1
|
Linder N, Denecke T, Busse H. Body composition analysis by radiological imaging - methods, applications, and prospects. ROFO-FORTSCHR RONTG 2024. [PMID: 38569516 DOI: 10.1055/a-2263-1501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2024]
Abstract
BACKGROUND This review discusses the quantitative assessment of tissue composition in the human body (body composition, BC) using radiological methods. Such analyses are gaining importance, in particular, for oncological and metabolic problems. The aim is to present the different methods and definitions in this field to a radiological readership in order to facilitate application and dissemination of BC methods. The main focus is on radiological cross-sectional imaging. METHODS The review is based on a recent literature search in the US National Library of Medicine catalog (pubmed.gov) using appropriate search terms (body composition, obesity, sarcopenia, osteopenia in conjunction with imaging and radiology, respectively), as well as our own work and experience, particularly with MRI- and CT-based analyses of abdominal fat compartments and muscle groups. RESULTS AND CONCLUSION Key post-processing methods such as segmentation of tomographic datasets are now well established and used in numerous clinical disciplines, including bariatric surgery. Validated reference values are required for a reliable assessment of radiological measures, such as fatty liver or muscle. Artificial intelligence approaches (deep learning) already enable the automated segmentation of different tissues and compartments so that the extensive datasets can be processed in a time-efficient manner - in the case of so-called opportunistic screening, even retrospectively from diagnostic examinations. The availability of analysis tools and suitable datasets for AI training is considered a limitation. KEY POINTS · Radiological imaging methods are increasingly used to determine body composition (BC).. · BC parameters are usually quantitative and well reproducible.. · CT image data from routine clinical examinations can be used retrospectively for BC analysis.. · Prospectively, MRI examinations can be used to determine organ-specific BC parameters.. · Automated and in-depth analysis methods (deep learning or radiomics) appear to become important in the future.. CITATION FORMAT · Linder N, Denecke T, Busse H. Body composition analysis by radiological imaging - methods, applications, and prospects. Fortschr Röntgenstr 2024; DOI: 10.1055/a-2263-1501.
Collapse
Affiliation(s)
- Nicolas Linder
- Department of Diagnostic and Interventional Radiology, University of Leipzig Medical Center, Leipzig, Germany
- Division of Radiology and Nuclear Medicine, Kantonsspital St. Gallen, Sankt Gallen, Switzerland
| | - Timm Denecke
- Department of Diagnostic and Interventional Radiology, University of Leipzig Medical Center, Leipzig, Germany
| | - Harald Busse
- Department of Diagnostic and Interventional Radiology, University of Leipzig Medical Center, Leipzig, Germany
| |
Collapse
|
2
|
Xu J, Liu B, Han K, Ye Z, Zhang X, Qiao Y, Jin Y, Jiang J, Su W, Li Y, Zhao J. The Modified Assessment Tool Based on Scapular Y-View for Global Fatty Infiltration in the Supraspinatus Muscle: Correlation, Predictive Performance, and Reliability Analyses. Am J Sports Med 2023; 51:1243-1254. [PMID: 36917780 DOI: 10.1177/03635465231158372] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
BACKGROUND The accurate evaluation of rotator cuff (RC) fatty degeneration after tears is critical for appropriate surgical decision making and prognosis. However, there is currently no reliable and practical tool to reflect the global fatty infiltration (Global-FI) throughout the 3-dimensional (3D) volumetric RC muscles. PURPOSE (1) To determine the correlations between 2 modified assessment tools and the Global-FI and their predictive performances and reliabilities for Global-FI prediction, and (2) to compare these predictive parameters with those of the conventional tool using a single scapular Y-view slice. STUDY DESIGN Cohort study (diagnosis); Level of evidence, 3. METHODS A total of 49 patients with full-thickness RC tears scheduled to undergo arthroscopic repairs were included, and their surgical shoulders underwent 6-point Dixon magnetic resonance imaging preoperatively. The Global-FI was measured by calculating the 3D-volumetric fat fraction (FF) of the whole supraspinatus muscle through all acquired oblique sagittal slices. As a commonly used radiological landmark, the scapular Y-view was used to evaluate single-plane fatty infiltration (Y-FI) by calculating the FF in 1 slice, defined as the conventional assessment tool. Two modified assessment tools expand the analytic imaging by integrating the FFs from the scapular Y-view slice and its neighboring slices, which were calculated by averaging the FFs of these 3 slices (meanY3-FI) and accumulating local 3D-volumetric FFs from 3 slices (volY3-FI), respectively. The correlations between 3 assessment tools and the Global-FI were analyzed, and the predictive performance for Global-FI prediction using these tools was determined by goodness of fit and agreement. Moreover, the inter- and intraobserver reliabilities of these assessment tools were evaluated. Similar analyses were performed in the small-medium, large, or massive tear subgroups. RESULTS The Y-FI was significantly higher than the Global-FI in all cases and tear size subgroups, while the 2 modified assessment tools (meanY3-FI and volY3-FI) did not significantly differ from the Global-FI. All assessment tools were significantly correlated with the Global-FI, but the meanY3-FI and volY3-FI showed stronger correlations than the Y-FI, which was also determined in different tear sizes. Moreover, the regression models of the meanY3-FI and volY3-FI showed superior goodness of fit to Y-FI in Global-FI prediction in all cases and subgroups, with larger coefficients of determination (R2) and smaller root mean square errors. The predicted Global-FI using the regression model of volY3-FI had the best agreement with the measured Global-FI, followed by the meanY3-FI, both showing smaller biases and standard deviation of the percentage difference between predicted- and measured Global-FI than the conventional Y-FI. In addition, the 2 modified assessment tools achieved better interobserver and intraobserver reliabilities than the conventional tool in all cases and subgroups. CONCLUSION Two modified assessment tools (meanY3-FI and volY3-FI) were comparable with the Global-FI of the whole supraspinatus muscle, showing stronger correlations with the Global-FI and better predictive performances and reliabilities than the conventional tool (Y-FI). Moreover, the volY3-FI was slightly superior to meanY3-FI in the predictive performance and reliability.
