Radiomics nomogram for predicting disease-free survival after partial resection or radical cystectomy in patients with bladder cancer.

ABSTRACT:

Objectives

To create a MRI-derived radiomics nomogram that combined clinicopathological factors and radiomics signature (Rad-score) for predicting disease-free survival (DFS) in patients with bladder cancer (BCa) following partial resection (PR) or radical cystectomy (RC), including lymphadenectomy (LAE).

Methods

Finally, 80 patients with BCa after PR or RC with LAE were enrolled. Patients were randomly split into training (n = 56) and internal validation (n = 24) cohorts. Radiomic features were extracted from T2-weighted, dynamic contrast-enhanced, diffusion-weighted imaging, and apparent diffusion coefficient sequence. The least absolute shrinkage and selection operator (LASSO) Cox regression algorithm was applied to choose the valuable features and construct the Rad-score

SUBMITTER: Cai Q 

PROVIDER: S-EPMC11027261 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature