A New Deep Learning Algorithm for Detecting Spinal Metastases on Computed Tomography Images.

ABSTRACT:

Study design

Retrospective diagnostic study.

Objective

To automatically detect osteolytic bone metastasis lesions in the thoracolumbar region using conventional computed tomography (CT) scans, we developed a new deep learning (DL)-based computer-aided detection model.

Summary of background data

Radiographic detection of bone metastasis is often difficult, even for orthopedic surgeons and diagnostic radiologists, with a consequent risk for pathologic fracture or spinal cord injury. If we can improve detection rates, we will be able to prevent the deterioration of patients' quality of life at the end stage of cancer.

Materials and methods

This study included CT scans acquired at Tokyo Medical and Dental University (TMDU) Hospital between 2016 and 2022. A total of

SUBMITTER: Motohashi M 

PROVIDER: S-EPMC10898548 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature