Pulmonary HypertensionADOPTNCT06145880
ADOPT: Improving Diagnosis of Pulmonary Hypertension With AI and Echo
An observational study of Pulmonary Hypertension, run by Royal United Hospitals Bath NHS Foundation Trust at 1 site in United Kingdom.
Trial summary
Pulmonary Hypertension (PH) is a condition caused by high blood pressure in the blood vessels that carry blood to the lungs. It can cause severe breathlessness and failure of the right side of the heart. Sadly it is often fatal, and life expectancy ranges from months to years. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Pulmonary Hypertension
- What is being tested?
- Artificial intelligence tool for transthoracic echocardiography
- How many people
- 0 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 1 Dec 2023to 1 Dec 2025
- 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 have undergone an assessment for potential pulmonary hypertension with both a transthoracic echocardiogram and a right heart catheter as part of their diagnostic work-up at one of the 5 collaborating UK centres.
Who may be able to join
- Patients aged ≥18
- Have undergone a transthoracic echo and right heart catheter as part of their routine clinical care.
Who cannot join
- Patients aged <18
- Known or suspected congenital heart disease
- Patient opted out of allowing their information to be used for research and planning (via the national data opt-out choice).
Trial locations and contacts
1 site in 1 country.
United Kingdom1 site
Royal United Hospitals Bath NHS Foundation Trust
Bath, BA1 3NG
About this study
Official title: Artificial Intelligence: Improving Early Detection of Pulmonary Hypertension by Transthoracic Echocardiography: ADOPT
Pulmonary Hypertension (PH) is a condition caused by high blood pressure in the blood vessels that carry blood to the lungs. It can cause severe breathlessness and failure of the right side of the heart. Sadly it is often fatal, and life expectancy ranges from months to years. For some subtypes of PH, effective treatments exist which can improve life expectancy and quality-of-life. Accurate tools for the assessment of PH are therefore essential so that life-saving medications can be started earlier.
In existing diagnostic pathways, evidence for the suspicion of PH is frequently overlooked, significantly delaying the time to diagnosis. Echocardiography (echo) is a quick, safe and well-tolerated test requested to investigate breathless patients, and which can provide useful information about the suspicion of PH. However, outside of specialist PH centres, doctors may not routinely look for and comment on the presence of clues to possible PH.
Read more
The investigators think that using Artificial Intelligence (AI) techniques to read echo's could make their interpretation faster and more reliable. There may also be subtle clues to the presence or severity of PH on echo, less recognisable to the human eye, which AI can identify.
In this study the investigators will gather echo images from 5 specialist PH hospitals across the UK which have all been anonymised (patient's name and personal details removed). These will all be historic scans (i.e. have already taken place) and will be grouped into those with PH present (including PH sub-type) or absent. These anonymised echo images will be used to develop and train an AI tool to identify scans where PH is present, including which specific type of PH may be present. The developed AI tool will then be tested on a separate group of scans (not used in the training stage) to validate its performance.
Read the detailed description
In this study the investigators will gather retrospective echo images from 5 specialist PH hospitals across the UK (Royal Free Hospital NHS FT; Sheffield Teaching Hospitals NHS FT; Royal Papworth Hospital NHS FT; NHS Golden Jubilee National Hospital Glasgow; Royal United Hospitals Bath NHS FT).
These will all be historic scans (i.e. have already taken place) and will be grouped into those with PH present (including PH sub-type) or PH absent. Inclusion criteria involve patients aged ≥18 who have undergone both a transthoracic echo (TTE) and a right heart catheter (RHC) as part of their clinical care. Exclusion Criteria will involve patients aged <18, known or suspected congenital heart disease and patients who have opted out of allowing their information to be used for research and planning (via the national data opt-out choice). A clinical case report form (CRF) will be used to capture patient demographics, clinical data with regards to the PH assessment including previous TTE results. Where available, mortality data will be recorded within 5 years of the RHC.
These anonymised echo images will be collated and labelled centrally in a core lab at the RUH Bath, who will work with Janssen to develop and train an AI tool to identify scans where PH is present, including which specific type of PH may be present.
AI tool training will be based on 5 groups (each group anticipated to contain 415 echocardiograms): mild pre-capillary PH; moderate pre-capillary PH; severe pre-capillary PH; post capillary PH; no PH. The tool will then be validated in a separate pool made up of 425 echocardiograms (a combination of pre-capillary, post capillary PH and no PH). The validation cohort will not have been used in the training stage.
