TY - JOUR T1 - Differences of <sup>18</sup>F-FDG PET tumor texture parameters according to the presence of epidermal growth factor receptor mutation in non-small cell lung cancer JF - Journal of Nuclear Medicine JO - J Nucl Med SP - 1393 LP - 1393 VL - 56 IS - supplement 3 AU - Hansol Moon AU - Joon Ho Choi AU - Ji Hyun Park AU - Byung Hyun Byun AU - Ilhan Lim AU - Byung Il Kim AU - Chang Woon Choi AU - Sang Moo Lim Y1 - 2015/05/01 UR - http://jnm.snmjournals.org/content/56/supplement_3/1393.abstract N2 - 1393 Objectives We evaluated the differences of 18F-FDG PET tumor texture parameters according to epidermal growth factor receptor (EGFR) mutation (+) and EGFR mutation (-).Methods A total of 58 patients with AJCC stage Ⅰ to Ⅲ NSCLC (29 SqCC, 29 Adc) were retrospectively analyzed. All patients underwent pretreatment 18F-FDG PET/CT. To analyze the conventional PET parameters, the maximum SUV (SUVmax), the metabolic tumor volume (MTV) and the total lesion glycolysis (TLG) of the primary tumor at the cutoff SUV of 2.5 were respectively measured. For the texture analyses of PET images, we chose a transverse PET slice containing SUVmax and manually drew the region of interest (ROI) including the tumor region with SUV &gt; 2.5. Then First- (skewness, kurtosis) and second-order (contrast, entropy) texture analyses were performed using MaZda software v.4.6. The most useful texture parameters to predict the EGFR mutation were selected among conventional and texture PET parameters, respectively, on the basis of receiver operating characteristic (ROC) curve analysis. Differences of these selected parameters between EGFR mutation (+) and EGFR mutation (-) groups were tested using t-test. Correlations between these 2 parameters were also evaluated.Results Thirteen of fifty-eight patients (22.4%) had tumors with positive EGFR mutation (2 squamous cell carcinoma, 11 adenocarcinoma). Among the conventional PET parameters, SUVmax best predicted EGFR mutation (AUC=0.655, p = 0.0670). Among the texture parameters, entropy best predicted EGFR mutation (AUC=0.638, p = 0.1556). SUVmax was significantly higher in EGFR mutation (-) group than in EGFR mutation (+) group (mean: 11.5 vs 8.9, p &lt; 0.05), and entropy was higher in EGFR mutation (-) group than EGFR mutation (+) group (mean: 2.5 vs 2.4, p &lt; 0.05). There was no significant correlation between SUVmax and entropy (p = 0.6516).Conclusions Both SUVmax and entropy were significantly higher in EGFR mutation (-) NSCLC than in EGFR mutation (+) NSCLC. ER -