Automated assessment of whole‐body adipose tissue depots from continuously moving bed MRI: A feasibility study

Kullberg, Joel; Johansson, Lars; Åhlström, Håkan; Courivaud, Frédéric; Koken, Peter; Eggers, Holger; Börnert, Peter

doi:10.1002/jmri.21820

Cited by 82 publications

(95 citation statements)

References 26 publications

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“…Fat-water MRI can be used to assess body tissues with a threedimensional (no gap between slices) multi-gradient-echo MRI pulse sequence. Notably, such a contiguous acquisition can be combined with fully automated segmentation of adipose and lean soft tissue as well as quantification of abdominal visceral and subcutaneous depots (15,16). Moreover, the ability to use higher magnetic field strength 3 Tesla (3T) scanners offers the potential for improved signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), which can increase spatial resolution and/or reduce scan time (17).…”

Section: Introductionmentioning

confidence: 99%

Comparison of Gross Body Fat-Water Magnetic Resonance Imaging at 3 Tesla to Dual-Energy X-Ray Absorptiometry in Obese Women

Silver¹,

Niswender²,

Kullberg³

et al. 2012

Obesity

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Improved understanding of how depot-specific adipose tissue mass predisposes to obesity-related comorbidities could yield new insights into the pathogenesis and treatment of obesity as well as metabolic benefits of weight loss. We hypothesized that three-dimensional contiguous "fat-water" MR imaging (FWMRI) covering the majority of a whole-body field of view (FOV) acquired at 3 Tesla (3T) and coupled with automated segmentation and quantification of amount, type and distribution of adipose and lean soft tissue would show great promise in body composition methodology. Precision of adipose and lean soft tissue measurements in body and trunk regions were assessed for 3T FWMRI and compared to DEXA. Anthropometric, FWMRI and DEXA measurements were obtained in twelve women with BMI 30-39.9 kg/m 2 . Test-retest results found coefficients of variation for FWMRI that were all under 3%: gross body adipose tissue (GBAT) 0.80%, total trunk adipose tissue (TTAT) 2.08%, visceral adipose tissue (VAT) 2.62%, subcutaneous adipose tissue (SAT) 2.11%, gross body lean soft tissue (GBLST) 0.60%, and total trunk lean soft tissue (TTLST) 2.43%. Concordance correlation coefficients between FWMRI and DEXA were 0.978, 0.802, 0.629, and 0.400 for GBAT, TTAT, GBLST and TTLST, respectively. While Bland Altman plots demonstrated agreement between FWMRI and DEXA for GBAT and Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license. TTAT, a negative bias existed for GBLST and TTLST measurements. Differences may be explained by the FWMRI FOV length and potential for DEXA to overestimate lean soft tissue. While more development is necessary, the described 3T FWMRI method combined with fullyautomated segmentation is fast (<30 minutes total scan and post-processing time), noninvasive, repeatable and cost effective.

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Section: Introductionmentioning

confidence: 99%

Comparison of Gross Body Fat-Water Magnetic Resonance Imaging at 3 Tesla to Dual-Energy X-Ray Absorptiometry in Obese Women

Silver¹,

Niswender²,

Kullberg³

et al. 2012

Obesity

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“…PV and FV fat volumes have a weak but not significant positive correlation between them with slope ¼ 0.27 (r ¼ 0.48, P ¼ 0. 19), showing that V p increases slightly when V f is larger (Fig. 3a).…”

Section: Partial-volume Fat Quantificationmentioning

confidence: 87%

“…Furthermore, effective water suppression can help improve differentiation between PV-fat and nonfat tissues, and therefore quantification methods that take PVE into consideration can be used to reduce the variability in VAT (11,17). Alternatively, more advanced multiecho techniques such as ''iterative decomposition of water and fat with echo asymmetry and least squares estimation'' (IDEAL) can be applied to generate fat-only MR images, which may help identify and therefore estimate PV fat amount due to greatly improved contrast (18,19). In addition to these methods, ultrafast imaging techniques can minimize potential motion-induced image blurring, and therefore improve PV fat quantification.…”

