Literature DB >> 27110732

The Diagnostic Value of MR Imaging in Determining the Lymph Node Status of Patients with Non-Small Cell Lung Cancer: A Meta-Analysis.

Jurgen Peerlings1, Esther G C Troost1, Patricia J Nelemans1, David C P Cobben1, Johannes C J de Boer1, Aswin L Hoffmann1, Regina G H Beets-Tan1.   

Abstract

Purpose To summarize existing evidence of thoracic magnetic resonance (MR) imaging in determining the nodal status of non-small cell lung cancer (NSCLC) with the aim of elucidating its diagnostic value on a per-patient basis (eg, in treatment decision making) and a per-node basis (eg, in target volume delineation for radiation therapy), with results of cytologic and/or histologic examination as the reference standard. Materials and Methods A systematic literature search for original diagnostic studies was performed in PubMed, Web of Science, Embase, and MEDLINE. The methodologic quality of each study was evaluated by using the Quality Assessment of Diagnostic Accuracy Studies 2, or QUADAS-2, tool. Hierarchic summary receiver operating characteristic curves were generated to estimate the diagnostic performance of MR imaging. Subgroup analyses, expressed as relative diagnostic odds ratios (DORs) (rDORs), were performed to evaluate whether publication year, methodologic quality, and/or method of evaluation (qualitative [ie, lesion size and/or morphology] vs quantitative [eg, apparent diffusion coefficients in diffusion-weighted images]) affected diagnostic performance. Results Twelve of 2551 initially identified studies were included in this meta-analysis (1122 patients; 4302 lymph nodes). On a per-patient basis, the pooled estimates of MR imaging for sensitivity, specificity, and DOR were 0.87 (95% confidence interval [CI]: 0.78, 0.92), 0.88 (95% CI: 0.77, 0.94), and 48.1 (95% CI: 23.4, 98.9), respectively. On a per-node basis, the respective measures were 0.88 (95% CI: 0.78, 0.94), 0.95 (95% CI: 0.87, 0.98), and 129.5 (95% CI: 49.3, 340.0). Subgroup analyses suggested greater diagnostic performance of quantitative evaluation on both a per-patient and per-node basis (rDOR = 2.76 [95% CI: 0.83, 9.10], P = .09 and rDOR = 7.25 [95% CI: 1.75, 30.09], P = .01, respectively). Conclusion This meta-analysis demonstrated high diagnostic performance of MR imaging in staging hilar and mediastinal lymph nodes in NSCLC on both a per-patient and per-node basis. (©) RSNA, 2016 Online supplemental material is available for this article.

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Year:  2016        PMID: 27110732     DOI: 10.1148/radiol.2016151631

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  12 in total

1.  Whole-body MRI compared with standard pathways for staging metastatic disease in lung and colorectal cancer: the Streamline diagnostic accuracy studies.

Authors:  Stuart A Taylor; Susan Mallett; Anne Miles; Stephen Morris; Laura Quinn; Caroline S Clarke; Sandy Beare; John Bridgewater; Vicky Goh; Sam Janes; Dow-Mu Koh; Alison Morton; Neal Navani; Alfred Oliver; Anwar Padhani; Shonit Punwani; Andrea Rockall; Steve Halligan
Journal:  Health Technol Assess       Date:  2019-12       Impact factor: 4.014

2.  Discrimination of Malignant versus Benign Mediastinal Lymph Nodes Using Diffusion MRI with an IVIM Model.

Authors:  Li-Ping Qi; Wan-Pu Yan; Ke-Neng Chen; Zheng Zhong; Xiao-Ting Li; Kejia Cai; Ying-Shi Sun; Xiaohong Joe Zhou
Journal:  Eur Radiol       Date:  2017-09-19       Impact factor: 5.315

Review 3.  Economic Benefits and Diagnostic Quality of Diffusion-Weighted Magnetic Resonance Imaging for Primary Lung Cancer.