- Conditions
- Pulmonary Hypertension
- Being tested
- Artificial intelligence tool for transthoracic echocardiography
- Keywords
- Echocardiography, Artificial intelligence
- Medical subject headings
- Hypertension, Pulmonary
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Artificial intelligence tool for transthoracic echocardiographyDiagnostic test
Pre-defined cohorts will be used to train the artificial intelligence tool for transthoracic echocardiography to improve the diagnosis of PH on TTE.
| Study group | Role | What they receive |
|---|---|---|
| Mild pre-capillary PH | Right heart catheterisation (performed as part of usual care) diagnoses pulmonary hypertension and categorises it as mild and pre-capillary. Receives: Diagnostic Test: Artificial intelligence tool for transthoracic echocardiography | |
| Moderate pre-capillary PH | Right heart catheterisation (performed as part of usual care) diagnoses pulmonary hypertension and categorises it as moderate and pre-capillary. Receives: Diagnostic Test: Artificial intelligence tool for transthoracic echocardiography | |
| Severe pre-capillary PH | Right heart catheterisation (performed as part of usual care) diagnoses pulmonary hypertension and categorises it as severe and pre-capillary. Receives: Diagnostic Test: Artificial intelligence tool for transthoracic echocardiography | |
| Post capillary PH | Right heart catheterisation (performed as part of usual care) diagnoses pulmonary hypertension and categorises it as post-capillary. Receives: Diagnostic Test: Artificial intelligence tool for transthoracic echocardiography | |
| No PH | Right heart catheterisation (performed as part of usual care) demonstrates normal pulmonary pressures (i.e. no evidence of pulmonary hypertension). Receives: Diagnostic Test: Artificial intelligence tool for transthoracic echocardiography |
What is being measured
The primary outcome is the main question the study is designed to answer.
Detect patients with pulmonary hypertension (PH) with the novel artificial intelligence tool (AIT)
Measure the proportion of patients the developed AIT correctly identifies as having PH.
Measured: Month 24
Detect patients without pulmonary hypertension (PH) with the novel artificial intelligence tool (AIT)
Measure the proportion of patients the developed AIT correctly identifies as not having PH.
Measured: Month 24
Detect patients with pre-capillary pulmonary hypertension (PH) with the novel artificial intelligence tool (AIT)
Measure the proportion of patients the developed AIT correctly identifies as having pre-capillary PH.
Measured: Month 24
Detect patients with post-capillary pulmonary hypertension (PH) with the novel artificial intelligence tool (AIT)
Measure the proportion of patients the developed AIT correctly identifies as having post-capillary PH.
Measured: Month 24
Compare the artificial intelligence tool (AIT) performance for detecting pulmonary hypertension (PH) with the current probability criteria
Compare the proportion of patients identified by the AI tool as having PH with the current guideline criteria for diagnosing PH from a TTE.
Measured: Month 24
Evaluate early detection capabilities of the artificial intelligence tool (AIT) compared to standard of care clinical diagnosis
Compare the proportion of patients identified by the AI tool as having PH with current standard clinical practice
Measured: Month 24
Secondary outcomes (2)
The novel artificial intelligence tool (AIT) is able to assess the severity of pulmonary hypertension (PH)
Measure the proportion of patients tested where the AIT accurately diagnoses PH severity
Measured: Month 24
The artificial intelligence tool (AIT) is able to predict mortality
Measure the proportion of patients where the AIT correctly predicted risk of PH-related mortality
Measured: Month 24
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Nov 2023
- Study start1 Dec 2023
- Primary completion1 Dec 2025 (estimated)
- Study completion1 Dec 2025 (estimated)
Why it stopped: The Commercial Funder withdrew the funding
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Pulmonary HypertensionStudies 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
- 0 participants (actual)
Sponsor and investigators
- Lead sponsor
- Royal United Hospitals Bath NHS Foundation Trust
- Sponsor type
- University, hospital or other
- Collaborators
- Janssen Research & Development, LLC, Royal Free Hospital NHS Foundation Trust, Sheffield Teaching Hospitals NHS Foundation Trust, Papworth Hospital NHS Foundation Trust, NHS Golden Jubilee National Hospital Glasgow
- Responsible party
- Sponsor
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06145880
- Sponsor's protocol ID
- RUH Bath - ADOPT
- Acronym
- ADOPT
- Status last verified
- Aug 2023
- First submitted
- 7 Sep 2023
