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Pulmonary Nodule Detection with Low-Dose CT of the Lung: Agreement Among Radiologists

¹ Department of Radiology, Imaging Research Division, University of Pittsburgh, 300 Halket St., Ste. 4200, Pittsburgh, PA 15213.
² Departments of Medicine and Epidemiology and University of Pittsburgh Cancer Institute, University of Pittsburgh, Pittsburgh, PA 15213.
³ General Electric Global Research Center, One Research Cir., Niskayuna, NY 12309.

OBJECTIVE. The purpose of our study was to assess relative intra- and interobserver agreement in detecting pulmonary nodules when interpreting low-dose chest CT screening examinations.

MATERIALS AND METHODS. Two hundred ninety-three selected low-dose CT examinations of the lung were independently interpreted by three radiologists to detect and classify pulmonary nodules. The data set selected was enriched with examinations depicting pulmonary nodules. A subset of 30 examinations was interpreted twice. All pulmonary nodules greater than 1.0 mm were marked. All nodules greater than 3.0 mm were marked, measured, and scored as to their probability of being benign or malignant. Nodule-based and examination-based relative reviewer agreements were evaluated using percentage of agreement and kappa statistics. Similar assessments were performed on the subset of examinations interpreted twice.

RESULTS. The three radiologists identified a total of 470, 729, and 876 pulmonary nodules of which 395, 641, and 778 were rated as noncalcified with some level of suspicion for being malignant. Nodule-based interobserver agreement among the radiologists was poor (highest kappa value in a paired comparison, 0.120). Examination-based agreement was higher (highest kappa value in a paired comparison, 0.458). Intraobserver agreement was higher than interobserver agreement for examination-based agreement (highest = 0.889) but lower for nodule-based agreement (highest = -0.035). Agreement improved as the suspicion of malignancy increased.

CONCLUSION. Unaided intra- and interobserver agreement in detecting pulmonary nodules in low-dose CT of the lung is relatively low. Computer-assisted detection may provide the consistency that is needed for this purpose.

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