Evidence map›Paper›PMID 27053294›Full record

ArticlePhysiological reports2016

Hyperpolarized 3He magnetic resonance imaging ventilation defects in asthma: relationship to airway mechanics.

Del Leary, Sarah Svenningsen, Fumin Guo, Swati Bhatawadekar, Grace Parraga, Geoffrey N Maksym

Open access · goldAbstract read
In one paragraph

Article in Physiological reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.8field-weighted citation impact, top 15% 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

6 citing papers in PubMed, 24 citations in OpenAlex.

  1. Review
  2. Article
  3. HyperpolarizedMagnetic resonance in medicine · 2022
    Review
  4. Paediatric lung imaging: the times they are a-changin'.European respiratory review : an official journal of the European Respiratory Society · 2018
    Review
  5. Review
  6. 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

6 authors at 4 institutions in 2 countries.

Del LearyDepartment of Environmental and Radiological Health Sciences, Colorado State University, Fort Collins, Colorado.
Sarah SvenningsenRobarts Research Institute, The University of Western Ontario, London, Canada Department of Medical Biophysics, The University of Western Ontario, London, Canada.
Fumin GuoRobarts Research Institute, The University of Western Ontario, London, Canada Graduate Program in Biomedical Engineering, The University of Western Ontario, London, Canada.
Swati BhatawadekarUniversity Health Network-Toronto Rehabilitation Institute, Toronto, Canada.
Grace ParragaRobarts Research Institute, The University of Western Ontario, London, Canada Department of Medical Biophysics, The University of Western Ontario, London, Canada Graduate Program in Biomedical Engineering, The University of Western Ontario, London, Canada.
Geoffrey N MaksymSchool of Biomedical Engineering, Dalhousie University, Halifax, Canada gmaksym@dal.ca.
Western University · CAColorado State University · USDalhousie University · CAToronto Rehabilitation Institute · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In patients with asthma, magnetic resonance imaging (MRI) provides direct measurements of regional ventilation heterogeneity, the etiology of which is not well-understood, nor is the relationship of ventilation abnormalities with lung mechanics. In addition, respiratory resistance and reactance are often abnormal in asthmatics and the frequency dependence of respiratory resistance is thought to reflect ventilation heterogeneity. We acquiredMRIventilation defect maps, forced expiratory volume in one-second (FEV1), and airways resistance (Raw) measurements, and used a computational airway model to explore the relationship of ventilation defect percent (VDP) with simulated measurements of respiratory system resistance (Rrs) and reactance (Xrs).MRIventilation defect maps were experimentally acquired in 25 asthmatics before, during, and after methacholine challenge and these were nonrigidly coregistered to the airway tree model. Using the model coregistered to ventilation defect maps, we narrowed proximal (9th) and distal (14th) generation airways that were spatially related to theMRIventilation defects. The relationships forVDPwith Raw measured using plethysmography (r = 0.79), and model predictions of Rrs>14(r = 0.91,P < 0.0001) and Rrs>9(r = 0.88,P < 0.0001) were significantly stronger (P = 0.005;P = 0.03, respectively) than withFEV1(r = -0.68,P = 0.0001). The slopes for the relationship ofVDPwith simulated lung mechanics measurements were different (P < 0.0001); among these, the slope for theVDP-Xrs0.2relationship was largest, suggesting thatVDPwas dominated by peripheral airway heterogeneity in these patients. In conclusion, as a first step toward understanding potential links between lung mechanics and ventilation defects, impedance predictions were made using a computational airway tree model with simulated constriction of airways related to ventilation defects measured in mild-moderate asthmatics.

Indexed as

Pulmonary VentilationRespiratory MechanicsAdultAirway ResistanceAsthmaBronchial Provocation TestsComputer SimulationFemaleForced Expiratory VolumeHeliumHumansIsotopesLungMagnetic Resonance ImagingMaleMiddle AgedHeliumIsotopesFEV 1heterogeneityhyperpolarized MRIlung impedanceventilation defects

Identifiers

PMID27053294
PMCPMC4831329
OpenAlexW2329579756

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.