- Last updated
- 22 Nov 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
Study at a glance
From the registry record, last updated by the sponsor on 22 Nov 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence: Improving Early Detection of Pulmonary Hypertension by Transthoracic Echocardiography: ADOPT
- ClinicalTrials.gov ID
- NCT06145880
- Acronym / sponsor ID
- ADOPT / RUH Bath - ADOPT
- Conditions
- Pulmonary Hypertension
- Keywords
- Echocardiography, Artificial intelligence
- Study type
- Observational
- Recruitment status
- WithdrawnReason stopped: The Commercial Funder withdrew the funding
- Enrolment
- 0 participants (actual)
- Lead sponsor
- Royal United Hospitals Bath NHS Foundation TrustUniversity, hospital or other
- Collaborators
- Janssen Research & Development, LLC, Royal Free Hospital NHS Foundation Trust, Sheffield Teaching Hospitals NHS Foundation Trust, Papworth Hospital NHS Foundation Trust, NHS Golden Jubilee National Hospital Glasgow
- Study start
- 1 Dec 2023 (actual)
- Primary completion
- 1 Dec 2025 (estimated)
- Study completion
- 1 Dec 2025 (estimated)
- First posted
- 24 Nov 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.
Pulmonary Hypertension (PH) is a condition caused by high blood pressure in the blood vessels that carry blood to the lungs. It can cause severe breathlessness and failure of the right side of the heart. Sadly it is often fatal, and life expectancy ranges from months to years. For some subtypes of PH, effective treatments exist which can improve life expectancy and quality-of-life. Accurate tools for the assessment of PH are therefore essential so that life-saving medications can be started earlier.
In existing diagnostic pathways, evidence for the suspicion of PH is frequently overlooked, significantly delaying the time to diagnosis. Echocardiography (echo) is a quick, safe and well-tolerated test requested to investigate breathless patients, and which can provide useful information about the suspicion of PH. However, outside of specialist PH centres, doctors may not routinely look for and comment on the presence of clues to possible PH.
The investigators think that using Artificial Intelligence (AI) techniques to read echo's could make their interpretation faster and more reliable. There may also be subtle clues to the presence or severity of PH on echo, less recognisable to the human eye, which AI can identify.
In this study the investigators will gather echo images from 5 specialist PH hospitals across the UK which have all been anonymised (patient's name and personal details removed). These will all be historic scans (i.e. have already taken place) and will be grouped into those with PH present (including PH sub-type) or absent. These anonymised echo images will be used to develop and train an AI tool to identify scans where PH is present, including which specific type of PH may be present. The developed AI tool will then be tested on a separate group of scans (not used in the training stage) to validate its performance.
Detailed description
In this study the investigators will gather retrospective echo images from 5 specialist PH hospitals across the UK (Royal Free Hospital NHS FT; Sheffield Teaching Hospitals NHS FT; Royal Papworth Hospital NHS FT; NHS Golden Jubilee National Hospital Glasgow; Royal United Hospitals Bath NHS FT).
These will all be historic scans (i.e. have already taken place) and will be grouped into those with PH present (including PH sub-type) or PH absent. Inclusion criteria involve patients aged ≥18 who have undergone both a transthoracic echo (TTE) and a right heart catheter (RHC) as part of their clinical care. Exclusion Criteria will involve patients aged <18, known or suspected congenital heart disease and patients who have opted out of allowing their information to be used for research and planning (via the national data opt-out choice). A clinical case report form (CRF) will be used to capture patient demographics, clinical data with regards to the PH assessment including previous TTE results. Where available, mortality data will be recorded within 5 years of the RHC.
These anonymised echo images will be collated and labelled centrally in a core lab at the RUH Bath, who will work with Janssen to develop and train an AI tool to identify scans where PH is present, including which specific type of PH may be present.
AI tool training will be based on 5 groups (each group anticipated to contain 415 echocardiograms): mild pre-capillary PH; moderate pre-capillary PH; severe pre-capillary PH; post capillary PH; no PH. The tool will then be validated in a separate pool made up of 425 echocardiograms (a combination of pre-capillary, post capillary PH and no PH). The validation cohort will not have been used in the training stage.
