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2. Cross-sectional assessment of body composition and detection of malnutrition risk in participants with low body mass index and eating disorders using 3D optical surface scans

Author

Garber, Andrea K, Bennett, Jonathan P, Wong, Michael C, Tian, Isaac Y, Maskarinec, Gertraud, Kennedy, Samantha F, McCarthy, Cassidy, Kelly, Nisa N, Liu, Yong E, Machen, Vanessa I, Heymsfield, Steven B, and Shepherd, John A

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Clinical Sciences, Clinical Research, Aging, Sarcopenia, Women's Health, Obesity, Nutrition, Metabolic and endocrine, Zero Hunger, Adult, Male, Child, Adolescent, Humans, Female, Body Mass Index, Body Composition, Malnutrition, Absorptiometry, Photon, Weight Loss, Feeding and Eating Disorders, 3-Dimensional Optical imaging, anorexia nervosa, atypical anorexia nervosa, adolescents, body composition, malnutrition, sarcopenia, nutritional rehabilitation, body mass index, dual X-ray absorptiometry, Engineering, Medical and Health Sciences, Nutrition & Dietetics, Clinical sciences, Nutrition and dietetics
Abstract

BackgroundNew recommendations for the assessment of malnutrition and sarcopenia include body composition, specifically reduced muscle mass. Three-dimensional optical imaging (3DO) is a validated, accessible, and affordable alternative to dual X-ray absorptiometry (DXA).ObjectiveIdentify strengths and weaknesses of 3DO for identification of malnutrition in participants with low body mass index (BMI) and eating disorders.DesignParticipants were enrolled in the cross-sectional Shape Up! Adults and Kids studies of body shape, metabolic risk, and functional assessment and had BMI of

Published
2023

3. The bioelectrical impedance analysis (BIA) international database: aims, scope, and call for data

Author

Silva, Analiza M., Campa, Francesco, Stagi, Silvia, Gobbo, Luís A., Buffa, Roberto, Toselli, Stefania, Silva, Diego Augusto Santos, Gonçalves, Ezequiel M., Langer, Raquel D., Guerra-Júnior, Gil, Machado, Dalmo R. L., Kondo, Emi, Sagayama, Hiroyuki, Omi, Naomi, Yamada, Yosuke, Yoshida, Tsukasa, Fukuda, Wataru, Gonzalez, Maria Cristina, Orlandi, Silvana P., Koury, Josely C., Moro, Tatiana, Paoli, Antonio, Kruger, Salome, Schutte, Aletta E., Andreolli, Angela, Earthman, Carrie P., Fuchs-Tarlovsky, Vanessa, Irurtia, Alfredo, Castizo-Olier, Jorge, Mascherini, Gabriele, Petri, Cristian, Busert, Laura K., Cortina-Borja, Mario, Bailey, Jeanette, Tausanovitch, Zachary, Lelijveld, Natasha, Ghazzawi, Hadeel Ali, Amawi, Adam Tawfiq, Tinsley, Grant, Kangas, Suvi T., Salpéteur, Cécile, Vázquez-Vázquez, Adriana, Fewtrell, Mary, Ceolin, Chiara, Sergi, Giuseppe, Ward, Leigh C., Heitmann, Berit L., da Costa, Roberto Fernandes, Vicente-Rodriguez, German, Cremasco, Margherita Micheletti, Moroni, Alessia, Shepherd, John, Moon, Jordan, Knaan, Tzachi, Müller, Manfred J., Braun, Wiebke, García‐Almeida, José M., Palmeira, António L., Santos, Inês, Larsen, Sofus C., Zhang, Xueying, Speakman, John R., Plank, Lindsay D., Swinburn, Boyd A., Ssensamba, Jude Thaddeus, Shiose, Keisuke, Cyrino, Edilson S., Bosy-Westphal, Anja, Heymsfield, Steven B., Lukaski, Henry, Sardinha, Luís B., Wells, Jonathan C., and Marini, Elisabetta

Published
2023
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5. Quantitative Imaging Principles Improves Medical Image Learning

Author

Leong, Lambert T., Wong, Michael C., Glaser, Yannik, Wolfgruber, Thomas, Heymsfield, Steven B., Sadowski, Peter, and Shepherd, John A.

