT_L1/L2 (β = 0.53, p = 0.03). Furthermore, BMAT_L1/L2 was associated with age (β = 5.40 per 10-years, p < 0.001), hemoglobin A1c (HbA1c; β = 1.55 per 1%, p = 0.04), lipids (β = 0.20 per 10 mg/dL triglycerides; β = 0.40 per 10 mg/dL low-density lipoprotein (LDL); β =−3.21 lipid-lowering medication; all p < 0.05), and less physical activity (β = 3.7 “no or nearly no exercise” as compared to “≥2 h per week, regularly”, p = 0.003); gender was not significantly different (p = 0.57). In the population-based cohort, VAT but not SAT were associated with higher BMAT_L1/L2 independently of physical activity and other cardiovascular risk factors. Further, BMAT_L1/L2 increased with older age, less physical activity, higher HbA1c, and increased lipids but decreased with lipid-lowering medication.

Magnetic Resonance Imaging and Bioelectrical Impedance Analysis to Assess Visceral and Abdominal Adipose Tissue

OBJECTIVE

This study aimed to compare a state-of-the-art bioelectrical impedance analysis (BIA) device with two-point Dixon magnetic resonance imaging (MRI) for the quantification of visceral adipose tissue (VAT) as a health-related risk factor.

METHODS

A total of 63 male participants were measured using a 3-T MRI scanner and a segmental, multifrequency BIA device. MRI generated fat fraction (FF) maps, in which VAT volume, total abdominal adipose tissue volume, and FF of visceral and total abdominal compartments were quantified. BIA estimated body fat mass and VAT area.

RESULTS

Coefficients of determination between abdominal (r²  = 0.75) and visceral compartments (r²  = 0.78) were similar for both groups, but slopes differed by a factor of two. The ratio of visceral to total abdominal FF was increased in older men compared with younger men. This difference was not detected with BIA. MRI and BIA measurements of the total abdominal volume correlated moderately (r²  = 0.31-0.56), and visceral measurements correlated poorly (r²  = 0.13-0.44).

CONCLUSIONS

Visceral BIA measurements agreed better with MRI measurements of the total abdomen than of the visceral compartment, indicating that BIA visceral fat area assessment cannot differentiate adipose tissue between visceral and abdominal compartments in young and older participants.

MRI-based assessment and characterization of epicardial and paracardial fat depots in the context of impaired glucose metabolism and subclinical left-ventricular alterations

OBJECTIVE:

To analyze the associations between epicardial and paracardial fat and impaired glucose tolerance as well as left ventricular (LV) alterations.

METHODS:

400 subjects underwent 3 T MRI and fat depots were delineated in the four chamber-view of the steady-state free precession cine sequence (repetition time: 29.97 ms; echo time 1.46 ms). LV parameters were also derived from MRI. Oral glucose tolerance tests were performed.

RESULTS:

Epi- and paracardial fat was derived in 372 (93%) subjects (220 healthy controls, 100 persons with prediabetes, 52 with diabetes). Epi- and paracardial fat increased from normal glucose tolerance (NGT) to prediabetes and diabetes (7.7 vs 9.2 vs 10.3 cm² and 14.3 vs 20.3 vs 27.4 cm², respectively; all p < 0.001). However, the association between impaired glucose metabolism and cardiac fat attenuated after adjustment, mainly confounded by visceral adipose tissue (VAT). 93 subjects (27%) had LV impairment, defined as late gadolinium enhancement, ejection fraction < 55% or LV concentricity index > 1.3 g ml^-1 . Mean epicardial fat was higher in subjects with LV impairment (11.0 vs 8.1 cm², p < 0.001). This association remained independent after adjustment for traditional risk factors and VAT [β: 1.13 (0.22; 2.03), p = 0.02].

CONCLUSION:

Although epicardial and paracardial fat are increased in prediabetes and diabetes, the association is mostly confounded by VAT. Epicardial fat is independently associated with subclinical LV impairment in subjects without known cardiovascular disease.

ADVANCES IN KNOWLEDGE:

This study contributes to the picture of epicardial fat as a pathogenic local fat depot that is independently associated with MR-derived markers of left ventricular alterations.

