Neovascular Age-related Macular DegenerationNCT05208931
Development of an Optimal Algorithm for the Management of Patients With Retinal Pigment Epithelium Detachment in Neovascular Age-related Macular Degeneration Using Artificial Intelligence
An observational study of Neovascular Age-related Macular Degeneration, run by The S.N. Fyodorov Eye Microsurgery State Institution at 1 site in Russia.
Trial summary
The study involves the development of an algorithm for predicting anatomical and functional results of therapy with angiogenesis inhibitors in patients with retinal pigment epithelium detachments in neovascular age-related macular degeneration, based on primary optical coherence tomography of the macular zone and… Read more about this study
- Who is it for?
- Ages 18 to 80 yearsHealthy volunteers can take part
- Conditions the study is for
- Neovascular Age-related Macular Degeneration
- What is being tested?
- Anti-vascular endothelial growth factor therapy
- Type of treatment
- Surgery or procedure
- How many people
- 300 participants
- Where
- 1 siteRussia
- Study dates
- 1 Nov 2021to 1 Sep 2022
- 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 to 80 years
- All sexes
- Healthy volunteers accepted
- Adult, Older adult
Study population: Patients with retinal pigment epithelium detachments with age-related neovascular macular degeneration
Who may be able to join
- Linear B - scan through the macular area with the longest detachment
- Other pathologies
Who cannot join
- Images without detachment
- Images on which it is possible to diagnose the need for therapy only in the presence of additional factors not considered in the study.
Trial locations and contacts
1 site in 1 country.
Russia1 site
The S.N. Fyodorov Eye Microsurgery State Institution
Krasnodar, 350012
About this study
Official title: Development of an Algorithm for Predicting Anatomical and Functional the Results of Therapy With Angiogenesis Inhibitors in Patients With Retinal Pigment Epithelium Detachments in Neovascular Age-related Macular Degeneration, Based on Primary Optical Coherence Tomography of the Macular Zone and Clinical Data.
The study involves the development of an algorithm for predicting anatomical and functional results of therapy with angiogenesis inhibitors in patients with retinal pigment epithelium detachments in neovascular age-related macular degeneration, based on primary optical coherence tomography of the macular zone and clinical data.
Read the detailed description
Patients were divided into 3 groups according to the results of therapy: adhesion of detachment, lack of adherence to detachment, rupture of detachment. For these groups, OCT images of the macular zone with maximum detachment before therapy are selected. These images, along with other clinical parameters, are input to the algorithm. The result is one of the 3 treatment outcomes listed above. The methods that will be used to develop the algorithm include methods for processing and transforming data, deep machine learning, metrics for calculating the accuracy of algorithms.
- Being tested
- Anti-vascular endothelial growth factor therapy
- Keywords
- Machine learning, Artificial intelligence, anti-VEGF therapy, AMD
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Anti-vascular endothelial growth factor therapyProcedure or surgery
Also called anti-VEGF
0.05 ml anti-VEGF, intravitreal, monthly
| Study group | Role | What they receive |
|---|---|---|
| adhesion | the group in which the adhesion of neuroepithelial detachment was observed after Anti-vascular endothelial growth factor therapy Receives: Procedure: Anti-vascular endothelial growth factor therapy | |
| no adhesion | group in which there was no adherence of neuroepithelial detachment after Anti-vascular endothelial growth factor therapy Receives: Procedure: Anti-vascular endothelial growth factor therapy | |
| разрыв | group in which neuroepithelial detachment rupture was observed after anti-vascular endothelial growth factor therapy Receives: Procedure: Anti-vascular endothelial growth factor therapy |
What is being measured
The primary outcome is the main question the study is designed to answer.
Prediction algorithm
Neural network classifier
Measured: 1.09.2022
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Jan 2022
- Study start1 Nov 2021
- Primary completion1 Sep 2022
- Study completion1 Sep 2022
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 Neovascular Age-related Macular DegenerationStudies of the same condition, open and under way.
- 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
- Case-control
- Time perspective
- Retrospective
- Enrolment
- 300 participants (actual)
Sponsor and investigators
- Lead sponsor
- The S.N. Fyodorov Eye Microsurgery State Institution
- Sponsor type
- Other government
- Responsible party
- Principal investigator, Viktoria Myasnikova, The S.N. Fyodorov Eye Microsurgery State Institution
- Investigators
- Viktoria Myasnikova, D.Med.Sc., Study director, Deputy Director for Research
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05208931
- Sponsor's protocol ID
- 1
- Status last verified
- Apr 2023
- First submitted
- 5 Jan 2022
- Last updated
- 13 Apr 2023
- Results posted
- No
- Data monitoring committee
- Yes
Publications
Rohm M, Tresp V, Muller M, Kern C, Manakov I, Weiss M, Sim DA, Priglinger S, Keane PA, Kortuem K. Predicting Visual Acuity by Using Machine Learning in Patients Treated for Neovascular Age-Related Macular Degeneration. Ophthalmology. 2018 Jul;125(7):1028-1036. doi: 10.1016/j.ophtha.2017.12.034. Epub 2018 Feb 14.
PubMed 29454659Prahs P, Radeck V, Mayer C, Cvetkov Y, Cvetkova N, Helbig H, Marker D. OCT-based deep learning algorithm for the evaluation of treatment indication with anti-vascular endothelial growth factor medications. Graefes Arch Clin Exp Ophthalmol. 2018 Jan;256(1):91-98. doi: 10.1007/s00417-017-3839-y. Epub 2017 Nov 10.
PubMed 29127485Schmidt-Erfurth U, Bogunovic H, Sadeghipour A, Schlegl T, Langs G, Gerendas BS, Osborne A, Waldstein SM. Machine Learning to Analyze the Prognostic Value of Current Imaging Biomarkers in Neovascular Age-Related Macular Degeneration. Ophthalmol Retina. 2018 Jan;2(1):24-30. doi: 10.1016/j.oret.2017.03.015. Epub 2017 May 31.
PubMed 31047298Bogunovic H, Montuoro A, Baratsits M, Karantonis MG, Waldstein SM, Schlanitz F, Schmidt-Erfurth U. Machine Learning of the Progression of Intermediate Age-Related Macular Degeneration Based on OCT Imaging. Invest Ophthalmol Vis Sci. 2017 May 1;58(6):BIO141-BIO150. doi: 10.1167/iovs.17-21789.
PubMed 28658477Schmidt-Erfurth U, Waldstein SM, Klimscha S, Sadeghipour A, Hu X, Gerendas BS, Osborne A, Bogunovic H. Prediction of Individual Disease Conversion in Early AMD Using Artificial Intelligence. Invest Ophthalmol Vis Sci. 2018 Jul 2;59(8):3199-3208. doi: 10.1167/iovs.18-24106.
PubMed 29971444Kozina, E. V., S. N. Sakhnov, V. V. Myasnikova, E. V. Bykova, and L. E. Aksenova. 2021. 'Modern Trends in Diagnostics and Prediction of Results of Anti-Vascular Endothelial Growth Factor Therapy of Pigment Epithelial Detachment in Neovascular Agerelated Macular Degeneration Using Deep Machine Learning Method (Literature Review)'. Acta Biomedica Scientifica 6 (6-1): 190-203. https://doi.org/10.29413/ABS.2021-6.6-1.22.
Study at a glance
From the registry record, last updated by the sponsor on 13 Apr 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Development of an Algorithm for Predicting Anatomical and Functional the Results of Therapy With Angiogenesis Inhibitors in Patients With Retinal Pigment Epithelium Detachments in Neovascular Age-related Macular Degeneration, Based on Primary Optical Coherence Tomography of the Macular Zone and Clinical Data.
- ClinicalTrials.gov ID
- NCT05208931
- Acronym / sponsor ID
- 1
- Keywords
- Machine learning, Artificial intelligence, anti-VEGF therapy, AMD
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 300 participants (actual)
- Lead sponsor
- The S.N. Fyodorov Eye Microsurgery State InstitutionOther government
- Study start
- 1 Nov 2021 (actual)
- Primary completion
- 1 Sep 2022 (actual)
- Study completion
- 1 Sep 2022 (actual)
- First posted
- 26 Jan 2022 (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.
The study involves the development of an algorithm for predicting anatomical and functional results of therapy with angiogenesis inhibitors in patients with retinal pigment epithelium detachments in neovascular age-related macular degeneration, based on primary optical coherence tomography of the macular zone and clinical data.
Detailed description
Patients were divided into 3 groups according to the results of therapy: adhesion of detachment, lack of adherence to detachment, rupture of detachment. For these groups, OCT images of the macular zone with maximum detachment before therapy are selected. These images, along with other clinical parameters, are input to the algorithm. The result is one of the 3 treatment outcomes listed above. The methods that will be used to develop the algorithm include methods for processing and transforming data, deep machine learning, metrics for calculating the accuracy of algorithms.
Study design
- Observational model
- Case-control
- Time perspective
- Retrospective
- Number of arms
- 3
| Arm | Type | Receives |
|---|---|---|
| adhesion | – | Procedure: Anti-vascular endothelial growth factor therapythe group in which the adhesion of neuroepithelial detachment was observed after Anti-vascular endothelial growth factor therapy |
| no adhesion | – | Procedure: Anti-vascular endothelial growth factor therapygroup in which there was no adherence of neuroepithelial detachment after Anti-vascular endothelial growth factor therapy |
| разрыв | – | Procedure: Anti-vascular endothelial growth factor therapygroup in which neuroepithelial detachment rupture was observed after anti-vascular endothelial growth factor therapy |
Who may qualify
- Ages
- 18 to 80 years
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Patients with retinal pigment epithelium detachments with age-related neovascular macular degeneration
Key inclusion criteria (2 listed)
- Linear B - scan through the macular area with the longest detachment
- Other pathologies
Key exclusion criteria (2 listed)
- Images without detachment
- Images on which it is possible to diagnose the need for therapy only in the presence of additional factors not considered in the study.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Anti-vascular endothelial growth factor therapyAlso: anti-VEGF0.05 ml anti-VEGF, intravitreal, monthly | Procedure or surgery | adhesion, no adhesion, разрыв |
Primary outcome
Prediction algorithm
Time frame: 1.09.2022
Neural network classifier
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 13 Apr 2023.
- Background: PubMed 29454659Rohm M, Tresp V, Muller M, Kern C, Manakov I, Weiss M, Sim DA, Priglinger S, Keane PA, Kortuem K. Predicting Visual Acuity by Using Machine Learning in Patients Treated for Neovascular Age-Related Macular Degeneration. Ophthalmology. 2018 Jul;125(7):1028-1036. doi: 10.1016/j.ophtha.2017.12.034. Epub 2018 Feb 14.
- Background: PubMed 29127485Prahs P, Radeck V, Mayer C, Cvetkov Y, Cvetkova N, Helbig H, Marker D. OCT-based deep learning algorithm for the evaluation of treatment indication with anti-vascular endothelial growth factor medications. Graefes Arch Clin Exp Ophthalmol. 2018 Jan;256(1):91-98. doi: 10.1007/s00417-017-3839-y. Epub 2017 Nov 10.
- Background: PubMed 31047298Schmidt-Erfurth U, Bogunovic H, Sadeghipour A, Schlegl T, Langs G, Gerendas BS, Osborne A, Waldstein SM. Machine Learning to Analyze the Prognostic Value of Current Imaging Biomarkers in Neovascular Age-Related Macular Degeneration. Ophthalmol Retina. 2018 Jan;2(1):24-30. doi: 10.1016/j.oret.2017.03.015. Epub 2017 May 31.
- Background: PubMed 28658477Bogunovic H, Montuoro A, Baratsits M, Karantonis MG, Waldstein SM, Schlanitz F, Schmidt-Erfurth U. Machine Learning of the Progression of Intermediate Age-Related Macular Degeneration Based on OCT Imaging. Invest Ophthalmol Vis Sci. 2017 May 1;58(6):BIO141-BIO150. doi: 10.1167/iovs.17-21789.
- Background: PubMed 29971444Schmidt-Erfurth U, Waldstein SM, Klimscha S, Sadeghipour A, Hu X, Gerendas BS, Osborne A, Bogunovic H. Prediction of Individual Disease Conversion in Early AMD Using Artificial Intelligence. Invest Ophthalmol Vis Sci. 2018 Jul 2;59(8):3199-3208. doi: 10.1167/iovs.18-24106.
- BackgroundKozina, E. V., S. N. Sakhnov, V. V. Myasnikova, E. V. Bykova, and L. E. Aksenova. 2021. 'Modern Trends in Diagnostics and Prediction of Results of Anti-Vascular Endothelial Growth Factor Therapy of Pigment Epithelial Detachment in Neovascular Agerelated Macular Degeneration Using Deep Machine Learning Method (Literature Review)'. Acta Biomedica Scientifica 6 (6-1): 190-203. https://doi.org/10.29413/ABS.2021-6.6-1.22.
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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.
Viktoria Myasnikova, D.Med.Sc. study director
Deputy Director for Research
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 Neovascular Age-related Macular Degeneration, run by The S.N. Fyodorov Eye Microsurgery State Institution at 1 site in Russia.
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 2 inclusion and 2 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: finished, as of the sponsor's last update on 13 Apr 2023. 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 Russia. 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?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
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?
Prediction algorithm (time frame: 1.09.2022). 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 NCT05208931, 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 13 Apr 2023.