Myocardial Strain

by Circle Cardiovascular Imaging  · Based in Canada → — Improve Outcomes & Efficiency With AI-Powered Imaging
Cardiology Radiology

Contact for pricing
Regulatory Status Disclosed

Overview

Circle Cardiovascular Imaging’s flagship platform, cvi42, is a comprehensive cardiovascular imaging post-processing software designed to enhance the analysis of Cardiovascular Magnetic Resonance (CMR) and Cardiac Computed Tomography (CCT) images. The Myocardial Strain feature within cvi42 leverages AI-based analysis to quantify myocardial deformation, including longitudinal, circumferential, and radial strain. This advanced capability aids in the assessment of regional and global myocardial function, enabling the detection of subtle alterations in cardiac mechanics that may precede changes in ejection fraction. The platform provides best-in-class image reading and reporting tools for both quantitative and qualitative assessment, supporting clinical and research use with full DICOM and PACS connectivity.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • AI-based myocardial deformation analysis
  • Quantification of longitudinal, circumferential, and radial strain
  • Supports Cardiovascular Magnetic Resonance (CMR) imaging
  • Supports Cardiac Computed Tomography (CCT) imaging (CT Strain for research use only)
  • Semi-automated endocardial and epicardial contour delineation
  • Automated tracking of myocardial features throughout the cardiac cycle
  • Assessment of global and regional myocardial function
  • DICOM and PACS connectivity for seamless workflow integration
  • Provides strain rate, displacement, velocity, torsion, and torsion rate metrics
  • Comprehensive reporting tools

Use Cases

  • Early detection of subclinical myocardial dysfunction
  • Diagnosis and assessment of cardiomyopathies
  • Evaluation of heart failure with preserved ejection fraction (HFpEF)
  • Risk stratification in patients with coronary artery disease (CAD)
  • Patient selection for Cardiac Resynchronization Therapy (CRT)
  • Monitoring for anticancer therapy cardiotoxicity

What Physicians Need to Know

Echocardiography AI Features
Circle CVI integrates DiA Imaging Analysis' LVivo Toolbox, providing AI-based cardiac ultrasound solutions. LVivo Seamless automatically selects optimal cardiac ultrasound views and generates automated quantifications of left and right ventricles, extracting results to echo reports.
Cardiac CT/MRI Analysis
The cvi42 platform offers AI-driven myocardial strain analysis for both Cardiac CT (CT Strain, for research use only) and Cardiac MR. For CT, it pre-processes multi-phase volumetric studies to detect early signs of dysfunction and provides automated calculations of radial, circumferential, and longitudinal peak strain, strain rate, displacement, velocity, torsion, and torsion rate. For MR, it quantifies global and regional radial, circumferential, and longitudinal strain in 2D and 3D, with AI-based LV contour detection and calculation of various strain parameters. It also includes AI-driven left and right heart ventricle segmentations for cardiac CT function and AI-based ventricular contour detection for cardiac MR function.
Heart Failure Risk Prediction
Myocardial strain measurements from cardiac MRI, particularly right ventricular global longitudinal strain (RV GLS), demonstrate significant prognostic value in identifying individuals at risk of developing heart failure. Strain provides incremental value to ejection fraction in predicting adverse outcomes in chronic systolic heart failure. cvi42's Cardiac MR applications include Heart Failure.
Coronary Artery Assessment
cvi42 | Plaque provides AI-enabled, on-premise quantification of atherosclerotic burden from Cardiac CT, including automated coronary lumen and wall segmentation. It offers detailed assessment of calcified, non-calcified, and low-attenuation plaques, per-lesion and per-vessel plaque analysis, and remodeling index assessment to identify high-risk plaques. The platform also features AI-powered coronary artery centerline segmentation and automated detection of suspected coronary lesions (cvi42 | CORE CT Coronaries). Pericoronary Adipose Tissue (PCAT) analysis for cardiac CT studies is available for research use only to assess inflammation surrounding vasculature.
AHA/ACC Guideline Alignment
The tool supports standardized reporting with integrated CAD-RADS classification for coronary artery assessment. The AMA's update to a Category I CPT code for AI-enabled coronary plaque quantification signifies its recognition as standard clinical care in cardiovascular medicine, effective January 2026. The platform aims for standardized protocols and reports to support collaboration and guideline adherence.
Physician Tip

