Diabetic RetinopathyNCT03903042
Comparison of Aurora Fundus Camera With Traditional Camera in Diabetic Retinopathy With Visual Artificial Intelligence
An observational study of Diabetic Retinopathy, run by Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine at 1 site in China.
Trial summary
This study aims to compare the effect of Aurora handheld fundus camera with traditional desktop fundus camera in the fundus photography screening of diabetic patients, and to evaluate the effect of artificial intelligence algorithm in the diagnosis of diabetic retinopathy. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Diabetic Retinopathy
- How many people
- 300 participants
- Where
- 1 siteChina
- Study dates
- 1 Nov 2018to May 2019
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: Patients who were diagnosed with diabetes, more than 18 years of age, male or female Chinese patients.
Who may be able to join
- Participants are more than 18 years of age, male or female Chinese patients;
- Diagnosed with diabetes;
- Prior written informed consent should be obtained
Who cannot join
- Patients with invisible fundus caused by any cause;
- Patients or his/her licensor unwill to sign an informed consent or follow this protocol;
- Pregnant women
Trial locations and contacts
1 site in 1 country.
China1 site
Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
Shanghai, Shanghai Municipality, 200080
About this study
Official title: Comparison of Aurora Fundus Camera With Traditional Fundus Camera in Diabetic Retinopathy With Phoebus Visual Artificial Intelligence
This study aims to compare the effect of Aurora handheld fundus camera with traditional desktop fundus camera in the fundus photography screening of diabetic patients, and to evaluate the effect of artificial intelligence algorithm in the diagnosis of diabetic retinopathy.
Read the detailed description
Aurora handheld fundus cameras are used to take fundus photography on diabetic patients in 3 ophthalmic diabetic retinopathy screening centers in China to compare its effect with the hospital's traditional desktop fundus camera, and evaluate the auxiliary diagnostic effect of Phoebus artificial intelligence algorithm in diabetic retinopathy.
- Conditions
- Diabetic Retinopathy
- Keywords
- Aurora fundus camera, Artificial intelligence, Diabetic retinopathy
- Medical subject headings
- Diabetic Retinopathy
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Group 1 | Center 1: Traditional camera(Canon) vs Aurora camera | |
| Group 2 | Center 2: Traditional camera(Zeiss) vs Aurora camera | |
| Group 3 | Center 3: Traditional camera(Topcon) vs Aurora camera |
What is being measured
The primary outcome is the main question the study is designed to answer.
Image Quality of Aurora camera
Score of Image Quality
Measured: within 3 months
Secondary outcomes (6)
Outcome of gold standard
Gold standard: 8 photographs of one patient(4 by Aurora camera, 4 by traditional camera) by ophthalmologist（double blinded）
Measured: within 3 months
Image of Aurora camera
Images taken by Aurora camera
Measured: 1 month
Image of traditional camera (Center 1: Canon)
Image taken by traditional camera（Center 1: Canon, pupil not dilated）
Measured: 1 month
Image of traditional camera (Center 2: Zeiss)
Image taken by traditional camera（Center 2: Zeiss, pupil dilated）
Measured: 1 month
Image of traditional camera (Center 3: Topcon)
Image taken by traditional camera（Center 3: Topcon, pupil dilated）
Measured: 1 month
Outcome of artificial intelligence algorithm
Outcome of artificial intelligence algorithm(Normal or Referral Required)
Measured: 3 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted4 Apr 2019
- Study start1 Nov 2018
- Primary completionMay 2019 (estimated)
- Study completionMay 2019 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (6)Papers the sponsor has linked to this study.
- Other trials for Diabetic RetinopathyStudies of the same condition, open and under way.
- More trials run by Shanghai General Hospital, Shanghai Jiao Tong University School of MedicineThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 300 participants (estimated)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Fenghua Wang, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
- Investigators
- Fenghua Wang, Principal investigator, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03903042
- Sponsor's protocol ID
- Shanghai1stAI
- Status last verified
- Apr 2019
- First submitted
- 3 Apr 2019
- Last updated
- 4 Apr 2019
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Clinical Study Report will be published
Publications
Jin G, Xiao W, Ding X, Xu X, An L, Congdon N, Zhao J, He M. Prevalence of and Risk Factors for Diabetic Retinopathy in a Rural Chinese Population: The Yangxi Eye Study. Invest Ophthalmol Vis Sci. 2018 Oct 1;59(12):5067-5073. doi: 10.1167/iovs.18-24280.
PubMed 30357401Zheng X, Zhang L. A study of retinopathy analysis in type 2 diabetes patients in Chinese population. Pak J Pharm Sci. 2018 Sep;31(5(Supplementary)):2041-2046.
PubMed 30393210Hendrick AM, Gibson MV, Kulshreshtha A. Diabetic Retinopathy. Prim Care. 2015 Sep;42(3):451-64. doi: 10.1016/j.pop.2015.05.005.
PubMed 26319349Wong TY, Bressler NM. Artificial Intelligence With Deep Learning Technology Looks Into Diabetic Retinopathy Screening. JAMA. 2016 Dec 13;316(22):2366-2367. doi: 10.1001/jama.2016.17563. No abstract available.
PubMed 27898977Abramoff MD, Niemeijer M, Russell SR. Automated detection of diabetic retinopathy: barriers to translation into clinical practice. Expert Rev Med Devices. 2010 Mar;7(2):287-96. doi: 10.1586/erd.09.76.
