| CTRI Number |
CTRI/2025/10/095888 [Registered on: 10/10/2025] Trial Registered Prospectively |
| Last Modified On: |
08/10/2025 |
| Post Graduate Thesis |
No |
| Type of Trial |
Observational |
|
Type of Study
|
retrospective |
| Study Design |
Other |
|
Public Title of Study
|
Accuracy of AI versus Opthalmologist in detecting Diabetic Retinopathy from fundus images |
|
Scientific Title of Study
|
Comparison of the DRISTi -Artificial Intelligence System with Ophthalmologist
grading for Detection of Diabetic Retinopathy from fundus images. |
| Trial Acronym |
NIL |
|
Secondary IDs if Any
|
| Secondary ID |
Identifier |
| nil |
NIL |
|
|
Details of Principal Investigator or overall Trial Coordinator (multi-center study)
|
| Name |
jyothsna rajagopal |
| Designation |
Medical Head |
| Affiliation |
ARTELUS-Artificial Learning Systems India Private Limited, |
| Address |
No. 1665/A, II Floor, 14th Main Road, HSR Layout Sector 7, Bengaluru,
No. 1665/A, II Floor, 14th Main Road, HSR Layout Sector 7, Bengaluru, 560102
Bangalore
KARNATAKA
560102
India |
| Phone |
9980949289 |
| Fax |
|
| Email |
j.rajagopal@artelus.ai |
|
Details of Contact Person
Scientific Query
|
| Name |
jyothsna rajagopal |
| Designation |
Medical Head |
| Affiliation |
ARTELUS-Artificial Learning Systems India Private Limited, |
| Address |
No. 1665/A, II Floor, 14th Main Road, HSR Layout Sector 7, Bengaluru,
No. 1665/A, II Floor, 14th Main Road, HSR Layout Sector 7, Bengaluru, 560102
Bangalore
KARNATAKA
560102
India |
| Phone |
9980949289 |
| Fax |
|
| Email |
j.rajagopal@artelus.ai |
|
Details of Contact Person
Public Query
|
| Name |
jyothsna rajagopal |
| Designation |
Medical Head |
| Affiliation |
ARTELUS-Artificial Learning Systems India Private Limited, |
| Address |
No. 1665/A, II Floor, 14th Main Road, HSR Layout Sector 7, Bengaluru,
No. 1665/A, II Floor, 14th Main Road, HSR Layout Sector 7, Bengaluru, 560102
Bangalore
KARNATAKA
560102
India |
| Phone |
9980949289 |
| Fax |
|
| Email |
j.rajagopal@artelus.ai |
|
|
Source of Monetary or Material Support
|
| ARTELUS-Artificial Learning Systems India Private Limited, No. 1665/A, II Floor, 14th Main Road, HSR Layout Sector 7, Bengaluru, INDIA-560102 |
|
|
Primary Sponsor
|
| Name |
none |
| Address |
NIl |
| Type of Sponsor |
Other [med tech company] |
|
|
Details of Secondary Sponsor
|
|
|
Countries of Recruitment
|
India |
|
Sites of Study
|
| No of Sites = 1 |
| Name of Principal
Investigator |
Name of Site |
Site Address |
Phone/Fax/Email |
| jyothsna rajagopal |
ARTELUS-Artificial Learning Systems India Private Limited |
No. 1665/A, II Floor, 14th Main
Road, HSR Layout Sector 7, Bengaluru, INDIA-560102
Bangalore
KARNATAKA |
09980949289
j.rajagopal@artelus.ai |
|
|
Details of Ethics Committee
|
| No of Ethics Committees= 1 |
| Name of Committee |
Approval Status |
| ACE Independent Ethics Committee, |
Approved |
|
|
Regulatory Clearance Status from DCGI
|
|
|
Health Condition / Problems Studied
|
| Health Type |
Condition |
| Patients |
(1) ICD-10 Condition: H350||Background retinopathy and retinalvascular changes, |
|
|
Intervention / Comparator Agent
|
| Type |
Name |
Details |
| Intervention |
Nil |
Nil |
|
|
Inclusion Criteria
|
| Age From |
18.00 Year(s) |
| Age To |
80.00 Year(s) |
| Gender |
Both |
| Details |
patients presenting for DR screening collected from multiple secondary and tertiary eye care hospitals and community screening site |
|
| ExclusionCriteria |
| Details |
patients attending hospital for reasons other than DR screening |
|
|
Method of Generating Random Sequence