Quantifying skeletal muscle volume and shape in humans using MRI: A systematic review of validity and reliability

AIMS

The aim of this study was to report the metrological qualities of techniques currently used to quantify skeletal muscle volume and 3D shape in healthy and pathological muscles.

METHODS

A systematic review was conducted (Prospero CRD42018082708). PubMed, Web of Science, Cochrane and Scopus databases were searched using relevant keywords and inclusion/exclusion criteria. The quality of the articles was evaluated using a customized scale.

RESULTS

Thirty articles were included, 6 of which included pathological muscles. Most evaluated lower limb muscles. Partially or completely automatic and manual techniques were assessed in 10 and 24 articles, respectively. Manual slice-by-slice segmentation reliability was good-to-excellent (n = 8 articles) and validity against dissection was moderate to good(n = 1). Manual slice-by-slice segmentation was used as a gold-standard method in the other articles. Reduction of the number of manually segmented slices (n = 6) provided good to excellent validity if a sufficient number of appropriate slices was chosen. Segmentation on one slice (n = 11) increased volume errors. The Deformation of a Parametric Specific Object (DPSO) method (n = 5) decreased the number of manually-segmented slices required for any chosen level of error. Other automatic techniques combined with different statistical shape or atlas/images-based methods (n = 4) had good validity. Some particularities were highlighted for specific muscles. Except for manual slice by slice segmentation, reliability has rarely been reported.

CONCLUSIONS

The results of this systematic review help the choice of appropriate segmentation techniques, according to the purpose of the measurement. In healthy populations, techniques that greatly simplified the process of manual segmentation yielded greater errors in volume and shape estimations. Reduction of the number of manually segmented slices was possible with appropriately chosen segmented slices or with DPSO. Other automatic techniques showed promise, but data were insufficient for their validation. More data on the metrological quality of techniques used in the cases of muscle pathology are required.

Simultaneous Volumetric Segmentation of Vertebral Bodies and Intervertebral Discs on Fat-Water MR Images

Fat-water magnetic resonance (MR) images allow automated noninvasive analysis of morphological properties and fat fractions of vertebral bodies (VBs) and intervertebral discs (IVDs) that constitute an important part of human biomechanical systems. In this paper, we propose a fully automated approach for simultaneously segmenting multiple VBs and IVDs on fat-water MR images without prior localization or geometry estimation. This method involved a hierarchical random forest (HRF) classifier and a hierarchical conditional random field (HCRF) that encoded a multi-resolution image pyramid based on a set of multiscale local and contextual features. The HRF classifier employed penalized multivariate linear discriminants and SMOTEBagging to handle limited and imbalanced training data with large feature dimension. The HCRF estimated optimum labels according to their spatial and hierarchical consistencies by using the layer-wise significant features determined over the trained HRF classifier. To handle variable sample numbers at different resolutions, resolution-specific hyperparameters were used. This method was trained and evaluated for segmenting 15 thoracic and lumbar VBs and their IVDs on fat-water MR images of a subset of a large cohort data set. It was further evaluated for segmenting seven IVDs of the lower spine on fat-water images of a public grand challenge. These evaluations revealed the comparable accuracy of this method with the state-of-the-art while requiring less computational burden due to a simultaneous localization and segmentation.

How to best assess abdominal obesity

PURPOSE OF REVIEW

Abdominal obesity, especially the increase of visceral adipose tissue (VAT), is closely associated with increased mortality related to cardiovascular disease, diabetes, and fatty liver disease. This review provides an overview of the recent advances for abdominal obesity measurement.

RECENT FINDINGS

Compared to simple waist circumference, emerging three-dimensional (3D) body-scanning techniques also measure abdominal volume and shape. Abdominal dimension measures have been implemented in bioelectrical impedance analysis to improve accuracy when estimating VAT. Geometrical models have been applied in ultrasound to convert depth measurement into VAT area. Only computed tomography (CT) and MRI can provide direct measures of VAT. Recent advances in imaging allow for evaluating functional aspects of abdominal fat such as brown adipose tissue and fatty acid composition.

