Artificial Intelligence: Improving Early Detection of Pulmonary Hypertension by Transthoracic Echocardiography: ADOPT
Trial ID: NCT06145880
Status: WITHDRAWN
Study type: OBSERVATIONAL
Start date: 2023-12-01
Completion date: 2025-12-01
Sponsor: Royal United Hospitals Bath NHS Foundation Trust
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
Conditions: Pulmonary Hypertension
Interventions: Artificial intelligence tool for transthoracic echocardiography
Locations: Royal United Hospitals Bath NHS Foundation Trust
Countries: United Kingdom
Enrollment: 0
Age range: 18 Years - None
Sex: ALL

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. 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.

Eligibility criteria:
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).

Outcomes:
Detect patients with pulmonary hypertension (PH) with the novel artificial intelligence tool (AIT); Detect patients without pulmonary hypertension (PH) with the novel artificial intelligence tool (AIT); Detect patients with pre-capillary pulmonary hypertension (PH) with the novel artificial intelligence tool (AIT); Detect patients with post-capillary pulmonary hypertension (PH) with the novel artificial intelligence tool (AIT); Compare the artificial intelligence tool (AIT) performance for detecting pulmonary hypertension (PH) with the current probability criteria; Evaluate early detection capabilities of the artificial intelligence tool (AIT) compared to standard of care clinical diagnosis