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Computer Vision and Pattern Recognition, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

Fundamental differences between natural and medical images have recently favored the use of self-supervised learning (SSL) over ImageNet transfer learning for medical image applications. Differences between image types are primarily due to the imaging modality and medical images utilize a wide range of physics based techniques while natural images are captured using only visible light. While many have demonstrated that SSL on medical images has resulted in better downstream task performance, our work suggests that more performance can be gained. The scientific principles which are used to acquire medical images are not often considered when constructing learning problems. For this reason, we propose incorporating quantitative imaging principles during generative SSL to improve image quality and quantitative biological accuracy. We show that this training schema results in better starting states for downstream supervised training on limited data. Our model also generates images that validate on clinical quantitative analysis software.

Published
2022

12. Guidance for assessment of the inflammation etiologic criterion for the GLIM diagnosis of malnutrition: A modified Delphi approach

Author

Cederholm, Tommy, Jensen, Gordon L., Ballesteros-Pomar, Maria D., Blaauw, Renee, Correia, M. Isabel T.D., Cuerda, Cristina, Evans, David C., Fukushima, Ryoji, Ochoa Gautier, Juan Bernardo, Gonzalez, M. Cristina, van Gossum, Andre, Gramlich, Leah, Hartono, Joseph, Heymsfield, Steven B., Jager-Wittenaar, Harriët, Jayatissa, Renuka, Keller, Heather, Malone, Ainsley, Manzanares, William, McMahon, M. Molly, Mendez, Yolanda, Mogensen, Kris M., Mori, Naoharu, Muscaritoli, Maurizio, Nogales, Guillermo Contreras, Nyulasi, Ibolya, Phillips, Wendy, Pirlich, Matthias, Pisprasert, Veeradej, Rothenberg, Elisabet, de van der Schueren, Marian, Shi, Han Ping, Steiber, Alison, Winkler, Marion F., Barazzoni, Rocco, and Compher, Charlene

Published
2024
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14. Subcutaneous and visceral fat assessment by DXA and MRI in older adults and children

Author

Maskarinec, Gertraud, Shvetsov, Yurii B, Wong, Michael C, Garber, Andrea, Monroe, Kristine, Ernst, Thomas M, Buchthal, Steven D, Lim, Unhee, Le Marchand, Loïc, Heymsfield, Steven B, and Shepherd, John A

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Health Sciences, Pediatric, Prevention, Clinical Research, Biomedical Imaging, Obesity, Absorptiometry, Photon, Adiposity, Adolescent, Aged, Humans, Intra-Abdominal Fat, Magnetic Resonance Imaging, Subcutaneous Fat, Endocrinology & Metabolism
Abstract

ObjectiveGiven the importance of body fat distribution in chronic disease development, feasible methods to assess body fat are essential. This study compared dual-energy x-ray absorptiometry (DXA) in measuring visceral and subcutaneous adipose tissue (VAT and SAT) with magnetic resonance imaging (MRI).MethodsVAT and SAT were assessed using similar DXA and MRI protocols among 1,795 elderly participants of the Adiposity Phenotype Study (APS) and 309 children/adolescents in Shape Up! Kids (SKids). Spearman correlations, Bland-Altman plots, and coefficients of determination (R2 ) assessed agreement between DXA and MRI measures.ResultsDXA overestimated SAT values in APS (315 vs. 229 cm2 ) and SKids (212 vs. 161 cm2 ), whereas DXA underestimated VAT measures (141 vs. 167 cm2 ) in adults only. The correlations between DXA and MRI values were stronger for SAT than VAT (APS: r = 0.92 vs. 0.88; SKids: 0.90 vs. 0.74). Bland-Altman plots confirmed better agreement for SAT than VAT despite differences by sex, ethnicity, and weight status with respective R2 values for SAT and VAT of 0.88 and 0.84 (APS) and 0.81 and 0.69 (SKids).ConclusionThese findings indicate that SAT by DXA reflects MRI measures in children and older adults, whereas agreement for VAT is weaker for individuals with low VAT levels.

