Evidence map›Paper›PMID 38089550›Full record

ArticleJHEP reports : innovation in hepatology2024

Marked difference in liver fat measured by histology

Sami Qadri, Emilia Vartiainen, Mari Lahelma, Kimmo Porthan, An Tang, Ilkay S Idilman, Jurgen H Runge, Anne Juuti, Anne K Penttilä, Juhani Dabek and 11 more

Open access · goldAbstract read
In one paragraph

Article in JHEP reports : innovation in hepatology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 4 pooled it
8.4field-weighted citation impact, top 2% 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

34 citing papers in PubMed, 4 syntheses or guidelines pooled it, 39 citations in OpenAlex.

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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

21 authors at 10 institutions in 6 countries.

Sami QadriDepartment of Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
Emilia VartiainenInstitute for Molecular Medicine Finland, FIMM, University of Helsinki, Helsinki, Finland.
Mari LahelmaDepartment of Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
Kimmo PorthanDepartment of Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
An TangDepartment of Radiology, Centre hospitalier de l'Université de Montréal (CHUM), Montreal, QC, Canada.
Ilkay S IdilmanLiver Imaging Team, Hacettepe University, School of Medicine, Department of Radiology, Ankara, Turkey.
Jurgen H RungeDepartment of Radiology and Nuclear Medicine, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands.
Anne JuutiDepartment of Gastrointestinal Surgery, Abdominal Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
Anne K PenttiläDepartment of Gastrointestinal Surgery, Abdominal Center, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
Juhani DabekDepartment of Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
Tiina E LehtimäkiHUS Medical Imaging Center, Helsinki University Hospital, Helsinki, Finland.
Wenla SeppänenHUS Medical Imaging Center, Helsinki University Hospital, Helsinki, Finland.
Johanna ArolaDepartment of Pathology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
Perttu ArkkilaDepartment of Gastroenterology, Abdominal Center, Helsinki University Hospital and University of Helsinki, Helsinki, Finland.
Jaap StokerDepartment of Radiology and Nuclear Medicine, Amsterdam UMC location University of Amsterdam, Amsterdam, The Netherlands.
Musturay KarcaaltincabaLiver Imaging Team, Hacettepe University, School of Medicine, Department of Radiology, Ankara, Turkey.
Michael PavlidesRadcliffe Department of Medicine, University of Oxford, Oxford, UK.
Rohit LoombaNAFLD Research Center, Division of Gastroenterology and Hepatology, Department of Medicine, University of California San Diego, La Jolla, CA, USA.
Claude B SirlinLiver Imaging Group, Department of Radiology, University of California San Diego, La Jolla, CA, USA.
Taru TukiainenInstitute for Molecular Medicine Finland, FIMM, University of Helsinki, Helsinki, Finland.
Hannele Yki-JärvinenDepartment of Medicine, University of Helsinki and Helsinki University Hospital, Helsinki, Finland.
University of Helsinki · FIHelsinki University Hospital · FIHacettepe University · TRUniversity of California, San Diego · USAmsterdam University Medical Centers · NLCentre Hospitalier de l’Université de Montréal · CAInstitute for Molecular Medicine Finland · FIMinerva Foundation · FIUniversity of Amsterdam · NLUniversity of Oxford · GB

Funding

San Diego Digestive Diseases Research CenterP30DK120515 · NIDDK · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI LARS ECKMANN, Bernd G. Schnabl · 2019 to 2026
$10.8M
NIDDK NIH HHS P30 DK120515
6 · The paper itself

Abstract

Background & Aims: Pathologists quantify liver steatosis as the fraction of lipid droplet-containing hepatocytes out of all hepatocytes, whereas the magnetic resonance-determined proton density fat fraction (PDFF) reflects the tissue triacylglycerol concentration. We investigated the linearity, agreement, and correspondence thresholds between histological steatosis and PDFF across the full clinical spectrum of liver fat content associated with non-alcoholic fatty liver disease. Methods: Using individual patient-level measurements, we conducted a systematic review and meta-analysis of studies comparing histological steatosis with PDFF determined by magnetic resonance spectroscopy or imaging in adults with suspected non-alcoholic fatty liver disease. Linearity was assessed by meta-analysis of correlation coefficients and by linear mixed modelling of pooled data, agreement by Bland-Altman analysis, and thresholds by receiver operating characteristic analysis. To explain observed differences between the methods, we used RNA-seq to determine the fraction of hepatocytes in human liver biopsies. Results: Eligible studies numbered 9 (N = 597). The relationship between PDFF and histology was predominantly linear (r = 0.85 [95% CI, 0.80-0.89]), and their values approximately coincided at 5% steatosis. Above 5% and towards higher levels of steatosis, absolute values of the methods diverged markedly, with histology exceeding PDFF by up to 3.4-fold. On average, 100% histological steatosis corresponded to a PDFF of 33.0% (29.5-36.7%). Targeting at a specificity of 90%, optimal PDFF thresholds to predict histological steatosis grades were ≥5.75% for ≥S1, ≥15.50% for ≥S2, and ≥21.35% for S3. Hepatocytes comprised 58 ± 5% of liver cells, which may partly explain the lower values of PDFF Conclusions: Histological steatosis and PDFF have non-perfect linearity and fundamentally different scales of measurement. Liver fat values obtained using these methods may be rendered comparable by conversion equations or threshold values. Impact and implications: Magnetic resonance-proton density fat fraction (PDFF) is increasingly being used to measure liver fat in place of the invasive liver biopsy. Understanding the relationship between PDFF and histological steatosis fraction is important for preventing misjudgement of clinical status or treatment effects in patient care. Our analysis revealed that histological steatosis fraction is often significantly higher than PDFF, and their association varies across the spectrum of fatty liver severity. These findings are particularly important for physicians and clinical researchers, who may use these data to interpret PDFF measurements in the context of histologically evaluated liver fat content.

Indexed as

BiopsyFatty liverHepatocytesHistologyMagnetic resonance imagingMagnetic resonance spectroscopyMeta-analysisMetabolic dysfunction-associated steatotic liver diseasePathologistsSystematic reviewTranscriptomeTriglycerides

Identifiers

PMID38089550
PMCPMC10711480
OpenAlexW4387534095

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.