ADOPT: Improving Diagnosis of Pulmonary Hypertension With AI and Echo (ADOPT)

April 11, 2024 updated by: Royal United Hospitals Bath NHS Foundation Trust

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.

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.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

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 Type

Observational

Enrollment (Estimated)

2500

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

  • United Kingdom
      • Bath, United Kingdom, BA1 3NG
        • Recruiting
        • Royal United Hospitals Bath NHS Foundation Trust
        • Contact:

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Non-Probability Sample

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.

Description

Inclusion Criteria:

  • Patients aged ≥18
  • Have undergone a transthoracic echo and right heart catheter as part of their routine clinical care.

Exclusion Criteria:

  • 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).

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Mild pre-capillary PH
Right heart catheterisation (performed as part of usual care) diagnoses pulmonary hypertension and categorises it as mild and pre-capillary.
Diagnostic test: Artificial intelligence tool for transthoracic echocardiography
Pre-defined cohorts will be used to train the artificial intelligence tool for transthoracic echocardiography to improve the diagnosis of PH on TTE.
Moderate pre-capillary PH
Right heart catheterisation (performed as part of usual care) diagnoses pulmonary hypertension and categorises it as moderate and pre-capillary.
Diagnostic test: Artificial intelligence tool for transthoracic echocardiography
Pre-defined cohorts will be used to train the artificial intelligence tool for transthoracic echocardiography to improve the diagnosis of PH on TTE.
Severe pre-capillary PH
Right heart catheterisation (performed as part of usual care) diagnoses pulmonary hypertension and categorises it as severe and pre-capillary.
Diagnostic test: Artificial intelligence tool for transthoracic echocardiography
Pre-defined cohorts will be used to train the artificial intelligence tool for transthoracic echocardiography to improve the diagnosis of PH on TTE.
Post capillary PH
Right heart catheterisation (performed as part of usual care) diagnoses pulmonary hypertension and categorises it as post-capillary.
Diagnostic test: Artificial intelligence tool for transthoracic echocardiography
Pre-defined cohorts will be used to train the artificial intelligence tool for transthoracic echocardiography to improve the diagnosis of PH on TTE.
No PH
Right heart catheterisation (performed as part of usual care) demonstrates normal pulmonary pressures (i.e. no evidence of pulmonary hypertension).
Diagnostic test: Artificial intelligence tool for transthoracic echocardiography
Pre-defined cohorts will be used to train the artificial intelligence tool for transthoracic echocardiography to improve the diagnosis of PH on TTE.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
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.
Month 24
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.
Month 24
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.
Month 24
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.
Month 24
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.
Month 24
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
Month 24

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
The novel artificial intelligence tool (AIT) is able to assess the severity of pulmonary hypertension (PH)
Time Frame: Month 24
Measure the proportion of patients tested where the AIT accurately diagnoses PH severity
Month 24
The artificial intelligence tool (AIT) is able to predict mortality
Time Frame: Month 24
Measure the proportion of patients where the AIT correctly predicted risk of PH-related mortality
Month 24

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Royal United Hospitals Bath NHS Foundation Trust

Collaborators

Janssen Research & Development, LLC
Sheffield Teaching Hospitals NHS Foundation Trust
Royal Free Hospital NHS Foundation Trust
Royal Papworth Hospital NHS Foundation Trust
NHS Golden Jubilee National Hospital Glasgow

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

December 1, 2023

Primary Completion (Estimated)

December 1, 2025

Study Completion (Estimated)

December 1, 2025

Study Registration Dates

First Submitted

September 7, 2023

First Submitted That Met QC Criteria

November 16, 2023

First Posted (Actual)

November 24, 2023

Study Record Updates

Last Update Posted (Actual)

April 12, 2024

Last Update Submitted That Met QC Criteria

April 11, 2024

Last Verified

August 1, 2023

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • RUH Bath - ADOPT

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

UNDECIDED

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

Clinical Trials on Pulmonary Hypertension

Clinical Trials on Artificial intelligence tool for transthoracic echocardiography

Search Similar Trials

Sponsors and Collaborators

Medical Conditions

Drug Interventions

CROs by country

CROs in Norway

Conditions

Rare Diseases

Drug Interventions

Dietary Supplements

Sponsor/Collaborators

Locations

3
Subscribe