Combination of clinical, radiomic, and “delta” radiomic features in survival prediction of metastatic gastroesophageal adenocarcinoma - Krishna, Satheesh; Sertic, Andrew; Liu, Zhihui (Amy); Liu, Zijin; Darling, Gail E.; Yeung, Jonathon; Wong, Rebecca; Chen, Eric X.; Kalimuthu, Sangeetha; Allen, Michael J.; Suzuki, Chihiro; Panov, Elan; et al. (Frontiers in Oncology, 2023)
Abstract Objectives: To identify combined clinical, radiomic and delta radiomic features in metastatic gastroesophageal adenocarcinomas (GEA) that may predict survival outcomes. Methods: 166 patients with metastatic GEA on palliative chemotherapy with baseline and treatment/follow-up (8-12 weeks) contrast-enhanced CT were retrospectively identified. Demographic and clinical data were collected. Three-dimensional whole-lesional radiomic analysis was performed on the treatment/follow-up scans. ‘Delta’ radiomic features were calculated based on change in radiomic parameters compared to the baseline. Univariable (UVA) Cox proportional hazards model was used to select clinical variables predictive of overall survival (OS) and progression-free survival (PFS) (p-value <0.05). The radiomic and ‘delta’ features were then assessed in a multivariable (MVA) Cox model in combination with clinical features identified on UVA. Features with a p-value <0.01 in the MVA models were selected to assess their pairwise correlation. Only non-highly correlated features (Pearson correlation coefficient < 0.7) were included in the final model. Leave-one-out cross-validation method was used, and the one-year area under the curve (AUC) was calculated for PFS and OS. Results: Of the 166 patients (median age of 59.8 years), 114 (69%) were male, 139 (84%) were non-asian, and 147 (89%) had an Eastern Cooperative Oncology Group (ECOG), performance status 0-1. The median PFS and OS on treatment was 3.6 months (95% CI 2.86, 4.63) and 9 months (95% CI 7.49, 11.04) respectively. On UVA analysis the number of chemotherapy cycles and number of lesions at the end of treatment were associated with both PFS and OS (p<0.001). ECOG status was associated with OS (p=0.0063), but not PFS (p=0.054). Of the delta radiomic features, delta conventional HUmin, delta GLZLM GLNU, delta GLZLM LGZE were incorporated into the model for PFS and delta shape compacity was incorporated in the model for OS. Of the treatment/follow-up radiomic features, shape compacity and NGLDM contrast were used in both models. The combined one-year AUC (Kaplan-Meier Estimator), was 0.82 and 0.81 for PFS and OS respectively. Conclusions: A combination of clinical, and delta radiomic features may predict PFS and OS in GEA with reasonable accuracy.