|
Not Applicable |
|
Method of Concealment
|
Not Applicable |
|
Blinding/Masking
|
Not Applicable |
|
Primary Outcome
|
| Outcome |
TimePoints |
| The primary outcome is the sensitivity and specificity of the AI system in detecting eyes with mtmDR or vtDR, compared to the reference standard |
NA |
|
|
Secondary Outcome
|
| Outcome |
TimePoints |
The primary outcome is the sensitivity and specificity of the AI system in detecting eyes with mtmDR or vtDR, compared to the reference standard. The secondary outcomes include the sensitivity and specificity of the AI system in identifying eyes with DME relative to the reference standard.
|
NA |
|
|
Target Sample Size
|
Total Sample Size="760"
Sample Size from India="760"
Final Enrollment numbers achieved (Total)= "Applicable only for Completed/Terminated trials"
Final Enrollment numbers achieved (India)="Applicable only for Completed/Terminated trials" |
|
Phase of Trial
|
N/A |
|
Date of First Enrollment (India)
|
22/10/2025 |
| Date of Study Completion (India) |
Applicable only for Completed/Terminated trials |
| Date of First Enrollment (Global) |
Date Missing |
| Date of Study Completion (Global) |
Applicable only for Completed/Terminated trials |
|
Estimated Duration of Trial
|
Years="0"
Months="0"
Days="7" |
|
Recruitment Status of Trial (Global)
|
Not Applicable |
| Recruitment Status of Trial (India) |
Not Yet Recruiting |
|
Publication Details
|
N/A |
|
Individual Participant Data (IPD) Sharing Statement
|
Will individual participant data (IPD) be shared publicly (including data dictionaries)?
Response - YES
- What data in particular will be shared?
Response (Others) - fundus images
- What additional supporting information will be shared?
Response - Study Protocol
Response - Statistical Analysis Plan
- Who will be able to view these files?
Response - Researchers whose proposed use of the data has been approved by an independent review committee identiļ¬ed for this purpose.
- For what types of analyses will this data be available?
Response - To achieve aims in the approved proposal.
- By what mechanism will data be made available?
Response - Proposals should be directed to [j.rajagopal@artelus.ai].
- For how long will this data be available start date provided 02-01-1970 and end date provided 02-01-1970?
Response - Beginning 3 months and ending 5 years following article publication.
- Any URL or additional information regarding plan/policy for sharing IPD?
Additional Information - NIL
|
|
Brief Summary
|
India currently has 101 million people with diabetes, expected to rise to 134 million by 2045. Diabetic retinopathy affects about 35 percent of people with diabetes for over five years. Due to limited eye care access and few ophthalmologists, only a small percentage of diabetics receive regular screening. AI-based tools like DRISTi can help scale DR detection. This study aims to compare the diagnostic performance of Artificial Intelligence System with that of expert ophthalmologists.
To compare the sensitivity and specificity of DRISTi in detecting mtmDR and vtDR from fundus images versus ophthalmologist grading. Retrospective observational study to be done over Three months for data collection, analysis, and reporting.
800 images in total Single-field images from different non-mydriatic cameras (Crystal Vue, Zeiss, Canon, Topcon) . Data will be de-identified with secure storage and Ophthalmologist will be blinded to AI results.
Metrics calculated at the eye level with 95 percent confidence intervals and Subgroup analysis by camera and for DME . |