Evidence map›Paper›PMID 33936996›Full record

ArticleQuantitative imaging in medicine and surgery2021

Adipose tissue fibrosis assessed by high resolution

Khaoula Bouazizi, Mohamed Zarai, Florian Marquet, Judith Aron-Wisnewsky, Karine Clément, Alban Redheuil, Nadjia Kachenoura

Open access · diamondAbstract read
In one paragraph

Article in Quantitative imaging in medicine and surgery, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.8field-weighted citation impact, top 27% of its field
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

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 1 country.

Khaoula BouaziziInstitute of Cardiometabolism and Nutrition (ICAN), Paris, France.
Mohamed ZaraiInstitute of Cardiometabolism and Nutrition (ICAN), Paris, France.
Florian MarquetInstitute of Cardiometabolism and Nutrition (ICAN), Paris, France.
Judith Aron-WisnewskySorbonne Université, INSERM, Nutrition and Obesities; approches systémiques (NutriOmique), Pitié-Salpêtrière Hospital, Nutrition department, Paris, France.
Karine ClémentSorbonne Université, INSERM, Nutrition and Obesities; approches systémiques (NutriOmique), Pitié-Salpêtrière Hospital, Nutrition department, Paris, France.
Alban RedheuilInstitute of Cardiometabolism and Nutrition (ICAN), Paris, France.
Nadjia KachenouraInstitute of Cardiometabolism and Nutrition (ICAN), Paris, France.
Fondation pour l’innovation en Cadiométabolisme et Nutrition · FRSorbonne Université · FRLaboratoire d’Imagerie Biomédicale · FRNutrition et obésité : approches systémiques · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To determine whether magnetic resonance imaging (MRI) when used in an optimal ex vivo setting can help detecting and quantifying the 3D fibrosis fraction in human subcutaneous adipose tissue (SAT) samples, as compared to histology. This prospective observational study was approved by our institutional review board 3D MRI acquisitions were performed at 4.0 T (Bruker) on XX human SAT samples (around 1 cm3) collected from biopsy in morbidly obese patients. Such acquisitions included saturation-recovery T1 mapping (spatial resolution: 200 µm, acquisition time: ~16 minutes) and DIXON imaging (spatial resolution: 200 µm, acquisition time: ~20 minutes). After MRI, histological quantification of fibrosis was performed using picrosirius staining. T1 maps were clustered based on a k-means algorithm allowing quantification of fibrosis within the adipose tissue and percentage of fibrosis over the entire sample volume was calculated. Fat maps were computed from DIXON in-phase and out-of-phase images. The 3D MRI fibrosis percentage within the SAT samples were comprised between 6% and 15%. Excellent correlations and levels of agreement were observed between single slice MRI and histology (r=0.9, P=0.08) and between 3D MRI and histology in terms fibrosis percentages within SAT samples (r=0.9, P=0.01). High Field ex vivo MRI was able to quantify fibrosis in human SAT samples with high agreement with histology and moreover to provide 3D SAT fibrosis quantification avoiding histological sampling errors.

Indexed as

fibrosismagnetic resonance imaging (MRI)Subcutaneous adipose tissue

Identifiers

PMID33936996
PMCPMC8047361
OpenAlexW3135529974

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.