Published
2022

17. Assessment of clinical measures of total and regional body composition from a commercial 3-dimensional optical body scanner

Author

Bennett, Jonathan P, Liu, Yong En, Quon, Brandon K, Kelly, Nisa N, Wong, Michael C, Kennedy, Samantha F, Chow, Dominic C, Garber, Andrea K, Weiss, Ethan J, Heymsfield, Steven B, and Shepherd, John A

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Biomedical Imaging, Obesity, Clinical Trials and Supportive Activities, Nutrition, Prevention, Clinical Research, Metabolic and endocrine, Cancer, Stroke, Oral and gastrointestinal, Absorptiometry, Photon, Adolescent, Adult, Anthropometry, Body Composition, Body Mass Index, Female, Humans, Imaging, Three-Dimensional, Male, Middle Aged, Reproducibility of Results, Whole Body Imaging, Young Adult, 3-Dimensional optical, Digital anthropometry, DXA, Fat free mass, Body fat percent, Validation, Nutrition and Dietetics, Nutrition & Dietetics, Nutrition and dietetics
Abstract

BackgroundThe accurate assessment of total body and regional body circumferences, volumes, and compositions are critical to monitor physical activity and dietary interventions, as well as accurate disease classifications including obesity, metabolic syndrome, sarcopenia, and lymphedema. We assessed body composition and anthropometry estimates provided by a commercial 3-dimensional optical (3DO) imaging system compared to criterion measures.MethodsParticipants of the Shape Up! Adults study were recruited for similar sized stratifications by sex, age (18-40, 40-60, >60 years), BMI (under, normal, overweight, obese), and across five ethnicities (non-Hispanic [NH] Black, NH White, Hispanic, Asian, Native Hawaiian/Pacific Islander). All participants received manual anthropometry assessments, duplicate whole-body 3DO (Styku S100), and dual-energy X-ray absorptiometry (DXA) scans. 3DO estimates provided by the manufacturer for anthropometry and body composition were compared to the criterion measures using concordance correlation coefficient (CCC) and Bland-Altman analysis. Test-retest precision was assessed by root mean square error (RMSE) and coefficient of variation.ResultsA total of 188 (102 female) participants were included. The overall fat free mass (FFM) as measured by DXA (54.1 ± 15.2 kg) and 3DO (55.3 ± 15.0 kg) showed a small mean difference of 1.2 ± 3.4 kg (95% limits of agreement -7.0 to +5.6) and the CCC was 0.97 (95% CI: 0.96-0.98). The CCC for FM was 0.95 (95% CI: 0.94-0.97) and the mean difference of 1.3 ± 3.4 kg (95% CI: -5.5 to +8.1) reflected the difference in FFM measures. 3DO anthropometry and body composition measurements showed high test-retest precision for whole body volume (1.1 L), fat mass (0.41 kg), percent fat (0.60%), arm and leg volumes, (0.11 and 0.21 L, respectively), and waist and hip circumferences (all

Published
2022

18. The carbohydrate-insulin model: a physiological perspective on the obesity pandemic

Author

Ludwig, David S, Aronne, Louis J, Astrup, Arne, de Cabo, Rafael, Cantley, Lewis C, Friedman, Mark I, Heymsfield, Steven B, Johnson, James D, King, Janet C, Krauss, Ronald M, Lieberman, Daniel E, Taubes, Gary, Volek, Jeff S, Westman, Eric C, Willett, Walter C, Yancy, William S, and Ebbeling, Cara B

Subjects
Prevention, Obesity, Nutrition, Cancer, Cardiovascular, Oral and gastrointestinal, Metabolic and endocrine, Stroke, Affordable and Clean Energy, Carbohydrates, Dietary Carbohydrates, Dietary Fats, Energy Intake, Energy Metabolism, Humans, Insulin, Pandemics, obesity, weight loss, dietary carbohydrate, energy balance, macronutrients, endocrinology, insulin, glucagon, incretins, scholarly discourse, Engineering, Medical and Health Sciences, Nutrition & Dietetics
Abstract

