Evidence map›Paper›PMID 32298358›Full record

ArticlePloS one2020

Calculating air volume fractions from computed tomography images for chronic obstructive pulmonary disease diagnosis.

Chun-Chao Chuang, Ying-Hsiang Chou, Shin-Lei Peng, Jou-Erh Tai, Shan-Chih Lee, Yeu-Sheng Tyan, Cheng-Ting Shih

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–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

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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

7 authors.

Chun-Chao ChuangDepartment of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan.
Ying-Hsiang ChouDepartment of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan.
Shin-Lei PengDepartment of Biomedical Imaging and Radiological Science, China Medical University, Taichung, Taiwan.
Jou-Erh TaiDepartment of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan.
Shan-Chih LeeDepartment of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan.
Yeu-Sheng TyanDepartment of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan.
Cheng-Ting ShihDepartment of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung, Taiwan.ORCID 0000-0002-8554-9136

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Quantitative evaluation using image biomarkers calculated from threshold-segmented low-attenuation areas on chest computed tomography (CT) images for diagnosing chronic obstructive pulmonary diseases (COPD) has been widely investigated. However, the segmentation results depend on the applied threshold and slice thickness of the CT images because of the partial volume effect (PVE). In this study, the air volume fraction (AV/TV) of lungs was calculated from CT images using a two-compartment model (TCM) for COPD diagnosis. A relative air volume histogram (RAVH) was constructed using the AV/TV values to describe the air content characteristics of lungs. In phantom studies, the TCM accurately calculated total cavity volumes and foam masses with percent errors of less than 8% and ±4%, respectively. In patient studies, the relative volumes of normal and damaged lung tissues and the damaged-to-normal RV ratio were defined and calculated from the RAVHs as image biomarkers, which correctly differentiated COPD patients from controls in 2.5- and 5-mm-thick images with areas under receiver operating characteristic curves of >0.94. The AV/TV calculated using the TCM can prevent the effect of slice thickness, and the image biomarkers calculated from the RAVH are reliable for diagnosing COPD.

Indexed as

AdultAgedAirAlgorithmsComputer SimulationFemaleHumansLungMaleMiddle AgedPhantoms, ImagingPulmonary Disease, Chronic ObstructiveThoraxTomography, X-Ray Computed

Identifiers

PMID32298358
PMCPMC7162278

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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.