Authors:  Katsuo Usuda; Aika Funazaki; Ryo Maeda; Atsushi Sekimura; Nozomu Motono; Munetaka Matoba; Hidetaka Uramoto
Journal:  Ann Thorac Cardiovasc Surg       Date:  2017-10-04       Impact factor: 1.520

4.  Circulating exosomal microRNA-96 promotes cell proliferation, migration and drug resistance by targeting LMO7.

Authors:  Hao Wu; Jingcheng Zhou; Shanshan Mei; Da Wu; Zhimin Mu; Baokun Chen; Yuancai Xie; Yiwang Ye; Jixian Liu
Journal:  J Cell Mol Med       Date:  2016-12-27       Impact factor: 5.310

5.  Stability of radiomics features in apparent diffusion coefficient maps from a multi-centre test-retest trial.

Authors:  Jurgen Peerlings; Henry C Woodruff; Jessica M Winfield; Abdalla Ibrahim; Bernard E Van Beers; Arend Heerschap; Alan Jackson; Joachim E Wildberger; Felix M Mottaghy; Nandita M DeSouza; Philippe Lambin
Journal:  Sci Rep       Date:  2019-03-18       Impact factor: 4.379

6.  Diagnostic accuracy of whole-body MRI versus standard imaging pathways for metastatic disease in newly diagnosed colorectal cancer: the prospective Streamline C trial.

Authors:  Stuart A Taylor; Sue Mallett; Sandy Beare; Gauraang Bhatnagar; Dominic Blunt; Peter Boavida; John Bridgewater; Caroline S Clarke; Marian Duggan; Steve Ellis; Robert Glynne-Jones; Vicky Goh; Ashley M Groves; Ayshea Hameeduddin; Sam M Janes; Edward W Johnston; Dow-Mu Koh; Anne Miles; Stephen Morris; Alison Morton; Neal Navani; John O'Donohue; Alfred Oliver; Anwar R Padhani; Helen Pardoe; Uday Patel; Shonit Punwani; Laura Quinn; Hameed Rafiee; Krystyna Reczko; Andrea G Rockall; Khawaja Shahabuddin; Harbir S Sidhu; Jonathan Teague; Mohamed A Thaha; Matthew Train; Katherine van Ree; Sanjaya Wijeyekoon; Steve Halligan
Journal:  Lancet Gastroenterol Hepatol       Date:  2019-05-09

7.  Diffusion-weighted magnetic resonance imaging is useful for the response evaluation of chemotherapy and/or radiotherapy to recurrent lesions of lung cancer.

Authors:  Katsuo Usuda; Shun Iwai; Aika Funasaki; Atsushi Sekimura; Nozomu Motono; Munetaka Matoba; Mariko Doai; Sohsuke Yamada; Yoshimichi Ueda; Hidetaka Uramoto
Journal:  Transl Oncol       Date:  2019-03-09       Impact factor: 4.243

8.  Diagnostic accuracy of whole-body MRI versus standard imaging pathways for metastatic disease in newly diagnosed non-small-cell lung cancer: the prospective Streamline L trial.

Authors:  Stuart A Taylor; Sue Mallett; Simon Ball; Sandy Beare; Gauraang Bhatnagar; Angshu Bhowmik; Peter Boavida; John Bridgewater; Caroline S Clarke; Marian Duggan; Steve Ellis; Robert Glynne-Jones; Vicky Goh; Ashley M Groves; Ayshea Hameeduddin; Sam M Janes; Edward W Johnston; Dow-Mu Koh; Sara Lock; Anne Miles; Stephen Morris; Alison Morton; Neal Navani; Alfred Oliver; Terry O'Shaughnessy; Anwar R Padhani; David Prezzi; Shonit Punwani; Laura Quinn; Hameed Rafiee; Krystyna Reczko; Andrea G Rockall; Peter Russell; Harbir S Sidhu; Nicola Strickland; Kathryn Tarver; Jonathan Teague; Steve Halligan
Journal:  Lancet Respir Med       Date:  2019-05-09       Impact factor: 30.700

9.  FDG-PET/CT and diffusion-weighted imaging for resected lung cancer: correlation of maximum standardized uptake value and apparent diffusion coefficient value with prognostic factors.

Authors:  Katsuo Usuda; Aika Funasaki; Atsushi Sekimura; Nozomu Motono; Munetaka Matoba; Mariko Doai; Sohsuke Yamada; Yoshimichi Ueda; Hidetaka Uramoto
Journal:  Med Oncol       Date:  2018-04-09       Impact factor: 3.064

10.  Relationships and Qualitative Evaluation Between Diffusion-Weighted Imaging and Pathologic Findings of Resected Lung Cancers.

Authors:  Katsuo Usuda; Shun Iwai; Aika Yamagata; Atsushi Sekimura; Nozomu Motono; Munetaka Matoba; Mariko Doai; Sohsuke Yamada; Yoshimichi Ueda; Keiya Hirata; Hidetaka Uramoto
Journal:  Cancers (Basel)       Date:  2020-05-08       Impact factor: 6.639

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