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.