Leverage AI-driven myocardial strain analysis from both CT and MR to detect subtle functional abnormalities earlier than traditional ejection fraction measurements, particularly in conditions like heart failure. Utilize the comprehensive AI-automated coronary artery assessment tools, including plaque quantification and remodeling index, for precise risk stratification and personalized treatment planning for coronary artery disease. Integrate the AI-based echocardiography solutions for automated, reproducible quantification of left and right ventricular function and strain, streamlining echo workflows. Note that CT Strain and PCAT analysis are currently for research use only. Take advantage of the unified platform for consistent workflows across multiple modalities (MR, CT, Echo) to reduce diagnostic friction and improve efficiency.

cvi42 integrates seamlessly into existing CT workflows and is compatible with all major vendor systems. The platform offers integrations with GE Healthcare (AW workstation or AW Server) and Siemens Healthineers (syngo.via workstation). It supports enterprise-class interoperability with enhancements for hospital IT environments, including PowerScribe One Integration for automated transcription and advanced enterprise security with Single Sign-on (SSO) and Multi-factor Authentication (MFA) via Microsoft Entra. The solutions are vendor-neutral, running on any scanner, and can easily integrate into hospital and enterprise sites with various IT infrastructures.

Details

Category Cardiology AI, Radiology & Imaging AI
Pricing Contact for pricing — Not publicly disclosed; contact vendor for details
DeploymentOn-premise (server-client architecture, integrates with hospital PACS)
Compliance
BAA AvailableUnknown AI-estimated
HIPAA CompliantUnknown AI-estimated
FDA Status Yes AI-estimated

The cvi42 platform is FDA cleared. Specifically, the K232661 clearance on 12/07/2023 was for cvi42 | Plaque, an AI-enabled solution for coronary plaque analysis. The 'CT Strain' module is noted as being for research use only. CMR-based myocardial strain analysis using cvi42 is widely discussed in clinical research and is part of the FDA-cleared cvi42 platform.

Integrations
EHR Not specified
Specialties Cardiology, Radiology

What the Web Says

Myocardial Strain, particularly Global Longitudinal Strain (GLS), is a measure of cardiac muscle function that can identify global and regional abnormalities and differentiate types of cardiomyopathy. It is considered an earlier and more sensitive marker of myocardial disease and dysfunction than ejection fraction (LVEF), and it is predictive of cardiovascular adverse events. The technology is used with conventional imaging techniques like echocardiography and cardiac MRI, with Circle CVI offering AI-driven solutions for cardiac CT studies to detect subtle changes over time.

Overall: Mixed

Strengths

  • Earlier detection of myocardial dysfunction than LVEF.
  • Provides increased precision in cardiac assessment.
  • Identifies global and regional abnormalities in myocardial function.
  • Differentiates types of cardiomyopathy.
  • Predictive of cardiovascular adverse events.
  • Can be used to monitor cardiotoxicity during chemotherapy.

Limitations

  • Requires high-quality images and experienced practitioners for accurate measurement.
  • The value of detecting sub-clinical changes in predicting clinical outcomes or guiding therapy is still uncertain.
  • Myocardial strain measurements are not interchangeable across different software and imaging modalities due to inconsistencies.
  • Some strain imaging techniques, like cardiac MRI tagging, are time-consuming and primarily research tools.
  • CMR Feature Tracking, while easy to use, has lower reproducibility and resolution than gold standard techniques and is vendor-dependent.
  • Considered investigational and not medically necessary for all indications by some policies.

Based on reviews from: PMC, Semantic Scholar, PubMed, My Health Toolkit, Bynder, Reddit, Circle Cardiovascular Imaging (Circle CVI)

