Clinical trial NCT05471986: Multicenter Diagnostic Clinical Performance Study For Automated Detection of Diabetic Retinopathy
Official title: Multicenter Diagnostic Clinical Performance Study For Automated Detection of Diabetic Retinopathy
Study type: OBSERVATIONAL
Overall status: NOT_YET_RECRUITING
Conditions: Diabetic Retinopathy
Keywords: Diabetic Retinopathy
Artificial Intelligence
Deep Learning
Retinal images
Diabetic Macular Edema
Diabetic Eye Problems
Lead sponsor: Ural Telekomunikasyon Sanayi Ticaret Anonim Sirketi
Sponsor class: INDUSTRY
First posted: 2022-07-25
Enrollment: 900
Sex: ALL
Minimum age (years): 22
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_ONLY
Time perspective: RETROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Diabetic Patients of 22 years or older

Brief summary: This study is a retrospective study to assess the efficacy and accuracy of the EyeCheckup software in screening for diabetic retinopathy in healthcare settings.

Detailed description: This is a clinical diagnostic performance study for EyeCheckup with data obtained consecutively at multiple geographically different sites within the US population. These sites include all healthcare settings with a trained ophthalmic camera operator using non-mydriatic cameras that are compatible with EyeCheckup. Moreover, primary endpoints are devised that will be used to validate EyeCheckup to diagnose DR in the primary care and eye care settings. During this color fundus images representing either 4 wide field or 7 standard fields of view will be graded by a qualified professional for diabetic retinopathy according to ETDRS on DRSS scale. The human grading output will be compared with diagnosis generated for diabetic retinopathy by AI software. A comparison of both these grades will be used to determine sensitivity and specificity for the EyeCheckup software for screening for diabetic retinopathy.

Eligibility criteria: Inclusion Criteria:

* A diagnosis of either diabetes type 1 or diabetes type 2
* 22 years of age or older
* Patients Fundus images must include at least 1 macula centered and 1 optic disc nerve centered image
* All the subjects must be sequentially photographed meaning no omissions of data between a certain time frame by the sites providing images to ensure consecutive selection
* No history of any other retinal vascular disease, glaucoma, or another disease that may affect the appearance of the retina or optic disc (refractive error and ocular surface disease are allowed)

Subject with image taken by color fundus photography that meets the following requirements:

* The resolution of image is 1024×1024 pixels or higher
* The ability to provide a 7 standard or 4 wide field of view
* Must obtained from either Topcon NW400 or Cannon Model CR-2 AF or CR-2 Plus AF or Optomed Aurora Cameras along with the following data: their age, ethnicity and gender, patient ocular history as evaluated of verified by the clinical sites where data is obtained

Exclusion Criteria:

* No diagnosis of either diabetes type 1 or diabetes type 2
* The macula, optic nerve, or other part in the image of color fundus photography is unclear to determine the disease condition as judged by the certified ophthalmologist who is grading the images.

Primary outcomes:
measure: Sensitivity and Specificity of EyeCheckup to detect more than mild diabetic retinopathy
timeFrame: 1 visit (1 day)
measure: Sensitivity and Specificity of EyeCheckup to detect vision-threatening diabetic retinopathy
timeFrame: 1 visit (1 day)
Secondary outcomes:
measure: Positive Predictive Value
timeFrame: 1 visit (1 day)
measure: Negative Predictive Value
timeFrame: 1 visit (1 day)
Other outcomes:
Locations:
Study officials:
affiliation: Ural Telekom
name: Rim Khazhin
role: STUDY_CHAIR
References: