Literature DB >> 28670043

Obesity, adiposopathy, and quantitative imaging biomarkers.

Fernando Ide Yamauchi1, Adham do Amaral E Castro2.   

Abstract

Entities:  

Year:  2017        PMID: 28670043      PMCID: PMC5487244          DOI: 10.1590/0100-3984.2017.50.3e2

Source DB:  PubMed          Journal:  Radiol Bras        ISSN: 0100-3984


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Obesity is a metabolic disease with increasing incidence at a global level. The prevalence of obesity doubled between 1980 and 2014, now corresponding to more than half a billion obese people worldwide(. The World Health Organization estimates that more than a third of adults over 18 years of age are now overweight. Obesity plays an important role in the development of several diseases, such as atherosclerosis, diabetes, musculoskeletal conditions (e.g., osteoarthritis, tendinopathy, and carpal tunnel syndrome), and chronic pain(. Another important association is the increased risk of cancer(. The development of these conditions is likely related to increased production of pro-inflammatory adipokines (e.g., interleukin 6 and tumor necrosis factor alpha) and decreased production of (or decreased tissue sensitivity to) anti-inflammatory adipokines (e.g., adiponectin). The final result is that those individuals are in an inflammatory state and show increased levels of acute phase reagents such as C-reactive protein(. In the field of radiology, there is a trend toward more quantitative science that could increase the value of quantitative imaging biomarkers and reduce variability across devices, patients, and time. A quantitative imaging biomarker can be defined as “an objective characteristic derived from an in vivo image measured on a ratio or interval scale as indicators of normal biological processes, pathogenic processes, or a response to a therapeutic intervention”(. It is extremely important that measurements can be reproduced by different observers on different equipment. In this context, the Radiological Society of North America has organized a Quantitative Imaging Biomarker Alliance. There is great interest in quantitative measurements of adipose tissue, to serve as imaging biomarkers. Total body adipose tissue can be better understood and quantified through sectional imaging methods such as computed tomography and magnetic resonance imaging. It can be divided into two main categories: subcutaneous and internal. Internal fat can be further divided into two components: visceral and nonvisceral. The visceral component includes the adipose tissue distributed in three body cavities: thoracic, intra-abdominal, and pelvic. The nonvisceral component includes intermuscular and paravertebral adipose tissue(. Recent studies have demonstrated that deposition of visceral fat is an important imaging biomarker of metabolic disease(, linked to the concept of adiposopathy, also known as sick fat syndrome. Adiposopathy can be defined as “a pathologic adipose tissue anatomic/functional disturbances promoted by positive caloric balance in genetically and environmentally susceptible individuals which results in adverse endocrine and immune responses that both directly and indirectly contribute to metabolic disease and increased cardiovascular disease risk”(. In an article published in this issue of Radiologia Brasileira, Mauad et al. proposed using ultrasound and computed tomography to quantify abdominal fat and found correlations with body mass index, serum cholesterol, and abdominal circumference(. Although their study has certain limitations, the authors suggest that ultrasound might be used as an alternative method for abdominal fat quantification, with advantages including its wide availability, its lower cost, and the fact that it does not involve the use of ionizing radiation. It is important to notice that, in order to be considered suitable for quantitative imaging biomarkers, ultrasound measurements should be further correlated with cardiovascular events.
  13 in total

1.  Ultrasound evaluation on carpal tunnel syndrome before and after bariatric surgery.

Authors:  Adham do Amaral E Castro; Thelma Larocca Skare; Paulo Afonso Nunes Nassif; Alexandre Kaue Sakuma; Bruno Luiz Ariede; Wagner Haese Barros
Journal:  Rev Col Bras Cir       Date:  2014 Nov-Dec

2.  The emerging science of quantitative imaging biomarkers terminology and definitions for scientific studies and regulatory submissions.

Authors:  Larry G Kessler; Huiman X Barnhart; Andrew J Buckler; Kingshuk Roy Choudhury; Marina V Kondratovich; Alicia Toledano; Alexander R Guimaraes; Ross Filice; Zheng Zhang; Daniel C Sullivan
Journal:  Stat Methods Med Res       Date:  2014-06-11       Impact factor: 3.021

3.  The relationship among central obesity, systemic inflammation, and left ventricular diastolic dysfunction as determined by structural equation modeling.