Collapse
Affiliation(s)
- Junjie Xu
- Department of Sports Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Beibei Liu
- Institute of Diagnostic and Interventional Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Kang Han
- Department of Sports Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zipeng Ye
- Department of Sports Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiuyuan Zhang
- Department of Sports Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yi Qiao
- Department of Sports Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuchen Jin
- Department of Nuclear Medicine, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.,Department of Nuclear Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University, Shanghai, China.,Human Oncology and Pathogenesis, Memorial Sloan-Kettering Cancer Center, New York, New York, USA
| | - Jia Jiang
- Department of Sports Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wei Su
- Department of Sports Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuehua Li
- Institute of Diagnostic and Interventional Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jinzhong Zhao
- Department of Sports Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| |
Collapse
|
3
|
Xu J, Liu B, Qiao Y, Ye Z, Su W, Zhao J. The 3-Dimensional Fatty Infiltration in the Overall Supraspinatus Can Be Predicted by Localized Sectional Accumulation Units: A Cross-Sectional Study in Patients with Atraumatic Small-to-Massive Rotator Cuff Tears. J Bone Joint Surg Am 2023; 105:380-388. [PMID: 36728395 DOI: 10.2106/jbjs.22.00767] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
BACKGROUND Fatty infiltration (FI) of the rotator cuff (RC) muscles is one of the most common risk factors for a retear following RC repair. Recent methodological developments focus on using 3-dimensional measurements of the overall FI of RC muscles instead of using single-plane-based measurements. However, the required labor-intensive segmentation and time-consuming post-processing steps need to be optimized for routine clinical use. METHODS We collected all 6-point Dixon magnetic resonance imaging (MRI) slices of the overall supraspinatus in 46 patients with atraumatic small-to-massive RC tears. Using emerging techniques, the overall 3-dimensional FI of the supraspinatus (overall FI, using all N slices) was assessed as the reference. Each sagittal segment of the supraspinatus was defined as a sectional accumulation unit (SAU). The localized FI in SAUs with different scales of N/3, N/6, and N/12 slices (SAU-FIs) was then calculated using piecewise accumulation by stacking neighboring slices after the overall supraspinatus had been sequentially segmented using MRI slices of the same thickness. The capacity of the SAU-FIs to predict the overall FI, and the ideal locations for prediction, were evaluated using linear regression models after the associations were examined. Goodness-of-fit of the regression models was appraised by the coefficient of determination (R 2 ) and root-mean-square error (RMSE). The agreement between the predicted and measured overall FI was assessed using Bland-Altman analysis and the standard deviation of the percent differences (sd%). RESULTS The localized SAU-FIs of the N/3, N/6, and N/12 SAUs generally displayed comparable distributions throughout the normalized distal-proximal long axis of the supraspinatus. The localized SAU-FIs showed substantial correspondence with the overall FI, and the highest correlations were found in the 2/3 SAU (Pearson r and Spearman ρ: 0.95, 0.98), 3/6 and 4/6 SAUs (Pearson r and Spearman ρ: 0.97), and 5/12 to 7/12 SAUs (Pearson r and Spearman ρ: 0.95 to 0.96). The strongest predictors to estimate the overall supraspinatus FI in the regression analysis were these SAU-FIs located in the middle third, which demonstrated good fits to the overall FI (all R 2 ≥ 0.90; RMSE ≤ 1.69). The best agreements between the overall FI predicted by the regression models and the measured overall FI were found in these SAUs (2/3 SAU: sd% = 4.84%; 3/6 and 4/6 SAUs: sd% = 5.14%; 5/12 to 7/12 SAUs: sd% = 6.44%). CONCLUSIONS Specific SAUs near the center of the supraspinatus (2/3, 3/6 and 4/6, and 5/12 to 7/12 SAUs), which displayed the best agreement between the predictions and actual measurements of overall FI values, can serve as appropriate surrogates to estimate the overall FI of the supraspinatus in small-to-massive RC tears. The potential to assess the overall FI of the supraspinatus using specific localized SAUs may improve the speed of analytical strategies for accurately assessing the overall FI of RC muscles and thus enable their routine clinical use in the future. LEVEL OF EVIDENCE Prognostic Level IV . See Instructions for Authors for a complete description of levels of evidence.
Collapse
Affiliation(s)
- Junjie Xu
- Department of Sports Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Beibei Liu
- Institute of Diagnostic and Interventional Radiology, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Yi Qiao
- Department of Sports Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Zipeng Ye
- Department of Sports Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Wei Su
- Department of Sports Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| | - Jinzhong Zhao
- Department of Sports Medicine, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, People's Republic of China
| |
Collapse
|
4
|
Lambert L, Novak M, Siklova M, Krauzova E, Stich V, Burgetova A. Hybrid and Model-Based Iterative Reconstruction Influences the Volumetry of Visceral and Subcutaneous Adipose Tissue on Ultra-Low-Dose CT. Obesity (Silver Spring) 2020; 28:2083-2089. [PMID: 32929884 DOI: 10.1002/oby.22945] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Revised: 06/15/2020] [Accepted: 06/16/2020] [Indexed: 01/18/2023]
Abstract
OBJECTIVE The aim of this study was to compare three different reconstruction algorithms for the volumetry of the visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) on ultra-low-dose computed tomography (CT) images. METHODS Thirty-seven male patients underwent ultra-low-dose CT at the level of the fourth lumbar vertebra (22.5 mm in z-axis). The acquisitions were reconstructed in 5-mm slices with 50% overlap using filtered back projection (FBP), hybrid iterative reconstruction (HIR), and iterative model-based reconstruction (IMR) techniques. The volume of VAT and SAT was measured using an interactive seed-growing segmentation and by thresholding (-30 to -190 HU). RESULTS The volume of SAT measured by the interactive method was smaller in FBP compared with both HIR (P = 0.0011) and IMR (P = 0.0034), and the volume of VAT was greater in IMR compared with HIR (P = 0.0253) or FBP (P = 0.0065). Using the thresholding method, IMR volumes of VAT were greater compared with HIR (P < 0.0001), and volumes of SAT were greater compared with both HIR and FBP (both P ≤ 0.0001). The VAT to SAT ratio was greater in IMR compared with HIR or FBP (both P < 0.0001). CONCLUSIONS There are significant differences among FBP, HIR, and IMR in the volumetry of SAT and VAT, their ratios, and attenuation measured on ultra-low-dose images.
Collapse
Affiliation(s)
- Lukas Lambert
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Matej Novak
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| | - Michaela Siklova
- Department of Pathophysiology, Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Eva Krauzova
- Department of Pathophysiology, Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Vladimir Stich
- Department of Pathophysiology, Third Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Andrea Burgetova
- Department of Radiology, First Faculty of Medicine, Charles University and General University Hospital in Prague, Prague, Czech Republic
| |
Collapse
|
5
|
Orsso CE, Silva MIB, Gonzalez MC, Rubin DA, Heymsfield SB, Prado CM, Haqq AM. Assessment of body composition in pediatric overweight and obesity: A systematic review of the reliability and validity of common techniques. Obes Rev 2020; 21:e13041. [PMID: 32374499 DOI: 10.1111/obr.13041] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2020] [Revised: 04/05/2020] [Accepted: 04/16/2020] [Indexed: 01/13/2023]
Abstract
Accurate measurement of body composition is required to improve health outcomes in children and adolescents with overweight or obesity. This systematic review aimed to summarize the reliability and validity of field and laboratory body composition techniques employed in pediatric obesity studies to facilitate technique selection for research and clinical practice implementation. A systematic search in MEDLINE (via PubMed), EMBASE, CINAHL, and SPORTDiscus from inception up to December 2019 was conducted, using a combination of the following concepts: body composition, pediatric overweight/obesity, and reliability/validity. The search strategy resulted in 66 eligible articles reporting reliability (19.7%), agreement between body composition techniques cross sectionally (80.3%), and/or diagnostic test accuracy (10.6%) in children and adolescents with overweight or obesity (mean age range = 7.0-16.5 years). Skinfolds, air-displacement plethysmography (ADP), dual-energy X-ray absorptiometry (DXA), and ultrasound presented as reliable techniques. DXA, ADP, and isotope dilution showed similar and the best agreement with reference standards. Compared with these laboratory techniques, the validity of estimating body composition by anthropometric equations, skinfolds, and BIA was inferior. In conclusion, the assessment of body composition by laboratory techniques cannot be replaced by field techniques due to introduction of measurement errors, which potentially conceal actual changes in body components.