Last updated: 2026-07-21

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Press & Coverage

Cedars-Sinai
RESEARCH ALERT: Standardizing Analysis of Myocardial Strain - Cedars-Sinai
Cedars-Sinai investigators have developed a new AI tool to standardize cardiac strain measurements from standard heart ultrasounds, addressing issues of variability and proprietary software. This open-source program measures global longitudinal myocardial strain, a key indicator of muscle function.
2024-04
RSNA Journals
Myocardial Strain Evaluation with Cardiovascular MRI: Physics, Principles, and Clinical Applications | RadioGraphics - RSNA Journals
This article reviews the physics, principles, and clinical applications of cardiovascular MRI (CMR) strain techniques, highlighting myocardial strain as a more sensitive biomarker for myocardial disease than ejection fraction. CMR, particularly feature tracking, is increasingly used for this purpose.
2022-05
PMC (via Ir J Med Sci)
Myocardial strain: a clinical review - PMC
This clinical review emphasizes that myocardial strain offers increased precision in cardiac assessment, identifying myocardial dysfunction earlier than ejection fraction. It has clinical utility in various cardiac diseases, cardio-oncology, and screening healthy populations.
2022-11
Circle Cardiovascular Imaging
Circle CVI Announces FDA Clearance for cvi42 | Plaque for Coronary Artery Disease Evaluation.
Circle Cardiovascular Imaging announced FDA 510(k) clearance for its cvi42 | Plaque solution, an AI-enabled tool for comprehensive coronary plaque analysis. This expands their cvi42 platform and is available for clinical use in the US.
2025-10
FDA
Myocardial Strain Software Application (K232661) u2014 FDA 510(k)
The FDA 510(k) clearance for Circle's Myocardial Strain Software Application (Strain Module) indicates its intended use for qualitative and quantitative evaluation of cardiovascular magnetic resonance (CMR) images. It provides measurements of 2D LV myocardial function to aid in diagnosing suspected heart disease.
2023-12
American Society of Echocardiography (ASE)
Pertains to Strain? November JASE Has You Covered! - ASE
The November issue of JASE features expert recommendations on the value of myocardial strain measurements in various clinical conditions, including heart failure, cardio-oncology, and valve disease. This consensus statement serves as a resource for practitioners utilizing strain echocardiography.
2025-11
DAIC
Myocardial Strain Parameters on MRI in Patients With Dilated Cardiomyopathy | DAIC
A study published in the American Journal of Roentgenology found that left ventricular global longitudinal strain, derived from cardiac MRI feature tracking, is a significant independent predictor of adverse outcomes in patients with dilated cardiomyopathy.
2022-11
MDPI
Cardiac Magnetic Resonance Imaging with Myocardial Strain Assessment Correlates with Cardiopulmonary Exercise Testing in Patients with Pectus Excavatum - MDPI
This research, utilizing cvi42 software from Circle Cardiovascular Imaging, demonstrates that biventricular myocardial strain analyses from cardiac MRI correlate with cardiopulmonary exercise testing in pectus excavatum patients. The study assessed peak systolic circumferential and radial strain rates.
2024-12

Videos

Product demos, reviews, and walkthroughs for Myocardial Strain.

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Frequently Asked Questions

AI solutions for myocardial strain analysis typically integrate as software overlays or cloud-based platforms that process existing echocardiographic images, often providing fully automated analysis. These tools significantly reduce manual tracing time, minimize inter-observer variability, and can improve diagnostic speed and quality, especially for conditions like heart failure with preserved ejection fraction (HFpEF) and coronary artery disease.
Physicians should seek AI tools with appropriate regulatory clearances such as FDA 510(k) in the US or CE Mark in Europe, which indicate the device meets safety and performance standards. These tools typically adhere to strict data privacy regulations like HIPAA or GDPR through de-identification, encryption, and secure data handling protocols to protect patient information.
The primary alternative is manual or semi-automated myocardial strain analysis performed by a sonographer or cardiologist using conventional software, which is more time-consuming and operator-dependent. Traditional methods might be preferred in cases of highly atypical anatomy, very poor image quality where AI struggles, or when a physician desires complete manual control over every measurement.
Cost models for AI myocardial strain software often include subscription-based licenses, per-study fees, or a one-time capital expenditure for perpetual licenses. While initial investment might be present, the efficiency gains, reduced labor costs, and improved throughput over time can offer a favorable return on investment compared to the ongoing costs and time associated with manual analysis.
Limitations include potential inaccuracies with suboptimal image quality, challenges in generalizing across diverse patient populations or rare pathologies not well-represented in training data, and the 'black box' nature of some AI algorithms. Physicians must understand that AI is a tool to assist, not replace, clinical judgment, and its performance can vary with image quality and patient characteristics.
The reliability of AI algorithms for myocardial strain can vary, often performing best on image qualities similar to their training data. While many show high accuracy in controlled studies, performance may degrade with very poor image quality or in highly diverse, atypical patient cohorts, necessitating careful physician oversight and validation.
AI solutions aim to comply with clinical guidelines by standardizing measurements according to established protocols, such as ASE and EACVI recommendations, and by providing reproducible results. However, the ultimate responsibility for interpreting the results within the context of clinical guidelines and patient care remains with the physician.

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Suggest an Edit → | Last Verified: 2026-04-21 | First Added: 2026-04-21
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