Section: Discussionmentioning

confidence: 99%

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

Zhou

Murillo

Peng

2011

Magnetic Resonance Imaging

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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 6 25.6 and water-saturation was effective, with the average fat-to-water signal intensity ratio ¼ 20.7 6 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. IMAGING OF HUMAN BODY FAT and its distribution have gained renewed attention because of the link between obesity and physical inactivity to multiple disease states. Excessive body fat, particularly visceral adipose tissue (VAT), correlates with adverse metabolic consequences especially those related to the metabolic syndrome such as diabetes type 2 and cardiovascular disease (1-3). Moreover, the global obesity epidemic has heightened the importance and magnitude of the problems (4). Thus, accurate and rapid methods for measuring VAT have been sought to better investigate its contribution to many disease states as well as the development of diagnostic biomarkers (5,6).VAT imaging and quantification have been challenging because of motion artifacts, the highly complicated nature of anatomic fat compartments, and the disseminated nature of visceral fat. Compared with computerized tomography (CT), magnetic resonance imaging (MRI) has no associated ionizing radiation and is more desirable for repeated studies for infants, children, and healthy subjects. MRI is therefore the method of choice for VAT quantification in such clinical research studies despite its known relatively poor spatial resolution due to signal-to-noise ratio (SNR) and scan duration limitation of a clinical scan. Human abdominal fat quantification by MRI has been historically performed using T1-weighted (T1W) turbo spin-echo (TSE) or gradient-echo imaging techniques. These techniques can generate moderate contrast between fat and nonfat tissues to enable classification of these pixels using postprocessing methods such as a manual contour drawing method (7)...

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“…[4], and volumes were converted into mass estimates using Eq. [5] and literature values for tissue densities: 0.923 kg/L for adipose, 1.100 kg/L for soft lean, and 1.72 kg/L for cortical bone (13). Once all tissues were segmented, and the calculated volumes converted into masses using the corresponding densities, the TAT, LT and CB masses were summed to form an FWMRIderived total body mass estimate.…”

mentioning

confidence: 97%

“…Calculate depot volumes for TAT, LT, VAT, SAT and CB binary images volumes [4] 8. Calculate depot masses for TAT, LT, VAT, SAT and CB [5] After segmentation, tissue depot volumes were calculated using Eq. [4], and volumes were converted into mass estimates using Eq.…”

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confidence: 99%

Canine body composition quantification using 3 tesla fat–water MRI

Gifford

Kullberg

Berglund

et al. 2014

Magnetic Resonance Imaging

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Purpose-To test the hypothesis that a whole-body fat-water MRI (FWMRI) protocol acquired at 3 Tesla combined with semi-automated image analysis techniques enables precise volume and mass quantification of adipose, lean and bone tissue depots that agree with static scale mass and scale mass changes in the context of a longitudinal study of large-breed dogs placed on an obesogenic high-fat, high-fructose diet.Materials and Methods-Six healthy adult male dogs were scanned twice, at weeks 0 (baseline) and 4, of the dietary regiment. FWMRI-derived volumes of adipose tissue (total, visceral, and subcutaneous), lean tissue, and cortical bone were quantified using a semi-automated approach. Volumes were converted to masses using published tissue densities.Results-FWMRI-derived total mass corresponds with scale mass with a concordance correlation coefficient of 0.931 (95% confidence interval = [0.813, 0.975]), and slope and intercept values of 1.12 and −2.23 kg respectively. Visceral, subcutaneous and total adipose tissue masses increased significantly from weeks 0 to 4, while neither cortical bone nor lean tissue masses changed significantly. This is evidenced by a mean percent change of 70.2% for visceral, 67.0% for subcutaneous, and 67.1% for total adipose tissue.Conclusion-FWMRI can precisely quantify and map body composition with respect to adipose, lean and bone tissue depots. The described approach provides a valuable tool to examine the role of distinct tissue depots in an established animal model of human metabolic disease.

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Automated assessment of whole‐body adipose tissue depots from continuously moving bed MRI: A feasibility study

Cited by 82 publications

References 26 publications

Comparison of Gross Body Fat-Water Magnetic Resonance Imaging at 3 Tesla to Dual-Energy X-Ray Absorptiometry in Obese Women

Comparison of Gross Body Fat-Water Magnetic Resonance Imaging at 3 Tesla to Dual-Energy X-Ray Absorptiometry in Obese Women

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

Canine body composition quantification using 3 tesla fat–water MRI

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