Translational lung cancer research · 2025
Radiomic phenotypes of oligometastatic non-small cell lung cancer.
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Boehm Kevin M, Lebow Emily S, Wijetunga N Ari, Haseltine Justin, Rimner Andreas, Shaverdian Narek, Yu Helena, Li Bob T, Isbell James M, Mirtcheva-Trocheva Rosna, Iyengar Puneeth, Gomez Daniel R
Аннотация
BACKGROUND: Identifying biomarkers that optimize patient selection for ablative therapy in metastatic non-small cell lung cancer (NSCLC) remains an unmet need. In this study, we identified radiomic features associated with sustained oligometastatic and indolent NSCLC.
METHODS: We curated a retrospective cohort of 167 patients (132 training/validation, 35 test) with treatment-naïve, metastatic NSCLC and pre-treatment positron emission tomography/computed tomography (PET/CT). We extracted radiomic features from the primary lesion and used Pearson's correlation to identify those associated with extent of metastatic disease. For a subset (n=83), we also identified features associated with overall survival (OS) using Cox proportional hazards models.
RESULTS: We found that the inverse flatness was lower (r=-0.23; q=0.04) and surface area-to-volume ratio (SVR) was higher (r=0.24; q=0.04) in primary lesions for cases with more metastases. We further found that higher gray level variance on CT portends shorter OS [hazard ratio (HR) =1.84, 95% confidence interval (CI): 1.32-2.56, q=0.004; test c=0.74, 95% CI: 0.52-0.90]. Risk groups derived from these scores exhibited median survival times in the training set of 12.6 and >50 months (P=0.001) and in the test set of 13.8 and 32.7 months (P=0.06). This feature was determined primarily by inclusion of low-intensity voxels.
CONCLUSIONS: This study identifies radiomic features of indolent NSCLC, demonstrating that flatter, higher surface area primary disease is associated with a greater number of metastases, and primary lesions with lower density representing lung parenchyma, airspace, or lower-density tumor portend shorter OS. These findings lay the groundwork toward identifying patients suitable for ablative radiotherapy despite the presence of metastatic disease.
METHODS: We curated a retrospective cohort of 167 patients (132 training/validation, 35 test) with treatment-naïve, metastatic NSCLC and pre-treatment positron emission tomography/computed tomography (PET/CT). We extracted radiomic features from the primary lesion and used Pearson's correlation to identify those associated with extent of metastatic disease. For a subset (n=83), we also identified features associated with overall survival (OS) using Cox proportional hazards models.
RESULTS: We found that the inverse flatness was lower (r=-0.23; q=0.04) and surface area-to-volume ratio (SVR) was higher (r=0.24; q=0.04) in primary lesions for cases with more metastases. We further found that higher gray level variance on CT portends shorter OS [hazard ratio (HR) =1.84, 95% confidence interval (CI): 1.32-2.56, q=0.004; test c=0.74, 95% CI: 0.52-0.90]. Risk groups derived from these scores exhibited median survival times in the training set of 12.6 and >50 months (P=0.001) and in the test set of 13.8 and 32.7 months (P=0.06). This feature was determined primarily by inclusion of low-intensity voxels.
CONCLUSIONS: This study identifies radiomic features of indolent NSCLC, demonstrating that flatter, higher surface area primary disease is associated with a greater number of metastases, and primary lesions with lower density representing lung parenchyma, airspace, or lower-density tumor portend shorter OS. These findings lay the groundwork toward identifying patients suitable for ablative radiotherapy despite the presence of metastatic disease.