Esophageal cancer detection via non-contrast CT and deep learning.

ABSTRACT:

Background

Esophageal cancer is the seventh most frequently diagnosed cancer with a high mortality rate and the sixth leading cause of cancer deaths in the world. Early detection of esophageal cancer is very vital for the patients. Traditionally, contrast computed tomography (CT) was used to detect esophageal carcinomas, but with the development of deep learning (DL) technology, it may now be possible for non-contrast CT to detect esophageal carcinomas. In this study, we aimed to establish a DL-based diagnostic system to stage esophageal cancer from non-contrast chest CT images.

Methods

In this retrospective dual-center study, we included 397 primary esophageal cancer patients with pathologically confirmed non-contrast chest CT images, as well as 250 healthy individuals with

SUBMITTER: Lin C 

PROVIDER: S-EPMC10953501 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature