Strain AI

by Exo  · Based in United States → — Revolutionizing medical imaging with high-performance handheld ultrasound and AI-driven solutions.
Cardiology Oncology Radiology

Contact for pricing
Regulatory Status Disclosed

Overview

Exo’s Strain AI is a medical software device designed to analyze cardiac ultrasound images. It specifically measures global longitudinal strain (GLS), a key indicator that helps clinicians assess heart function in adult patients. This AI tool integrates seamlessly with existing ultrasound devices, providing quantitative strain measurements and supporting diagnostic evaluations without the need for manual image interpretation. As part of Exo’s broader AI platform, Strain AI delivers real-time, on-device AI insights for comprehensive cardiac assessments. It is engineered to provide objective data that assists in the early detection of various heart conditions, including heart failure (CHF, HFpEF, and HFrEF), cardiac hypertrophy, and the monitoring of chemotherapy-induced cardiotoxicity.

Reviewed by Pouyan Golshani, MD — Interventional Radiologist

Key Features

  • Analyzes cardiac ultrasound images
  • Measures Global Longitudinal Strain (GLS)
  • Aids in assessing heart function in adult patients
  • Integrates with existing ultrasound devices
  • Provides quantitative strain measurements
  • Supports diagnostic evaluation without manual image interpretation
  • Delivers real-time, on-device AI insights
  • Assists in detecting heart failure (CHF, HFpEF, HFrEF) and hypertrophy
  • Identifies chemotherapy-induced cardiotoxicity
  • FDA-cleared medical device

Use Cases

  • Early detection and assessment of heart failure (HFpEF, HFrEF)
  • Monitoring for chemotherapy-induced cardiotoxicity in oncology patients
  • Assessing myocardial dysfunction
  • Diagnostic evaluation of cardiac function in adult patients
  • Enhancing point-of-care cardiac diagnostics

What Physicians Need to Know

ECG/EKG Analysis Capability
AI can generate ECG-GLS scores to diagnose LV systolic dysfunction and predict heart failure prognosis, demonstrating strong correlation with echocardiography-derived GLS. It significantly improves STEMI detection, reduces false activations, and enhances arrhythmia recognition with high accuracy.
Echocardiography AI Features
Strain AI primarily focuses on fully automated Global Longitudinal Strain (GLS) analysis from echocardiograms, offering a more sensitive and earlier indicator of heart failure, including HFpEF, compared to traditional ejection fraction. It minimizes variability, increases diagnostic speed and quality, and can accurately identify regional wall motion abnormalities.
Cardiac CT/MRI Analysis
AI-powered analysis of Coronary CT Angiography (CCTA) is highly accurate for CAD interpretation and stenosis classification. For Cardiac MRI (CMR), AI can assess myocardial ischemia with high accuracy and enable fully automated global longitudinal and circumferential strain analysis for risk stratification and management in CAD patients.
Arrhythmia Detection Accuracy
AI algorithms are trained to identify patterns in ECG signals for accurate and efficient arrhythmia detection. Commercially available AI-equipped digital stethoscopes can identify Atrial Fibrillation (AF) with high sensitivity (99%) and specificity (97%) from single-lead ECGs, and AI can detect asymptomatic abnormal heart rhythms.
Heart Failure Risk Prediction
GLS, enhanced by AI, is a superior and earlier predictor of heart failure and adverse events. AI models improve heart failure diagnosis quality, assist in diagnostic confirmation, and can predict HF a decade before diagnosis by integrating genetic and clinical data. AI-ECG screens are associated with a significantly increased risk of new-onset HF.
Coronary Artery Assessment
Strain AI can identify regional wall motion abnormalities indicative of ischemic heart disease. AI enables accurate radial wall strain assessment from OCT and coronary angiography, providing insights into plaque vulnerability. AI models analyze coronary angiography and CCTA to predict stenosis with high sensitivity and specificity, differentiating CAD severity faster than manual methods.
Cardiac Monitoring Integration
AI-integrated wearable devices offer continuous, patient-centered cardiovascular monitoring. Remote cardiac monitoring systems with AI detect abnormalities earlier, enabling proactive disease management. The trend is towards multimodal, multi-sensor fusion models integrating wearables, EHRs, imaging, and genomics.
AHA/ACC Guideline Alignment
The 2022 AHA/ACC/HFSA Guidelines recommend Global Longitudinal Strain (GLS) in routine clinical workflow for heart failure management. The 2021 EACVI and ASE Guidelines also recommend strain measurement on all echo tests, with AI solutions aiding in overcoming implementation challenges.
Real-Time Alert Capability
AI-driven analytics in remote cardiac monitoring enable early detection of arrhythmias and heart failure exacerbations. AI systems can provide real-time support to clinicians for managing complex cardiac conditions, with AI-enabled ECG monitoring achieving high diagnostic accuracy for real-time arrhythmia detection.
Physician Tip

Leverage Strain AI for its ability to provide highly accurate, standardized, and efficient cardiac strain measurements, particularly Global Longitudinal Strain (GLS), which is a superior prognostic indicator for heart failure and early myocardial dysfunction. Integrate these AI tools to reduce inter-operator variability and streamline workflow in echocardiography labs. Consider its utility in identifying high-risk patients for heart failure and coronary artery disease earlier, aligning with current AHA/ACC guidelines. While primarily focused on strain, explore its potential in ECG and CMR analysis for a comprehensive diagnostic approach. Remember that AI is a powerful augmentative tool, not a replacement for clinical expertise, and its outputs should be interpreted within the broader clinical context.

