Literature DB >> 26250623

Imaging methods for analyzing body composition in human obesity and cardiometabolic disease.

Lynn A Seabolt1, E Brian Welch2, Heidi J Silver1.   

Abstract

Advances in the technological qualities of imaging modalities for assessing human body composition have been stimulated by accumulating evidence that individual components of body composition have significant influences on chronic disease onset, disease progression, treatment response, and health outcomes. Importantly, imaging modalities have provided a systematic method for differentiating phenotypes of body composition that diverge from what is considered normal, that is, having low bone mass (osteopenia/osteoporosis), low muscle mass (sarcopenia), high fat mass (obesity), or high fat with low muscle mass (sarcopenic obesity). Moreover, advances over the past three decades in the sensitivity and quality of imaging not just to discern the amount and distribution of adipose and lean tissue but also to differentiate layers or depots within tissues and cells is enhancing our understanding of distinct mechanistic, metabolic, and functional roles of body composition within human phenotypes. In this review, we focus on advances in imaging technologies that show great promise for future investigation of human body composition and how they are being used to address the pandemic of obesity, metabolic syndrome, and diabetes.
© 2015 New York Academy of Sciences.

Entities:  

Keywords:  CT; DXA; MRI; MRS; body composition; diabetes; imaging; obesity

Mesh:

Year:  2015        PMID: 26250623     DOI: 10.1111/nyas.12842

Source DB:  PubMed          Journal:  Ann N Y Acad Sci        ISSN: 0077-8923            Impact factor:   5.691


  26 in total

1.  Deep Learning-based Quantification of Abdominal Subcutaneous and Visceral Fat Volume on CT Images.

Authors:  Andrew T Grainger; Arun Krishnaraj; Michael H Quinones; Nicholas J Tustison; Samantha Epstein; Daniela Fuller; Aakash Jha; Kevin L Allman; Weibin Shi
Journal:  Acad Radiol       Date:  2020-08-05       Impact factor: 3.173

2.  Muscle Quality, Strength, and Lower Extremity Physical Performance in the Baltimore Longitudinal Study of Aging.

Authors:  N Chiles Shaffer; E Fabbri; L Ferrucci; M Shardell; E M Simonsick; S Studenski
Journal:  J Frailty Aging       Date:  2017

Review 3.  Diagnostic imaging in the management of patients with metabolic syndrome.

Authors:  Seo Rin Kim; Lilach O Lerman
Journal:  Transl Res       Date:  2017-11-22       Impact factor: 7.012

Review 4.  Quantification of skeletal muscle mass: sarcopenia as a marker of overall health in children and adults.

Authors:  Leah A Gilligan; Alexander J Towbin; Jonathan R Dillman; Elanchezhian Somasundaram; Andrew T Trout
Journal:  Pediatr Radiol       Date:  2019-11-20

5.  Multi-disciplinary weight management compared to routine care in youth with obesity: what else should be monitored?

Authors:  Indrajit Majumdar; Brittany Espino; Kristina Bianco; Jeanette Epstein; Leena Mamilly; Carroll M Harmon
Journal:  Endocrine       Date:  2019-06-27       Impact factor: 3.633

6.  Atherothrombosis and Thromboembolism: Position Paper from the Second Maastricht Consensus Conference on Thrombosis.

Authors:  H M H Spronk; T Padro; J E Siland; J H Prochaska; J Winters; A C van der Wal; J J Posthuma; G Lowe; E d'Alessandro; P Wenzel; D M Coenen; P H Reitsma; W Ruf; R H van Gorp; R R Koenen; T Vajen; N A Alshaikh; A S Wolberg; F L Macrae; N Asquith; J Heemskerk; A Heinzmann; M Moorlag; N Mackman; P van der Meijden; J C M Meijers; M Heestermans; T Renné; S Dólleman; W Chayouâ; R A S Ariëns; C C Baaten; M Nagy; A Kuliopulos; J J Posma; P Harrison; M J Vries; H J G M Crijns; E A M P Dudink; H R Buller; Y M C Henskens; A Själander; S Zwaveling; O Erküner; J W Eikelboom; A Gulpen; F E C M Peeters; J Douxfils; R H Olie; T Baglin; A Leader; U Schotten; B Scaf; H M M van Beusekom; L O Mosnier; L van der Vorm; P Declerck; M Visser; D W J Dippel; V J Strijbis; K Pertiwi; A J Ten Cate-Hoek; H Ten Cate
Journal:  Thromb Haemost       Date:  2018-01-29       Impact factor: 5.249

7.  Regional variation in paraspinal muscle composition using chemical shift encoding-based water-fat MRI.

Authors:  Nico Sollmann; Agnes Zoffl; Daniela Franz; Jan Syväri; Michael Dieckmeyer; Egon Burian; Elisabeth Klupp; Dennis M Hedderich; Christina Holzapfel; Theresa Drabsch; Jan S Kirschke; Ernst J Rummeny; Claus Zimmer; Hans Hauner; Dimitrios C Karampinos; Thomas Baum
Journal:  Quant Imaging Med Surg       Date:  2020-02

8.  The perils of using predicted values in place of observed covariates: an example of predicted values of body composition and mortality risk.

Authors:  Gregory Haber; Joshua Sampson; Katherine M Flegal; Barry Graubard
Journal:  Am J Clin Nutr       Date:  2021-08-02       Impact factor: 7.045

9.  Association of Sarcopenia and Body Composition With Short-term Outcomes After Liver Resection for Malignant Tumors.

Authors:  Giammauro Berardi; Giulio Antonelli; Marco Colasanti; Roberto Meniconi; Nicola Guglielmo; Andrea Laurenzi; Stefano Ferretti; Giovanni Battista Levi Sandri; Alessandra Spagnoli; Giovanni Moschetta; Vincenzo Schininà; Mario Antonini; Massimo Marignani; Giuseppe Maria Ettorre
Journal:  JAMA Surg       Date:  2020-11-18       Impact factor: 14.766

Review 10.  Application of Magnetic Resonance Imaging in the Evaluation of Nutritional Status: A Literature Review with Focus on Dialysis Patients.

Authors:  Tsutomu Inoue; Eito Kozawa; Masahiro Ishikawa; Hirokazu Okada
Journal:  Nutrients       Date:  2021-06-14       Impact factor: 5.717

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