Lung adenocarcinoma is a heterogeneous malignancy characterized by diverse molecular profiles that influence prognosis and treatment response. Identifying noninvasive imaging biomarkers capable of predicting genetic alterations may support early diagnosis and facilitate personalized therapeutic strategies. In this retrospective study, 225 patients with lung adenocarcinoma who underwent baseline 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) imaging and molecular mutation testing were evaluated. Tumor metabolic activity was quantified using the maximum standardized uptake value (SUVmax) of the primary lesion. The relationship between SUVmax and molecular alterations, including epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), ROS proto-oncogene 1 receptor tyrosine kinase (ROS1), Kirsten rat sarcoma viral oncogene homolog mutations, and programmed deathligand 1 (PD-L1) expression, was analyzed. EGFR mutation-positive tumors demonstrated significantly lower SUVmax values compared with mutation-negative tumors. In contrast, PD-L1- positive tumors were associated with higher SUVmax values. No significant correlation was identified between SUVmax and ALK or ROS1 alterations. Tumor metabolic activity measured by PET/CT may reflect specific molecular characteristics of lung adenocarcinoma. PET/CT-derived metabolic parameters, particularly when integrated with artificial intelligence and radiomics, could serve as non-invasive predictors of molecular alterations and help guide individualized treatment strategies. Prospective multicenter studies are warranted to validate these findings and confirm their clinical applicability.
山东省济南市章丘区文博路2号
齐鲁师范学院 genelibs生信实验室
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