Collapse
Affiliation(s)
- Camila E Orsso
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Alberta, Canada
| | - Maria Ines B Silva
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Alberta, Canada.,Department of Applied Nutrition, Nutrition Institute, Rio de Janeiro State University, Rio de Janeiro, Brazil.,Department of Applied Nutrition, Nutrition School, Federal University of Rio de Janeiro State, Rio de Janeiro, Brazil
| | - Maria Cristina Gonzalez
- Postgraduate Program in Health and Behavior, Catholic University of Pelotas, Pelotas, Brazil.,Pennington Biomedical Research Center, LSU System, Baton Rouge, Louisiana, USA
| | - Daniela A Rubin
- Department of Kinesiology, California State University, Fullerton, California, USA
| | - Steven B Heymsfield
- Pennington Biomedical Research Center, LSU System, Baton Rouge, Louisiana, USA
| | - Carla M Prado
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Alberta, Canada
| | - Andrea M Haqq
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, Alberta, Canada.,Department of Pediatrics, University of Alberta, Edmonton, Alberta, Canada
| |
Collapse
|
6
|
Linder N, Michel S, Eggebrecht T, Schaudinn A, Blüher M, Dietrich A, Denecke T, Busse H. Estimation of abdominal subcutaneous fat volume of obese adults from single-slice MRI data - Regression coefficients and agreement. Eur J Radiol 2020; 130:109184. [PMID: 32712498 DOI: 10.1016/j.ejrad.2020.109184] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Revised: 06/18/2020] [Accepted: 07/13/2020] [Indexed: 11/19/2022]
Abstract
PURPOSE Cross-sectional imaging is increasingly used to quantify adipose tissue compartments in subjects with overweight or obesity. The lack of ionizing radiation makes magnetic resonance imaging (MRI) highly preferable to computed tomography (CT) although it is generally less standardized and time-consuming. Fat areas of single or stacks of neighboring slices have previously been considered as surrogates to avoid laborious processing of whole abdominal data-but studies are inconsistent in design and results. The present work therefore analyzed a relatively large number of overweight or obese adults and involved a total of eight landmarks and two surrogates (slice and stack). The goals were to identify the most reliable estimators of abdominal subcutaneous adipose tissue (ASAT) volume for both genders and to relate the findings to the pertinent literature. MATERIAL AND METHODS Anthropometric and fat-sensitive 1.5 T MRI data of 193 patients (116 female, 77 male) from different IRB-approved studies at a single clinical research institution (IFB Adiposity Diseases, University Medicine Leipzig, Germany) were analyzed retrospectively. Mean (± SD) age and BMI were 51.5 (± 12.4) years and 33.7 (± 3.9) kg/m2 for females versus 57.6 (± 12.4) years and 32.1 (± 3.7) kg/m2 for males. Areas of selected axial slices (10 mm thick, 0.5 mm gap) and of stacks of five slices at common landmarks - intervertebral disc spaces L1/L2 to L5/S1, anterior superior iliac spine (ASIS), femoral head (FH) and umbilicus (UM) - were considered as estimators for ASAT volume (reference). Agreement between simple areas and reference volumes was asssessed by linear regression (coefficient of determination R2) as well as standard deviations of percent differences sd% between estimated and measured volumes. RESULTS ASAT volumes ranged from 6.61 to 21.94 L for females (mean: 13.37 L) and from 5.42 to 17.90 L (mean: 9.89 L) for males. The smallest sd% (8.4 %-10.1 %) and largest R2 values (0.86-0.92) for single slices were observed for three candidate slice positions that were also associated with the highest ASAT volume fraction: L4/L5, L5/S1 and UM. The stack estimates for these landmarks were overall somewhat better (7.3 %-9.7 %, 0.88-0.94, respectively). The differences in sd% between genders ranged between 0.2 % and 1.1 %. CONCLUSION ASAT volume in overweight or obese patients can be readily estimated with good accuracy from a single MRI slice centered at intervertebral disc space L5/S1 for both genders. Disc space L4/L5 or the umbilicus are nearly equivalent landmarks, in particular for male subjects. The extension to stack measures may yield too little improvement to justify the extra effort. Landmarks like ASIS, FH or the remaining lumbar disc spaces are considered as unreliable.
Collapse
Affiliation(s)
- Nicolas Linder
- Integrated Research and Treatment Center (IFB) Adiposity Diseases, Leipzig University Medical Center, Leipzig, Germany; Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Leipzig, Germany
| | - Sophia Michel
- Integrated Research and Treatment Center (IFB) Adiposity Diseases, Leipzig University Medical Center, Leipzig, Germany; Department of Internal Medicine, Neurology and Dermatology, Division of Endocrinology and Nephrology, Leipzig University Hospital, Leipzig, Germany
| | - Tobias Eggebrecht
- Integrated Research and Treatment Center (IFB) Adiposity Diseases, Leipzig University Medical Center, Leipzig, Germany; Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Leipzig, Germany
| | - Alexander Schaudinn
- Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Leipzig, Germany
| | - Matthias Blüher
- Integrated Research and Treatment Center (IFB) Adiposity Diseases, Leipzig University Medical Center, Leipzig, Germany; Department of Internal Medicine, Neurology and Dermatology, Division of Endocrinology and Nephrology, Leipzig University Hospital, Leipzig, Germany
| | - Arne Dietrich
- Integrated Research and Treatment Center (IFB) Adiposity Diseases, Leipzig University Medical Center, Leipzig, Germany; Department of Visceral, Transplantation, Thoracic and Vascular Surgery, Division of Bariatric Surgery, Leipzig University Hospital, Leipzig, Germany
| | - Timm Denecke
- Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Leipzig, Germany
| | - Harald Busse
- Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Leipzig, Germany.
| |
Collapse
|
7
|
Machann J, Stefan N, Wagner R, Fritsche A, Bell JD, Whitcher B, Häring HU, Birkenfeld AL, Nikolaou K, Schick F, Thomas EL. Normalized Indices Derived from Visceral Adipose Mass Assessed by Magnetic Resonance Imaging and Their Correlation with Markers for Insulin Resistance and Prediabetes. Nutrients 2020; 12:nu12072064. [PMID: 32664590 PMCID: PMC7400828 DOI: 10.3390/nu12072064] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 07/08/2020] [Accepted: 07/09/2020] [Indexed: 12/30/2022] Open
Abstract
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.
