Differentiation of Malignant and Benign Pulmonary Nodules with Quantitative First-Pass 320–Detector Row Perfusion CT versus FDG PET/CT

Abstract

To prospectively compare the capability of quantitative first-pass perfusion 320-detector row computed tomography (CT) (ie, area-detector CT) with that of combined positron emission tomography and CT (PET/CT) for differentiation between malignant and benign pulmonary nodules. This prospective study was approved by the institutional review board, and written informed consent was obtained from 50 consecutive patients with 76 pulmonary nodules. All patients underwent dynamic area-detector CT, PET/CT, and microbacterial and/or histopathologic examinations. All pulmonary nodules were divided into three groups: malignant nodules (n = 43), benign nodules with low biologic activity (n = 6), and benign nodules with high biologic activity (n = 27). For each dynamic area-detector CT data set, the perfusion derived by using the maximum slope model (PF(MS)), extraction fraction derived by using the Patlak plot model (EF(PP)), and blood volume derived by using the Patlak plot model (BV(PP)) were calculated. These parameters were statistically compared among the three nodule groups. Receiver operating characteristic (ROC) analyses were used to compare the diagnostic capability of the CT and PET/CT indexes. Finally, the sensitivity, specificity, and accuracy of each index were compared by using the McNemar test. All indexes in the malignant nodule group were significantly different from those in the low-biologic-activity benign nodule group (P < .05). Areas under the ROC curve for PF(MS) and EF(PP) were significantly larger than those for BV(PP) (P < .05) and maximal standard uptake value (SUV(max)) (P < .05). The specificity and accuracy of PF(MS) and EF(PP) were significantly higher than those of BV(PP) and SUV(max) (P < .05). Dynamic first-pass area-detector perfusion CT has the potential to be more specific and accurate than PET/CT for differentiating malignant from benign pulmonary nodules. http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.10100245/-/DC1.