AIMC Topic: Mitral Valve

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EasyPISA: Automatic Integrated PISA Measurements of Mitral Regurgitation From 2-D Color-Doppler Using Deep Learning.

Ultrasound in medicine & biology
OBJECTIVE: The proximal isovelocity surface area (PISA) method is a well-established approach for mitral regurgitation (MR) quantification. However, it exhibits high inter-observer variability and inaccuracies in cases of non-hemispherical flow conve...

Deep Learning for Echo Analysis, Tracking, and Evaluation of Mitral Regurgitation (DELINEATE-MR).

Circulation
BACKGROUND: Artificial intelligence, particularly deep learning (DL), has immense potential to improve the interpretation of transthoracic echocardiography (TTE). Mitral regurgitation (MR) is the most common valvular heart disease and presents unique...

A complexity evaluation system for mitral valve repair based on preoperative echocardiographic and machine learning.

Hellenic journal of cardiology : HJC = Hellenike kardiologike epitheorese
BACKGROUND: To develop a novel complexity evaluation system for mitral valve repair based on preoperative echocardiographic data and multiple machine learning algorithms.

Diastolic function assessment with four-dimensional flow cardiovascular magnetic resonance using automatic deep learning E/A ratio analysis.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance
BACKGROUND: Diastolic left ventricular (LV) dysfunction is a powerful contributor to the symptoms and prognosis of patients with heart failure. In patients with depressed LV systolic function, the E/A ratio, the ratio between the peak early (E) and t...

Automated mitral inflow Doppler peak velocity measurement using deep learning.

Computers in biology and medicine
Doppler echocardiography is a widely utilised non-invasive imaging modality for assessing the functionality of heart valves, including the mitral valve. Manual assessments of Doppler traces by clinicians introduce variability, prompting the need for ...

Path tracking control of a steerable catheter in transcatheter cardiology interventions.

International journal of computer assisted radiology and surgery
PURPOSE: Intracardiac transcatheter interventions allow for reducing trauma and hospitalization stays as compared to standard surgery. In the treatment of mitral regurgitation, the most widely adopted transcatheter approach consists in deploying a cl...

Mitral Valve Segmentation and Tracking from Transthoracic Echocardiography Using Deep Learning.

Ultrasound in medicine & biology
OBJECTIVE: Valvular heart diseases (VHDs) pose a significant public health burden, and deciding the best treatment strategy necessitates accurate assessment of heart valve function. Transthoracic echocardiography (TTE) is the key modality to evaluate...

Automated estimation of mitral annular plane systolic excursion by artificial intelligence from 3D ultrasound recordings.

Artificial intelligence in medicine
Perioperative monitoring of cardiac function is beneficial for early detection of cardiovascular complications. The standard of care for cardiac monitoring performed by trained cardiologists and anesthesiologists involves a manual and qualitative eva...

Propensity-matched analysis of robotic versus sternotomy approaches for mitral valve replacement.

Journal of robotic surgery
To compare early and medium-term outcomes between robotic and sternotomy approaches for mitral valve replacement (MVR). Clinical data of 1393 cases who underwent MVR between January 2014 and January 2023 were collected and stratified into robotic MVR...

A New Frontier: No Working Port for Robotic Mitral Valve Repair.

Innovations (Philadelphia, Pa.)
A 61-year-old male presented via referral for mitral regurgitation and was deemed an appropriate robotic surgery candidate for complex mitral valve repair with the maze procedure and patent foramen ovale and left atrial appendage closures, using all ...