Deep Learning-Based Automated Pressure-Strain Loop Analysis

September 24, 2026 updated by: Norwegian University of Science and Technology

Noninvasive left ventricular pressure-strain loop analysis estimates myocardial work from longitudinal strain, brachial systolic blood pressure, and cardiac valve-event timing. It provides global work index, constructive work, wasted work, and work efficiency.

This study evaluates a deep-learning method that automates myocardial work and loop-shape analysis. The method may reduce analysis time, improve reproducibility, and identify patterns associated with heart failure.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Study Type

Interventional

Enrollment (Estimated)

25

Phase

  • Not Applicable

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

  • Name: Håvard Dalen, Professor Havard Dalen, MD, Ph
  • Phone Number: +4772828027
  • Email: havard.dalen@ntnu.no

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

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Description

Inclusion Criteria:

Heart failure participants:

  • Age ≥18 years
  • Able to provide informed consent
  • Previous myocardial infarction
  • Left ventricular ejection fraction ≤40% after myocardial infarction

Healthy volunteers:

  • Age ≥18 years
  • Able to provide informed consent

Exclusion Criteria:

Heart failure participants:

  • Unstable disease
  • Contraindication to exercise testing or echocardiography, as judged by an experienced cardiologist

Healthy volunteers:

  • Hypertension
  • Diabetes mellitus
  • Dyslipidemia
  • Current smoking
  • Pregnancy
  • Significant systemic disease
  • Cardioactive medication affecting heart rate, myocardial contractility, or vascular tone
  • Echocardiographic findings suggesting structural heart disease

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

  • Primary Purpose: Basic Science
  • Allocation: Non-Randomized
  • Interventional Model: Parallel Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: Participants With Heart Failure

Participants undergo echocardiography at rest, during sustained handgrip, and during semi-supine bicycle exercise.

Participants perform sustained isometric handgrip at around 30 % of maximal voluntary contraction for 5 minutes during echocardiography.

Participants perform graded semi-supine bicycle exercise during echocardiography.

Experimental: Healthy Volunteers

Healthy volunteers undergo echocardiography at rest, during sustained handgrip, and during semi-supine bicycle exercise.

Participants perform sustained isometric handgrip at around 30 % of maximal voluntary contraction for 5 minutes during echocardiography.

Participants perform graded semi-supine bicycle exercise during echocardiography.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Echocardiographic Acquisition Success
Time Frame: During one study visit: at rest, during the handgrip and bicycle test.

Percentage of acquired examinations successfully processed by the deep-learning pipeline to generate myocardial work indices, assessed separately at rest, during handgrip, and during bicycle exercise.

During one study visit: at rest, during the handgrip and bicycle test.

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Agreement Between Deep Learning- and Expert-Derived Myocardial Work Indices
Time Frame: Echocardiograms acquired at rest and during handgrip and bicycle exercise at a single study visit.

Agreement for myocardial work indices will be assessed using mean bias with 95% limits of agreement, and mean absolute error.

Echocardiograms acquired at rest and during handgrip and bicycle exercise at a single study visit.

Collaborators and Investigators

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

Sponsor

Collaborators

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 (Estimated)

September 1, 2026

Primary Completion (Estimated)

May 1, 2027

Study Completion (Estimated)

May 1, 2027

Study Registration Dates

First Submitted

September 24, 2026

First Submitted That Met QC Criteria

September 24, 2026

First Posted (Actual)

September 30, 2026

Study Record Updates

Last Update Posted (Actual)

September 30, 2026

Last Update Submitted That Met QC Criteria

September 24, 2026

Last Verified

September 1, 2026

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 2019/1059_1

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

Individual participant data sharing is not currently planned. Any future sharing would require appropriate ethical, institutional, and data-protection approvals.

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.