ArticleNMR in biomedicine2015
Validation of a fast method for quantification of intra-abdominal and subcutaneous adipose tissue for large-scale human studies.
Article in NMR in biomedicine, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to 3 registered trials, which are not on this map. Cited by 53 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Impact of Liraglutide 3.0 on Body Fat Distribution, Visceral Adiposity, and Cardiometabolic Risk Markers In Overweight and Obese Adults at High Risk for Cardiovascular Disease
Longitudinal Assessment of Muscle Health in Patients Undergoing Liver Transplantation (LT) for Hepatocellular Carcinoma (HCC)
Adverse Outcomes and Mortality in Liver Transplant
Who cites it
53 citing papers in PubMed, 75 citations in OpenAlex.
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- MRI-Derived Body Composition and Breast Cancer Risk in Postmenopausal Women: UK Biobank Study.Cancers · 2025Article
- Ectopic Fat distribution and adverse muscle composition in South Asians: Findings from the UK biobank.American journal of preventive cardiology · 2025Article
- Body composition mediates the association between fatty acids and NAFLD risk: a prospective cohort study.Journal of health, population, and nutrition · 2025Article
- Evaluating the prevalence and severity of metabolic dysfunction-associated steatotic liver disease in patients with type 2 diabetes mellitus in primary care.Journal of internal medicine · 2025Article
- Sleep chart of biological aging clocks across organs and omics.medRxiv : the preprint server for health sciences · 2025Article
- Multi-organ MRI digitizes biological aging clocks across proteomics, metabolomics, and genetics.medRxiv : the preprint server for health sciences · 2025Article
- Higher Aircraft Noise Exposure Is Linked to Worse Heart Structure and Function by Cardiovascular MRI.Journal of the American College of Cardiology · 2025Article
- PennPRS: a centralized cloud computing platform for efficient polygenic risk score training in precision medicine.medRxiv : the preprint server for health sciences · 2025Article
- What is normal age-related thigh muscle composition among 45- to 84-year-old adults from the UK Biobank study.GeroScience · 2025Article
- Reproducibility of automatic adipose tissue segmentation using proton density fat fraction images between 1.5 and 3.0 T magnetic resonance.Quantitative imaging in medicine and surgery · 2025Article
- Body composition and muscle composition phenotypes in patients on waitlist and shortly after liver transplant - results from a pilot study.BMC gastroenterology · 2024Article
- Interactions between age, sex and visceral adipose tissue on brain ageing.Diabetes, obesity & metabolism · 2024Article
- Multi-organ imaging-derived polygenic indexes for brain and body health.medRxiv : the preprint server for health sciences · 2024Article
- Skewness in Body fat Distribution Pattern Links to Specific Cardiometabolic Disease Risk Profiles.The Journal of clinical endocrinology and metabolism · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
Abstract
Central obesity is the hallmark of a number of non-inheritable disorders. The advent of imaging techniques such as MRI has allowed for a fast and accurate assessment of body fat content and distribution. However, image analysis continues to be one of the major obstacles to the use of MRI in large-scale studies. In this study we assess the validity of the recently proposed fat-muscle quantitation system (AMRA(TM) Profiler) for the quantification of intra-abdominal adipose tissue (IAAT) and abdominal subcutaneous adipose tissue (ASAT) from abdominal MR images. Abdominal MR images were acquired from 23 volunteers with a broad range of BMIs and analysed using sliceOmatic, the current gold-standard, and the AMRA(TM) Profiler based on a non-rigid image registration of a library of segmented atlases. The results show that there was a highly significant correlation between the fat volumes generated by the two analysis methods, (Pearson correlation r = 0.97, p < 0.001), with the AMRA(TM) Profiler analysis being significantly faster (~3 min) than the conventional sliceOmatic approach (~40 min). There was also excellent agreement between the methods for the quantification of IAAT (AMRA 4.73 ± 1.99 versus sliceOmatic 4.73 ± 1.75 l, p = 0.97). For the AMRA(TM) Profiler analysis, the intra-observer coefficient of variation was 1.6% for IAAT and 1.1% for ASAT, the inter-observer coefficient of variation was 1.4% for IAAT and 1.2% for ASAT, the intra-observer correlation was 0.998 for IAAT and 0.999 for ASAT, and the inter-observer correlation was 0.999 for both IAAT and ASAT. These results indicate that precise and accurate measures of body fat content and distribution can be obtained in a fast and reliable form by the AMRA(TM) Profiler, opening up the possibility of large-scale human phenotypic studies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.