Evidence map›Paper›PMID 26638164›Full record

ArticleEuropean radiology2016

Magnetic resonance imaging of pulmonary nodules: accuracy in a granulomatous disease-endemic region.

Natália Henz Concatto, Guilherme Watte, Edson Marchiori, Klaus Irion, José Carlos Felicetti, José Jesus Camargo, Bruno Hochhegger

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In one paragraph

Article in European radiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.2field-weighted citation impact, top 12% 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

17 citing papers in PubMed, 25 citations in OpenAlex.

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  12. Thoracic calcifications on magnetic resonance imaging: correlations with computed tomography.Jornal brasileiro de pneumologia : publicacao oficial da Sociedade Brasileira de Pneumologia e Tisilogia · 2019
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 4 institutions in 2 countries.

Natália Henz ConcattoUniversity of Caxias do Sul, Caxias do Sul, 95070-560, Brazil. naticoncatto@hotmail.com.
Guilherme WatteMedical Imaging Research Laboratory, Federal University of Health Sciences of Porto Alegre, Porto Alegre, 90050-170, Brazil.
Edson MarchioriDepartment of Radiology, Federal University of Rio de Janeiro, Rio de Janeiro, 21941-901, Brazil.
Klaus IrionDepartment of Radiology, Liverpool Heart and Chest Hospital NHS Foundation Trust, Liverpool, L14 3PE, UK.
José Carlos FelicettiDepartment of Thoracic Surgery, Santa Casa Hospital Complex, Porto Alegre, 90020-090, Brazil.
José Jesus CamargoDepartment of Thoracic Surgery, Santa Casa Hospital Complex, Porto Alegre, 90020-090, Brazil.
Bruno HochheggerDepartment of Radiology, Santa Casa Hospital Complex, Porto Alegre, 90020-090, Brazil.
Santa Casa Hospital · BRUniversidade de Caxias do Sul · BRUniversidade Federal do Rio de Janeiro · BRUniversity of Liverpool · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo estimate the diagnostic accuracy of signal intensity of the lesion-to-spinal cord ratio (LSR) and apparent diffusion coefficient (ADC) in diffusion-weighted (DW) magnetic resonance imaging of pulmonary nodules suspicious for lung cancer in granulomatous lung disease-endemic regions.

methodsForty-nine patients with indeterminate solitary pulmonary nodules detected by chest computed tomography and histopathologically confirmed diagnoses were included in the study. DW images were analysed semiquantitatively by focusing regions of interest on the lesion and spinal cord at the same level (for LSR calculation). ADCs were estimated from ratios of the two image signal intensities. Ratios of T1 and T2 signal intensity between nodules and muscle were calculated for comparison.

resultsMean ADCs ± standard deviations for lung cancer and benign lesions were 0.9 ± 0.2 and 1.3 ± 0.2 × 10(-3) mm(2)/s, respectively. Mean LSRs were 1.4 ± 0.3 for lung cancer and 1 ± 0.1 for benign lesions. ADCs and LSRs differed significantly between malignant and benign lesions (P < 0.001). Mean T2 signal intensity ratios also differed significantly between benign and malignant lesions (0.8 ± 0.2 vs. 1.6 ± 0.2; P < 0.05).

conclusionsDWI can help to differentiate malignant from benign lesions according to ADC and the LSR with good accuracy. KEY POINTS: • DW imaging can help differentiate malignant from benign pulmonary nodules. • ADC and LSR signal intensities had only small overlap between malignant and benign pulmonary nodules. • Mean T2 signal intensity ratios differed significantly between benign and malignant lesions.

Indexed as

Endemic DiseasesGranulomaAgedDiagnosis, DifferentialDiffusion Magnetic Resonance ImagingFemaleHumansLung NeoplasmsMaleMiddle AgedMultiple Pulmonary NodulesReproducibility of ResultsSensitivity and SpecificitySolitary Pulmonary NoduleSpinal Cord DiseasesTomography, X-Ray ComputedDifferentiation of malignant from benign lesionsDiffusion weightedGranulomatous disease-endemic regionMagnetic resonance imagingPulmonary nodules

Identifiers

PMID26638164
OpenAlexW2263972458

What OpenQuestion holds

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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.