June 2023
Volume 64, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2023
An Artificial Intelligence (AI) Model for Screening Computed Tomography (CT) Imaging for Thyroid Eye Disease
Author Affiliations & Notes
  • Paul Zhou
    Ophthalmology, Massachusetts Eye and Ear, Boston, Massachusetts, United States
    Ophthalmology, University of California Irvine, Irvine, California, United States
  • Lisa Lin
    Ophthalmology, Massachusetts Eye and Ear, Boston, Massachusetts, United States
  • Min Shi
    Ophthalmology, Massachusetts Eye and Ear, Boston, Massachusetts, United States
  • Jon Lu
    Ophthalmology, Massachusetts Eye and Ear, Boston, Massachusetts, United States
  • Mengyu Wang
    Ophthalmology, Massachusetts Eye and Ear, Boston, Massachusetts, United States
  • Synho Do
    Radiology, Massachusetts General Hospital, Boston, Massachusetts, United States
  • Nahyoung Grace Lee
    Ophthalmology, Massachusetts Eye and Ear, Boston, Massachusetts, United States
  • Footnotes
    Commercial Relationships   Paul Zhou None; Lisa Lin None; Min Shi None; Jon Lu None; Mengyu Wang None; Synho Do None; Nahyoung Lee None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2023, Vol.64, 1095. doi:
  • Views
  • Share
  • Tools
    • Alerts
      ×
      This feature is available to authenticated users only.
      Sign In or Create an Account ×
    • Get Citation

      Paul Zhou, Lisa Lin, Min Shi, Jon Lu, Mengyu Wang, Synho Do, Nahyoung Grace Lee; An Artificial Intelligence (AI) Model for Screening Computed Tomography (CT) Imaging for Thyroid Eye Disease. Invest. Ophthalmol. Vis. Sci. 2023;64(8):1095.

      Download citation file:


      © ARVO (1962-2015); The Authors (2016-present)

      ×
  • Supplements
Abstract

Purpose : Thyroid eye disease (TED) is a rare autoimmune disease that leads to enlargement of the extraocular muscles, fat and connective tissue volume. Given the characteristic orbital involvement, computed tomography (CT) has been widely adopted to aid in the diagnosis and monitoring of TED. Our present study aims to enhance the neural network-based method in screening for and assessing the severity of TED.

Methods : Patients were divided into three subgroups based on clinical diagnoses and radiographic findings. In the control group, patients were seen at the Massachusetts Eye and Ear Oculoplastics clinics and underwent an orbit CT scan for a presumed orbital process but were not found to have any orbital pathology. In group two (Mild TED), patients were diagnosed with thyroid eye disease but no evidence of compressive optic neuropathy. In group three (Severe TED), patients were diagnosed with thyroid eye disease plus features of compressive optic neuropathy. The raw dataset included a total of 885 cross-section 2D images from the seventy-two CT scans in coronal view, which was resampled and adapted to focus on the eye as the region of interest. There were 20 eyes in the control group, 60 eyes in the Mild TED group, 64 eyes in the severe TED group.
The visual geometry group from Oxford (VGG16) model is a convolutional neural network pre-trained on ImageNet dataset, a collection with over 14 million images in 22,000 categories. All the TED datasets were trained using the VGG16 model 100 epochs. There were 628 images used in the training dataset: 231 images from the control group, 200 from group 2, and 197 from group 3. 157 images were used for the testing dataset: 50 images from group 1, 52 from group 2, and 55 from group 3.

Results : The overall prediction accuracy is 94.27%. Two images from the control group were misclassified as group 2 (Mild TED), and six images from Mild TED were misclassified as the normal control group. Images from group 3, the severe TED group with compressive optic neuropathy was never misclassified as normal or Mild TED.

Conclusions : Neural network-based analytic AI models can not only help diagnose TED and screen for disease severity for TED entirely based on CT scans, which may allow for automated screening of TED and timely referral of patients with compressive optic neuropathy from TED severe.

This abstract was presented at the 2023 ARVO Annual Meeting, held in New Orleans, LA, April 23-27, 2023.

×
×

This PDF is available to Subscribers Only

Sign in or purchase a subscription to access this content. ×

You must be signed into an individual account to use this feature.

×