Evidence map›Paper›PMID 39090324›Full record

ArticleEuropean radiology experimental2024

Automated evaluation of diaphragm configuration based on chest CT in COPD patients.

Jens T Bakker, Jorine E Hartman, Karin Klooster, David A Lynch, Marieke C van der Molen, Jean-Paul Charbonnier, Michail Tsiaousis, Rozemarijn Vliegenthart, Dirk-Jan Slebos

Abstract read
In one paragraph

Article 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 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Review
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

9 authors.

Jens T BakkerUniversity of Groningen, University Medical Center Groningen, Department of Pulmonary Diseases, Groningen, The Netherlands. j.t.bakker@umcg.nl.ORCID http://orcid.org/0000-0002-0499-9793
Jorine E HartmanUniversity of Groningen, University Medical Center Groningen, Department of Pulmonary Diseases, Groningen, The Netherlands.
Karin KloosterUniversity of Groningen, University Medical Center Groningen, Department of Pulmonary Diseases, Groningen, The Netherlands.
David A LynchNational Jewish Health, Department of Radiology, Denver, CO, USA.
Marieke C van der MolenUniversity of Groningen, University Medical Center Groningen, Department of Pulmonary Diseases, Groningen, The Netherlands.
Jean-Paul CharbonnierThirona, Nijmegen, The Netherlands.
Michail TsiaousisThirona, Nijmegen, The Netherlands.
Rozemarijn VliegenthartUniversity of Groningen, University Medical Center Groningen, Department of Radiology, Groningen, The Netherlands.
Dirk-Jan SlebosUniversity of Groningen, University Medical Center Groningen, Department of Pulmonary Diseases, Groningen, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSevere chronic obstructive pulmonary disease (COPD) often results in hyperinflation and flattening of the diaphragm. An automated computed tomography (CT)-based tool for quantifying diaphragm configuration, a biomarker for COPD, was developed in-house and tested in a large cohort of COPD patients.

methodsWe used the LungQ platform to extract the lung-diaphragm intersection, as direct diaphragm segmentation is challenging. The tool computed the diaphragm index (surface area/projected surface area) as a measure of diaphragm configuration on inspiratory scans in a COPDGene subcohort. Visual inspection of 250 randomly selected segmentations served as a quality check. Associations between the diaphragm index, Global Initiative for Chronic Obstructive Lung Disease (GOLD) stages, forced expiratory volume in 1 s (FEV1) % predicted, and CT-derived emphysema scores were explored using analysis of variance and Pearson correlation.

resultsThe tool yielded incomplete segmentation in 9.2% (2.4% major defect, 6.8% minor defect) of 250 randomly selected cases. In 8431 COPDGene subjects (4240 healthy; 4191 COPD), the diaphragm index was increasingly lower with higher GOLD stages (never-smoked 1.83 ± 0.16; GOLD-0 1.79 ± 0.18; GOLD-1 1.71 ± 0.15; GOLD-2: 1.67 ± 0.16; GOLD-3 1.58 ± 0.14; GOLD-4 1.54 ± 0.11) (p < 0.001). Associations were found between the diaphragm index and both FEV1% predicted (r = 0.44, p < 0.001) and emphysema score (r = -0.36, p < 0.001).

conclusionWe developed an automated tool to quantify the diaphragm configuration in chest CT. The diaphragm index was associated with COPD severity, FEV1%predicted, and emphysema score. RELEVANCE STATEMENT: Due to the hypothesized relationship between diaphragm dysfunction and diaphragm configuration in COPD patients, automatic quantification of diaphragm configuration may prove useful in evaluating treatment efficacy in terms of lung volume reduction. KEY POINTS: Severe COPD changes diaphragm configuration to a flattened state, impeding function. An automated tool quantified diaphragm configuration on chest-CT providing a diaphragm index. The diaphragm index was correlated to COPD severity and may aid treatment assessment.

Indexed as

DiaphragmPulmonary Disease, Chronic ObstructiveTomography, X-Ray ComputedAgedFemaleForced Expiratory VolumeHumansMaleMiddle AgedDiaphragmLung pulmonary disease (chronic obstructive)Segmentation toolTomography (x-ray computed)

Identifiers

PMID39090324
PMCPMC11294507

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.