Collapse
Affiliation(s)
- Jürgen Machann
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich at the University of Tübingen, 72076 Tübingen, Germany; (N.S.); (R.W.); (A.F.); (A.L.B.); (F.S.)
- German Center for Diabetes Research (DZD), 72076 Tübingen, Germany;
- Section on Experimental Radiology, Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, Hoppe-Seyler-Str. 3, 72076 Tübingen, Germany
- Correspondence:
| | - Norbert Stefan
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich at the University of Tübingen, 72076 Tübingen, Germany; (N.S.); (R.W.); (A.F.); (A.L.B.); (F.S.)
- German Center for Diabetes Research (DZD), 72076 Tübingen, Germany;
- Department of Endocrinology, Diabetology and Nephrology, University Hospital Tübingen, 72076 Tübingen, Germany
| | - Robert Wagner
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich at the University of Tübingen, 72076 Tübingen, Germany; (N.S.); (R.W.); (A.F.); (A.L.B.); (F.S.)
- German Center for Diabetes Research (DZD), 72076 Tübingen, Germany;
- Department of Endocrinology, Diabetology and Nephrology, University Hospital Tübingen, 72076 Tübingen, Germany
| | - Andreas Fritsche
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich at the University of Tübingen, 72076 Tübingen, Germany; (N.S.); (R.W.); (A.F.); (A.L.B.); (F.S.)
- German Center for Diabetes Research (DZD), 72076 Tübingen, Germany;
- Department of Endocrinology, Diabetology and Nephrology, University Hospital Tübingen, 72076 Tübingen, Germany
| | - Jimmy D. Bell
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London W1W 6UW, UK; (J.D.B.); (B.W.); (E.L.T)
| | - Brandon Whitcher
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London W1W 6UW, UK; (J.D.B.); (B.W.); (E.L.T)
| | | | - Andreas L. Birkenfeld
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich at the University of Tübingen, 72076 Tübingen, Germany; (N.S.); (R.W.); (A.F.); (A.L.B.); (F.S.)
- German Center for Diabetes Research (DZD), 72076 Tübingen, Germany;
- Department of Endocrinology, Diabetology and Nephrology, University Hospital Tübingen, 72076 Tübingen, Germany
| | - Konstantin Nikolaou
- Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, 72076 Tübingen, Germany;
| | - Fritz Schick
- Institute for Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Center Munich at the University of Tübingen, 72076 Tübingen, Germany; (N.S.); (R.W.); (A.F.); (A.L.B.); (F.S.)
- German Center for Diabetes Research (DZD), 72076 Tübingen, Germany;
- Section on Experimental Radiology, Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, Hoppe-Seyler-Str. 3, 72076 Tübingen, Germany
| | - E. Louise Thomas
- Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London W1W 6UW, UK; (J.D.B.); (B.W.); (E.L.T)
| |
Collapse
|
8
|
Pescatori LC, Savarino E, Mauri G, Silvestri E, Cariati M, Sardanelli F, Sconfienza LM. Quantification of visceral adipose tissue by computed tomography and magnetic resonance imaging: reproducibility and accuracy. Radiol Bras 2019; 52:1-6. [PMID: 30804608 PMCID: PMC6383529 DOI: 10.1590/0100-3984.2017.0211] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/30/2023] Open
Abstract
Objective To evaluate the feasibility of quantifying visceral adipose tissue (VAT) on
computed tomography (CT) and magnetic resonance imaging (MRI) scans, using
freeware, as well as calculating intraobserver and interobserver
reproducibility. Materials and Methods We quantified VAT in patients who underwent abdominal CT and MRI at our
institution between 2010 and 2015, with a maximum of three months between
the two examinations. A slice acquired at the level of the umbilicus was
selected. Segmentation was performed with the region growing algorithm of
the freeware employed. Intraobserver and interobserver reproducibility were
evaluated, as was the accuracy of MRI in relation to that of CT. Results Thirty-one patients (14 males and 17 females; mean age of 57 ± 15
years) underwent CT and MRI (mean interval between the examinations, 28
± 12 days). The interobserver reproducibility was 82% for CT (bias =
1.52 cm2; p = 0.488), 86% for T1-weighted MRI
(bias = −4.36 cm2; p = 0.006), and 88% for
T2-weighted MRI (bias = −0.52 cm2; p = 0.735).
The intraobserver reproducibility was 90% for CT (bias = 0.14
cm2; p = 0.912), 92% for T1-weighted MRI (bias =
−3,4 cm2; p = 0.035), and 90% for T2-weighted
MRI (bias = −0.30 cm2; p = 0.887). The
reproducibility between T1-weighted MRI and T2-weighted MRI was 87% (bias =
−0.11 cm2; p = 0.957). In comparison with the
accuracy of CT, that of T1-weighted and T2-weighted MRI was 89% and 91%,
respectively. Conclusion The program employed can be used in order to quantify VAT on CT, T1-weighted
MRI, and T2-weighted MRI scans. Overall, the accuracy of MRI (in comparison
with that of CT) appears to be high, as do intraobserver and interobserver
reproducibility. However, the quantification of VAT seems to be less
reproducible in T1-weighted sequences.
