Solitary Pulmonary Nodules: Meta-analytic Comparison of Cross-sectional Imaging Modalities for Diagnosis of Malignancy

doi:10.1148/radiol.2463062148

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Evidence-based Practice

Solitary Pulmonary Nodules: Meta-analytic Comparison of Cross-sectional Imaging Modalities for Diagnosis of Malignancy¹

Paul Cronin, MD, MS, Ben A. Dwamena, MD, Aine Marie Kelly, MD, MS, and Ruth C. Carlos, MD, MS

¹ From the Department of Radiology, Divisions of Cardiothoracic Radiology (P.C., A.M.K.), Nuclear Medicine (B.A.D.), and Magnetic Resonance Imaging (R.C.C.), University of Michigan Medical Center, B1 132F Taubman Center/0302, 1500 E Medical Center Dr, Ann Arbor, MI 48109-0030; and Veterans Administration Ann Arbor Healthcare System Nuclear Medicine Service, Ann Arbor, Mich (B.A.D.). Received December 20, 2006; revision requested February 13, 2007; revision received May 23; accepted June 13; final version accepted August 29. Funded in part by National Institutes of Health/National Cancer Institute grant 1 K07 CA108664 01A1 and a GE-AUR Radiology Research Academic Fellowship. Address correspondence to P.C. (e-mail: pcronin{at}med.umich.edu).

Purpose: To perform a meta-analysis to estimate the diagnostic accuracyof dynamic contrast material–enhanced computed tomography (CT)and magnetic resonance (MR) imaging, fluorine 18 fluorodeoxyglucose(FDG) positron emission tomography (PET), and technetium 99m (^99mTc)depreotide single photon emission computed tomography (SPECT) forevaluation of solitary pulmonary nodules (SPNs).

Materials and Methods: Data sources were studies published in PubMedbetween January 1990 and December 2005. The selected investigationswere comparative and noncomparative diagnostic cohort studies toexamine the operating characteristics of the four imaging modalitiesfor evaluation of SPNs, involving at least 10 enrolled participantswith histologic confirmation and having sufficient data to calculatecontingency tables. A random coefficient binary regression modelwith disease probability conditioned on test results was used tosummarize test performance and construct summary receiver operatingcharacteristic (ROC) curves. Sensitivities, specificities, predictivevalues, diagnostic odds ratios, and areas under the ROC curve werecalculated.

Results: Forty-four studies—10 dynamic CT, six dynamic MR,22 FDG PET, and seven ^99mTc-depreotide SPECT—met the inclusioncriteria. (One study was included in both the FDG PET and SPECT groups.)Sensitivities, specificities, positive predictive values, negativepredictive values, diagnostic odds ratios, and areas under the ROCcurve were, respectively, 0.93 (95% confidence interval [CI]: 0.88,0.97), 0.76 (95% CI: 0.68, 0.97), 0.80 (95% CI: 0.74, 0.86), 0.95(95% CI: 0.93, 0.98), 39.91 (95% CI: 1.21, 81.04), and 0.93 (95%CI: 0.81, 0.97) for dynamic CT; 0.94 (95% CI: 0.91, 0.97), 0.79 (95%CI: 0.73, 0.86), 0.86 (95% CI: 0.83, 0.89), 0.93 (95% CI: 0.90, 0.96),60.59 (95% CI: 5.56, 115.62), and 0.94 (95% CI: 0.83, 0.98) for dynamicMR; 0.95 (95% CI: 0.93, 0.98), 0.82 (95% CI: 0.77, 0.88), 0.91 (95%CI: 0.88, 0.93), 0.90 (95% CI: 0.85, 0.94), 97.31 (95% CI: 6.26,188.37), and 0.94 (95% CI: 0.83, 0.98) for FDG PET; and 0.95 (95%CI: 0.93, 0.97), 0.82 (95% CI: 0.78, 0.85), 0.90 (95% CI: 0.83, 0.97),0.91 (95% CI: 0.84, 0.98), 84.50 (95% CI: 34.28, 134.73), and 0.94(95% CI: 0.83, 0.98) for ^99mTc-depreotide SPECT.

Conclusion: Dynamic CT and MR, FDG PET, and ^99mTc-depreotide SPECTare noninvasive and accurate in distinguishing malignant from benignSPNs; differences among these tests are nonsignificant.