We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
GLOBETECH PUBLISHING LLC

Download Mobile App




AI Tool Identifies and Distinguishes Between Difficult-to-Diagnose Cardiac Conditions on Echocardiograms

By MedImaging International staff writers
Posted on 07 Apr 2023
Print article
Image: A new artificial intelligence tool can detect often overlooked heart diseases (Photo courtesy of Pexels)
Image: A new artificial intelligence tool can detect often overlooked heart diseases (Photo courtesy of Pexels)

Identifying hypertrophic cardiomyopathy and cardiac amyloidosis, two critical heart conditions can be quite challenging, even for seasoned cardiologists, resulting in patients waiting years to decades before receiving an accurate diagnosis. Without comprehensive testing, differentiating between these conditions and changes in heart shape and size that may be associated with normal aging can be perplexing for cardiologists. Notably, in the initial stages of the disease, both of these cardiac conditions can resemble the appearance of a heart that has aged and progressed naturally without any disease. Now, for the first time, an algorithm can spot these difficult-to-diagnose cardiac conditions.

Deposits of abnormal protein (amyloid) in heart tissue cause cardiac amyloidosis, also known as "stiff heart syndrome." These deposits replace healthy heart muscle, making it difficult for the heart to function correctly. Hypertrophic cardiomyopathy, on the other hand, causes the heart muscle to thicken and stiffen, leading to inadequate relaxation and blood filling, which can result in heart valve damage, fluid buildup in the lungs, and irregular heart rhythms. Physician-scientists at the Smidt Heart Institute at Cedars-Sinai (Los Angeles, CA, USA) have developed an artificial intelligence (AI) tool that can differentiate between these two life-threatening heart conditions effectively. The novel, two-step algorithm analyzed more than 34,000 cardiac ultrasound videos from Cedars-Sinai and Stanford Healthcare's echocardiography laboratories. The algorithm identified particular features related to heart wall thickness and chamber size and flagged patients who were suspicious of having these potentially unrecognized cardiac conditions.

The AI algorithm not only accurately distinguishes abnormal from normal cardiac conditions but can also identify which potentially life-threatening heart diseases may be present. It provides warning signals that can detect the disease well before it progresses to a stage that can impact health outcomes. With earlier diagnosis, patients can receive effective treatment sooner, prevent adverse clinical events, and improve their quality of life. The researchers hope that the technology will be utilized to identify patients at an early stage of the disease, as earlier diagnosis enables the most benefit from available therapies that can prevent the worst outcomes such as hospitalizations, heart failure, and sudden death.

“Our AI algorithm can pinpoint disease patterns that can’t be seen by the naked eye, and then use these patterns to predict the right diagnosis,” said David Ouyang, MD, a cardiologist in the Smidt Heart Institute and senior author of the study.

“One of the most important aspects of this AI technology is not only the ability to distinguish abnormal from normal, but also to distinguish between these abnormal conditions, because the treatment and management of each cardiac disease is very different,” added Susan Cheng, MD, MPH, director of the Institute for Research on Healthy Aging in the Department of Cardiology at the Smidt Heart Institute and co-senior author of the study.

Related Links:
Cedars-Sinai 

New
Gold Member
X-Ray QA Meter
T3 AD Pro
New
Ultrasound Imaging System
P12 Elite
Radiation Therapy Treatment Software Application
Elekta ONE
New
Multi-Use Ultrasound Table
Clinton

Print article
Radcal

Channels

Radiography

view channel
Image: The CT scanner prototype eliminates the need for physical compression of the breast (Photo courtesy of Quion Lowe and Lisa Dahm/U of A Cancer Center)

Novel Breast Cancer Screening Technology Could Offer Superior Alternative to Mammogram

Breast cancer represents 15.5% of new cancer cases and 7% of cancer-related deaths in the United States. Approximately 13.1% of women will be diagnosed with breast cancer during their lifetime.... Read more

Nuclear Medicine

view channel
Image: PET scans of a glioblastoma patient\'s brain, 72 hours after injection with the radiotracer (Photo courtesy of Dr Gabriela Kramer-Marek, The Institute of Cancer Research, London)

New Immuno-PET Imaging Technique Identifies Glioblastoma Patients Who Would Benefit from Immunotherapy

Glioblastoma is a type of brain tumor associated with a very poor prognosis, with average survival rates of 12 to 18 months and only 5% of patients surviving beyond five years. Research has shown that... Read more

General/Advanced Imaging

view channel
Image: Heavy smokers can ben Image (2):	efit from lung cancer screening using low-dose CT (Photo courtesy of 123RF)

Low-Dose CT Screening for Lung Cancer Can Benefit Heavy Smokers

Lung cancer is often diagnosed at a late stage, with only about one-fifth to one-sixth of patients surviving five years after diagnosis. A new report now suggests that low-dose computed tomography (CT)... Read more

Imaging IT

view channel
Image: The new Medical Imaging Suite makes healthcare imaging data more accessible, interoperable and useful (Photo courtesy of Google Cloud)

New Google Cloud Medical Imaging Suite Makes Imaging Healthcare Data More Accessible

Medical imaging is a critical tool used to diagnose patients, and there are billions of medical images scanned globally each year. Imaging data accounts for about 90% of all healthcare data1 and, until... Read more

Industry News

view channel
Image: The advocacy partnership aims to help accelerate access to life-saving treatments (Photo courtesy of Philips)

Philips and Medtronic Partner on Stroke Care

A stroke is typically an acute incident primarily caused by a blockage in a brain blood vessel, which disrupts the adequate blood supply to brain tissue and results in the permanent loss of brain cells.... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.