Collapse
Affiliation(s)
| | | | | | | | - Maurizio Cariati
- ASST Santi Paolo e Carlo, Presidio San Carlo Borromeo, Milano, Italia
| | - Francesco Sardanelli
- Università degli Studi di Milano, Milano, Italia.,IRCCS Policlinico San Donato, San Donato Milanese, Milano, Italia
| | - Luca Maria Sconfienza
- Università degli Studi di Milano, Milano, Italia.,IRCCS Istituto Ortopedico Galeazzi, Milano, Italia
| |
Collapse
|
9
|
Hübers M, Pourhassan M, Braun W, Geisler C, Müller MJ. Definition of new cut-offs of BMI and waist circumference based on body composition and insulin resistance: differences between children, adolescents and adults. Obes Sci Pract 2017; 3:272-281. [PMID: 29071103 PMCID: PMC5598017 DOI: 10.1002/osp4.121] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2017] [Revised: 06/07/2017] [Accepted: 06/21/2017] [Indexed: 12/17/2022] Open
Abstract
Objective This study aims to determine associations between anthropometric traits, regional fat depots and insulin resistance in children, adolescents and adults to define new cut‐offs of body mass index (BMI) or waist circumference (WC). Design Cross‐sectional data were assessed in 433 children, adolescents and adults (aged: 6–60 years, BMI: 23.6 [21.0–27.7] kg m−2). Total adipose tissue (TAT), regional subcutaneous adipose tissue (SATtotal, SATtrunk) and visceral adipose tissue (VAT) were determined by whole‐body magnetic resonance imaging, fat mass by air‐displacement plethysmography. Insulin resistance was evaluated by homeostasis model assessment of insulin resistance (HOMA‐IR). Bivariate as well as partial correlations and regression analyses were used. Cut‐off values of BMI and WC related to regional fat depots and HOMA‐IR were analysed by receiver operating characteristics curve. Results In adults, TAT, SATtotal and SATtrunk increased linearly with increasing BMI and WC, whereas they followed a cubic function in children and adolescents with a steep increase at BMI and WC ≥1 standard deviation score and VAT at WC ≥2 standard deviation score. Sex differences were apparent in adults with women having higher masses of TAT and SAT and men having higher VAT. Using established BMI or WC cut‐offs, correspondent masses of TAT, SATtotal, SATtrunk and VAT increased from childhood to adulthood. In all age groups, there were positive associations between BMI, WC, SATtrunk, VAT and HOMA‐IR. When compared with normative cut‐offs of BMI or WC, HOMA‐IR‐derived cut‐offs of regional fat depots were lower in all age groups. Conclusions Associations between BMI, WC and regional fat depots varied between children, adolescents, young and older adults. When compared with BMI‐derived and WC‐derived values, an insulin resistance‐derived cut‐off corresponded to lower masses of regional fat depots. Thus, established BMI and WC cut‐offs are not appropriate to assess metabolic disturbances associated with obesity; therefore, new cut‐offs of BMI and WC are needed for clinical practice.
Collapse
Affiliation(s)
- M Hübers
- Institute of Human Nutrition and Food Science, Christian-Albrechts-University Kiel Germany
| | - M Pourhassan
- Department of Geriatric Medicine, Marien Hospital Herne Ruhr-University Bochum Bochum Germany
| | - W Braun
- Institute of Human Nutrition and Food Science, Christian-Albrechts-University Kiel Germany
| | - C Geisler
- Institute of Human Nutrition and Food Science, Christian-Albrechts-University Kiel Germany
| | - M J Müller
- Institute of Human Nutrition and Food Science, Christian-Albrechts-University Kiel Germany
| |
Collapse
|
10
|
Middleton MS, Haufe W, Hooker J, Borga M, Dahlqvist Leinhard O, Romu T, Tunón P, Hamilton G, Wolfson T, Gamst A, Loomba R, Sirlin CB. Quantifying Abdominal Adipose Tissue and Thigh Muscle Volume and Hepatic Proton Density Fat Fraction: Repeatability and Accuracy of an MR Imaging-based, Semiautomated Analysis Method. Radiology 2017; 283:438-449. [PMID: 28278002 DOI: 10.1148/radiol.2017160606] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Purpose To determine the repeatability and accuracy of a commercially available magnetic resonance (MR) imaging-based, semiautomated method to quantify abdominal adipose tissue and thigh muscle volume and hepatic proton density fat fraction (PDFF). Materials and Methods This prospective study was institutional review board- approved and HIPAA compliant. All subjects provided written informed consent. Inclusion criteria were age of 18 years or older and willingness to participate. The exclusion criterion was contraindication to MR imaging. Three-dimensional T1-weighted dual-echo body-coil images were acquired three times. Source images were reconstructed to generate water and calibrated fat images. Abdominal adipose tissue and thigh muscle were segmented, and their volumes were estimated by using a semiautomated method and, as a reference standard, a manual method. Hepatic PDFF was estimated by using a confounder-corrected chemical shift-encoded MR imaging method with hybrid complex-magnitude reconstruction and, as a reference standard, MR spectroscopy. Tissue volume and hepatic PDFF intra- and interexamination repeatability were assessed by using intraclass correlation and coefficient of variation analysis. Tissue volume and hepatic PDFF accuracy were assessed by means of linear regression with the respective reference standards. Results Adipose and thigh muscle tissue volumes of 20 subjects (18 women; age range, 25-76 years; body mass index range, 19.3-43.9 kg/m2) were estimated by using the semiautomated method. Intra- and interexamination intraclass correlation coefficients were 0.996-0.998 and coefficients of variation were 1.5%-3.6%. For hepatic MR imaging PDFF, intra- and interexamination intraclass correlation coefficients were greater than or equal to 0.994 and coefficients of variation were less than or equal to 7.3%. In the regression analyses of manual versus semiautomated volume and spectroscopy versus MR imaging, PDFF slopes and intercepts were close to the identity line, and correlations of determination at multivariate analysis (R2) ranged from 0.744 to 0.994. Conclusion This MR imaging-based, semiautomated method provides high repeatability and accuracy for estimating abdominal adipose tissue and thigh muscle volumes and hepatic PDFF. © RSNA, 2017.
Collapse
Affiliation(s)
- Michael S Middleton
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - William Haufe
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Jonathan Hooker
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Magnus Borga
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Olof Dahlqvist Leinhard
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Thobias Romu
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Patrik Tunón
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Gavin Hamilton
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Tanya Wolfson
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Anthony Gamst
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Rohit Loomba
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| | - Claude B Sirlin
- From the Liver Imaging Group, Department of Radiology (M.S.M., W.H., J.H., G.H., C.B.S.), Computational and Applied Statistics Laboratory, San Diego Supercomputing Center (T.W., A.G.), and Department of Medicine, Division of Gastroenterology and Hepatology (R.L.), University of California, San Diego, 9500 Gilman Dr, MC 0888, San Diego, CA 92093-0888; Advanced MR Analytics AB, Linköping, Sweden (M.B., O.D.L., T.R., P.T.); and Center for Medical Image Science and Visualization (M.B., O.D.L., T.R.), Department of Biomedical Engineering (M.B., T.R.), and Department of Medicine and Health (O.D.L.), Linköping University, Linköping, Sweden
| |
Collapse
|
11
|
Linder N, Schaudinn A, Garnov N, Blüher M, Dietrich A, Schütz T, Lehmann S, Retschlag U, Karlas T, Kahn T, Busse H. Age and gender specific estimation of visceral adipose tissue amounts from radiological images in morbidly obese patients. Sci Rep 2016; 6:22261. [PMID: 27009353 PMCID: PMC4806365 DOI: 10.1038/srep22261] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2015] [Accepted: 02/10/2016] [Indexed: 12/21/2022] Open
Abstract
Image-based quantifications of visceral adipose tissue (VAT) volumes from segmented VAT areas are increasingly considered for risk assessment in obese patients. The goal of this study was to determine the power of partial VAT areas to predict total VAT volume in morbidly obese patients (BMI > 40 kg/m2) as a function of gender, age and anatomical landmarks. 130 morbidly obese patients (mean BMI 46.5 kg/m2; 94 females) underwent IRB-approved MRI. Total VAT volumes were predicted from segmented VAT areas (of single or five adjacent slices) at common axial landmark levels and compared with the measured ones (VVAT-T, about 40 slices between diaphragm and pelvic floor). Standard deviations σ1 and σ5 of the respective VAT volume differences served as measures of agreement. Mean VVAT-T was 4.9 L for females and 8.1 L for males. Best predictions were found at intervertebral spaces L3-L4 for females (σ5 = 688 ml, σ1 = 832 ml) and L1-L2 for males (σ5 = 846 ml, σ1 = 992 ml), irrespective of age. In conclusion, VAT volumes in morbidly obese patients can be reliably predicted by multiplying the segmented VAT area at a gender-specific lumbar reference level with a fixed scaling factor and effective slice thickness.