According to a commonly held view, the obesity pandemic is caused by overconsumption of modern, highly palatable, energy-dense processed foods, exacerbated by a sedentary lifestyle. However, obesity rates remain at historic highs, despite a persistent focus on eating less and moving more, as guided by the energy balance model (EBM). This public health failure may arise from a fundamental limitation of the EBM itself. Conceptualizing obesity as a disorder of energy balance restates a principle of physics without considering the biological mechanisms that promote weight gain. An alternative paradigm, the carbohydrate-insulin model (CIM), proposes a reversal of causal direction. According to the CIM, increasing fat deposition in the body-resulting from the hormonal responses to a high-glycemic-load diet-drives positive energy balance. The CIM provides a conceptual framework with testable hypotheses for how various modifiable factors influence energy balance and fat storage. Rigorous research is needed to compare the validity of these 2 models, which have substantially different implications for obesity management, and to generate new models that best encompass the evidence.

Published
2021

19. A pose‐independent method for accurate and precise body composition from 3D optical scans

Author

Wong, Michael C, Ng, Bennett K, Tian, Isaac, Sobhiyeh, Sima, Pagano, Ian, Dechenaud, Marcelline, Kennedy, Samantha F, Liu, Yong E, Kelly, Nisa N, Chow, Dominic, Garber, Andrea K, Maskarinec, Gertraud, Pujades, Sergi, Black, Michael J, Curless, Brian, Heymsfield, Steven B, and Shepherd, John A

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Absorptiometry, Photon, Adipose Tissue, Adult, Anthropometry, Body Composition, Female, Humans, Linear Models, Male, Whole Body Imaging, Endocrinology & Metabolism
Abstract

ObjectiveThe aim of this study was to investigate whether digitally re-posing three-dimensional optical (3DO) whole-body scans to a standardized pose would improve body composition accuracy and precision regardless of the initial pose.MethodsHealthy adults (n = 540), stratified by sex, BMI, and age, completed whole-body 3DO and dual-energy X-ray absorptiometry (DXA) scans in the Shape Up! Adults study. The 3DO mesh vertices were represented with standardized templates and a low-dimensional space by principal component analysis (stratified by sex). The total sample was split into a training (80%) and test (20%) set for both males and females. Stepwise linear regression was used to build prediction models for body composition and anthropometry outputs using 3DO principal components (PCs).ResultsThe analysis included 472 participants after exclusions. After re-posing, three PCs described 95% of the shape variance in the male and female training sets. 3DO body composition accuracy compared with DXA was as follows: fat mass R2 = 0.91 male, 0.94 female; fat-free mass R2 = 0.95 male, 0.92 female; visceral fat mass R2 = 0.77 male, 0.79 female.ConclusionsRe-posed 3DO body shape PCs produced more accurate and precise body composition models that may be used in clinical or nonclinical settings when DXA is unavailable or when frequent ionizing radiation exposure is unwanted.

Published
2021

26. Sarcopenic obesity research perspectives outlined by the sarcopenic obesity global leadership initiative (SOGLI) – Proceedings from the SOGLI consortium meeting in Rome November 2022

Author

Bosy-Westphal, Anja, Brunani, Amelia, Capodaglio, Paolo, Coletti, Dario, Ferretti, Elisabetta, Frigerio, Francesco, Giustina, Andrea, Lenzi, Andrea, Marini, Elisabetta, Migliaccio, Silvia, Minnetti, Marianna, Mocini, Edoardo, Moro, Tatiana, Muscaritoli, Maurizio, Noirez, Philippe, Paoli, Antonio, Rondanelli, Mariangela, Rughetti, Auralia, Schoufour, Josje D., Skalska, Anna, Topinkova, Eva, Wakabayashi, Hidekata, Yu, Jianchun, Gortan Cappellari, Gianluca, Guillet, Christelle, Poggiogalle, Eleonora, Ballesteros Pomar, Maria D., Batsis, John A., Boirie, Yves, Breton, Irene, Frara, Stefano, Genton, Laurence, Gepner, Yftach, Gonzalez, Maria Cristina, Heymsfield, Steven B., Kiesswetter, Eva, Laviano, Alessandro, Prado, Carla M., Santini, Ferruccio, Serlie, Mireille J., Siervo, Mario, Villareal, Dennis T., Volkert, Dorothee, Voortman, Trudy, Weijs, Peter JM., Zamboni, Mauro, Bischoff, Stephan C., Busetto, Luca, Cederholm, Tommy, Barazzoni, Rocco, and Donini, Lorenzo M.

