Evidence map›Paper›PMID 38379016›Full record

ArticlePhysical and engineering sciences in medicine2024

Usefulness of fat-containing agents: an initial study on estimating fat content for magnetic resonance imaging.

Yasuo Takatsu, Hiroshi Ohnishi, Tomoko Tateyama, Tosiaki Miyati

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Article in Physical and engineering sciences in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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3 · Its place in the literature

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0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

4 authors at 2 institutions in 1 country.

Yasuo TakatsuMolecular Imaging, School of Medical Sciences, Fujita Health University, 1-98, Dengakugakubo, Kutsukake-Cho, Toyoake, Aichi, 470-1192, Japan. yasuo.takatsu@fujita-hu.ac.jp.ORCID http://orcid.org/0000-0002-4384-089X
Hiroshi OhnishiDepartment of Radiology, Geisei Ortho Clinic, 1495-1, Wajikikou, Geisei-Mura, Aki-Gun, Kochi, 781-5701, Japan.
Tomoko TateyamaDepartment of Intelligent Information Engineering, School of Medical Sciences, Fujita Health University, 1-98, Dengakugakubo, Kutsukake-Cho, Toyoake, Aichi, 470-1192, Japan.
Tosiaki MiyatiDivision of Health Sciences, Graduate School of Medical Sciences, Kanazawa University, 5-11-80 Kodatsuno, Kanazawa, 920-0942, Japan.
Kanazawa University · JPFujita Health University Hospital · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This initial study aimed at testing whether fat-containing agents can be used for the fat mass estimation methods using magnetic resonance imaging (MRI). As an example for clinical application, fat-containing agents (based on soybean oil, 10% and 20%), 100% soybean oil, and saline as reference substances were placed outside the proximal femurs obtained from 14 participants and analyzed by 0.3 T MRI. Fat content was the estimated fat fraction (FF) based on signal intensity (SIeFF, %). The SIeFF values of the femoral bone marrow, including the femoral head, neck, shaft, and trochanter area, were measured. MRI data were compared in terms of bone mineral content (BMC) and bone mineral density (BMD) by dual-energy X-ray absorptiometry (DXA) in the proximal femur. Twelve pig femurs were also used to confirm the correlation between FF by the DIXON method and SIeFF. According to Pearson's correlation coefficient, the SIeFF and total BMC and BMD data revealed strong and moderate negative correlations in the femoral head (r <  - 0.74) and other sites (r =  - 0.66 to - 0.45). FF and SIeFF showed a strong correlation (r = 0.96). This study was an initial investigation of a method for estimating fat mass with fat-containing agents and showed the potential for use in MRI. SIeFF and FF showed a strong correlation, and SIeFF and BMD and BMC showed correlation; however, further studies are needed to use SIeFF as a substitute for DXA.

Indexed as

Bone DensitySoybean OilAbsorptiometry, PhotonAnimalsFemurHumansMagnetic Resonance ImagingSwineSoybean OilBone mineral contentBone mineral densityEstimated fat fraction based on signal intensityFat-containing nutrient solutionMagnetic resonance imaging

Identifiers

PMID38379016
OpenAlexW4391964816

What OpenQuestion holds

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Registered trials

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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 OpenQuestion graph.