Trial · NCT07901907
Monitoring and Early Detection of Treatable Inherited RETinal Disease in Children and Adolescents
NCT07901907, Recruiting, University College, London
3 sourcestrials-2026-11-12-0.5.0
Cite this record
ConductScience Library. Monitoring and Early Detection of Treatable Inherited RETinal Disease in Children and Adolescents. Trials, record NCT07901907. Release trials-2026-11-12-0.5.0, 12 Nov 2026. https://conductscience.org/library/trials/NCT07901907
On this page
Trial
As registered on ClinicalTrials.gov, in the graph's capture of the registry.
- Title
- Monitoring and Early Detection of Treatable Inherited RETinal Disease in Children and Adolescents
- NCT number
- NCT07901907
- Status
- Recruiting
- Enrollment
- 4,887 participants, estimated
- Lead sponsor
- University College, London
- Conditions
- Inherited Retinal Degeneration Associated With RPGR Mutations, Inherited Retinal Degeneration Associated With Biallelic RPE65 Mutations
- First posted
- 2026-10-28
- Last updated
- 2026-10-28
Source ClinicalTrials.gov
Registered outcomes4
Each outcome the trial registered, primary first, in ClinicalTrials.gov's words.
| List | Outcome | Time frame | Description |
|---|---|---|---|
| Primary | Performance of an Artificial Intelligence (AI) algorithm for the diagnosis of Inherited Retinal Degeneration Associated With Biallelic RPE65- mutations using Ultra-Wide field retinal imaging | Up to approximately 1 year after study completion. | The primary outcome will be the performance of the artificial intelligence algorithm for the diagnosis of RPE65- associated retinal degeneration using wide-field color/ pseudocolor fundus images acquired with Optos and Clarus and fundus autofluorescence images acquired from Clarus and Heidelberg engineering imaging systems. Performance will be evaluated on an independent held-out test dataset using standard classification metrics, including sensitivity (recall), specificity, precision (positive predictive value), negative predictive value, accuracy, F1 score, and area under the receiver operating characteristic curve (AUROC). |
| Primary | Performance of an Artificial Intelligence (AI) algorithm for the diagnosis of Inherited Retinal Degeneration Associated With RPGR- mutations using Ultra-Wide field retinal imaging | Up to approximately 1 year after study completion. | The primary outcome will be the performance of the artificial intelligence algorithm for the diagnosis of RPGR- associated retinal degeneration using wide-field color/ pseudocolor fundus images acquired with Optos and Clarus and fundus autofluorescence images acquired from Clarus and Heidelberg engineering imaging systems. Performance will be evaluated on an independent held-out test dataset using standard classification metrics, including sensitivity (recall), specificity, precision (positive predictive value), negative predictive value, accuracy, F1 score, and area under the receiver operating characteristic curve (AUROC). |
| Primary | Performance of an Artificial Intelligence (AI) algorithm for quantification and longitudinal monitoring of Inherited Retinal Degeneration Associated With Biallelic RPE65- Mutations. | Up to approximately 1 year after study completion. | The performance of an AI algorithm will be evaluated for the detection, segmentation, and quantitative assessment of panretinal pathological features (before and after therapy) associated with biallelic RPE65-related retinal degeneration using wide-field color/ pseudocolor fundus images acquired with Optos and Clarus and fundus autofluorescence images acquired from Clarus and Heidelberg engineering imaging systems. Algorithm performance will be assessed using predefined metrics including sensitivity (recall), specificity, precision, negative predictive value, accuracy, F1 score, Dice similarity coefficient, and area under the receiver operating characteristic curve (AUROC), as applicable. |
| Primary | Performance of an Artificial Intelligence (AI) algorithm for quantification and longitudinal monitoring of Inherited Retinal Degeneration Associated With RPGR- Mutations. | Up to approximately 1 year after study completion. | The performance of an AI algorithm will be evaluated for the detection, segmentation, and quantitative assessment of panretinal pathological features associated with RPGR-related retinal degeneration using wide-field color/ pseudocolor fundus images acquired with Optos and Clarus and fundus autofluorescence images acquired from Clarus and Heidelberg engineering imaging systems. Algorithm performance will be assessed using predefined metrics including sensitivity (recall), specificity, precision, negative predictive value, accuracy, F1 score, Dice similarity coefficient, and area under the receiver operating characteristic curve (AUROC), as applicable. |
Source ClinicalTrials.gov
Outcomes0
Each outcome the trial posted results for, in ClinicalTrials.gov's words.
None in this release.
Results by group0
Each measurement the trial posted, group by group, in the words and numbers it posted.
None in this release.
Participant flow0
How many started, completed or left each group, period by period.
None in this release.
Adverse events0
Each adverse event the trial posted, group by group: the participants affected out of those at risk.
None in this release.
Adverse event totals0
The totals the trial posted for each group.
None in this release.
Papers8
The papers the trial lists on ClinicalTrials.gov.
Grants0
The grants NIH RePORTER links to the trial, newest funded first: NIH's, and some of AHRQ's, CDC's, FDA's and VA's. Each shows its title, principal investigators, organization and funder in its newest year.
None in this release.
Trial comparisons0
Comparisons of the trial's two groups, calculated by ConductScience from the counts it posted.
None in this release.
Tests0
The ConductCognition tests this trial's registered outcomes name, as ScienceGraph matched them in trial-tests-2026-11-12-0.2.1.
None in this release.
Data dates
The day each source was copied for this release.
Sources 3
- ClinicalTrials.gov's posted results, through CTTI's AACTFreely available. Acknowledgement requested
- ClinicalTrials.govNo license stated
- NIH RePORTER's clinical studies and project filesPublic domain
Each source's terms
- ClinicalTrials.gov's posted results, through CTTI's AACTClinicalTrials.gov data via Aggregate Analysis of ClinicalTrials.gov (AACT), CTTI. CTTI makes its materials freely available and requests acknowledgement. https://aact.ctti-clinicaltrials.org/documentation/299
- ClinicalTrials.govnone stated
- NIH RePORTER's clinical studies and project filesPublic domain (NIH RePORTER)
ClinicalTrials.gov's data carry an international copyright outside the United States: https://clinicaltrials.gov/about-site/terms-conditions.
For software
Read this trial from software.
The record and each of its lists are JSON, twenty rows a page. No key.
GET https://conductscience.org/api/trials/v1/NCT07901907
GET https://conductscience.org/api/trials/v1/NCT07901907/registered