PubMed 20214432Li Z, Keel S, Liu C, He Y, Meng W, Scheetz J, Lee PY, Shaw J, Ting D, Wong TY, Taylor H, Chang R, He M. An Automated Grading System for Detection of Vision-Threatening Referable Diabetic Retinopathy on the Basis of Color Fundus Photographs. Diabetes Care. 2018 Dec;41(12):2509-2516. doi: 10.2337/dc18-0147. Epub 2018 Oct 1.
PubMed 30275284
Study at a glance
From the registry record, last updated by the sponsor on 4 Apr 2019. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Comparison of Aurora Fundus Camera With Traditional Fundus Camera in Diabetic Retinopathy With Phoebus Visual Artificial Intelligence
- ClinicalTrials.gov ID
- NCT03903042
- Acronym / sponsor ID
- Shanghai1stAI
- Conditions
- Diabetic Retinopathy
- Keywords
- Aurora fundus camera, Artificial intelligence, Diabetic retinopathy
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 300 participants (estimated)
- Lead sponsor
- Shanghai General Hospital, Shanghai Jiao Tong University School of MedicineUniversity, hospital or other
- Study start
- 1 Nov 2018 (actual)
- Primary completion
- May 2019 (estimated)
- Study completion
- May 2019 (estimated)
- First posted
- 4 Apr 2019 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
This study aims to compare the effect of Aurora handheld fundus camera with traditional desktop fundus camera in the fundus photography screening of diabetic patients, and to evaluate the effect of artificial intelligence algorithm in the diagnosis of diabetic retinopathy.
Detailed description
Aurora handheld fundus cameras are used to take fundus photography on diabetic patients in 3 ophthalmic diabetic retinopathy screening centers in China to compare its effect with the hospital's traditional desktop fundus camera, and evaluate the auxiliary diagnostic effect of Phoebus artificial intelligence algorithm in diabetic retinopathy.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| Group 1 | – | –Center 1: Traditional camera(Canon) vs Aurora camera |
| Group 2 | – | –Center 2: Traditional camera(Zeiss) vs Aurora camera |
| Group 3 | – | –Center 3: Traditional camera(Topcon) vs Aurora camera |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients who were diagnosed with diabetes, more than 18 years of age, male or female Chinese patients.
Key inclusion criteria (3 listed)
- Participants are more than 18 years of age, male or female Chinese patients;
- Diagnosed with diabetes;
- Prior written informed consent should be obtained
Key exclusion criteria (3 listed)
- Patients with invisible fundus caused by any cause;
- Patients or his/her licensor unwill to sign an informed consent or follow this protocol;
- Pregnant women
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Image Quality of Aurora camera
Time frame: within 3 months
Score of Image Quality
6 secondary outcomes
Outcome of gold standard
Time frame: within 3 months
Image of Aurora camera
Time frame: 1 month
Image of traditional camera (Center 1: Canon)
Time frame: 1 month
Image of traditional camera (Center 2: Zeiss)
Time frame: 1 month
Image of traditional camera (Center 3: Topcon)
Time frame: 1 month
Outcome of artificial intelligence algorithm
Time frame: 3 months
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 4 Apr 2019.
- Background: PubMed 30357401Jin G, Xiao W, Ding X, Xu X, An L, Congdon N, Zhao J, He M. Prevalence of and Risk Factors for Diabetic Retinopathy in a Rural Chinese Population: The Yangxi Eye Study. Invest Ophthalmol Vis Sci. 2018 Oct 1;59(12):5067-5073. doi: 10.1167/iovs.18-24280.
- Background: PubMed 30393210Zheng X, Zhang L. A study of retinopathy analysis in type 2 diabetes patients in Chinese population. Pak J Pharm Sci. 2018 Sep;31(5(Supplementary)):2041-2046.
- Background: PubMed 26319349Hendrick AM, Gibson MV, Kulshreshtha A. Diabetic Retinopathy. Prim Care. 2015 Sep;42(3):451-64. doi: 10.1016/j.pop.2015.05.005.
- Background: PubMed 27898977Wong TY, Bressler NM. Artificial Intelligence With Deep Learning Technology Looks Into Diabetic Retinopathy Screening. JAMA. 2016 Dec 13;316(22):2366-2367. doi: 10.1001/jama.2016.17563. No abstract available.
- Background: PubMed 20214432Abramoff MD, Niemeijer M, Russell SR. Automated detection of diabetic retinopathy: barriers to translation into clinical practice. Expert Rev Med Devices. 2010 Mar;7(2):287-96. doi: 10.1586/erd.09.76.
- Background: PubMed 30275284Li Z, Keel S, Liu C, He Y, Meng W, Scheetz J, Lee PY, Shaw J, Ting D, Wong TY, Taylor H, Chang R, He M. An Automated Grading System for Detection of Vision-Threatening Referable Diabetic Retinopathy on the Basis of Color Fundus Photographs. Diabetes Care. 2018 Dec;41(12):2509-2516. doi: 10.2337/dc18-0147. Epub 2018 Oct 1.
- Individual participant dataSharing planned: Yes. Clinical Study Report will be published
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Fenghua Wang principal investigator
Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Diabetic Retinopathy, run by Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine at 1 site in China.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 3 inclusion and 3 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: status not confirmed, as of the sponsor's last update on 4 Apr 2019. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in China. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
Results are not available in the source record.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Image Quality of Aurora camera (time frame: within 3 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT03903042, which also lists 6 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 4 Apr 2019.