Evidence map›Paper›PMID 34711378›Full record

ArticleThe Lancet. Digital health2021

X-ray dark-field chest imaging for detection and quantification of emphysema in patients with chronic obstructive pulmonary disease: a diagnostic accuracy study.

Konstantin Willer, Alexander A Fingerle, Wolfgang Noichl, Fabio De Marco, Manuela Frank, Theresa Urban, Rafael Schick, Alex Gustschin, Bernhard Gleich, Julia Herzen and 11 more

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in The Lancet. Digital health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
64citing papers in PubMed, 1 pooled it
17.7field-weighted citation impact, top 1% 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

64 citing papers in PubMed, 1 synthesis or guideline pooled it, 159 citations in OpenAlex.

  1. Pooled it
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  12. Advanced X-Ray Imaging Technology.Recent results in cancer research. Fortschritte der Krebsforschung. Progres dans les recherches sur le cancer · 2026
    Review
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  14. Functional Pulmonary Imaging.Journal of magnetic resonance imaging : JMRI · 2025
    Review
  15. Article
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  17. Article
  18. Article
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  20. Article

4 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

21 authors at 5 institutions in 2 countries.

Konstantin WillerDepartment of Physics, Technical University of Munich, Garching, Germany; Munich School of BioEngineering, Technical University of Munich, Garching, Germany. Electronic address: konstantin.willer@ph.tum.de.
Alexander A FingerleDepartment of Diagnostic and Interventional Radiology, School of Medicine & Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Wolfgang NoichlDepartment of Physics, Technical University of Munich, Garching, Germany; Munich School of BioEngineering, Technical University of Munich, Garching, Germany.
Fabio De MarcoDepartment of Physics, Technical University of Munich, Garching, Germany; Munich School of BioEngineering, Technical University of Munich, Garching, Germany.
Manuela FrankDepartment of Physics, Technical University of Munich, Garching, Germany; Munich School of BioEngineering, Technical University of Munich, Garching, Germany.
Theresa UrbanDepartment of Physics, Technical University of Munich, Garching, Germany; Munich School of BioEngineering, Technical University of Munich, Garching, Germany.
Rafael SchickDepartment of Physics, Technical University of Munich, Garching, Germany; Munich School of BioEngineering, Technical University of Munich, Garching, Germany.
Alex GustschinDepartment of Physics, Technical University of Munich, Garching, Germany; Munich School of BioEngineering, Technical University of Munich, Garching, Germany.
Bernhard GleichDepartment of Physics, Technical University of Munich, Garching, Germany; Munich School of BioEngineering, Technical University of Munich, Garching, Germany.
Julia HerzenDepartment of Physics, Technical University of Munich, Garching, Germany; Munich School of BioEngineering, Technical University of Munich, Garching, Germany.
Thomas KoehlerInstitute for Advanced Study, Technical University of Munich, Garching, Germany; Philips Research Hamburg, Hamburg, Germany.
Andre YaroshenkoPhilips Medical Systems DMC Hamburg, Hamburg, Germany.
Thomas PralowPhilips Medical Systems DMC Hamburg, Hamburg, Germany.
Gregor S ZimmermannDepartment of Cardiology, Angiology, and Pneumology, School of Medicine & Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Bernhard RengerDepartment of Diagnostic and Interventional Radiology, School of Medicine & Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Andreas P SauterDepartment of Diagnostic and Interventional Radiology, School of Medicine & Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Daniela PfeifferInstitute for Advanced Study, Technical University of Munich, Garching, Germany; Department of Diagnostic and Interventional Radiology, School of Medicine & Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Marcus R MakowskiDepartment of Diagnostic and Interventional Radiology, School of Medicine & Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Ernst J RummenyDepartment of Diagnostic and Interventional Radiology, School of Medicine & Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Philippe A GrenierDepartment of Clinical Research and Innovation, Hôpital Foch, Suresnes, Paris, France.
Franz PfeifferDepartment of Physics, Technical University of Munich, Garching, Germany; Munich School of BioEngineering, Technical University of Munich, Garching, Germany; Institute for Advanced Study, Technical University of Munich, Garching, Germany; Department of Diagnostic and Interventional Radiology, School of Medicine & Klinikum rechts der Isar, Technical University of Munich, Munich, Germany.
Technical University of Munich · DEKlinikum rechts der Isar · DEPhilips (Germany) · DEHôpital Foch · FRInstitute for Advanced Study · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough advanced medical imaging technologies give detailed diagnostic information, a low-dose, fast, and inexpensive option for early detection of respiratory diseases and follow-ups is still lacking. The novel method of x-ray dark-field chest imaging might fill this gap but has not yet been studied in living humans. Enabling the assessment of microstructural changes in lung parenchyma, this technique presents a more sensitive alternative to conventional chest x-rays, and yet requires only a fraction of the dose applied in CT. We studied the application of this technique to assess pulmonary emphysema in patients with chronic obstructive pulmonary disease (COPD).

methodsIn this diagnostic accuracy study, we designed and built a novel dark-field chest x-ray system (Technical University of Munich, Munich, Germany)-which is also capable of simultaneously acquiring a conventional thorax radiograph (7 s, 0·035 mSv effective dose). Patients who had undergone a medically indicated chest CT were recruited from the department of Radiology and Pneumology of our site (Klinikum rechts der Isar, Technical University of Munich, Munich, Germany). Patients with pulmonary pathologies, or conditions other than COPD, that might influence lung parenchyma were excluded. For patients with different disease stages of pulmonary emphysema, x-ray dark-field images and CT images were acquired and visually assessed by five readers. Pulmonary function tests (spirometry and body plethysmography) were performed for every patient and for a subgroup of patients the measurement of diffusion capacity was performed. Individual patient datasets were statistically evaluated using correlation testing, rank-based analysis of variance, and pair-wise post-hoc comparison.

findingsBetween October, 2018 and December, 2019 we enrolled 77 patients. Compared with CT-based parameters (quantitative emphysema ρ=-0·27, p=0·089 and visual emphysema ρ=-0·45, p=0·0028), the dark-field signal (ρ=0·62, p<0·0001) yields a stronger correlation with lung diffusion capacity in the evaluated cohort. Emphysema assessment based on dark-field chest x-ray features yields consistent conclusions with findings from visual CT image interpretation and shows improved diagnostic performance than conventional clinical tests characterising emphysema. Pair-wise comparison of corresponding test parameters between adjacent visual emphysema severity groups (CT-based, reference standard) showed higher effect sizes. The mean effect size over the group comparisons (absent-trace, trace-mild, mild-moderate, and moderate-confluent or advanced destructive visual emphysema grades) for the COPD assessment test score is 0·21, for forced expiratory volume in 1 s (FEV

interpretationX-ray dark-field chest imaging allows the diagnosis of pulmonary emphysema in patients with COPD because this technique provides relevant information representing the structural condition of lung parenchyma. This technique might offer a low radiation dose alternative to CT in COPD and potentially other lung disorders.

fundingEuropean Research Council, Deutsche Forschungsgemeinschaft, Royal Philips, and Karlsruhe Nano Micro Facility.

Indexed as

X-RaysAdultAgedAged, 80 and overEmphysemaFemaleForced Expiratory VolumeGermanyHumansLungMaleMiddle AgedPulmonary Disease, Chronic ObstructivePulmonary EmphysemaRadiographyRadiography, Thoracic

Identifiers

PMID34711378
PMCPMC8565798
OpenAlexW3207985869

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.