Study design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 5
| Arm | Type | Receives |
|---|---|---|
| Mild pre-capillary PH | – | Diagnostic Test: Artificial intelligence tool for transthoracic echocardiographyRight heart catheterisation (performed as part of usual care) diagnoses pulmonary hypertension and categorises it as mild and pre-capillary. |
| Moderate pre-capillary PH | – | Diagnostic Test: Artificial intelligence tool for transthoracic echocardiographyRight heart catheterisation (performed as part of usual care) diagnoses pulmonary hypertension and categorises it as moderate and pre-capillary. |
| Severe pre-capillary PH | – | Diagnostic Test: Artificial intelligence tool for transthoracic echocardiographyRight heart catheterisation (performed as part of usual care) diagnoses pulmonary hypertension and categorises it as severe and pre-capillary. |
| Post capillary PH | – | Diagnostic Test: Artificial intelligence tool for transthoracic echocardiographyRight heart catheterisation (performed as part of usual care) diagnoses pulmonary hypertension and categorises it as post-capillary. |
| No PH | – | Diagnostic Test: Artificial intelligence tool for transthoracic echocardiographyRight heart catheterisation (performed as part of usual care) demonstrates normal pulmonary pressures (i.e. no evidence of pulmonary hypertension). |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- Patients who have undergone an assessment for potential pulmonary hypertension with both a transthoracic echocardiogram and a right heart catheter as part of their diagnostic work-up at one of the 5 collaborating UK centres.
Key inclusion criteria (2 listed)
- Patients aged ≥18
- Have undergone a transthoracic echo and right heart catheter as part of their routine clinical care.
Key exclusion criteria (3 listed)
- Patients aged <18
- Known or suspected congenital heart disease
- Patient opted out of allowing their information to be used for research and planning (via the national data opt-out choice).
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 |
|---|---|---|
| Artificial intelligence tool for transthoracic echocardiographyPre-defined cohorts will be used to train the artificial intelligence tool for transthoracic echocardiography to improve the diagnosis of PH on TTE. | Diagnostic test | Mild pre-capillary PH, Moderate pre-capillary PH, No PH, Post capillary PH, Severe pre-capillary PH |
Primary outcome
Detect patients with pulmonary hypertension (PH) with the novel artificial intelligence tool (AIT)
Time frame: Month 24
Measure the proportion of patients the developed AIT correctly identifies as having PH.
Detect patients without pulmonary hypertension (PH) with the novel artificial intelligence tool (AIT)
Time frame: Month 24
Measure the proportion of patients the developed AIT correctly identifies as not having PH.
Detect patients with pre-capillary pulmonary hypertension (PH) with the novel artificial intelligence tool (AIT)
Time frame: Month 24
Measure the proportion of patients the developed AIT correctly identifies as having pre-capillary PH.
Detect patients with post-capillary pulmonary hypertension (PH) with the novel artificial intelligence tool (AIT)
Time frame: Month 24
Measure the proportion of patients the developed AIT correctly identifies as having post-capillary PH.
Compare the artificial intelligence tool (AIT) performance for detecting pulmonary hypertension (PH) with the current probability criteria
Time frame: Month 24
Compare the proportion of patients identified by the AI tool as having PH with the current guideline criteria for diagnosing PH from a TTE.
Evaluate early detection capabilities of the artificial intelligence tool (AIT) compared to standard of care clinical diagnosis
Time frame: Month 24
Compare the proportion of patients identified by the AI tool as having PH with current standard clinical practice
2 secondary outcomes
The novel artificial intelligence tool (AIT) is able to assess the severity of pulmonary hypertension (PH)
Time frame: Month 24
The artificial intelligence tool (AIT) is able to predict mortality
Time frame: Month 24
Results and safety
The study was withdrawn before enrolling participants, so there are no results.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 22 Nov 2024.
- Individual participant dataSharing planned: Undecided
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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 Pulmonary Hypertension, run by Royal United Hospitals Bath NHS Foundation Trust 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: withdrawn, as of the sponsor's last update on 22 Nov 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?
The study was withdrawn before enrolling participants, so there are no results.
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?
Detect patients with pulmonary hypertension (PH) with the novel artificial intelligence tool (AIT) (time frame: Month 24). The study lists 6 primary outcomes in all. 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 22 Nov 2024.