Evidence map›Paper›PMID 33362273›Full record

ArticlePloS one2020

Diagnostic accuracy of magnetic resonance imaging for the detection of pulmonary nodules simulated in a dedicated porcine chest phantom.

Madeleine Bonert, Moritz Schneider, Olga Solyanik, Katharina Hellbach, David Bondesson, Thomas Gaass, Natalie Thaens, Jens Ricke, Thomas Benkert, Julien Dinkel

Abstract readComparative Study
In one paragraph

Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

10 authors.

Madeleine BonertDepartment of Radiology, University Hospital, LMU Munich, Munich, Germany.ORCID 0000-0002-8478-6770
Moritz SchneiderDepartment of Radiology, University Hospital, LMU Munich, Munich, Germany.
Olga SolyanikDepartment of Radiology, University Hospital, LMU Munich, Munich, Germany.
Katharina HellbachDepartment of Radiology, University Hospital, LMU Munich, Munich, Germany.
David BondessonDepartment of Radiology, University Hospital, LMU Munich, Munich, Germany.
Thomas GaassDepartment of Radiology, University Hospital, LMU Munich, Munich, Germany.
Natalie ThaensDepartment of Radiology, University Hospital, LMU Munich, Munich, Germany.
Jens RickeDepartment of Radiology, University Hospital, LMU Munich, Munich, Germany.
Thomas BenkertMR Applications Predevelopment, Siemens Healthcare GmbH, Erlangen, Germany.
Julien DinkelDepartment of Radiology, University Hospital, LMU Munich, Munich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveCT serves as gold standard for the evaluation of pulmonary nodules. However, CT exposes patients to ionizing radiation, a concern especially in screening scenarios with repeated examinations. Due to recent technological advances, MRI emerges as a potential alternative for lung imaging using 3D steady state free precession and ultra-short echo-time sequences. Therefore, in this study we assessed the performance of three state-of-the-art MRI sequences for the evaluation of pulmonary nodules.

methodsLesions of variable sizes were simulated in porcine lungs placed in a dedicated chest phantom mimicking a human thorax, followed by CT and MRI examinations. Two blinded readers evaluated the acquired MR-images locating and measuring every suspect lesion. Using the CT-images as reference, logistic regression was performed to investigate the sensitivity of the tested MRI-sequences for the detection of pulmonary nodules.

resultsFor nodules with a diameter of 6 mm, all three sequences achieved high sensitivity values above 0.91. However, the sensitivity dropped for smaller nodules, yielding an average of 0.83 for lesions with 4 mm in diameter and less than 0.69 for lesions with 2 mm in diameter. The positive predictive values ranged between 0.91 and 0.96, indicating a low amount of false positive findings. Furthermore, the size measurements done on the MR-images were subject to a bias ranging from 0.83 mm to -1.77 mm with standard deviations ranging from 1.40 mm to 2.11 mm. There was no statistically significant difference between the three tested sequences.

conclusionWhile showing promising sensitivity values for lesions larger than 4 mm, MRI appears to be not yet suited for lung cancer screening. Nonetheless, the three tested MRI sequences yielded high positive predictive values and accurate size measurements; therefore, MRI could potentially figure as imaging method of the chest in selected follow-up scenarios, e.g. of incidental findings subject to the Fleischner Criteria.

Indexed as

AnimalsEarly Detection of CancerHumansLung NeoplasmsMagnetic Resonance ImagingMultiple Pulmonary NodulesPhantoms, ImagingRadiographic Image Interpretation, Computer-AssistedSensitivity and SpecificitySwineTomography, X-Ray Computed

Identifiers

PMID33362273
PMCPMC7757901

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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.