Deep Learning-based System and AIDS-related Cytomegalovirus Retinitis

Overview

Ophthalmological screening for cytomegalovirus retinitis (CMVR) for HIV/AIDS patients is important. However, the manual screening with fundus imaging is laborious and subjective. Deep learning (DL) system has been developed for the automated detection of various eye diseases with high accuracy and efficiency, including diabetic retinopathy, glaucoma, age-related macular degeneration (AMD), papilledema, lattice degeneration and retinal breaks, from ocular fundus photographs. UWF imaging is a relatively new imaging modality for DL system but has also shown extraordinary talents in automatic retinal analysis With the press for routine CMVR screening in AIDS patients and the great capacity of DL system, the use of deep learning (DL) system to AIDS-related CMVR with Ultra-Widefield (UWF) fundus images is promising. The investigators previously developed a DL system to detect AIDS-related CMVR. For further evaluating the applicability of the DL system, a prospective dataset is needed.

Full Title of Study: “Deep Learning-based System for Detection of AIDS-related Cytomegalovirus Retinitis in Ultra-Widefield Fundus Images”

Study Type

  • Study Type: Observational [Patient Registry]
  • Study Design
    • Time Perspective: Cross-Sectional
  • Study Primary Completion Date: May 1, 2021

Arms, Groups and Cohorts

  • Active CMVR
    • The UWF images of cytomegalovirus retinitis (CMVR) included various patterns: hemorrhagic necrotizing lesion, granular lesion, frosted branch angiitis, and optic neuropathy lesion. Active CMVR lesion was defined as obvious opacity (mild, moderate, severe, very severe)
  • Inactive CMVR
    • Inactive CMVR lesion was defined as a lack of opacity or questionable/equivocal activity.
  • Non-CMVR
    • The non-CMVR images included normal retina and other retinopathies such as HIV-related microvascular retinopathy, diabetic retinopathy, retinal detachment, vitreous hemorrhage.

Clinical Trial Outcome Measures

Primary Measures

  • Evaluating the applicability of the DL system to identify AIDS-related CMVR
    • Time Frame: April 2021
    • The investigators compared the performance between two trained (senior and junior) retinal ophthalmologists with the DL system. A senior retinal ophthalmologist and a junior retinal ophthalmologist were asked to independently screen the UWF images in the prospective dataset. Accuracy, sensitivity and specificity were used to evaluate the performance.

Participating in This Clinical Trial

Inclusion Criteria

The UWF images from HIV/AIDS patients. Exclusion Criteria:

1. The UWF images would be excluded if all three human graders gave different diagnosis. 2. The UWF images with poor quality would be excluded.

Gender Eligibility: All

Minimum Age: 18 Years

Maximum Age: N/A

Are Healthy Volunteers Accepted: No

Investigator Details

  • Lead Sponsor
    • Kuifang Du
  • Collaborator
    • Beijing Tongren Hospital
  • Provider of Information About this Clinical Study
    • Sponsor-Investigator: Kuifang Du, Principal investigator – Beijing YouAn Hospital
  • Overall Official(s)
    • Kui-Fang Du, Study Director, Beijing YouAn Hospital
    • Li Dong, Study Director, Beijing Tongren Hospital
    • Kai Zhang, Principal Investigator, Beijing Tongren Hospital
    • Chao Chen, Principal Investigator, Beijing YouAn Hospital
    • Lian-Yong Xie, Principal Investigator, Beijing YouAn Hospital
    • Wen-Jun Kong, Principal Investigator, Beijing YouAn Hospital
    • Hong-Wei Dong, Principal Investigator, Beijing YouAn Hospital
    • He-Yan Li, Principal Investigator, Beijing Tongren Hospital
    • Rui-Heng Zhang, Principal Investigator, Beijing Tongren Hospital
    • Wen-Da Zhou, Principal Investigator, Beijing Tongren Hospital
    • Hao-Tian Wu, Principal Investigator, Beijing Tongren Hospital
    • Wen-Bin Wei, Study Chair, Beijing Tongren Hospital

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