Collapse
Affiliation(s)
- Nicolas Linder
- Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Liebigstrasse 20, Leipzig, Germany.,Integrated Research and Treatment Center (IFB) Adiposity Diseases, Leipzig University Medical Center, Leipzig, Germany
| | - Alexander Schaudinn
- Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Liebigstrasse 20, Leipzig, Germany.,Integrated Research and Treatment Center (IFB) Adiposity Diseases, Leipzig University Medical Center, Leipzig, Germany
| | - Nikita Garnov
- Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Liebigstrasse 20, Leipzig, Germany.,Integrated Research and Treatment Center (IFB) Adiposity Diseases, Leipzig University Medical Center, Leipzig, Germany
| | - Matthias Blüher
- Integrated Research and Treatment Center (IFB) Adiposity Diseases, Leipzig University Medical Center, Leipzig, Germany.,Department of Internal Medicine, Neurology and Dermatology, Division of Endocrinology and Nephrology, Leipzig University Hospital, Leipzig, Germany
| | - Arne Dietrich
- Integrated Research and Treatment Center (IFB) Adiposity Diseases, Leipzig University Medical Center, Leipzig, Germany.,Department of Visceral, Transplantation, Thoracic and Vascular Surgery, Division of Bariatric Surgery, Leipzig University Hospital, Leipzig, Germany
| | - Tatjana Schütz
- Integrated Research and Treatment Center (IFB) Adiposity Diseases, Leipzig University Medical Center, Leipzig, Germany.,Department of Visceral, Transplantation, Thoracic and Vascular Surgery, Division of Bariatric Surgery, Leipzig University Hospital, Leipzig, Germany
| | - Stefanie Lehmann
- Integrated Research and Treatment Center (IFB) Adiposity Diseases, Leipzig University Medical Center, Leipzig, Germany
| | - Ulf Retschlag
- Integrated Research and Treatment Center (IFB) Adiposity Diseases, Leipzig University Medical Center, Leipzig, Germany
| | - Thomas Karlas
- Integrated Research and Treatment Center (IFB) Adiposity Diseases, Leipzig University Medical Center, Leipzig, Germany.,Department of Internal Medicine, Neurology and Dermatology, Division of Gastroenterology and Rheumatology, Leipzig University Hospital, Leipzig, Germany
| | - Thomas Kahn
- Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Liebigstrasse 20, Leipzig, Germany
| | - Harald Busse
- Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Liebigstrasse 20, Leipzig, Germany
| |
Collapse
|
12
|
Hu HH, Chen J, Shen W. Segmentation and quantification of adipose tissue by magnetic resonance imaging. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2015; 29:259-76. [PMID: 26336839 DOI: 10.1007/s10334-015-0498-z] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2015] [Revised: 08/11/2015] [Accepted: 08/12/2015] [Indexed: 12/13/2022]
Abstract
In this brief review, introductory concepts in animal and human adipose tissue segmentation using proton magnetic resonance imaging (MRI) and computed tomography are summarized in the context of obesity research. Adipose tissue segmentation and quantification using spin relaxation-based (e.g., T1-weighted, T2-weighted), relaxometry-based (e.g., T1-, T2-, T2*-mapping), chemical-shift selective, and chemical-shift encoded water-fat MRI pulse sequences are briefly discussed. The continuing interest to classify subcutaneous and visceral adipose tissue depots into smaller sub-depot compartments is mentioned. The use of a single slice, a stack of slices across a limited anatomical region, or a whole body protocol is considered. Common image post-processing steps and emerging atlas-based automated segmentation techniques are noted. Finally, the article identifies some directions of future research, including a discussion on the growing topic of brown adipose tissue and related segmentation considerations.
Collapse
Affiliation(s)
- Houchun Harry Hu
- Department of Radiology, Phoenix Children's Hospital, 1919 East Thomas Road, Phoenix, AZ, 85016, USA.
| | - Jun Chen
- Obesity Research Center, Department of Medicine, Columbia University Medical Center, 1150 Saint Nicholas Avenue, New York, NY, 10032, USA
| | - Wei Shen
- Obesity Research Center, Department of Medicine and Institute of Human Nutrition, Columbia University Medical Center, 1150 Saint Nicholas Avenue, New York, NY, 10032, USA
| |
Collapse
|
13
|
Schaudinn A, Linder N, Garnov N, Kerlikowsky F, Blüher M, Dietrich A, Schütz T, Karlas T, Kahn T, Busse H. Predictive accuracy of single- and multi-slice MRI for the estimation of total visceral adipose tissue in overweight to severely obese patients. NMR IN BIOMEDICINE 2015; 28:583-590. [PMID: 25808071 DOI: 10.1002/nbm.3286] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2014] [Revised: 02/16/2015] [Accepted: 02/17/2015] [Indexed: 06/04/2023]
Abstract
The quantification of visceral adipose tissue (VAT) is increasingly being considered for risk assessment and treatment monitoring in obese patients, but is generally time-consuming. The goals of this work were to semi-automatically segment and quantify VAT areas of MRI slices at previously proposed anatomical landmarks and to evaluate their predictive power for whole-abdominal VAT volumes on a relatively large number of patients. One-hundred and ninety-seven overweight to severely obese patients (65 males; body mass index, 33.3 ± 3.5 kg/m(2); 132 females; body mass index, 34.3 ± 3.2 kg/m(2)) underwent MRI examination. Total VAT volumes (VVAT-T ) of the abdominopelvic cavity were quantified by retrospective analysis of two-point Dixon MRI data (active-contour segmentation, visual correction and histogram analysis). VVAT-T was then compared with VAT areas determined on one or five slices defined at seven anatomical landmarks (lumbar intervertebral spaces, umbilicus and femoral heads) and corresponding conversion factors were determined. Statistical measures were the coefficients of variation and standard deviations σ1 and σ5 of the difference between predicted and measured VAT volumes (Bland-Altman analysis). VVAT-T was 6.0 ± 2.0 L (2.5-11.2 L) for males and 3.2 ± 1.4 L (0.9-7.7 L) for females. The analysis of five slices yielded a better agreement than the analysis of single slices, required only a little extra time (4 min versus 2 min) and was substantially faster than whole-abdominal assessment (24 min). Best agreements were found at intervertebral spaces L3-L4 for females (σ5/1 = 523/608 mL) and L2-L3 for males (σ5/1 = 613/706 mL). Five-slice VAT volume estimates at the level of lumbar disc L3-L4 for females and L2-L3 for males can be obtained within 4 min and were a reliable predictor for abdominopelvic VAT volume in overweight to severely adipose patients. One-slice estimates took only 2 min and were slightly less accurate. These findings may contribute to the implementation of analytical methods for fast and reliable (routine) estimation of VAT volumes in obese patients.
