Noninvasive Prediction of Occult Peritoneal Metastasis in Gastric Cancer Using Deep Learning.

ABSTRACT:

Importance

Occult peritoneal metastasis frequently occurs in patients with advanced gastric cancer and is poorly diagnosed with currently available tools. Because the presence of peritoneal metastasis precludes the possibility of curative surgery, there is an unmet need for a noninvasive approach to reliably identify patients with occult peritoneal metastasis.

Objective

To assess the use of a deep learning model for predicting occult peritoneal metastasis based on preoperative computed tomography images.

Design, setting, and participants

In this multicenter, retrospective cohort study, a deep convolutional neural network, the Peritoneal Metastasis Network (PMetNet), was trained to predict occult peritoneal metastasis based on preoperative computed tomography images. D

SUBMITTER: Jiang Y 

PROVIDER: S-EPMC7786251 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature