Predictive Value of 18F-FDG PET and CT Morphologic Features for Recurrence in Pathological Stage IA Non-Small Cell Lung Cancer. Issue 3 (January 2015) - Ko, Kai-Hsiung; Hsu, Hsian-He; Huang, Tsai-Wang; Gao, Hong-Wei; Cheng, Cheng-Yi; Hsu, Yi-Chih; Chang, Wei-Chou; Chu, Chi-Ming; Chen, Jia-Hong; Lee, Shih-Chun; Liu., Yiyan
<x xml:space="preserve">Abstract</x> Abstract Patients with pathological stage IA non-small cell lung cancer (NSCLC) may relapse despite complete surgical resection without lymphovascular invasion. A method of selecting a high-risk group for adjuvant therapy is necessary. The aim of this study was to assess the predictive value of 18F-fluorodeoxyglucose (FDG) uptake and the morphologic features of computed tomography (CT) for recurrence in pathological stage IA NSCLC. One hundred forty-five patients with pathological stage IA NSCLC who underwent pretreatment with FDG positron emission tomography and CT evaluations were retrospectively enrolled. The associations among tumor recurrence and patient characteristics, maximal standard uptake value (SUVmax) of primary tumors, and CT imaging features were investigated using univariate and multivariate analyses. A receiver operating characteristic (ROC) curve analysis was performed to quantify the predictive value of these factors. Tumor recurrence developed in 21 (14.5%) of the 145 patients, and the 5-year recurrence-free survival rate was 77%. The univariate analysis demonstrated that SUVmax, the grade of histological differentiation, tumor size, and the presence of bronchovascular bundle thickening were significant predictive factors (P < 0.05). A higher SUVmax (≥2.5) (P = 0.021), a lower ground-glass opacity ratio (⩽17%) (P = 0.014), and the presence of bronchovascular bundle thickening (P = 0.003) were independent predictive factors of tumor recurrence in the multivariate analysis. The use of this predictive model yielded a greater area under the ROC curve (0.877), which suggests good discrimination. The combined evaluation of FDG uptake and CT morphologic features may be helpful in the prediction of recurrence in patients with pathological stage IA NSCLC and in the stratification of a high-risk group for postoperative adjuvant therapy or prospective clinical trials.