Abstract
Radiomics has become an area of interest for tumor characterization in 18F-Fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) imaging. The aim of the present study was to demonstrate how imaging phenotypes was connected to somatic mutations through an integrated analysis of 115 non-small cell lung cancer (NSCLC) patients with somatic mutation testings and engineered computed PET/CT image analytics. A total of 38 radiomic features quantifying tumor morphological, grayscale statistic, and texture features were extracted from the segmented entire-tumor region of interest (ROI) of the primary PET/CT images. The ensembles for boosting machine learning scheme were employed for classification, and the least absolute shrink age and selection operator (LASSO) method was used to select the most predictive radiomic features for the classifiers. A radiomic signature based on both PET and CT radiomic features outperformed individual radiomic features, the PET or CT radiomic signature, and the conventional PET parameters including the maximum standardized uptake value (SUVmax), SUVmean, SUVpeak, metabolic tumor volume (MTV), and total lesion glycolysis (TLG), in discriminating between mutant-type of epidermal growth factor receptor (EGFR) and wild-type of EGFR- cases with an AUC of 0.805, an accuracy of 80.798%, a sensitivity of 0.826 and a specificity of 0.783. Consistently, a combined radiomic signature with clinical factors exhibited a further improved performance in EGFR mutation differentiation in NSCLC. In conclusion, tumor imaging phenotypes that are driven by somatic mutations may be predicted by radiomics based on PET/CT images.
Highlights
Lung cancer is one of the most frequently diagnosed malignancies worldwide, and is the leading cause of cancer-related death, with a 5-year survival rate of only 15% [1]
To assess the association between conventional PET parameters (SUVmax, SUVmean, SUVpeak, metabolic tumor volume (MTV), and total lesion glycolysis (TLG)) and epidermal growth factor receptor (EGFR) mutational status, we first compared the conventional PET values between the mutant-type of EGFR and wild-type of EGFR subgroups, and conducted ROC analyses to evaluate their performances in distinguishing the EGFR mutation
For EGFR mutated non-small cell lung cancer (NSCLC) patients, the SUVmax, SUVmean, SUVpeak, and TLG were found to be underrepresented in comparison with the EGFR- subgroup, whereas no significant difference existed in the MTV between the EGFR+ and EGFR- subgroups (Figure 2A)
Summary
Lung cancer is one of the most frequently diagnosed malignancies worldwide, and is the leading cause of cancer-related death, with a 5-year survival rate of only 15% [1]. Several EGFR tyrosine kinase inhibitors (TKIs) have been developed as small molecule targeted therapeutic agents for the treatment of NSCLC [4,5,6]. Given the predictive role of EGFR mutational status in the efficacy of EGFR-TKI treatment, identification of EGFR mutational status in advance is crucial for selecting the most effective therapeutic strategy to achieve precise medicine [9]. The assessments for EGFR mutational status are based on biopsies of tumor tissue or surgical resection acquisition [10, 11]. Molecular testing to identify the mutational status may be limited by invasive procedure, long processing time, tissue sample availability and sampling error due to tumor heterogeneity. A non-invasive, direct radiographic method for the early detection of EGFR mutational status is needed
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