Authors:  Cho-Kai Wu; Chung-Yi Yang; Jou-Wei Lin; Hung-Jen Hsieh; Fu-Chun Chiu; Jen-Junn Chen; Jen-Kuang Lee; Shu-Wei Huang; Hung-Yuan Li; Fu-Tien Chiang; Jin-Jer Chen; Chia-Ti Tsai
Journal:  Obesity (Silver Spring)       Date:  2011-03-10       Impact factor: 5.002

4.  Obesity can predict and promote systemic inflammation in healthy adults.

Authors:  Mohammed S Ellulu; Huzwah Khaza'ai; Asmah Rahmat; Ismail Patimah; Yehia Abed
Journal:  Int J Cardiol       Date:  2016-04-14       Impact factor: 4.164

Review 5.  Quantitative imaging biomarkers: a review of statistical methods for technical performance assessment.

Authors:  David L Raunig; Lisa M McShane; Gene Pennello; Constantine Gatsonis; Paul L Carson; James T Voyvodic; Richard L Wahl; Brenda F Kurland; Adam J Schwarz; Mithat Gönen; Gudrun Zahlmann; Marina V Kondratovich; Kevin O'Donnell; Nicholas Petrick; Patricia E Cole; Brian Garra; Daniel C Sullivan
Journal:  Stat Methods Med Res       Date:  2014-06-11       Impact factor: 3.021

Review 6.  Impact of adiposity on immunological parameters.

Authors:  Cristiane Martins Moulin; Ivo Marguti; Jean Pierre S Peron; Luiz Vicente Rizzo; Alfredo Halpern
Journal:  Arq Bras Endocrinol Metabol       Date:  2009-03

7.  Global burden of cancer attributable to high body-mass index in 2012: a population-based study.

Authors:  Melina Arnold; Nirmala Pandeya; Graham Byrnes; Prof Andrew G Renehan; Gretchen A Stevens; Prof Majid Ezzati; Jacques Ferlay; J Jaime Miranda; Isabelle Romieu; Rajesh Dikshit; David Forman; Isabelle Soerjomataram
Journal:  Lancet Oncol       Date:  2014-11-26       Impact factor: 41.316

Review 8.  Adiposopathy, "sick fat," Ockham's razor, and resolution of the obesity paradox.

Authors:  Harold Bays
Journal:  Curr Atheroscler Rep       Date:  2014-05       Impact factor: 5.113

9.  Body-mass index and risk of 22 specific cancers: a population-based cohort study of 5·24 million UK adults.

Authors:  Krishnan Bhaskaran; Ian Douglas; Harriet Forbes; Isabel dos-Santos-Silva; David A Leon; Liam Smeeth
Journal:  Lancet       Date:  2014-08-13       Impact factor: 79.321

10.  TENDINOPATHY AND OBESITY.

Authors:  Adham do Amaral E Castro; Thelma Larocca Skare; Paulo Afonso Nunes Nassif; Alexandre Kaue Sakuma; Wagner Haese Barros
Journal:  Arq Bras Cir Dig       Date:  2016
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  2 in total

1.  DIAGNOSTIC VALUE OF C-REACTIVE PROTEIN AND THE INFLUENCE OF VISCERAL FAT IN PATIENTS WITH OBESITY AND ACUTE APPENDICITIS.

Authors:  Adham do Amaral E Castro; Thelma Larocca Skare; Fernando Ide Yamauchi; Adriano Tachibana; Suheyla Pollyana Pereira Ribeiro; Eduardo Kaiser Ururahy Nunes Fonseca; Andressa Tamy Sakuma; Milena Rocha Peixoto; Mariana Athaniel Silva Rodrigues; Maria Angela M Barreiros
Journal:  Arq Bras Cir Dig       Date:  2018-03-01

Review 2.  Atrial Fibrillation: Pathogenesis, Predisposing Factors, and Genetics.

Authors:  Marios Sagris; Emmanouil P Vardas; Panagiotis Theofilis; Alexios S Antonopoulos; Evangelos Oikonomou; Dimitris Tousoulis
Journal:  Int J Mol Sci       Date:  2021-12-21       Impact factor: 5.923

  2 in total

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