Clinical trial NCT04831333: Deep Learning-based System and AIDS-related Cytomegalovirus Retinitis
Official title: Deep Learning-based System for Detection of AIDS-related Cytomegalovirus Retinitis in Ultra-Widefield Fundus Images
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Cytomegalovirus Retinitis
Keywords: AIDS
HIV
Cytomegalovirus Retinitis
Deep learning
Ultra-wide-field imaging
Lead sponsor: Beijing YouAn Hospital
Sponsor class: OTHER
Collaborators: name: Beijing Tongren Hospital
First posted: 2021-04-05
Enrollment: 50
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: OTHER
Time perspective: CROSS_SECTIONAL
Sampling method: NON_PROBABILITY_SAMPLE
Study population: AIDS patients undergoing OPTOS camera (OPTOS® Daytona) from Department of Ophthalmology, Beijing Youan Hospital, were prospectively collected as a prospective dataset.

Brief 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.


Eligibility criteria: 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.

Primary outcomes:
measure: Evaluating the applicability of the DL system to identify AIDS-related CMVR
timeFrame: April 2021
Secondary outcomes:
Other outcomes:
Locations:
city: Beijing
country: China
facility: Beijing Youan Hospital, Capital Medical University
state: Beijing
Study officials:
affiliation: Beijing YouAn Hospital
name: Kui-Fang Du
role: STUDY_DIRECTOR
affiliation: Beijing Tongren Hospital
name: Li Dong
role: STUDY_DIRECTOR
affiliation: Beijing Tongren Hospital
name: Kai Zhang
role: PRINCIPAL_INVESTIGATOR
affiliation: Beijing YouAn Hospital
name: Chao Chen
role: PRINCIPAL_INVESTIGATOR
affiliation: Beijing YouAn Hospital
name: Lian-Yong Xie
role: PRINCIPAL_INVESTIGATOR
affiliation: Beijing YouAn Hospital
name: Wen-Jun Kong
role: PRINCIPAL_INVESTIGATOR
affiliation: Beijing YouAn Hospital
name: Hong-Wei Dong
role: PRINCIPAL_INVESTIGATOR
affiliation: Beijing Tongren Hospital
name: He-Yan Li
role: PRINCIPAL_INVESTIGATOR
affiliation: Beijing Tongren Hospital
name: Rui-Heng Zhang
role: PRINCIPAL_INVESTIGATOR
affiliation: Beijing Tongren Hospital
name: Wen-Da Zhou
role: PRINCIPAL_INVESTIGATOR
affiliation: Beijing Tongren Hospital
name: Hao-Tian Wu
role: PRINCIPAL_INVESTIGATOR
affiliation: Beijing Tongren Hospital
name: Wen-Bin Wei
role: STUDY_CHAIR
References: