Prediction of EGFR and KRAS mutation in non-small cell lung cancer using quantitative 18F FDG-PET/CT metrics

Abstract

This study investigated the relationship between epidermal growth factor receptor (<i>EGFR</i>) and Kirsten rat sarcoma viral oncogene homolog (<i>KRAS</i>) mutations in non-small-cell lung cancer (NSCLC) and quantitative FDG-PET/CT parameters including tumor heterogeneity. 131 patients with NSCLC underwent staging FDG-PET/CT followed by tumor resection and histopathological analysis that included testing for the <i>EGFR</i> and <i>KRAS</i> gene mutations. Patient and lesion characteristics, including smoking habits and FDG uptake parameters, were correlated to each gene mutation. Never-smoker (<i>P</i> < 0.001) or low pack-year smoking history (<i>p</i> = 0.002) and female gender (<i>p</i> = 0.047) were predictive factors for the presence of the EGFR mutations. Being a current or former smoker was a predictive factor for the KRAS mutations (<i>p</i> = 0.018). The maximum standardized uptake value (SUV_max) of FDG uptake in lung lesions was a predictive factor of the <i>EGFR</i> mutations (<i>p</i> = 0.029), while metabolic tumor volume and total lesion glycolysis were not predictive. Amongst several tumor heterogeneity metrics included in our analysis, inverse coefficient of variation (1/COV) was a predictive factor (<i>p</i> < 0.02) of <i>EGFR</i> mutations status, independent of metabolic tumor diameter. Multivariate analysis showed that being a never-smoker was the most significant factor (<i>p</i> < 0.001) for the <i>EGFR</i> mutations in lung cancer overall. The tumor heterogeneity metric 1/COV and SUV_max were both predictive for the <i>EGFR</i> mutations in NSCLC in a univariate analysis. Overall, smoking status was the most significant factor for the presence of the <i>EGFR</i> and <i>KRAS</i> mutations in lung cancer.