Collapse
Affiliation(s)
- Alexander Schaudinn
- Department of Diagnostic and Interventional Radiology, Leipzig University Hospital, Leipzig, Germany; Integrated Research and Treatment Center (IFB) AdiposityDiseases, Leipzig University Medical Center, Leipzig, Germany
| | | | | | | | | | | | | | | | | | | |
Collapse
|
14
|
Lange T, Buechert M, Baumstark MW, Deibert P, Gerner S, Rydén H, Seufert J, Korsten-Reck U. Value of MRI and MRS fat measurements to complement conventional screening methods for childhood obesity. J Magn Reson Imaging 2015; 42:1214-22. [DOI: 10.1002/jmri.24919] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2014] [Revised: 04/01/2015] [Accepted: 04/01/2015] [Indexed: 12/11/2022] Open
Affiliation(s)
- Thomas Lange
- Department of Radiology; Medical Physics, University Medical Center Freiburg; Freiburg Germany
- Freiburg Institute for Advanced Studies (FRIAS), University of Freiburg; Freiburg Germany
| | - Martin Buechert
- Department of Radiology; Medical Physics, University Medical Center Freiburg; Freiburg Germany
| | - Manfred W. Baumstark
- Department of Rehabilitative and Preventive Sports Medicine; University Medical Center Freiburg; Freiburg Germany
| | - Peter Deibert
- Department of Rehabilitative and Preventive Sports Medicine; University Medical Center Freiburg; Freiburg Germany
| | - Sarah Gerner
- Department of Rehabilitative and Preventive Sports Medicine; University Medical Center Freiburg; Freiburg Germany
| | - Henric Rydén
- Department of Radiology; Medical Physics, University Medical Center Freiburg; Freiburg Germany
| | - Jochen Seufert
- Department of Endocrinology and Diabetology; University Medical Center Freiburg; Freiburg Germany
| | - Ulrike Korsten-Reck
- Department of Rehabilitative and Preventive Sports Medicine; University Medical Center Freiburg; Freiburg Germany
| |
Collapse
|
15
|
Brown RE, Kuk JL, Lee S. Measurement site influences abdominal subcutaneous and visceral adipose tissue in obese adolescents before and after exercise. Pediatr Obes 2015; 10:98-104. [PMID: 24729534 PMCID: PMC4197119 DOI: 10.1111/j.2047-6310.2014.224.x] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2013] [Revised: 01/15/2014] [Accepted: 01/31/2014] [Indexed: 12/13/2022]
Abstract
BACKGROUND/OBJECTIVES The objective of this study was to determine if abdominal adipose tissue (AT) measurement site influences the association between baseline and change in abdominal subcutaneous (ASAT) and visceral AT (VAT), and metabolic risk factors in obese adolescents. METHODS Fifty-five obese adolescents (14.9 ± 1.7 years; 51% male; 42% white) participated in an aerobic or resistance exercise intervention three times/week for 3 months. We compared the association between changes in abdominal AT area (spanning 5 cm below to 15 cm above L4-L5) and volume measured by magnetic resonance imaging with concomitant changes in metabolic risk. RESULTS All AT areas were significantly (p < 0.05) correlated with the respective volume at baseline and follow-up. Baseline VAT areas at 5 and 10 cm above L4-L5 were more strongly associated with VAT volume than VAT area at L4-L5 (p < 0.05). After the intervention, changes in the area at 5 and 10 cm above L4-L5 were more strongly associated with changes in AT volumes than changes in L4-L5 (p < 0.05). Changes in abdominal AT volumes were more strongly associated with insulin area under the curve than any single-slice abdominal AT area. CONCLUSIONS The measurement site for abdominal AT has significant influence on the relationships with total VAT or ASAT and metabolic risk factors in obese adolescents before and after an exercise intervention.
Collapse
Affiliation(s)
- Ruth E. Brown
- School of Kinesiology and Health Science, York University, Toronto, ON, Canada
| | - Jennifer L. Kuk
- School of Kinesiology and Health Science, York University, Toronto, ON, Canada
| | - SoJung Lee
- Division of Weight Management and Wellness, Children’s Hospital of Pittsburgh of UPMC, University of Pittsburgh School of Medicine, Pittsburgh, PA
| |
Collapse
|
16
|
Can the use of blood-based biomarkers in addition to anthropometric indices substantially improve the prediction of visceral fat volume as measured by magnetic resonance imaging? Eur J Nutr 2014; 54:701-8. [DOI: 10.1007/s00394-014-0748-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2014] [Accepted: 07/24/2014] [Indexed: 12/12/2022]
|
17
|
Neamat-Allah J, Wald D, Hüsing A, Teucher B, Wendt A, Delorme S, Dinkel J, Vigl M, Bergmann MM, Feller S, Hierholzer J, Boeing H, Kaaks R. Validation of anthropometric indices of adiposity against whole-body magnetic resonance imaging--a study within the German European Prospective Investigation into Cancer and Nutrition (EPIC) cohorts. PLoS One 2014; 9:e91586. [PMID: 24626110 PMCID: PMC3953447 DOI: 10.1371/journal.pone.0091586] [Citation(s) in RCA: 65] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2013] [Accepted: 02/12/2014] [Indexed: 01/03/2023] Open
Abstract
Background In epidemiological studies, measures of body fat generally are obtained through anthropometric indices such as the body mass index (BMI), waist (WC), and hip circumferences (HC). Such indices, however, can only provide estimates of a person’s true body fat content, overall or by adipose compartment, and may have limited accuracy, especially for the visceral adipose compartment (VAT). Objective To determine the extent to which different body adipose tissue compartments are adequately predicted by anthropometry, and to identify anthropometric measures alone, or in combination to predict overall adiposity and specific adipose tissue compartments, independently of age and body size (height). Methods In a sub-study of 1,192 participants of the German EPIC (European Prospective Investigation into Cancer and Nutrition) cohorts, whole-body MRI was performed to determine adipose and muscle tissue compartments. Additional anthropometric measurements of BMI, WC and HC were taken. Results After adjusting for age and height, BMI, WC and HC were better predictors of total body volume (TBV), total adipose tissue (TAT) and subcutaneous adipose tissue (SAT) than for VAT, coronary adipose tissue (CAT) and skeletal muscle tissue (SMT). In both sexes, BMI was the best predictor for TBV (men: r = 0.72 [0.68–0.76], women: r = 0.80 [0.77–0.83]) and SMT (men: r = 0.52 [0.45–0.57], women: r = 0.48 [0.41–0.54]). WC was the best predictor variable for TAT (r = 0.48 [0.41–0.54]), VAT (r = 0.44 [0.37–0.50]) and CAT (r = 0.34 [0.26–0.41]) (men), and for VAT (r = 0.42 [0.35–0.49]) and CAT (r = 0.29 [0.22–0.37]) (women). BMI was the best predictor for TAT (r = 0.49 [0.43–0.55]) (women). HC was the best predictor for SAT (men (r = 0.39 [0.32–0.45]) and women (r = 0.52 [0.46–0.58])). Conclusions Especially the volumes of internal body fat compartments are poorly predicted by anthropometry. A possible implication may be that associations of chronic disease risks with the sizes of internal body fat as measured by BMI, WC and HC may be strongly underestimated.
