Deep learning-based diagnosis of disease activity in patients with Graves' orbitopathy using orbital SPECT/CT.

ABSTRACT:

Purpose

Orbital [^99mTc]TcDTPA orbital single-photon emission computed tomography (SPECT)/CT is an important method for assessing inflammatory activity in patients with Graves' orbitopathy (GO). However, interpreting the results requires substantial physician workload. We aim to propose an automated method called GO-Net to detect inflammatory activity in patients with GO.

Materials and methods

GO-Net had two stages: (1) a semantic V-Net segmentation network (SV-Net) that extracts extraocular muscles (EOMs) in orbital CT images and (2) a convolutional neural network (CNN) that uses SPECT/CT images and the segmentation results to classify inflammatory activity. A total of 956 eyes from 478 patients with GO (active: 475; inactive: 481) at Xiangya Hospital of Central S

SUBMITTER: Yao N 

PROVIDER: S-EPMC10547836 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature