Evidence map›Paper›PMID 34337778›Full record

ArticleMagnetic resonance in medicine2021

Defect distribution index: A novel metric for functional lung MRI in cystic fibrosis.

Anne Valk, Corin Willers, Kamal Shahim, Orso Pusterla, Grzegorz Bauman, Robin Sandkühler, Oliver Bieri, Florian Wyler, Philipp Latzin

Open access · hybridAbstract read
In one paragraph

Article in Magnetic resonance in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
1.9field-weighted citation impact, top 13% 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Magnetic resonance in medicine · 2025
    Article
  5. Article
  6. The ageing of people living with cystic fibrosis: what to expect now?European respiratory review : an official journal of the European Respiratory Society · 2024
    Review
  7. Article
  8. Article
  9. Article
  10. 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

9 authors at 2 institutions in 2 countries.

Anne ValkDivision of Paediatric Respiratory Medicine and Allergology, Department of Paediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.ORCID 0000-0002-6190-0438
Corin WillersDivision of Paediatric Respiratory Medicine and Allergology, Department of Paediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.ORCID 0000-0003-1140-9437
Kamal ShahimDivision of Paediatric Respiratory Medicine and Allergology, Department of Paediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Orso PusterlaDivision of Paediatric Respiratory Medicine and Allergology, Department of Paediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.ORCID 0000-0003-1879-055X
Grzegorz BaumanDivision of Radiological Physics, Department of Radiology, University of Basel Hospital, Basel, Switzerland.ORCID 0000-0001-6972-0776
Robin SandkühlerDepartment of Biomedical Engineering, University of Basel, Allschwil, Switzerland.
Oliver BieriDivision of Radiological Physics, Department of Radiology, University of Basel Hospital, Basel, Switzerland.
Florian WylerDivision of Paediatric Respiratory Medicine and Allergology, Department of Paediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.ORCID 0000-0002-1232-1392
Philipp LatzinDivision of Paediatric Respiratory Medicine and Allergology, Department of Paediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.ORCID 0000-0002-5239-1571
University of Bern · CHUniversity of Basel · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeLung impairment from functional MRI is frequently assessed as defect percentage. The defect distribution, however, is currently not quantified. The purpose of this work was to develop a novel measure that quantifies how clustered or scattered defects in functional lung MRI appear, and to evaluate it in pediatric cystic fibrosis. THEORY: The defect distribution index (DDI) calculates a score for each lung voxel categorized as defected. The index increases according to how densely and how far an expanding circle around a defect voxel contains more than 50% defect voxels.

methodsFractional ventilation and perfusion maps of 53 children with cystic fibrosis were previously acquired with matrix pencil decomposition MRI. In this work, the DDI is compared to a visual score of 3 raters who evaluated how clustered the lung defects appear. Further, spearman correlations between DDI and lung function parameters were determined.

resultsThe DDI strongly correlates with the visual scoring (r = 0.90 for ventilation; r = 0.88 for perfusion; P < .0001). Although correlations between DDI and defect percentage are moderate to strong (r = 0.61 for ventilation; r = 0.75 for perfusion; P < .0001), the DDI distinguishes between patients with comparable defect percentage.

conclusionThe DDI is a novel measure for functional lung MRI. It provides complementary information to the defect percentage because the DDI assesses defect distribution rather than defect size. The DDI is applicable to matrix pencil MRI data of cystic fibrosis patients and shows very good agreement with human perception of defect distributions.

Indexed as

Cystic FibrosisChildHumansLungMagnetic Resonance ImagingPerfusionRespirationcystic fibrosislungMRIpediatricsquantificationventilation and perfusion

Identifiers

PMID34337778
PMCPMC9292253
OpenAlexW3193272287

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.