Collapse
Affiliation(s)
- Jasmine Neamat-Allah
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
| | - Diana Wald
- Division of Medical and Biological Informatics, German Cancer Research Center, Heidelberg, Germany
| | - Anika Hüsing
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
| | - Birgit Teucher
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
- Department of Translational Pulmonology, Translational Lung Research Center, Member of the German Center for Lung Research, University of Heidelberg, Heidelberg, Germany
| | - Andrea Wendt
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
| | - Stefan Delorme
- Division of Radiology, German Cancer Research Center, Heidelberg, Germany
| | - Julien Dinkel
- Division of Radiology, German Cancer Research Center, Heidelberg, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Heidelberg, Heidelberg, Germany
| | - Matthaeus Vigl
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany
| | - Manuela M. Bergmann
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany
| | - Silke Feller
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany
| | - Johannes Hierholzer
- Department of Diagnostic and Interventional Radiology, Clinic Ernst-von-Bergmann, Potsdam, Germany
| | - Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
- * E-mail:
| |
Collapse
|
18
|
Scafoglieri A, Clarys JP, Cattrysse E, Bautmans I. Use of anthropometry for the prediction of regional body tissue distribution in adults: benefits and limitations in clinical practice. Aging Dis 2013; 5:373-93. [PMID: 25489489 DOI: 10.14366/ad.2014.0500373] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2013] [Revised: 12/06/2013] [Accepted: 12/07/2013] [Indexed: 12/25/2022] Open
Abstract
Regional body composition changes with aging. Some of the changes in composition are considered major risk factors for developing obesity related chronic diseases which in turn may lead to increased mortality in adults. The role of anthropometry is well recognized in the screening, diagnosis and follow-up of adults for risk classification, regardless of age. Regional body composition is influenced by a number of intrinsic and extrinsic factors. Therapeutic measures recommended to lower cardiovascular disease risk include lifestyle changes. The aim of this review is to systematically summarize studies that assessed the relationships between anthropometry and regional body composition. The potential benefits and limitations of anthropometry for use in clinical practice are presented and suggestions for future research given.
Collapse
Affiliation(s)
- Aldo Scafoglieri
- Department of Human Anatomy, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels ; Department of Experimental Anatomy, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels
| | - Jan Pieter Clarys
- Department of Experimental Anatomy, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels
| | - Erik Cattrysse
- Department of Experimental Anatomy, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels
| | - Ivan Bautmans
- Frailty in Ageing research department, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090 Brussels
| |
Collapse
|
19
|
Eastwood SV, Tillin T, Wright A, Heasman J, Willis J, Godsland IF, Forouhi N, Whincup P, Hughes AD, Chaturvedi N. Estimation of CT-derived abdominal visceral and subcutaneous adipose tissue depots from anthropometry in Europeans, South Asians and African Caribbeans. PLoS One 2013; 8:e75085. [PMID: 24069381 PMCID: PMC3775834 DOI: 10.1371/journal.pone.0075085] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2013] [Accepted: 08/12/2013] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND South Asians and African Caribbeans experience more cardiometabolic disease than Europeans. Risk factors include visceral (VAT) and subcutaneous abdominal (SAT) adipose tissue, which vary with ethnicity and are difficult to quantify using anthropometry. OBJECTIVE We developed and cross-validated ethnicity and gender-specific equations using anthropometrics to predict VAT and SAT. DESIGN 669 Europeans, 514 South Asians and 227 African Caribbeans (70 ± 7 years) underwent anthropometric measurement and abdominal CT scanning. South Asian and African Caribbean participants were first-generation migrants living in London. Prediction equations were derived for CT-measured VAT and SAT using stepwise regression, then cross-validated by comparing actual and predicted means. RESULTS South Asians had more and African Caribbeans less VAT than Europeans. For basic VAT prediction equations (age and waist circumference), model fit was better in men (R(2) range 0.59-0.71) than women (range 0.35-0.59). Expanded equations (+ weight, height, hip and thigh circumference) improved fit for South Asian and African Caribbean women (R(2) 0.35 to 0.55, and 0.43 to 0.56 respectively). For basic SAT equations, R(2) was 0.69-0.77, and for expanded equations it was 0.72-0.86. Cross-validation showed differences between actual and estimated VAT of <7%, and SAT of <8% in all groups, apart from VAT in South Asian women which disagreed by 16%. CONCLUSION We provide ethnicity- and gender-specific VAT and SAT prediction equations, derived from a large tri-ethnic sample. Model fit was reasonable for SAT and VAT in men, while basic VAT models should be used cautiously in South Asian and African Caribbean women. These equations will aid studies of mechanisms of cardiometabolic disease in later life, where imaging data are not available.
Collapse
Affiliation(s)
- Sophie V. Eastwood
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Therese Tillin
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Andrew Wright
- Department of Medicine, Imperial College Healthcare NHS Trust, London, United Kingdom
| | - John Heasman
- Department of Medicine, Imperial College Healthcare NHS Trust, London, United Kingdom
| | - Joseph Willis
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Ian F. Godsland
- Department of Endocrinology and Metabolic Medicine, Imperial College London, London, United Kingdom
| | - Nita Forouhi
- MRC (Medical Research Council) Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Peter Whincup
- Division of Population Health Sciences and Education, St. George’s University of London, London, United Kingdom
| | - Alun D. Hughes
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Nishi Chaturvedi
- National Heart and Lung Institute, Imperial College London, London, United Kingdom
| |
Collapse
|