Evidence map›Paper›PMID 39636527›Full record

Observational studyEuropean radiology experimental2024

Fully automatic quantification of pulmonary fat attenuation volume by CT: an exploratory pilot study.

Luca Salhöfer, Mathias Holtkamp, Francesco Bonella, Lale Umutlu, Johannes Wienker, Dirk Westhölter, Matthias Welsner, Christian Taube, Kaid Darwiche, Judith Kohnke and 9 more

Abstract readObservational Study
In one paragraph

Observational study in European radiology experimental, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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

19 authors.

Luca SalhöferInstitute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany. luca.salhoefer@uk-essen.de.ORCID http://orcid.org/0000-0002-5376-3154
Mathias HoltkampInstitute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.
Francesco BonellaCenter for Interstitial and Rare Lung Diseases, Department of Pneumology, University Hospital Essen, Essen, Germany.
Lale UmutluInstitute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.
Johannes WienkerDepartment of Pneumology, University Hospital Essen, Essen, Germany.
Dirk WesthölterDepartment of Pneumology, University Hospital Essen, Essen, Germany.
Matthias WelsnerDepartment of Pneumology, University Hospital Essen, Essen, Germany.
Christian TaubeDepartment of Pneumology, University Hospital Essen, Essen, Germany.
Kaid DarwicheDepartment of Pneumology, University Hospital Essen, Essen, Germany.
Judith KohnkeInstitute for Artificial Intelligence in Medicine, University Hospital Essen, Essen, Germany.
Jannis StrausInstitute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.
Nikolas BeckInstitute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.
Marko FringsInstitute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.
Sebastian ZensenInstitute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.
Rene HoschInstitute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.
Giulia BaldiniInstitute for Artificial Intelligence in Medicine, University Hospital Essen, Essen, Germany.
Felix NensaInstitute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.
Marcel OpitzInstitute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.
Johannes HauboldInstitute of Diagnostic and Interventional Radiology and Neuroradiology, University Hospital Essen, Essen, Germany.

Funding

Deutsche Forschungsgemeinschaft FU 356/12-2
6 · The paper itself

Abstract

backgroundNon-malignant chronic diseases remain a major public health concern. Given the alterations in lipid metabolism and deposition in the lung and its association with fibrotic interstitial lung disease (fILD) and chronic obstructive pulmonary disease (COPD), this study aimed to detect those alterations using computed tomography (CT)-based analysis of pulmonary fat attenuation volume (CTpfav).

methodsThis observational retrospective single-center study involved 716 chest CT scans from three subcohorts: control (n = 279), COPD (n = 283), and fILD (n = 154). Fully automated quantification of CTpfav based on lung segmentation and HU-thresholding. The pulmonary fat index (PFI) was derived by normalizing CTpfav to the CT lung volume. Statistical analyses were conducted using Kruskal-Wallis with Dunn's post hoc tests.

resultsPatients with fILDs demonstrated a significant increase in CTpfav (median 71.0 mL, interquartile range [IQR] 59.7 mL, p < 0.001) and PFI (median 1.9%, IQR 2.4%, p < 0.001) when compared to the control group (CTpfav median 43.6 mL, IQR 16.94 mL; PFI median 0.9%, IQR 0.5%). In contrast, individuals with COPD exhibited significantly reduced CTpfav (median 36.2 mL, IQR 11.4 mL, p < 0.001) and PFI (median 0.5%, IQR 0.2%, p < 0.001).

conclusionThe study underscores the potential of CTpfav and PFI as imaging biomarkers for detecting changes in lung lipid metabolism and deposition and demonstrates a possibility of tracking these alterations in patients with COPD and ILDs. Further research is needed to validate these findings and explore the clinical relevance of CTpfav and PFI in lung disease management. RELEVANCE STATEMENT: This study introduces a fully automated method for quantifying CTpfav, potentially establishing it as a new imaging biomarker for chronic lung diseases. KEY POINTS: This retrospective observational study employed an open-source, automated algorithm for the quantification of CT pulmonary fat attenuation volume (CTpfav). Patients with fibrotic interstitial lung disease (fILD) showed a significantly higher CTpfav and pulmonary fat index (PFI), i.e., CTpfav/CT lung volume, compared to a control group. Patients with chronic obstructive pulmonary disease (COPD) showed significantly lower CTpfav and PFI compared to the control group. CTpfav and PFI may each serve as imaging biomarkers for various lung diseases and warrant further investigation.

Indexed as

Lung Diseases, InterstitialPulmonary Disease, Chronic ObstructiveTomography, X-Ray ComputedAdipose TissueAgedFemaleHumansLungMaleMiddle AgedPilot ProjectsRetrospective StudiesBody compositionLung diseases (interstitial)Lung volume measurementsPulmonary disease (chronic obstructive)Tomography (x-ray computed)

Identifiers

PMID39636527
PMCPMC11621257

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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.