Deep Learning-based System and AIDS-related Cytomegalovirus Retinitis

Summary

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.

Conditions

• Cytomegalovirus Retinitis

Interventions

OTHER

Sponsors & Collaborators

• Beijing Tongren Hospital

  collaborator OTHER

• Kuifang Du

  lead OTHER

Principal Investigators

• Kui-Fang Du · Beijing YouAn Hospital

• Li Dong · Beijing Tongren Hospital

• Kai Zhang · Beijing Tongren Hospital

• Chao Chen · Beijing YouAn Hospital

• Lian-Yong Xie · Beijing YouAn Hospital

• Wen-Jun Kong · Beijing YouAn Hospital

• Hong-Wei Dong · Beijing YouAn Hospital

• He-Yan Li · Beijing Tongren Hospital

• Rui-Heng Zhang · Beijing Tongren Hospital

• Wen-Da Zhou · Beijing Tongren Hospital

• Hao-Tian Wu · Beijing Tongren Hospital

• Wen-Bin Wei · Beijing Tongren Hospital

Eligibility

Min Age

18 Years

Sex

ALL

Healthy Volunteers

No

Timeline & Regulatory

Start

2021-04-01

Primary Completion

2021-05-01

Completion

2021-05-01

Countries

• China

Study Locations