Automated detection of Polypoidal Choroidal Vasculopathy in spectral domain optical coherence tomography using deep learning algorithm

Status

Recruiting

Phases

Unknown

Study type

Observational

Source

TCTR

Registry ID

TCTR20200814007

Enrollment

500

Registered

2020-08-14

Start date

2020-05-20

Completion date

Unknown

Last updated

2026-08-03

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

patients whose diagnosed polypoidal choroidal vasculopathy PCV&#44

Interventions

normal macular OCT from normal subjects,abnormal macular OCT from patients whose diagnosed polypoidal choroidal vasculopathy&#44

confirmed by FFA+ICGA investigation

Diagnostic,Diagnostic

normal ,polypoidal choroidal vasculopathy

Eligibility

Sex/Gender

All

Age

18 Years to No maximum

Inclusion criteria

Inclusion criteria: patients diagnosed as PCV who came to outpatient department in Siriraj hospital

Exclusion criteria

Exclusion criteria: Poor quality fundus photo from diabetes patient Inconclusive clinical diagnosis

Design outcomes

Primary

Measure	Time frame
accuracy of automated algorithm for detection polypoidal choroidal vasculopathy by macular OCT at the time of investigation sensitivity, specificity, precision, accuracy	—

Secondary

Measure	Time frame
Program validation at the end of investigation accuracy	—

Contacts

Public ContactNida Wongchaisuwat

Faculty of Medicine Siriraj Hospital, Mahidol University

nida.oph@gmail.com0875952336

Outcome results

None listed

Source: TCTR (via WHO ICTRP) · Data processed: Aug 9, 2026