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Related Concept Videos

Mitral Regurgitation II: Clinical Features and Diagnostic Tests01:23

Mitral Regurgitation II: Clinical Features and Diagnostic Tests

Mitral regurgitation (MR) is a valvular heart disorder in which the mitral valve fails to close tightly, allowing blood to leak backward into the heart. Understanding the clinical manifestations, assessment, diagnostic findings, and medical management of MR is crucial to effectively managing affected patients.Clinical Manifestations of Mitral RegurgitationMitral regurgitation can be acute or chronic, each presenting differently and requiring different approaches:1. Acute Mitral...
Mitral Regurgitation III: Medical Management01:25

Mitral Regurgitation III: Medical Management

Mitral regurgitation (MR) is characterized by retrograde blood circulation from the left ventricle into the left atrium due to inadequate mitral valve closure. The severity of the condition, symptoms, and underlying cause determine treatment strategies.Monitoring and Pharmacological TreatmentPatients with mild to moderate MR typically do not need immediate intervention but regular monitoring to assess progression and guide treatment. Patients with mild MR should have an echocardiogram every 3-5...
Mitral Stenosis II: Clinical features and Diagnostic Tests01:23

Mitral Stenosis II: Clinical features and Diagnostic Tests

Mitral stenosis is a heart condition in which the mitral valve, which allows blood to flow from the left atrium to the left ventricle, becomes narrowed or stenotic. This narrowing hinders blood flow and leads to clinical symptoms requiring specific medical evaluations and management strategies. The following overview outlines the clinical symptoms, assessments, diagnostic findings, prevention methods, and treatments for mitral stenosis.Clinical ManifestationsDyspnea (shortness of breath): This...
Imaging Studies for Cardiovascular System I:Echocardiography01:17

Imaging Studies for Cardiovascular System I:Echocardiography

Cardiac imaging studies encompass a wide range of noninvasive and minimally invasive techniques designed to visualize the heart's structure and function in detail. One such technique is echocardiography, which uses high-frequency ultrasound waves to produce detailed images of the heart, known as echocardiograms.
Indications: Echocardiography is utilized to diagnose heart failure, valve disorders, and myocardial infarction. It also assesses cardiac structures' size, shape, and motion, evaluates...

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Related Experiment Video

Updated: Jul 16, 2026

A Simplified Stepwise Approach to Echo Guidance during Percutaneous Mitral Valve Repair
08:31

A Simplified Stepwise Approach to Echo Guidance during Percutaneous Mitral Valve Repair

Published on: October 16, 2021

Automated Detection of Clinically Significant Mitral Regurgitation from Single-View B-mode Echocardiography Using

Roman A Sandler1, Joseph Z Sokol2, Shubhadarshini Pawar3

  • 1iCardio.ai Corporation, Los Angeles, United States of America.

Journal of the American Society of Echocardiography : Official Publication of the American Society of Echocardiography
|July 14, 2026
PubMed
Summary

MitralVision, an AI tool, accurately identifies significant mitral regurgitation (MR) using B-mode echocardiograms, offering a standardized approach to screening for this common heart disease.

Keywords:
Convolutional neural networksDeep learningDiagnostic accuracyMitral regurgitationTransthoracic echocardiography

Related Experiment Videos

Last Updated: Jul 16, 2026

A Simplified Stepwise Approach to Echo Guidance during Percutaneous Mitral Valve Repair
08:31

A Simplified Stepwise Approach to Echo Guidance during Percutaneous Mitral Valve Repair

Published on: October 16, 2021

Area of Science:

  • Cardiology
  • Artificial Intelligence
  • Medical Imaging

Background:

  • Mitral regurgitation (MR) is a prevalent valvular heart disease.
  • Traditional diagnosis via Doppler echocardiography faces variability and technical challenges.
  • An AI model, MitralVision, was developed for automated MR classification.

Purpose of the Study:

  • To develop and validate MitralVision, a deep learning model.
  • To automate the classification of clinically significant MR.
  • To utilize single-view, B-mode echocardiographic loops for MR assessment.

Main Methods:

  • Trained a deep neural network (MitralVision) on 28,487 echocardiographic loops.
  • Model differentiates moderate/severe MR from none/trace/mild MR.
  • Externally validated on 629 studies from 26 independent sites.

Main Results:

  • Achieved an AUROC of 0.91 on external validation.
  • Demonstrated high sensitivity (82.1%) and specificity (84.3%).
  • Showed excellent calibration with a Brier score of 0.12.

Conclusions:

  • MitralVision reliably distinguishes significant MR using B-mode echocardiography.
  • The AI approach supports standardized and reproducible MR screening.
  • Potential for workflow integration in high-throughput or resource-limited settings.