Construction and Application of Precise Diagnosis and Treatment System for Thyroid-associated Ophthalmopathy

Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age7-90
SponsorSecond Affiliated Hospital, School of Medicine, Zhejiang University

About this trial

This study aims to develop the deep learning-based system that integrates multimodal information to automatically diagnose, stage, and grade thyroid-associated ophthalmopathy (TAO), assist in treatment decision-making, and predict patient prognosis, thereby providing novel tools to support clinical management.

Eligibility criteria

This trial accepts healthy volunteers

Qualifiers

normal participants without eyelid disorders (control group)

patients with thyroid-associated ophthalmopathy (TAO group)

cooperative participants

Disqualifiers

participants with pupil or cornea disorders

participants with history of eye injury

Trial population

500 patients with thyroid-associated ophthalomopahty 500 patients without thyroid-associated ophthalomopahty

Trial design

Design model

Other

Time perspective

Prospective

Treatments tested in this trial

  • Imaging and ocular examinations

    Other intervention

    2D and 3D Facial photography, blinking videos, orbital CT and MRI images, fundus images and images of nine gaze positions are taken. Clinical information is recorded. Quality of life is assessed. Ocular examinations, such as visual acuity, levator function, exophthalmos measurement, strabismus test, visual field examination, axial length measurement, OCT, OCTA are made.

Treatment groups

500 Participants
are divided into 2 treatment groups
Group A: Participants without Thyroid-associated ophthalmopathy1 intervention
Group B: Patients with Thyroid-associated ophthalmopathy1 intervention

Trial outcomes

Primary outcomes

1

eye morphological parameters

Margin reflex distances(mm)

Time frame
through study completion, average of 5 years
2

Blinking feature of patients with thyroid-associated ophthalmopathy

Blinking frequency

Time frame
through study completion, average of 5 years
3

Ocular movement measurement

Ocular movement ability in nine gaze positions

Time frame
through study completion, average of 5 years
4

Automatic orbital structures segmentation and measurement using deep learning methods

Automatic segmentation and measurement of orbital structures,such as eyeball, extraocular muscle, orbital fat, bony orbital region, optic nerves, etc

Time frame
through study completion, average of 5 years

Secondary outcomes

Other outcomes

Sponsors and contacts

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