Evidence map›Paper›PMID 38634743›Full record

SynthesisRadiology. Cardiothoracic imaging2024

Diagnostic Performance of MRI for the Detection of Pulmonary Nodules: A Systematic Review and Meta-Analysis.

César Campagnolo Cavion, Stephan Altmayer, Gabriele Carra Forte, Rubens Gabriel Feijó Andrade, Daniela Quinto Dos Reis Hochhegger, Martina Zaguini Francisco, Capitulino Camargo, Pratik Patel, Bruno Hochhegger

Abstract readMeta-AnalysisSystematic Review

PubMed Full text at PMC Publisher

In one paragraph

Synthesis in Radiology. Cardiothoracic imaging, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it

0cells of the map it votes in

8citing 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

8 citing papers in PubMed.

Diagnostic performance of a single breath-hold lung MRI scan with AI-powered compressed sensing for nodule detection in comparison to photon counting detector-CT.European radiology · 2026
Article
Pulmonary nodules: classification, biomarkers, signaling pathways, diseases, early diagnosis and management.Signal transduction and targeted therapy · 2026
Review
Deep learning-based super-resolution ultrashort echo time MRI for pulmonary nodule detection and longitudinal assessment in emphysema.BMC pulmonary medicine · 2026
Article
AI-accelerated 3D gradient echo versus ultrashort echo time MRI for lung nodule detection and measurement.Radiology advances · 2026
Article
MRI for Lung Cancer Management: Any Closer to Clinical Application?Journal of magnetic resonance imaging : JMRI · 2026
Review
Magnetic Resonance of Pulmonary Nodules in Oncological Patients: Are We Ready to Replace Chest CT in Detecting Extrathoracic Cancer?Current oncology (Toronto, Ont.) · 2025
Article
Beyond Morphology: Quantitative MR Relaxometry in Pulmonary Lesion Classification.Cancers · 2025
Article
Thoracic magnetic resonance imaging in non-tuberculous mycobacterial pulmonary disease: Characteristics and potential implementation.PloS one · 2025
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.

César Campagnolo CavionFrom the Department of Radiology, Pontifícia Universidade Católica do Rio Grande do Sul, Av Ipiranga, 6681 - Partenon, Porto Alegre, Rio Grande do Sul, Brazil, 90619-900 (C.C.C., G.C.F., R.G.F.A.); Department of Radiology, Stanford University, Stanford, Calif (S.A.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (D.Q.d.R.H., P.P., B.H.); and Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil (M.Z.F., C.C.J.).ORCID 0000-0003-4924-5044

Stephan AltmayerFrom the Department of Radiology, Pontifícia Universidade Católica do Rio Grande do Sul, Av Ipiranga, 6681 - Partenon, Porto Alegre, Rio Grande do Sul, Brazil, 90619-900 (C.C.C., G.C.F., R.G.F.A.); Department of Radiology, Stanford University, Stanford, Calif (S.A.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (D.Q.d.R.H., P.P., B.H.); and Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil (M.Z.F., C.C.J.).ORCID 0000-0001-9214-1916

Gabriele Carra ForteFrom the Department of Radiology, Pontifícia Universidade Católica do Rio Grande do Sul, Av Ipiranga, 6681 - Partenon, Porto Alegre, Rio Grande do Sul, Brazil, 90619-900 (C.C.C., G.C.F., R.G.F.A.); Department of Radiology, Stanford University, Stanford, Calif (S.A.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (D.Q.d.R.H., P.P., B.H.); and Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil (M.Z.F., C.C.J.).ORCID 0000-0002-1480-8196

Rubens Gabriel Feijó AndradeFrom the Department of Radiology, Pontifícia Universidade Católica do Rio Grande do Sul, Av Ipiranga, 6681 - Partenon, Porto Alegre, Rio Grande do Sul, Brazil, 90619-900 (C.C.C., G.C.F., R.G.F.A.); Department of Radiology, Stanford University, Stanford, Calif (S.A.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (D.Q.d.R.H., P.P., B.H.); and Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil (M.Z.F., C.C.J.).ORCID 0000-0003-1459-8667

Daniela Quinto Dos Reis HochheggerFrom the Department of Radiology, Pontifícia Universidade Católica do Rio Grande do Sul, Av Ipiranga, 6681 - Partenon, Porto Alegre, Rio Grande do Sul, Brazil, 90619-900 (C.C.C., G.C.F., R.G.F.A.); Department of Radiology, Stanford University, Stanford, Calif (S.A.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (D.Q.d.R.H., P.P., B.H.); and Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil (M.Z.F., C.C.J.).

