Unknown

Dataset Information

Preoperative prediction of early recurrence in resectable pancreatic cancer integrating clinical, radiologic, and CT radiomics features.


ABSTRACT:

Objectives

To use clinical, radiographic, and CT radiomics features to develop and validate a preoperative prediction model for the early recurrence of pancreatic cancer.

Methods

We retrospectively analyzed 190 patients (150 and 40 in the development and test cohort from different centers) with pancreatic cancer who underwent pancreatectomy between January 2018 and June 2021. Radiomics, clinical-radiologic (CR), and clinical-radiologic-radiomics (CRR) models were developed for the prediction of recurrence within 12 months after surgery. Performance was evaluated using the area under the curve (AUC), Brier score, sensitivity, and specificity.

Results

Early recurrence occurred in 36.7% and 42.5% of the development and test cohorts, respectively (P = 0.62). The features

SUBMITTER: Lee JH 

PROVIDER: S-EPMC10775464 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature