Role of chest MRI for the diagnosis of malignant pulmonary nodules: a systematic review and a meta-analysis

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Abstract

AIM: To evaluate the ability of magnetic resonance imaging (MRI) of the chest to detect malignant pulmonary nodules compared to compute tomography (CT).

MATERIALS AND METHODS: We searched the following databases with the final date of search on April 7th, 2021: PubMed, Google Scholar. We selected studies according to the inclusion and exclusion criteria that assessed the detection of malignant lung nodules by MRI and CT and included information about sensitivity and specificity. Method of the analysis and data grouping was chosen with regard to statistical heterogeneity of the studies included in the analysis. We used the χ2 test and I2 statistic to evaluate the heterogeneity.

RESULTS: We selected 168 articles for the systematic review from the PubMed and Google Scholar databases. We included 21 studies on 1,188 patients in the meta-analysis and revealed statistically significant heterogeneity (р<0,00001 for χ2 test; I2=99%) for sensitivity and specificity. Hence, we used a random-effect model for further analysis. As a result, values of sensitivity for detection of pulmonary nodules with MRI of 70.4%–100%, specificity ― from 60.6% to 100%.

CONCLUSIONS: Thus, MRI has sufficient sensitivity and specificity for detecting malignant pulmonary nodules primarily discovered with CT.

About the authors

Yuriy A. Vasilev

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of Moscow Health Care; City Clinical Oncological Hospital No. 1

Email: dr.vasilev@me.com
ORCID iD: 0000-0002-0208-5218
SPIN-code: 4458-5608

MD, Cand. Sci. (Med)

Russian Federation, 24/1 Petrovka str., 127051, Moscow; Moscow

Olga Y. Panina

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of Moscow Health Care; City Clinical Oncological Hospital No. 1; Moscow State University of Medicine and Dentistry named after A.I. Evdokimov

Email: o.panina@npcmr.ru
ORCID iD: 0000-0002-8684-775X
SPIN-code: 5504-8136
Scopus Author ID: 57219837311

Junior Scientist Researcher

Russian Federation, 24/1 Petrovka str., 127051, Moscow; Moscow; 20, p. 1, Delegatskaya str., Moscow, 127473

Evgeniia A. Grik

Moscow State University of Medicine and Dentistry named after A.I. Evdokimov

Email: evgeniyagrik@gmail.com
ORCID iD: 0000-0002-7908-3982
SPIN-code: 5558-7307

MD

Russian Federation, 20/1, Delegatskaya str., Moscow, 127473

Kate S. Akhmad

Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of Moscow Health Care

Email: e.ahmad@npcmr.ru
ORCID iD: 0000-0002-8235-9361
SPIN-code: 5891-4384
Russian Federation, 24/1, Petrovka street,127051 Moscow

Yulia N. Vasileva

Moscow State University of Medicine and Dentistry named after A.I. Evdokimov

Author for correspondence.
Email: drugya@yandex.ru
ORCID iD: 0000-0003-4955-2749
SPIN-code: 9777-2067

MD, Cand. Sci. (Med.)

Russian Federation, 20/1, Delegatskaya str., Moscow, 127473

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4. Fig. 3. Forest plot of grouped data for specificity (a) and sensitivity (b) [40]

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Copyright (c) 2021 Vasilev Y.A., Panina O.Y., Grik E.A., Akhmad K.S., Vasileva Y.N.

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

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