Utilizing temporal information to assess metabolic heterogeneity: a study of 18F-FDG dynamic positron emission tomography as a treatment response biomarker in small cell lung cancer

作者：Yubo Wang, Zhiheng Yao, Xinghua He, Jiuhui Zhao, Dehua Huang, Rongliang Wu, Xinyu Yang, Maoqun Zhang, Tao Sun, Ying Liang · 发表于：Quantitative Imaging in Medicine and Surgery · 年份：2025 · DOI：10.21037/qims-24-1687 · 被引用次数：2 · 研究领域：Lung Cancer Research Studies、Radiomics and Machine Learning in Medical Imaging、Medical Imaging Techniques and Applications

Background: F-FDG provides detailed temporal and metabolic data, reflecting tumor heterogeneity more effectively, but its potential for predicting treatment response in ES-SCLC remains inadequately explored. This study aimed to evaluate the relationship between time-activity curve (TAC) features from dynamic PET imaging and treatment outcomes in ES-SCLC, assisting in developing personalized treatment strategies. Methods: This prospective pilot cohort study enrolled 15 patients with SCLC who planned to undergo dynamic PET imaging (November 2022 to January 2024). All participants underwent dynamic PET imaging before receiving first-line treatment. Tumor regions of interest (ROIs) were delineated on the PET images to facilitate the calculation of TAC. From these curves, 6 dynamic features were derived. The Mann-Whitney U test was applied to evaluate the significance of variations in continuous variables, encompassing both TAC features and conventional metabolic parameters. Statistically significant features were used to distinguish between the OR group and the non-objective response (non-OR) group and the area under the receiver operating characteristic curve (AUC) was calculated. Results: : a threshold of 0.070 and a threshold of -0.018. After excluding an outlier patient with extensive metastatic dissemination affecting typical uptake patterns, the optimal cutoff value was determined to be -0.018. Conclusions: ) in dynamic PET imaging may serve as an indicative predictor of tr...