Diagnostic Accuracy of a Deep Learning-Based Software for Automated Multiparametric Echocardiographic Measurements (PANECHO)

July 27, 2026 updated by: Centro Cardiologico Monzino

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)

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.

Study Overview

Status

Recruiting

Conditions

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 Type

Observational

Enrollment (Estimated)

1157

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 Locations

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

Consecutive adult patients undergoing clinically indicated standard transthoracic echocardiography at seven high-volume echocardiography laboratories with experienced operators.

Description

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.

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
Prospective Cohort
Consecutive adult patients referred for clinically indicated standard transthoracic echocardiography at seven high-volume echocardiography laboratories will be enrolled. Echocardiographic examinations will be performed according to routine clinical practice by experienced operators. Standard two-dimensional, Doppler, and other clinically indicated measurements required for the diagnostic report will be obtained manually by expert echocardiographers and automatically by the artificial intelligence software (US2.AI). No additional study-specific imaging procedures or follow-up visits are planned.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
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.
January 2027
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.
Jan 2027
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.
January 2027

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Agreement between AI-assisted and expert final echocardiographic diagnoses
Time Frame: January 2027
Agreement between the final echocardiographic diagnosis suggested by the US2.AI software and the final diagnosis reported by the expert echocardiographer.
January 2027

Collaborators and Investigators

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

Sponsor

Centro Cardiologico Monzino

Collaborators

Universita di Verona
Azienda Ospedaliera Universitaria Policlinico "G. Martino"
ASST Grande Ospedale Metropolitano Niguarda
Monaldi Hospital, Napoli, Italy
Azienda Ospedaliero Universitaria Policlinico Modena
Ospedale San Giovanni Evangelista Tivoli

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)

April 27, 2026

Primary Completion (Estimated)

January 31, 2027

Study Completion (Estimated)

January 31, 2027

Study Registration Dates

First Submitted

July 27, 2026

First Submitted That Met QC Criteria

July 27, 2026

First Posted (Actual)

July 31, 2026

Study Record Updates

Last Update Posted (Actual)

July 31, 2026

Last Update Submitted That Met QC Criteria

July 27, 2026

Last Verified

July 1, 2026

More Information

Terms related to this study

Other Study ID Numbers

  • L2-309

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.

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