Martina Zaguini FranciscoFrom the Department of Radiology, Pontifícia Universidade Católica do Rio Grande do Sul, Av Ipiranga, 6681 - Partenon, Porto Alegre, Rio Grande do Sul, Brazil, 90619-900 (C.C.C., G.C.F., R.G.F.A.); Department of Radiology, Stanford University, Stanford, Calif (S.A.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (D.Q.d.R.H., P.P., B.H.); and Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil (M.Z.F., C.C.J.).ORCID 0000-0002-8110-2505

Capitulino CamargoFrom the Department of Radiology, Pontifícia Universidade Católica do Rio Grande do Sul, Av Ipiranga, 6681 - Partenon, Porto Alegre, Rio Grande do Sul, Brazil, 90619-900 (C.C.C., G.C.F., R.G.F.A.); Department of Radiology, Stanford University, Stanford, Calif (S.A.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (D.Q.d.R.H., P.P., B.H.); and Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil (M.Z.F., C.C.J.).ORCID 0000-0001-7279-5250

Pratik PatelFrom the Department of Radiology, Pontifícia Universidade Católica do Rio Grande do Sul, Av Ipiranga, 6681 - Partenon, Porto Alegre, Rio Grande do Sul, Brazil, 90619-900 (C.C.C., G.C.F., R.G.F.A.); Department of Radiology, Stanford University, Stanford, Calif (S.A.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (D.Q.d.R.H., P.P., B.H.); and Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil (M.Z.F., C.C.J.).

Bruno HochheggerFrom the Department of Radiology, Pontifícia Universidade Católica do Rio Grande do Sul, Av Ipiranga, 6681 - Partenon, Porto Alegre, Rio Grande do Sul, Brazil, 90619-900 (C.C.C., G.C.F., R.G.F.A.); Department of Radiology, Stanford University, Stanford, Calif (S.A.); Department of Radiology, College of Medicine, University of Florida, Gainesville, Fla (D.Q.d.R.H., P.P., B.H.); and Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil (M.Z.F., C.C.J.).

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Purpose To perform a meta-analysis of the diagnostic performance of MRI for the detection of pulmonary nodules, with use of CT as the reference standard. Materials and Methods PubMed, Embase, Scopus, and other databases were systematically searched for studies published from January 2000 to March 2023 evaluating the performance of MRI for diagnosis of lung nodules measuring 4 mm or larger, with CT as reference. Studies including micronodules, nodules without size stratification, or those from which data for contingency tables could not be extracted were excluded. Primary outcomes were the per-lesion sensitivity of MRI and the rate of false-positive nodules per patient (FPP). Subgroup analysis by size and meta-regression with other covariates were performed. The study protocol was registered in the International Prospective Register of Systematic Reviews, or PROSPERO (no. CRD42023437509). Results Ten studies met inclusion criteria (1354 patients and 2062 CT-detected nodules). Overall, per-lesion sensitivity of MRI for nodules measuring 4 mm or larger was 87.7% (95% CI: 81.1, 92.2), while the FPP rate was 12.4% (95% CI: 7.0, 21.1). Subgroup analyses demonstrated that MRI sensitivity was 98.5% (95% CI: 90.4, 99.8) for nodules measuring at least 8-10 mm and 80.5% (95% CI: 71.5, 87.1) for nodules less than 8 mm. Conclusion MRI demonstrated a good overall performance for detection of pulmonary nodules measuring 4 mm or larger and almost equal performance to CT for nodules measuring at least 8-10 mm, with a low rate of FPP. Systematic review registry no. CRD42023437509

Indexed as

Lung NeoplasmsMagnetic Resonance ImagingMultiple Pulmonary NodulesHumansLungSensitivity and SpecificitySolitary Pulmonary NoduleTomography, X-Ray ComputedCTLung CancerLung Cancer ScreeningLung NoduleMRI

Identifiers

PMID38634743

DOI10.1148/ryct.230241

PMCPMC11056753

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.