Published
2023
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29. Monitoring body composition change for intervention studies with advancing 3D optical imaging technology in comparison to dual-energy X-ray absorptiometry

Author

Wong, Michael C., Bennett, Jonathan P., Leong, Lambert T., Tian, Isaac Y., Liu, Yong E., Kelly, Nisa N., McCarthy, Cassidy, Wong, Julia M.W., Ebbeling, Cara B., Ludwig, David S., Irving, Brian A., Scott, Matthew C., Stampley, James, Davis, Brett, Johannsen, Neil, Matthews, Rachel, Vincellette, Cullen, Garber, Andrea K., Maskarinec, Gertraud, Weiss, Ethan, Rood, Jennifer, Varanoske, Alyssa N., Pasiakos, Stefan M., Heymsfield, Steven B., and Shepherd, John A.

Published
2023
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38. Genetic reprogramming of remnant duodenum may contribute to type 2 diabetes improvement after Roux-en-Y gastric bypass

Author

Sala, Priscila, Machado, Natasha Mendonça, Torrinhas, Raquel Susana Matos de Miranda, Fonseca, Danielle C., Ferreira, Beatriz AM, Ishida, Robson Kiyoshi, Guarda, Ismael Francisco Mota Siqueira, de Moura, Eduardo Guimarães Hourneaux, Sakai, Paulo, Santo, Marco Aurélio, Heymsfield, Steven B., Corrêa-Giannella, Maria Lúcia, and Waitzberg, Dan Linetzky

Published
2022
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40. Long‐term sustained effects of the Look AHEAD lifestyle intervention on body composition among adults with type 2 diabetes.

Author

Ashby‐Thompson, Maxine, Heshka, Stanley, Anderson, Andrea, Pownall, Henry, Laferrère, Blandine, Balasubramanyam, Ashok, Heymsfield, Steven B., Wadden, Thomas A., and Gallagher, Dympna

Subjects
BODY composition, TYPE 2 diabetes, LEAN body mass, DUAL-energy X-ray absorptiometry, BODY weight
Abstract

Objective: The objective of the study was to test whether there are sustained effects of the Look AHEAD intensive lifestyle intervention (ILI), versus diabetes support and education (DSE), on weight and body composition 12 to 16 years after randomization. Methods: Participants were a subset of enrollees in the Look AHEAD dual‐energy x‐ray absorptiometry substudy who completed the final visit, composed of men (DSE = 99; ILI = 94) and women (DSE = 134; ILI = 135) with type 2 diabetes and mean (SD) age 57.2 (6.4) years and BMI 34.9 (5.1) kg/m2 at randomization. Dual‐energy x‐ray absorptiometry measured total and regional fat and lean masses at randomization, at Years 1, 4, and 8, and at the final visit. Linear mixed‐effects regressions were applied with adjustment for group, clinic, sex, age, race/ethnicity, and baseline body composition. Results: Weight and most body compartments were reduced by 2% to 8% (and BMI 4%) in ILI versus DSE in men but not women. ILI‐induced loss of lean tissue did not show a lower percent lean mass versus DSE at 16 years after randomization. Conclusion: ILI‐related changes in weight, fat, and lean mass were detectable 12 to 16 years after randomization in men but, for unknown reasons, not in women. There was no evidence that the intervention led to a disproportionate loss of lean mass by the end of the study. [ABSTRACT FROM AUTHOR]

Published
2024
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43. The metabolic load‐capacity model and cardiometabolic health in children and youth with obesity

