Literature DB >> 29780624

Diagnostic performance of fluorine-18 fluorodeoxyglucose positron emission tomography in the management of solitary pulmonary nodule: a meta-analysis.

Duilio Divisi1, Mirko Barone1, Luca Bertolaccini2, Gino Zaccagna1, Francesca Gabriele1, Roberto Crisci1.   

Abstract

BACKGROUND: In the setting of solitary pulmonary nodules (SPNs), fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT) is considered a useful non-invasive diagnostic tool though false positive (FP) and false negative (FN) results affects accuracy due to different conditions, such as inflammatory diseases or low-uptake neoplasms. Aim of this study is to evaluate overall diagnostic performance of 18F-FDG-PET/CT for malignant pulmonary nodules.
METHODS: A computerized research, including published articles from 2012 and 2017, was carried out. 18F-FDG-PET/CT overall sensitivity (Se), specificity (Spe), positive likelihood ratio (PLR), negative likelihood ratio (NLR), positive predictive value (PPV), negative predictive value (NPV), diagnostic index and odds ratio were pooled. No selection-bias were found according to asymmetry test.
RESULTS: A total of twelve studies were included in the meta-analysis. The pooled Se, Spe, PLR, NLR, PPV, NPV and accuracy index (AI) with relative 95% confidence intervals (CI) were 0.819 (95% CI: 0.794-0.843), 0.624 (95% CI: 0.582-0.665), 2.190 (95% CI: 1.950-2.440), 0.290 (95% CI: 0.250-0.330), 0.802 (95% CI: 0.783-0.819), 0.652 (95% CI: 0.618-0.684) and 0.649 (95% CI: 0.625-0.673), respectively. The diagnostic odds ratio (DOR) was 7.049 with a relative 95% CI between 5.550 and 8.944.
CONCLUSIONS: The results suggest 18F-FDG-PET/CT has good diagnostic accuracy in SPNs evaluation; but, it should not be considered as a discriminatory test rather than a method to be included in a clinical and diagnostic pathway.

Entities:  

Keywords:  Fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG-PET/CT); lung cancer; solitary pulmonary nodules (SPNs)

Year:  2018        PMID: 29780624      PMCID: PMC5945698          DOI: 10.21037/jtd.2017.12.126

Source DB:  PubMed          Journal:  J Thorac Dis        ISSN: 2072-1439            Impact factor:   2.895


  41 in total

1.  Solitary pulmonary nodules and masses: a meta-analysis of the diagnostic utility of alternative imaging tests.

Authors:  Paul Cronin; Ben A Dwamena; Aine Marie Kelly; Steven J Bernstein; Ruth C Carlos
Journal:  Eur Radiol       Date:  2008-07-08       Impact factor: 5.315

2.  Executive Summary: Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines.

Authors:  Frank C Detterbeck; Sandra Zelman Lewis; Rebecca Diekemper; Doreen Addrizzo-Harris; W Michael Alberts
Journal:  Chest       Date:  2013-05       Impact factor: 9.410

3.  Guideline on management of solitary pulmonary nodule.

Authors:  Carlos J Álvarez Martínez; Gorka Bastarrika Alemañ; Carlos Disdier Vicente; Alberto Fernández Villar; Jesús R Hernández Hernández; Antonio Maldonado Suárez; Nicolás Moreno Mata; Antoni Rosell Gratacós
Journal:  Arch Bronconeumol       Date:  2014-03-13       Impact factor: 4.872

4.  Evaluation of Pulmonary Nodules: Clinical Practice Consensus Guidelines for Asia.

Authors:  Chunxue Bai; Chang-Min Choi; Chung Ming Chu; Devanand Anantham; James Chung-Man Ho; Ali Zamir Khan; Jang-Ming Lee; Shi Yue Li; Sawang Saenghirunvattana; Anthony Yim
Journal:  Chest       Date:  2016-02-27       Impact factor: 9.410

5.  Evaluation of primary pulmonary carcinoid tumors using FDG PET.

Authors:  J J Erasmus; H P McAdams; E F Patz; R E Coleman; V Ahuja; P C Goodman
Journal:  AJR Am J Roentgenol       Date:  1998-05       Impact factor: 3.959

Review 6.  PET/CT imaging in different types of lung cancer: an overview.

