Imaging-Based Surrogate Markers of Epidermal Growth Factor Receptor Mutation in Lung Adenocarcinoma: A Local Perspective. Issue 2 (May 2020) - AlGharras, Abdulaziz; Kovacina, Bojan; Tian, Zhe; Alexander, James W.; Semionov, Alexandre; van Kempen, Léon C.; Sayegh, Karl
Purpose: To identify computed tomography (CT) features of epidermal growth factor receptor (EGFR) mutation-positive lung adenocarcinoma in Canadian population and whether imaging-based surrogate markers of EGFR mutation in our population were similar to those found in the Asian population. Materials and Methods: Pretreatment CT scans of 223 patients with adenocarcinoma of the lung (112 with EGFR mutation and 111 without mutation) were retrospectively assessed for 20 specific CT features by 2 radiologists, who were blinded to the status of EGFR mutation. Univariate and multivariate logistic regression analyses as well as areas under the receiver operating characteristic curve were performed to discriminate characteristics of EGFR-activating mutation features. Results: Epidermal growth factor receptor mutation-positive adenocarcinomas were more frequently found in female ( P < .03), less than 20 pack-year smoking history ( P < .001), smaller tumor ( P < .01), spiculated margins ( P < .05), without centrilobular emphysema ( P < .001), and without lymphadenopathy ( P < .05), similarly to the Asian population. Multivariate logistic regression analyses of combined clinical and radiological features identified less than 20 pack-year smoking history, smaller tumor diameter, fine or coarse spiculations, noncentral location of the tumor, and lack of centrilobular emphysema and pleural attachment as the strongest independent prognostic factors for the presence of an EGFR mutation. These combined features improved prognostic ability area under the curve to 0.879, compared to 0.788 for clinical features only. Conclusion: Several CT findings may help predict the presence of an activating mutation in EGFR in lung adenocarcinomas in our Canadian population. Combining clinical and radiological features improves prognostic ability to determine the EGFR mutation status compared to clinical features alone.