Author

Orsso, Camila E., primary, Vieira, Flavio T., additional, Basuray, Nandini, additional, Duke, Reena L., additional, Pakseresht, Mohammadreza, additional, Rubin, Daniela A., additional, Ajamian, Faria, additional, Ball, Geoff D. C., additional, Field, Catherine J., additional, Heymsfield, Steven B., additional, Siervo, Mario, additional, Prado, Carla M., additional, and Haqq, Andrea M., additional

Published
2024
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44. Guidance for assessment of the inflammation etiologic criterion for the GLIM diagnosis of malnutrition: A modified Delphi approach

Author

Jensen, Gordon L., primary, Cederholm, Tommy, additional, Ballesteros‐Pomar, Maria D., additional, Blaauw, Renee, additional, Correia, M. Isabel T. D., additional, Cuerda, Cristina, additional, Evans, David C., additional, Fukushima, Ryoji, additional, Gautier, Juan Bernardo Ochoa, additional, Gonzalez, M. Cristina, additional, van Gossum, Andre, additional, Gramlich, Leah, additional, Hartono, Joseph, additional, Heymsfield, Steven B., additional, Jager‐Wittenaar, Harriët, additional, Jayatissa, Renuka, additional, Keller, Heather, additional, Malone, Ainsley, additional, Manzanares, William, additional, McMahon, M. Molly, additional, Mendez, Yolanda, additional, Mogensen, Kris M., additional, Mori, Naoharu, additional, Muscaritoli, Maurizio, additional, Nogales, Guillermo Contreras, additional, Nyulasi, Ibolya, additional, Phillips, Wendy, additional, Pirlich, Matthias, additional, Pisprasert, Veeradej, additional, Rothenberg, Elisabet, additional, de van der Schueren, Marian, additional, Shi, Han Ping, additional, Steiber, Alison, additional, Winkler, Marion F., additional, Compher, Charlene, additional, and Barazzoni, Rocco, additional

Published
2024
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48. Guidance for Assessment of the Inflammation Etiologic Criterion for the Global Leadership Initiative (GLIM) on Diagnosis of Malnutrition: A Modified Delphi Approach

Author

Cederholm, Tommy, primary, Jensen, Gordon L., additional, Ballesteros-Pomar, Maria D., additional, Blaauw, Renee, additional, Correia, M. Isabel T.D., additional, Cuerda, Cristina, additional, Evans, David C., additional, Fukushima, Ryoji, additional, Ochoa Gautier, Juan Bernardo, additional, Gonzalez, M. Cristina, additional, van Gossum, Andre, additional, Gramlich, Leah, additional, Hartono, Joseph, additional, Heymsfield, Steven B., additional, Jager-Wittenaar, Harriët, additional, Jayatissa, Renuka, additional, Keller, Heather, additional, Malone, Ainsley, additional, Manzanares, William, additional, McMahon, M. Molly, additional, Mendez, Yolanda, additional, Mogensen, Kris M., additional, Mori, Naoharu, additional, Muscaritoli, Maurizio, additional, Nogales, Guillermo Contreras, additional, Nyulasi, Ibolya, additional, Phillips, Wendy, additional, Pirlich, Matthias, additional, Pisprasert, Veeradej, additional, Rothenberg, Elisabet, additional, de van der Schueren, Marian, additional, Shi, Han Ping, additional, Steiber, Alison, additional, Winkler, Marion F., additional, Barazzoni, Rocco, additional, and Compher, Charlene, additional

Published
2023
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50. Gastrointestinal genetic reprogramming of vitamin A metabolic pathways in response of Roux-en-Y gastric bypass.

Author

Sampaio, Priscilla, Waitzberg, Dan Linetzky, Machado, Natasha Mendonça, de Miranda Torrinhas, Raquel Susana Matos, Fonseca, Danielle C., Ferreira, Beatriz A. M., Marques, Mariane, Barcelos, Samira, Ishida, Robson Kiyoshi, Guarda, Ismael Francisco Mota Siqueira, de Moura, Eduardo Guimarães Hourneaux, Sakai, Paulo, Santo, Marco Aurélio, Heymsfield, Steven B., Corrêa-Giannella, Maria Lúcia, Passadore, Mariana Doce, and Sala, Priscila

Published
2024
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