ArticleScientific reports2020
Abdominal subcutaneous fat quantification in obese patients from limited field-of-view MRI data.
Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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Who cites it
6 citing papers in PubMed, 10 citations in OpenAlex.
- Reduced visceral adipose tissue area linked to early recurrence in HCC patients with HBV: a parallel mediation analysis.Abdominal radiology (New York) · 2026Article
- Body composition quantified by CT: chemotherapy toxicity and prognosis in patients with diffuse large B-cell lymphoma.Abdominal radiology (New York) · 2025Review
- Quantification of Visceral Fat at the L5 Vertebral Body Level in Patients with Crohn's Disease Using T2-Weighted MRI.Bioengineering (Basel, Switzerland) · 2024Article
- Article
- MRI-based quantification of adipose tissue distribution in healthy adult cats during body weight gain.Frontiers in veterinary science · 2023Article
- Measurement of subcutaneous fat tissue: reliability and comparison of caliper and ultrasound via systematic body mapping.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Different types of adipose tissue can be accurately localized and quantified by tomographic imaging techniques (MRI or CT). One common shortcoming for the abdominal subcutaneous adipose tissue (ASAT) of obese subjects is the technically restricted imaging field of view (FOV). This work derives equations for the conversion between six surrogate measures and fully segmented ASAT volume and discusses the predictive power of these image-based quantities. Clinical (gender, age, anthropometry) and MRI data (1.5 T, two-point Dixon sequence) of 193 overweight and obese patients (116 female, 77 male) from a single research center for obesity were analyzed retrospectively. Six surrogate measures of fully segmented ASAT volume (V
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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.