SUMMARY

Waist circumference is a simple, inexpensive method to measure abdominal obesity. CT and MRI are reference methods for measuring VAT. Further studies are needed to establish the accuracy for dual-energy X-ray absorptiometry in estimating longitudinal changes of VAT. Further studies are needed to establish whether bioelectrical impedance analysis, ultrasound, or 3D body scanning is consistently superior to waist circumference in estimating VAT in different populations.

Peripouch Fat Area Measured on MRI Image and Its Association With Adverse Pouch Outcomes

BACKGROUND

There are no published studies on the impact of peripouch fat on pouch outcomes in inflammatory bowel disease (IBD) patients.

METHODS

Patients with pelvic MRI-DIXON scans from our prospectively maintained Pouch Database between 2002 and 2016 were evaluated. Peripouch fat area was measured on MRI-DIXON-F images at the middle height level of the pouch (area M) and the highest level of the pouch (area H).

RESULTS

Of all 1863 patients in the database, 197 eligible patients were included in this study. The median of area M was 52.4 cm2, so the 197 patients were classified into 2 groups: group 1 (Area-M <52.4 cm2) and group 2 (Area-M ≥52.4 cm2). Compared with group 1, group 2 was found to have thicker perianal fat, more Caucasian and more males. Group 2 also had a higher Area-H, more weight, height, and body mass index, along with greater age at IBD diagnosis, age at pouch construction and pouch age, and a higher frequency of total pouch complication (86.7% versus 66.7%, P = 0.001), chronic pouch complication (68.4% versus 51.5%, P = 0.016), and chronic antibiotic-refractory pouchitis (16.3% versus 7.1%, P = 0.043). Multivariate logistic analysis showed that Area-M was an independent risk factor for chronic antibiotic-refractory pouchitis (odds ratio [OR]: 1.025; 95% confidence interval [CI]: 1.007-1.042, P = 0.005). The 22 patients with 2 or more pelvic MRI-DIXON scans were further classified into 2 groups by the change from the initial to latest MRI-DIXON scans. Patients with Area-M increase ≥10% and Area-M/height increase ≥10% were found to have shorter pouch survivals than those with increase <10%.

CONCLUSIONS

A new method was established for measuring peripouch fat using pelvic MRI-DIXON-F image. Our study suggests that accumulation of peripouch fat may be associated with poor outcomes in selected IBD patients suspected of inflammatory or mechanical disorders of the pouch. Whether this association is causal warrants further investigation.

Adipose tissue and liver

Adipose tissue and liver are central tissues in whole body energy metabolism. Their composition, structure, and function can be noninvasively imaged using a variety of measurement techniques that provide a safe alternative to an invasive biopsy. Imaging of adipose tissue is focused on quantitating the distribution of adipose tissue in subcutaneous and intra-abdominal (visceral) adipose tissue depots. Also, detailed subdivisions of adipose tissue can be distinguished with modern imaging techniques. Adipose tissue (or adipocyte) accumulation or infiltration of other organs can also be imaged, with intramuscular adipose tissue a common example. Although liver fat content is now accurately imaged using standard magnetic resonance imaging (MRI) techniques, inflammation and fibrosis are more difficult to determine noninvasively. Liver imaging efforts are therefore concerted on developing accurate imaging markers of liver fibrosis and inflammatory status. Magnetic resonance elastography (MRE) is presently the most reliable imaging technique for measuring liver fibrosis but requires an external device for introduction of shear waves to the liver. Methods using multiparametric diffusion, perfusion, relaxometry, and hepatocyte-specific MRI contrast agents may prove to be more easily implemented by clinicians, provided they reach similar accuracy as MRE. Adipose tissue imaging is experiencing a revolution with renewed interest in characterizing and identifying distinct adipose depots, among them brown adipose tissue. Magnetic resonance spectroscopy provides an interesting yet underutilized way of imaging adipose tissue metabolism through its fatty acid composition. Further studies may shed light on the role of fatty acid composition in different depots and why saturated fat in subcutaneous adipose tissue is a marker of high insulin sensitivity.