A preoperative tool capable of predicting lymph node metastasis status in hilar cholangiocarcinoma is lacking and urgently needed for clinical practice. This study proposes to establish and evaluate a machine-learning algorithms of multiparametric MRI-based clinico-radiomics for identifying lymph node metastasis status in hilar cholangiocarcinoma. This study will investigate the relationship between radiomic depth information and tumor biological characteristics. The study includes the construction of capable MRI-based clinico-radiomics prediction model and the validation of the prediction model.
This is a prospective, observational diagnostic study aiming to assess multiparametric MRI-based clinico-radiomics for identifying lymph node metastasis status in hilar cholangiocarcinoma.