Javier Gómez-Ambrosi1, Ignacio González-Crespo2, Victoria Catalán3, Amaia Rodríguez3, Rafael Moncada4, Víctor Valentí5, Sonia Romero6, Beatriz Ramírez3, Camilo Silva7, María J Gil8, Javier Salvador9, Alberto Benito2, Inmaculada Colina10, Gema Frühbeck11. 1. Metabolic Research Laboratory, Clínica Universidad de Navarra, Pamplona, Spain; Centro de Investigación Biomédica en Red-Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Pamplona, Spain; Obesity and Adipobiology Group, Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain. Electronic address: jagomez@unav.es. 2. Department of Radiology, Clínica Universidad de Navarra, Pamplona, Spain. 3. Metabolic Research Laboratory, Clínica Universidad de Navarra, Pamplona, Spain; Centro de Investigación Biomédica en Red-Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Pamplona, Spain; Obesity and Adipobiology Group, Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain. 4. Centro de Investigación Biomédica en Red-Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Pamplona, Spain; Obesity and Adipobiology Group, Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain; Department of Anesthesia, Clínica Universidad de Navarra, Pamplona, Spain. 5. Centro de Investigación Biomédica en Red-Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Pamplona, Spain; Obesity and Adipobiology Group, Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain; Department of Surgery, Clínica Universidad de Navarra, Pamplona, Spain. 6. Obesity and Adipobiology Group, Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain; Department of Endocrinology & Nutrition, Clínica Universidad de Navarra, Pamplona, Spain. 7. Centro de Investigación Biomédica en Red-Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Pamplona, Spain; Obesity and Adipobiology Group, Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain; Department of Endocrinology & Nutrition, Clínica Universidad de Navarra, Pamplona, Spain. 8. Centro de Investigación Biomédica en Red-Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Pamplona, Spain; Obesity and Adipobiology Group, Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain; Department of Biochemistry, Clínica Universidad de Navarra, Pamplona, Spain. 9. Centro de Investigación Biomédica en Red-Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Pamplona, Spain; Department of Endocrinology & Nutrition, Clínica Universidad de Navarra, Pamplona, Spain. 10. Obesity and Adipobiology Group, Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain; Department of Internal Medicine, Clínica Universidad de Navarra, Pamplona, Spain. 11. Metabolic Research Laboratory, Clínica Universidad de Navarra, Pamplona, Spain; Centro de Investigación Biomédica en Red-Fisiopatología de la Obesidad y Nutrición (CIBEROBN), Instituto de Salud Carlos III, Pamplona, Spain; Obesity and Adipobiology Group, Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain; Department of Endocrinology & Nutrition, Clínica Universidad de Navarra, Pamplona, Spain.
Abstract
BACKGROUND & AIMS: Visceral adipose tissue (VAT) has been shown to be profoundly responsible of most of the obesity-associated metabolic derangements. The measurement of VAT usually implies the use of imaging techniques such as magnetic resonance imaging or computed tomography (CT). Our aim was to evaluate the accuracy of the determination of VAT by means of abdominal bioimpedance (BIA) with the ViScan device in comparison with CT and its clinical usefulness in the management of obesity. METHODS: We studied a sample of 140 subjects (73 males/67 females) with BMI ranging from 17.7 to 50.4 kg/m2 to evaluate the accuracy of the ViScan in comparison to CT to determine VAT. To further analyze ViScan's clinical usefulness we studied a separate cohort (n = 2849) analyzing cardiometabolic risk factors. Furthermore, we studied the ability of the ViScan to detect changes in VAT after weight gain (n = 107) or weight loss (n = 335). The study was performed from October 2009 through June 2015. RESULTS: ViScan determines VAT with a good accuracy in individuals with a CT-VAT up to 200 cm2, and then with lower precision with increasing body mass, exhibiting a moderate-high correlation with CT-VAT (r = 0.75, P < 0.001). Importantly, VAT determination with the ViScan exhibits better correlations with several cardiometabolic risk factors such as glucose, triglycerides, HDL-cholesterol and markers of fatty liver than anthropometric measurements such as BMI or waist circumference. ViScan is able to detect VAT variations after body weight changes. CONCLUSIONS: Since the possibility of measuring VAT by imaging techniques is not always available, abdominal BIA represents a good alternative to estimate VAT, allowing the identification of patients with increased VAT-related cardiometabolic risk and a better management of obese patients. TRIAL REGISTRATION: ClinicalTrials.gov NCT01055626 and NCT01572090.
BACKGROUND & AIMS: Visceral adipose tissue (VAT) has been shown to be profoundly responsible of most of the obesity-associated metabolic derangements. The measurement of VAT usually implies the use of imaging techniques such as magnetic resonance imaging or computed tomography (CT). Our aim was to evaluate the accuracy of the determination of VAT by means of abdominal bioimpedance (BIA) with the ViScan device in comparison with CT and its clinical usefulness in the management of obesity. METHODS: We studied a sample of 140 subjects (73 males/67 females) with BMI ranging from 17.7 to 50.4 kg/m2 to evaluate the accuracy of the ViScan in comparison to CT to determine VAT. To further analyze ViScan's clinical usefulness we studied a separate cohort (n = 2849) analyzing cardiometabolic risk factors. Furthermore, we studied the ability of the ViScan to detect changes in VAT after weight gain (n = 107) or weight loss (n = 335). The study was performed from October 2009 through June 2015. RESULTS: ViScan determines VAT with a good accuracy in individuals with a CT-VAT up to 200 cm2, and then with lower precision with increasing body mass, exhibiting a moderate-high correlation with CT-VAT (r = 0.75, P < 0.001). Importantly, VAT determination with the ViScan exhibits better correlations with several cardiometabolic risk factors such as glucose, triglycerides, HDL-cholesterol and markers of fatty liver than anthropometric measurements such as BMI or waist circumference. ViScan is able to detect VAT variations after body weight changes. CONCLUSIONS: Since the possibility of measuring VAT by imaging techniques is not always available, abdominal BIA represents a good alternative to estimate VAT, allowing the identification of patients with increased VAT-related cardiometabolic risk and a better management of obesepatients. TRIAL REGISTRATION: ClinicalTrials.gov NCT01055626 and NCT01572090.
Authors: J Gómez-Ambrosi; P Andrada; V Valentí; F Rotellar; C Silva; V Catalán; A Rodríguez; B Ramírez; R Moncada; J Escalada; J Salvador; G Frühbeck Journal: Int J Obes (Lond) Date: 2017-06-06 Impact factor: 5.095
Authors: Belén Pérez-Pevida; Javier Escalada; Alexander D Miras; Gema Frühbeck Journal: Front Endocrinol (Lausanne) Date: 2019-09-19 Impact factor: 5.555