Evidence map›Paper›PMID 28790813›Full record

ArticleInternational journal of chronic obstructive pulmonary disease2017

Asynchrony in respiratory movements between the pulmonary lobes in patients with COPD: continuous measurement of lung density by 4-dimensional dynamic-ventilation CT.

Tsuneo Yamashiro, Hiroshi Moriya, Shin Matsuoka, Yukihiro Nagatani, Maho Tsubakimoto, Nanae Tsuchiya, Sadayuki Murayama

Open access · goldAbstract read
In one paragraph

Article in International journal of chronic obstructive pulmonary disease, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.3field-weighted citation impact, top 7% 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

19 citing papers in PubMed, 32 citations in OpenAlex.

  1. Article
  2. Deep learning-based lung volume estimation with dynamic chest radiography.Journal of applied clinical medical physics · 2026
    Article
  3. Article
  4. Observational
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Strain Analysis in Patients at High-Risk for COPD Using Four-Dimensional Dynamic-Ventilation CT.International journal of chronic obstructive pulmonary disease · 2022
    Article
  13. Article
  14. Article
  15. Review
  16. Influence of Emphysema and Air Trapping Heterogeneity on Pulmonary Function in Patients with COPD.International journal of chronic obstructive pulmonary disease · 2019
    Article
  17. Quantitative Emphysema Measurement On Ultra-High-Resolution CT Scans.International journal of chronic obstructive pulmonary disease · 2019
    Article
  18. Article
  19. 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 at 4 institutions in 1 country.

Tsuneo YamashiroDepartment of Radiology, Graduate School of Medical Science, University of the Ryukyus, Nishihara, Okinawa, Japan.
Hiroshi MoriyaDepartment of Radiology, Ohara General Hospital, Fukushima-City, Fukushima, Japan.
Shin MatsuokaDepartment of Radiology, St Marianna University School of Medicine, Kawasaki, Kanagawa, Japan.
Yukihiro NagataniDepartment of Radiology, Shiga University of Medical Science, Otsu, Shiga, Japan.
Maho TsubakimotoDepartment of Radiology, Graduate School of Medical Science, University of the Ryukyus, Nishihara, Okinawa, Japan.
Nanae TsuchiyaDepartment of Radiology, Graduate School of Medical Science, University of the Ryukyus, Nishihara, Okinawa, Japan.
Sadayuki MurayamaDepartment of Radiology, Graduate School of Medical Science, University of the Ryukyus, Nishihara, Okinawa, Japan.
University of the Ryukyus · JPFukushima Medical University Hospital · JPShiga University of Medical Science · JPSt. Marianna University School of Medicine · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeFour-dimensional dynamic-ventilation CT imaging demonstrates continuous movement of the lung. The aim of this study was to assess the correlation between interlobar synchrony in lung density and spirometric values in COPD patients and smokers, by measuring the continuous changes in lung density during respiration on the dynamic-ventilation CT. MATERIALS AND

methodsThirty-two smokers, including ten with COPD, underwent dynamic-ventilation CT during free breathing. CT data were continuously reconstructed every 0.5 sec. Mean lung density (MLD) of the five lobes (right upper [RU], right middle [RM], right lower [RL], left upper [LU], and left lower [LL]) was continuously measured by commercially available software using a fixed volume of volume of interest which was placed and tracked on a single designated point in each lobe. Concordance between the MLD time curves of six pairs of lung lobes (RU-RL, RU-RM, RM-RL, LU-LL, RU-LU, and RL-LL lobes) was expressed by cross-correlation coefficients. The relationship between these cross-correlation coefficients and the forced expiratory volume in one second/forced vital capacity (FEV

resultsIn all six pairs of the pulmonary lobes, the cross-correlation coefficients of the two MLD curves were significantly positively correlated with FEV

conclusionThe synchrony of respiratory movements between the pulmonary lobes is limited or lost in patients with more severe airflow limitation.

Indexed as

Four-Dimensional Computed TomographyMultidetector Computed TomographyPulmonary VentilationRespirationAgedAged, 80 and overFemaleForced Expiratory VolumeHumansLungMaleMiddle AgedMovementPredictive Value of TestsPulmonary Disease, Chronic ObstructiveRadiographic Image Interpretation, Computer-Assistedairflow limitationchronic obstructive pulmonary diseasecomputed tomographyemphysemamean lung density

Identifiers

PMID28790813
PMCPMC5530056
OpenAlexW2738124979

What OpenQuestion holds

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LicenceCC BY-NC
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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.