Authors:  Valentina Ambrosini; Silvia Nicolini; Paola Caroli; Cristina Nanni; Arianna Massaro; Maria Cristina Marzola; Domenico Rubello; Stefano Fanti
Journal:  Eur J Radiol       Date:  2011-03-31       Impact factor: 3.528

7.  Baseline findings of a randomized feasibility trial of lung cancer screening with spiral CT scan vs chest radiograph: the Lung Screening Study of the National Cancer Institute.

Authors:  John Gohagan; Pamela Marcus; Richard Fagerstrom; Paul Pinsky; Barnett Kramer; Philip Prorok
Journal:  Chest       Date:  2004-07       Impact factor: 9.410

8.  Evaluation of F-18 fluorodeoxyglucose (FDG) PET scanning for pulmonary nodules less than 3 cm in diameter, with special reference to the CT images.

Authors:  Hiroaki Nomori; Kenichi Watanabe; Takashi Ohtsuka; Tsuguo Naruke; Keiichi Suemasu; Kimiichi Uno
Journal:  Lung Cancer       Date:  2004-07       Impact factor: 5.705

9.  Overestimated value of (18)F-FDG PET/CT to diagnose pulmonary nodules: Analysis of 298 patients.

Authors:  S Li; B Zhao; X Wang; J Yu; S Yan; C Lv; Y Yang
Journal:  Clin Radiol       Date:  2014-05-27       Impact factor: 2.350

Review 10.  Lung Cancer Statistics.

Authors:  Lindsey A Torre; Rebecca L Siegel; Ahmedin Jemal
Journal:  Adv Exp Med Biol       Date:  2016       Impact factor: 2.622

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  5 in total

1.  Prone position [18F]FDG PET/CT to reduce respiratory motion artefacts in the evaluation of lung nodules.

Authors:  Hyung Ju Lee; Hye Joo Son; Mijin Yun; Jung Won Moon; Yoo Na Kim; Ji Young Woo; Suk Hyun Lee
Journal:  Eur Radiol       Date:  2021-04-14       Impact factor: 5.315

2.  Contribution of 18F-FDG PET/CT in the Differential Diagnosis of Pulmonary Hamartomas and Pulmonary Carcinoids

Authors:  Ebru Tatcı; Özlem Özmen; Ayperi Öztürk; Funda Demirağ
Journal:  Mol Imaging Radionucl Ther       Date:  2021-06-03

Review 3.  Diagnostic Performance of PET or PET/CT with Different Radiotracers in Patients with Suspicious Lung Cancer or Pleural Tumours according to Published Meta-Analyses.

Authors:  Filippo Lococo; Barbara Muoio; Marco Chiappetta; Dania Nachira; Leonardo Petracca Ciavarella; Stefano Margaritora; Giorgio Treglia
Journal:  Contrast Media Mol Imaging       Date:  2020-04-25       Impact factor: 3.161

4.  Diagnostic Performance of Machine Learning Models Based on 18F-FDG PET/CT Radiomic Features in the Classification of Solitary Pulmonary Nodules.

Authors:  Yavuz Sami Salihoğlu; Rabiye Uslu Erdemir; Büşra Aydur Püren; Semra Özdemir; Çağlar Uyulan; Türker Tekin Ergüzel; Hüseyin Ozan Tekin
Journal:  Mol Imaging Radionucl Ther       Date:  2022-06-27

5.  Comparison of the diagnostic accuracy of diffusion-weighted magnetic resonance imaging and positron emission tomography/computed tomography in pulmonary nodules: a prospective study.

Authors:  Tuba Selcuk Can; Gulfidan Uzan
Journal:  Pol J Radiol       Date:  2019-11-27
  5 in total

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