Intracranial Pressure IncreaseSVP-MLNCT05731765
SVP Detection Using Machine Learning
An observational study of Intracranial Pressure Increase, run by King's College London at 1 site in United Kingdom.
Trial summary
This diagnostic study will use 410 retrospectively captured fundal videos to develop ML systems that detect SVPs and quantify ICP. The ground truth will be generated from the annotations of two independent, masked clinicians, with arbitration by an ophthalmology consultant in cases of disagreement. Read more about this study
- Who is it for?
- Ages 18 years and olderHealthy volunteers can take part
- Conditions the study is for
- Intracranial Pressure Increase
- What is being tested?
- Machine Learning Model
- How many people
- 210 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 1 Mar 2023to Nov 2024
- 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
- Healthy volunteers accepted
- Adult, Older adult
Study population: Patients aged ≥18 years with presumed normal ICP or suspected raised ICP
Who may be able to join
- Patients aged ≥18 years with presumed normal ICP undergoing routine dilated OCT scans.
- Patients undergoing a LP or continuous ICP monitoring with implanted transcranial pressure transducer devices at in- or out-patient neurology, neurosurgery or neuro-ophthalmology services.
Who cannot join
- Glaucoma diagnosis or glaucoma suspects in either eye.
- Bilateral restricted fundal view, e.g. advanced bilateral cataracts.
- Bilateral retinal vein or artery occlusion.
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Automated Detection of Spontaneous Venous Pulsations Within Fundal Videos Using Machine Learning
This diagnostic study will use 410 retrospectively captured fundal videos to develop ML systems that detect SVPs and quantify ICP. The ground truth will be generated from the annotations of two independent, masked clinicians, with arbitration by an ophthalmology consultant in cases of disagreement.
- Conditions
- Intracranial Pressure Increase
- Being tested
- Machine Learning Model
- Medical subject headings
- Intracranial Hypertension
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Machine Learning ModelDiagnostic test
Automated machine learning system for the detection of spontaneous venous pulsations and quantification of intracranial pressure
| Study group | Role | What they receive |
|---|---|---|
| Patients aged ≥18 years with presumed normal intracranial pressure | Not described Receives: Diagnostic Test: Machine Learning Model | |
| Patients aged ≥18 years with suspected raised intracranial pressure | Not described Receives: Diagnostic Test: Machine Learning Model |
What is being measured
The primary outcome is the main question the study is designed to answer.
Area-under-the receiver operating characteristic (AUROC) for spontaneous venous pulsations detection
Binary classification performance of the machine learning model
Measured: 1 year
Secondary outcomes (2)
Localisation of spontaneous venous pulsations
Bounding box overlap for the machine learning model
Measured: 1 year
Quantification of intracranial pressure
Mean absolute error for the prediction of the intracranial pressure
Measured: 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted16 Feb 2023
- Study start1 Mar 2023
- Primary completionNov 2024 (estimated)
- Study completionNov 2024 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Intracranial Pressure IncreaseStudies 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
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 210 participants (estimated)
Sponsor and investigators
- Lead sponsor
- King's College London
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05731765
- Sponsor's protocol ID
- 1.0
- Acronym
- SVP-ML
- Status last verified
- Mar 2024
- First submitted
- 30 Jan 2023
- Last updated
- 6 Mar 2024
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: The data would be shared, where possible, through a restricted-access data sharing agreement, where in line with KCL data governance requirements.
Study at a glance
From the registry record, last updated by the sponsor on 6 Mar 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Automated Detection of Spontaneous Venous Pulsations Within Fundal Videos Using Machine Learning
- ClinicalTrials.gov ID
- NCT05731765
- Acronym / sponsor ID
- SVP-ML / 1.0
- Conditions
- Intracranial Pressure Increase
- Study type
- Observational
- Recruitment status
- Unknown status
- Enrolment
- 210 participants (estimated)
- Lead sponsor
- King's College LondonUniversity, hospital or other
- Study start
- 1 Mar 2023 (actual)
- Primary completion
- Nov 2024 (estimated)
- Study completion
- Nov 2024 (estimated)
- First posted
- 16 Feb 2023 (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 diagnostic study will use 410 retrospectively captured fundal videos to develop ML systems that detect SVPs and quantify ICP. The ground truth will be generated from the annotations of two independent, masked clinicians, with arbitration by an ophthalmology consultant in cases of disagreement.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Patients aged ≥18 years with presumed normal intracranial pressure | – | Diagnostic Test: Machine Learning Model |
| Patients aged ≥18 years with suspected raised intracranial pressure | – | Diagnostic Test: Machine Learning Model |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Accepted
- Age groups
- Adult, Older adult
- Study population
- Patients aged ≥18 years with presumed normal ICP or suspected raised ICP
Key inclusion criteria (2 listed)
- Patients aged ≥18 years with presumed normal ICP undergoing routine dilated OCT scans.
- Patients undergoing a LP or continuous ICP monitoring with implanted transcranial pressure transducer devices at in- or out-patient neurology, neurosurgery or neuro-ophthalmology services.
Key exclusion criteria (3 listed)
- Glaucoma diagnosis or glaucoma suspects in either eye.
- Bilateral restricted fundal view, e.g. advanced bilateral cataracts.
- Bilateral retinal vein or artery occlusion.
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 |
|---|---|---|
| Machine Learning ModelAutomated machine learning system for the detection of spontaneous venous pulsations and quantification of intracranial pressure | Diagnostic test | Patients aged ≥18 years with presumed normal intracranial pressure, Patients aged ≥18 years with suspected raised intracranial pressure |
Primary outcome
Area-under-the receiver operating characteristic (AUROC) for spontaneous venous pulsations detection
Time frame: 1 year
Binary classification performance of the machine learning model
2 secondary outcomes
Localisation of spontaneous venous pulsations
Time frame: 1 year
Quantification of intracranial pressure
Time frame: 1 year
Results and safety
Results are not available in the source record.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 Mar 2024.
- Individual participant dataSharing planned: Yes. The data would be shared, where possible, through a restricted-access data sharing agreement, where in line with KCL data governance requirements.
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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.
The record lists no contact. Use the official record to reach the sponsor.
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 Intracranial Pressure Increase, run by King's College London at 1 site in United Kingdom.
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 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 6 Mar 2024. 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 United Kingdom. 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?
Area-under-the receiver operating characteristic (AUROC) for spontaneous venous pulsations detection (time frame: 1 year). 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 6 Mar 2024.