3D-reconstructionNCT05058599
Reconstruction Technology to Auxiliary Diagnosis and Guarantee Patient Privacy
An observational study of 3D-reconstruction and Patient Privacy, run by Sun Yat-sen University at 1 site in China.
Trial summary
Medical data that contain facial images are particularly sensitive as they retain important personal biometric identity, privacy protection. We developed a novel technology called "Digital Mask" (DM), based on real-time three-dimensional (3D) reconstruction and deep learning algorithm, to extract disease-relevant… Read more about this study
- Who is it for?
- Any ageHealthy volunteers can take part
- Conditions the study is for
- 3D-reconstruction, Patient Privacy, Deep Learning
- What is being tested?
- DM
- How many people
- 400 participants
- Where
- 1 siteChina
- Study dates
- 10 May 2020to 30 Jan 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 Any age
- All sexes
- Healthy volunteers accepted
- Child, Adult, Older adult
Study population: Outpatients from strabismus departments, paediatric ophthalmology departments, TAO departments, and ophthalmic plastic departments.
Who may be able to join
- The quality of facial images should be clinically acceptable.
Who cannot join
None listed.
Trial locations and contacts
1 site in 1 country.
China1 site, 1 recruiting
- Recruiting
Zhongshan Ophthalmic Center
Guangzhou, Guangdong, 510000
Haotian Lin, +86-020-87330274, gddlht@aliyun.com
About this study
Official title: Using a Reconstruction Technology With Facial Pathological Features to Auxiliary Diagnosis and Guarantee Patient Privacy
Medical data that contain facial images are particularly sensitive as they retain important personal biometric identity, privacy protection. We developed a novel technology called "Digital Mask" (DM), based on real-time three-dimensional (3D) reconstruction and deep learning algorithm, to extract disease-relevant features but remove patient identifiable features from facial images of patients.
- Conditions
- 3D-reconstruction, Patient Privacy, Deep Learning, Digital Medicine
- Being tested
- DM
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
DMDiagnostic test
A new technology based on 3D reconstruction and deep learning algorithm to irreversibly erase the biometric attributes whilst retaining the clinical attributes needed for diagnosis and management
| Study group | Role | What they receive |
|---|---|---|
| facial videos dataset | facial videos collected from Zhongshan Ophthalmic Center of Sun Yat-sen University. Receives: Diagnostic Test: DM |
What is being measured
The primary outcome is the main question the study is designed to answer.
Diagnostic consistency
For each eye, both the diagnosis from the original videos and the diagnosis from the DM-reconstructed videos were recorded and compared. If the two diagnoses were consistent, it suggests that the reconstruction would be precise enough in clinical practice.
Measured: baseline
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted28 Sep 2021
- Study start10 May 2020
- Primary completion20 Sep 2021 (estimated)
- Study completion30 Jan 2022 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for 3D-reconstructionStudies of the same condition, open and under way.
- More trials run by Sun Yat-sen UniversityThe 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
- 400 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Sun Yat-sen University
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Haotian Lin, Sun Yat-sen University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05058599
- Sponsor's protocol ID
- 2021KYPJ77
- Status last verified
- Sep 2021
- First submitted
- 16 Sep 2021
- Last updated
- 28 Sep 2021
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Study at a glance
From the registry record, last updated by the sponsor on 28 Sep 2021. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Using a Reconstruction Technology With Facial Pathological Features to Auxiliary Diagnosis and Guarantee Patient Privacy
- ClinicalTrials.gov ID
- NCT05058599
- Acronym / sponsor ID
- 2021KYPJ77
- Conditions
- 3D-reconstruction, Patient Privacy, Deep Learning, Digital Medicine
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 400 participants (estimated)
- Lead sponsor
- Sun Yat-sen UniversityUniversity, hospital or other
- Study start
- 10 May 2020 (actual)
- Primary completion
- 20 Sep 2021 (estimated)
- Study completion
- 30 Jan 2022 (estimated)
- First posted
- 28 Sep 2021 (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.
Medical data that contain facial images are particularly sensitive as they retain important personal biometric identity, privacy protection. We developed a novel technology called "Digital Mask" (DM), based on real-time three-dimensional (3D) reconstruction and deep learning algorithm, to extract disease-relevant features but remove patient identifiable features from facial images of patients.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| facial videos dataset | – | Diagnostic Test: DMfacial videos collected from Zhongshan Ophthalmic Center of Sun Yat-sen University. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Child, Adult, Older adult
- Study population
- Outpatients from strabismus departments, paediatric ophthalmology departments, TAO departments, and ophthalmic plastic departments.
Key inclusion criteria (1 listed)
- The quality of facial images should be clinically acceptable.
Key exclusion criteria (0 listed)
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 |
|---|---|---|
| DMA new technology based on 3D reconstruction and deep learning algorithm to irreversibly erase the biometric attributes whilst retaining the clinical attributes needed for diagnosis and management | Diagnostic test | facial videos dataset |
Primary outcome
Diagnostic consistency
Time frame: baseline
For each eye, both the diagnosis from the original videos and the diagnosis from the DM-reconstructed videos were recorded and compared. If the two diagnoses were consistent, it suggests that the reconstruction would be precise enough in clinical practice.
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 28 Sep 2021.
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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.
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 3D-reconstruction and Patient Privacy, run by Sun Yat-sen University 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 1 inclusion and 0 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 28 Sep 2021. 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?
Contact Haotian Lin (13802793086, gddlht@aliyun.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Diagnostic consistency (time frame: baseline). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
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 28 Sep 2021.