Cardiovascular Acoustics and an Intelligent Stethoscope

Heart Valve Diseases Clinical Trial

— CAIS  

Official title:

Cardiovascular Acoustics and an Intelligent Stethoscope. An Observational Study to Collect Heart Sound Recordings From Patients to Understand the Acoustic Characteristics of Murmurs and Develop an Artificially Intelligent Stethoscope.

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04445012
• Other study ID #: P02087
• Status: Recruiting
• Start date: October 24, 2019
• Est. completion date: January 31, 2023

Study information

• Verified date: September 2021
• Source: Papworth Hospital NHS Foundation Trust
• Contact: Nicky Watson, MSc
• Phone: 01223639684
• Email: nicky.watson2[@]nhs.net
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

The aim of the project is to develop an artificial intelligence software capable of analysing heart sounds to provide early diagnosis of a variety heart diseases at an early stage. Since the invention of the stethoscope by Laennec in 1816, the basic design has not changed significantly. Our software could be coupled with existing electronic stethoscopes to create an 'intelligent' stethoscope that could be used by healthcare assistants or practice nurses to screen for sound producing heart diseases. It could also be used at home by patients who would otherwise go undiagnosed.

The study investigators at Cambridge University Engineering Department (CUED) have developed a proof-of-concept AI algorithm to detect heart murmurs. However, in order to accurately detect the specific pathology and severity underlying the murmur, more heart sound recordings (matched with the ground truth from the patient's echocardiogram) are required. Patients presenting to one of the partner hospitals requiring an echocardiogram as part of their routine care will be invited to consent to this study. Participation will entail recording of a patient's heart sounds using an electronic stethoscope as well as collection of routine clinical data and a routine clinical echocardiogram at a single routine out patient visit.

Description:

This project will develop an AI algorithm which can be imported into a stethoscope to make it capable of automatically diagnosing any valve disease present and its severity. This will help GPs produce more accurate diagnoses, reduce costs by having fewer unnecessary referrals for echocardiogram, and produce more accurate diagnoses in countries where echocardiograms are not readily available due to their cost. Using a small sample of data as well as some which has been labelled by clinician auscultation, the team has created an award-winning AI algorithm capable of accurate detection of heart murmurs. However, in order to improve the accuracy and capability of this system more heart sound recordings from a range of diseases (matched with echocardiogram diagnosis) are required. The key to the success of this study will be to produce an AI algorithm that is more accurate than different grades of doctors at detecting the specific abnormality and severity underlying a heart murmur. This methodology will also provide a comprehensive study on acoustic characteristics of different heart sounds. So far all the acoustic characteristics of heart sounds taught to medical students are based on subjective opinion. This study will be able to objectively analyse these acoustic characteristics.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 1150
• Est. completion date: January 31, 2023
• Est. primary completion date: March 30, 2022
• Accepts healthy volunteers: No
• Gender: All
• Age group: N/A and older

Eligibility

Inclusion Criteria:

• Participant willing and able to give informed consent for participation in study

• Participant to undergo an echocardiogram as part of their routine assessment

Exclusion Criteria:

• Informed consent is not given

• New York Heart Association (NYHA) functional class = 4

Related Conditions & MeSH terms

• Heart Valve Diseases

Locations

Country	Name	City	State
United Kingdom	University Hospitals Birmingham NHS Foundation Trust	Birmingham
United Kingdom	Royal Papworth Hospital NHS Foundation Trust	Cambridge
United Kingdom	Guy's and St Thomas' NHS Foundation Trust	London
United Kingdom	Imperial College Healthcare NHS Trust	London
United Kingdom	King's College Hospital NHS Foundation Trust	London

Sponsors (1)

Lead Sponsor	Collaborator
Papworth Hospital NHS Foundation Trust

Country where clinical trial is conducted

United Kingdom, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	To assess specificity of an algorithm for detecting clinically significant valve disease and congenital heart disease relative to the performance of General Practitioners	We will obtain 4, 15 second heart sound recordings from patients (at the Aortic, Pulmonary, Mitral, and Tricuspid sites) using a Littmann 3200 electronic stethoscope.	Day 1