ESTRO 2023 - Abstract Book

S1915

Digital Posters

ESTRO 2023

Results The RC model containing six predictive features (GTV shape flatness, root-mean-square on fine Laplacian of Guassian- filtered image, PSA, GS, RS and GTV volume) has the best performance (AUC = 0.797, 95%CI = 0.768-0.826), which significantly outperformed the R-model (AUC = 0.795, 95%CI = 0.774-0.816) and C-model (AUC = 0.625, 95%CI = 0.585-0.665) in the independent validation cohort. Besides, only the RC model score significantly classified patients in both the training and independent validation cohorts into progression and progression-free groups regarding their 5-year PFS (p < 0.05).

Conclusion Radiomic features extracted from the pCT adds value to conventional clinical factors in the prognostication of HRPCa in our cohort. Our findings confirm the potential of incorporating radiomics into clinical decision-making in the era of personalised medicine.

PO-2127 Linear quadratic model is not a valid predictive model for post radiation clonogenic cell survival

H. Li 1