Strain AI solutions are often designed as vendor-neutral, cloud-based platforms (e.g., SaaS) that can be easily implemented into existing cardiology setups and PACS systems. They aim to integrate seamlessly into routine workflows without requiring significant additional time or effort from clinicians. Future developments are moving towards multimodal, multi-sensor fusion models that integrate data from wearables, electronic health records (EHRs), and various imaging modalities for a holistic cardiovascular profile. Compatibility with diverse ultrasound equipment vendors is a key consideration for widespread adoption.

Details

Category Cardiology AI, Radiology & Imaging AI
Pricing Contact for pricing
DeploymentOn-device AI, operates without internet connection.
Compliance
BAA Available Yes AI-estimated
HIPAA Compliant Yes AI-estimated
FDA Status Yes AI-estimated

Strain AI (SAI001) received FDA clearance (K242359) on November 20, 2024. It is a Software as a Medical Device (SaMD) intended as an aid in diagnostic analysis of echocardiography data to measure global longitudinal strain (GLS) of adult patients with suspected disease, providing objective data for heart failure and cardiotoxicity assessment.

Integrations
EHR Not specified
Specialties Cardiology, Oncology, Radiology

What the Web Says

Strain AI appears to be a relatively new or niche product, as comprehensive reviews from major healthcare IT platforms like G2 or Capterra, or widespread physician discussions, are not readily available through a general web search. Information is limited, making it difficult to form a robust opinion based on broad public sentiment.

Overall: Mixed

Strengths

  • No specific pros could be identified due to limited public reviews.
  • Potential for AI-driven insights in an unspecified domain (assuming 'Strain' relates to data or biological strain analysis).

Limitations

  • Lack of readily available reviews from physicians or healthcare IT professionals.
  • Absence of presence on major review platforms like G2 or Capterra.
  • No significant discussion found on Reddit or other tech review sites.
  • Limited public information regarding its specific functionalities and use cases.
  • Unclear target audience or problem it solves from publicly available information.

Based on reviews from: General web search (lack of specific named sources due to limited results)

Last updated: 2026-07-19

Ratings & Reviews

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Press & Coverage

FDA 510(k) Clearance Document
Exo's Strain AI Receives 510(k) Clearance from FDA
Exo Inc.'s Strain AI, a software as a medical device (SaMD), received 510(k) clearance from the FDA in November 2024. It is intended as an aid in diagnostic analysis of echocardiography data, specifically measuring global longitudinal strain (GLS) from apical 4-chamber cardiac ultrasound images.
2024-11
Impactfactor
Echo-Derived Strain Imaging Combined With AI to Predict Outcomes in Asymptomatic Valvular Disease
A study published in Impactfactor demonstrates that combining echo-derived strain imaging with AI significantly improves the prediction of clinical progression in asymptomatic valvular disease. The combined strain-AI model achieved an AUC of 0.89, outperforming conventional echo parameters or strain imaging alone.
unknown
European Heart Journal - Digital Health
AI-powered home ultrasound: Exploring feasibility of AI-powered ultrasound for home-based cardiac monitoring
The European Heart Journal - Digital Health featured an article in January 2024 exploring the feasibility of AI-powered ultrasound for home-based cardiac monitoring. This highlights the growing interest in leveraging AI for remote healthcare solutions.
2024-01
European Heart Journal - Digital Health
AI echo for strain imaging: Evaluating AI-automated strain imaging analysis compared to traditional vendor-specific solutions
Another article from the European Heart Journal - Digital Health in November 2023 evaluated AI-automated strain imaging analysis, comparing it to traditional vendor-specific solutions. This research suggests AI can offer a more efficient and potentially less variable approach to strain measurement.
2023-11
Us2.ai
Automated echo strain AI measurements
Us2.ai published an article in May 2023 on automated echo strain AI measurements, emphasizing that AI Echo can automate the generation and interpretation of strain, which is a sensitive measure of cardiac function but has been limited by expertise requirements and variability.
2023-05
Ultromics
Global longitudinal strain and how AI can aid fight against heart failure
An article by Ultromics from April 2021 discusses how AI can help overcome challenges in effectively utilizing global longitudinal strain (GLS) for measuring heart failure. AI can simplify and automate GLS measurements, moving its benefits from journals to clinical practice.
2021-04
Cardiovascular Diagnosis and Therapy
Artificial intelligence-enhanced automation of left ventricular diastolic assessment: a pilot study for feasibility, diagnostic validation, and outcome prediction
A pilot study published in Cardiovascular Diagnosis and Therapy in June 2024 demonstrated the feasibility and accuracy of an AI-based framework for fully automating left ventricular diastolic function (LVDF) assessment on echocardiography. The AI-based approach showed 94% concordance with manually derived LVDF and significant prognostic value.
2024-06
RSIS International
Leveraging AI-Driven Predictive Analytics to Strengthen Health System Resilience Against Climate-Related Patient Surges and Infrastructure Strain
A peer-reviewed article from RSIS International in September 2025 discusses how AI-driven predictive analytics can strengthen health system resilience against climate-related patient surges and infrastructure strain. It highlights AI's potential for early warning systems and efficient resource allocation.
2025-09

Videos

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Suggest an Edit → | Last Verified: 2026-04-18 | First Added: 2026-04-18
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