PANECHO: Diagnostic Accuracy of a Deep Learning-Based Artificial Intelligence Software Developed for Automated Multiparametric Echocardiographic Measurements From Echocardiographic Video Images: A Multicenter Study of the Italian Society of Echocardiography and Cardiovascular Imaging (SIECVI)
Trial Snapshot
- Phase
- Not Applicable
- Status
- Recruiting
- Sponsor
- Enrollment
- 1,157
- Locations
- 1
- Primary Endpoint
- Agreement between AI-derived and expert-derived echocardiographic measurements across predefined patient subgroups
Study Overview
Brief Summary
Transthoracic echocardiography is an essential imaging modality for the diagnosis and follow-up of cardiovascular diseases. Comprehensive echocardiographic assessment requires multiple quantitative measurements of cardiac structure and function, which are time-consuming and highly dependent on operator expertise. US2.AI (Us2.v1) is an artificial intelligence (deep learning)-based software designed to automatically analyze standard two-dimensional and Doppler echocardiographic DICOM video clips acquired from different ultrasound vendors. The software provides automated measurements of cardiac morphology and function, including chamber dimensions and volumes, left and right ventricular systolic and diastolic function, myocardial strain, and Doppler-derived parameters, generating a comprehensive echocardiographic report based on current international guideline recommendations. In addition, the software may assist in identifying echocardiographic features suggestive of several cardiovascular conditions, including heart failure, pulmonary hypertension, hypertrophic cardiomyopathy, cardiac amyloidosis, valvular heart disease, and ischemic cardiomyopathy.
Detailed Description
This is a non profit, prospective, multicenter observational study aimed at evaluating the diagnostic accuracy of the US2.AI software by comparing its automated echocardiographic measurements with measurements performed by experienced echocardiographers, considered the reference standard.
The study will assess the agreement between automated and expert-derived measurements and determine the reliability of the software in routine clinical practice. Demonstrating high diagnostic accuracy may support the use of artificial intelligence to standardize echocardiographic measurements and facilitate comprehensive image analysis, particularly in settings where advanced analysis tools or highly experienced operators are not readily available.
Study Design
- Study Type
- Observational
- Observational Model
- Cohort
- Time Perspective
- Prospective
Eligibility Criteria
- Ages
- 18 Years to — (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- •Adults aged 18 years or older.
- •Undergoing clinically indicated standard transthoracic echocardiography.
- •Adequate echocardiographic image quality for automated and expert analysis.
- •Written informed consent provided prior to study participation.
Exclusion Criteria
- •Age <18 years.
- •Frequent and/or complex cardiac arrhythmias during echocardiographic examination.
- •Suboptimal echocardiographic images.
Outcomes
Primary Outcomes
Agreement between AI-derived and expert-derived echocardiographic measurements across predefined patient subgroups
Time Frame: January 2027
Comparison of the agreement between automated and expert-derived measurements in predefined subgroups, including participants with normal echocardiographic findings and those with specific cardiovascular diseases.
Agreement between AI-derived and expert-derived echocardiographic measurements
Time Frame: Jan 2027
Agreement between automated echocardiographic measurements generated by the US2.AI software and manual measurements performed by experienced echocardiographers (reference standard) across standard two-dimensional, Doppler, and strain parameters.
Time required for echocardiographic analysis
Time Frame: January 2027
Comparison of the time required to obtain a complete set of echocardiographic measurements using manual analysis by experienced echocardiographers versus automated analysis by the US2.AI software.
Secondary Outcomes
- Agreement between AI-assisted and expert final echocardiographic diagnoses(January 2027)