DigitHeart Echo Study

NCT07558109 | Recruiting

• 2 other identifiers: DigitHeart-SHDHKWC/HKU IRB
• Study Type: observational
• Target: 478
• Locations: 1 country
• Sites: 1

Brief Summary

Eligible patients will be interviewed by research staff to explain the trial design and rationale. Written informed consent will be obtained from patients who voluntarily agree to participate. Demographics and medical history will be obtained. A 12-lead ECG will be performed; it has not been performed within 6 months. A photo of the 12-lead ECG will be taken by research staff using the DigitHeart-2 smartphone application. Predictions from DigitHeart-2/MERL-ECHO and other machine learning models hosted by the investigator team for each of the target anatomical and mechanical properties will be recorded. The cardiologist in charge of the patient, who is blinded to the prediction results from DigitHeart-2/MERL-ECHO, will perform echocardiography according to American Society of Echocardiography guidelines, which will serve as the gold standard for accuracy evaluation.

Conditions

Heart Disease; Electrocardiograph; Echocardiography

Outcome Measures

Primary Outcomes (1)

• Model's Accuracy in predicting key echocardiographic parameters

  The primary outcome is the accuracy of the integrated DigitHeart- 2/MERL-ECHO system in predicting key echocardiographic parameters from smartphone-captured ECG images, as measured by AUROC and F1 scores.

  Day 1

Secondary Outcomes (1)

• Model's Accuracy in predicting other key anatomical and mechanical properties

  Day 1

Study Arms (1)

Smartphone-Captured ECG Cohort

12-lead ECG will be performed if it has not been performed within 6 month. Photo of the 12-lead ECG will be taken by research staff using DigitHeart-2 smartphone application. Prediction from DigitHeart-2/MERL-ECHO and other machine learning model(s) hosted by the investigator team for each of the target anatomical and mechanical properties will be recorded. Cardiologist in-charge of the patient, who is blinded to the prediction results from DigitHeart-2/MERL-ECHO, will perform echocardiography according to American Society of Echocardiography guidelines, which serve as gold standard for accuracy evaluation.

Diagnostic Test: echocardiography

Interventions

echocardiography DIAGNOSTIC_TEST

Participants will undergo an echocardiography to determine their cardiac structure, heart function and valve function. The gold-standard measurement from the echocardiography text report will be the reference for validating the multi-modal prediction.

Smartphone-Captured ECG Cohort

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Adult patients aged ≥ 18 years old who fulfill recruitment criteria will be recruited from Queen Mary Hospital and Tung Wah Hospital, Hong Kong.

You may qualify if:

• aged ≥ 18 years old
• planned to have echocardiography performed
• voluntarily agree to participate in the trial.

You may not qualify if:

• had echocardiography performed within 1 month
• pacemaker rhythm on ECG
• dextrocardia
• complex adult congenital heart disease
• ventricular assist device implantation.

Sponsors & Collaborators

• The University of Hong Kong: lead

Study Sites (1)

Department of Medicine Queen Marry Hospital, Hong Kong

Hong Kong, Hong Kong

RECRUITING

Related Publications (1)

• Wong CK, Lau YM, Lui HW, Chan WF, San WC, Zhou M, Cheng Y, Huang D, Lai WH, Lau YM, Siu CW. Automatic detection of cardiac conditions from photos of electrocardiogram captured by smartphones. Heart. 2024 Aug 14;110(17):1074-1082. doi: 10.1136/heartjnl-2023-323822.

  PMID: 38768982 RESULT

MeSH Terms

Conditions

Heart Diseases

Interventions

Echocardiography

Condition Hierarchy (Ancestors)

Cardiovascular Diseases

Intervention Hierarchy (Ancestors)

Cardiac Imaging Techniques; Diagnostic Imaging; Diagnostic Techniques and Procedures; Diagnosis; Ultrasonography; Heart Function Tests; Diagnostic Techniques, Cardiovascular

Central Study Contacts

Chun Ka Dr Wong, Clinical Assistant Professor

CONTACT

+852-22553111; wongeck@hku.hk

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: PROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Clinical Assistant Professor

Study Record Dates

• First Submitted: March 26, 2025
• First Posted: April 30, 2026
• Study Start: February 14, 2025
• Primary Completion (Estimated): February 14, 2027
• Study Completion (Estimated): February 14, 2027
• Last Updated: April 30, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will not share

Locations

HK (1)