Evidence map›Paper›PMID 28932985›Full record

ArticleJournal of cancer research and clinical oncology2018

Lung cancer screening with MRI: results of the first screening round.

Michael Meier-Schroers, Rami Homsi, Dirk Skowasch, Jens Buermann, Matthias Zipfel, Hans Heinz Schild, Daniel Thomas

Open access · greenAbstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of cancer research and clinical oncology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 2 pooled it
5.1field-weighted citation impact, top 4% 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

30 citing papers in PubMed, 2 syntheses or guidelines pooled it, 50 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Article
  4. MRI for Lung Cancer Management: Any Closer to Clinical Application?Journal of magnetic resonance imaging : JMRI · 2026
    Review
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  11. [Magnetic resonance imaging of the lung : State of the art].Radiologie (Heidelberg, Germany) · 2023
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  14. Review
  15. Review
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Michael Meier-SchroersDepartment of Radiology, University of Bonn, Sigmund-Freud-Str 25, 53127, Bonn, Germany. michael.meier@ukbonn.de.ORCID http://orcid.org/0000-0002-4468-2504
Rami HomsiDepartment of Radiology, University of Bonn, Sigmund-Freud-Str 25, 53127, Bonn, Germany.
Dirk SkowaschDepartment of Cardiology, Pneumology and Angiology, University of Bonn, Sigmund-Freud-Str 25, 53127, Bonn, Germany.
Jens BuermannDepartment of Surgery, University of Bonn, Sigmund-Freud-Str 25, 53127, Bonn, Germany.
Matthias ZipfelDepartment of Oncology, Hematology, Immunooncology and Rheumatology, University of Bonn, Sigmund-Freud-Str 25, 53127, Bonn, Germany.
Hans Heinz SchildDepartment of Radiology, University of Bonn, Sigmund-Freud-Str 25, 53127, Bonn, Germany.
Daniel ThomasDepartment of Radiology, University of Bonn, Sigmund-Freud-Str 25, 53127, Bonn, Germany.
University of Bonn · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo evaluate the suitability of MRI for lung cancer screening in a high-risk population. MATERIALS AND

methodsA 5-year lung cancer screening program comparing MRI and low-dose CT (LDCT) in a high-risk population was initiated. 224 subjects were examined with MRI and LDCT. Acquired MRI sequences were T2w MultiVane XD, balanced steady-state-free precession, 3D T1w GRE, and DWI with a maximum in-room-time of 20 min. Categorization and management of nodules were based on Lung-RADS. MRI findings were correlated with LDCT as a reference. Here, we report on the first screening round.

resultsMRI accurately detected 61 of 88 nodules 4-5 mm, 20 of 21 nodules 6-7 mm, 12 of 12 nodules 8-14 mm, 4 of 4 nodules ≥ 15 mm (solid nodules), and 8 of 11 subsolid nodules. Sensitivity/specificity of MRI for nodule detection was 69.3/96.4% for 4-5 mm, 95.2/99.6% for 6-7 mm, 100/99.6% for 8-14 mm, 100/100% for ≥ 15 mm (solid nodules), and 72.7/99.2% for subsolid nodules. The early recall rate was 13.8% for MRI and 12.5% for LDCT. Following Lung-RADS recommendations and based on interdisciplinary consensus, histology was obtained in eight subjects. The biopsy rate was 3.6% for MRI and 3.4% for LDCT. In all of these eight cases, the nodules were carcinomas, and all of them were accurately detected by MRI.

conclusionThe results of the first screening round suggest that MRI is suitable for lung cancer screening with an excellent sensitivity and specificity for nodules ≥ 6 mm.

Indexed as

Early Detection of CancerHumansLung NeoplasmsMagnetic Resonance ImagingMiddle AgedMultimodal ImagingTomography, X-Ray ComputedLung cancerMRIScreening

Identifiers

PMID28932985
PMCPMC11813265
OpenAlexW2756312631

What OpenQuestion holds

Textmetadata
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.