A deep-learning radiomics-based lymph node metastasis predictive model for pancreatic cancer: a diagnostic study.

ABSTRACT:

Objectives

Preoperative lymph node (LN) status is essential in formulating the treatment strategy among pancreatic cancer patients. However, it is still challenging to evaluate the preoperative LN status precisely now.

Methods

A multivariate model was established based on the multiview-guided two-stream convolution network (MTCN) radiomics algorithms, which focused on primary tumor and peri-tumor features. Regarding discriminative ability, survival fitting, and model accuracy, different models were compared.

Results

Three hundred and sixty-three pancreatic cancer patients were divided in to train and test cohorts by 7:3. The modified MTCN (MTCN+) model was established based on age, CA125, MTCN scores, and radiologist judgement. The MTCN+ model outperformed the MTCN mo

SUBMITTER: Fu N 

PROVIDER: S-EPMC10442094 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature