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
Sign In
Advertise with Us
PURITAN MEDICAL

Download Mobile App




Events

ATTENTION: Due to the COVID-19 PANDEMIC, many events are being rescheduled for a later date, converted into virtual venues, or altogether cancelled. Please check with the event organizer or website prior to planning for any forthcoming event.

New AI Tool Can Identify and Distinguish Between Difficult-to-Diagnose Life-Threatening Heart Conditions

By HospiMedica International staff writers
Posted on 24 Feb 2022
Print article
Image: AI Algorithm Spots Difficult-to-Diagnose Cardiac Conditions (Photo courtesy of Unsplash)
Image: AI Algorithm Spots Difficult-to-Diagnose Cardiac Conditions (Photo courtesy of Unsplash)

For the first time, a team of physician-scientists has developed an algorithm that can spot difficult-to-diagnose cardiac conditions.

Physician-scientists in the Smidt Heart Institute at Cedars-Sinai (Los Angeles, CA, USA) have created an artificial intelligence (AI) tool that can effectively identify and distinguish between two life-threatening heart conditions that are often easy to miss: hypertrophic cardiomyopathy and cardiac amyloidosis. The two-step, novel algorithm was used on over 34,000 cardiac ultrasound videos. When applied to these clinical images, the algorithm identified specific features - related to the thickness of heart walls and the size of heart chambers - to efficiently flag certain patients as suspicious for having the potentially unrecognized cardiac diseases.

Without comprehensive testing, cardiologists find it challenging to distinguish between similar appearing diseases and changes in heart shape and size that can sometimes be thought of as a part of normal aging. This algorithm accurately distinguishes not only abnormal from normal, but also between which underlying potentially life-threatening cardiac conditions may be present - with warning signals that are now detectable well before the disease clinically progresses to the point where it can impact health outcomes. Getting an earlier diagnosis enables patients to begin effective treatments sooner, prevent adverse clinical events, and improve their quality of life.

Cardiac amyloidosis, often called “stiff heart syndrome,” is a disorder caused by deposits of an abnormal protein (amyloid) in the heart tissue. As amyloid builds up, it takes the place of healthy heart muscle, making it difficult for the heart to work properly. Cardiac amyloidosis often goes undetected because patients might not have any symptoms, or they might experience symptoms only sporadically. The disease tends to affect older, Black men or patients with cancer or diseases that cause inflammation. Many patients belong to underserved communities, making the study results an important tool in improving healthcare equity.

Hypertrophic cardiomyopathy is a disease that causes the heart muscle to thicken and stiffen. As a result, it's less able to relax and fill with blood, resulting in damage to heart valves, fluid buildup in the lungs, and abnormal heart rhythms. Although separate and distinct conditions, cardiac amyloidosis and hypertrophic cardiomyopathy often look very similar to each other on an echocardiogram, the most commonly used cardiac imaging diagnostic. Importantly, in the very early stages of disease, each of these cardiac conditions can also mimic the appearance of a non-diseased heart that has progressively changed in size and shape with aging.

The new AI technology can be used to identify patients from very early on in their disease course. That’s because clinicians know that earlier is always better for getting the most benefit from therapies that are available today and that can be very effective for preventing the worst possible outcomes, such as heart failure, hospitalizations, and sudden death. Researchers plan to soon launch clinical trials for patients flagged by the AI algorithm for suspected cardiac amyloidosis. A clinical trial for patients flagged by the algorithm for suspected hypertrophic cardiomyopathy has just started at Cedars-Sinai.

“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. “The algorithm identified high-risk patients with more accuracy than the well-trained eye of a clinical expert. This is because the algorithm picks up subtle cues on ultrasound videos that distinguish between heart conditions that can often look very similar to more benign conditions, as well as to each other, on initial review.”

Related Links:
Cedars-Sinai 


Print article
IIR Middle East

Channels

Critical Care

view channel
Image: Three dimensional measurement of the all-mesh thermistor (Photo courtesy of Shinshu University)

Ultraflexible, Gas-Permeable Thermistors to Pave Way for On-Skin Medical Sensors and Implantable Devices

On-skin medical sensors and wearable health devices are important health care tools that must be incredibly flexible and ultrathin so they can move with the human body. In addition, the technology has... Read more

Surgical Techniques

view channel
Image: Engineers have developed a process that enables soft robots to grow like plants (Photo courtesy of University of Minnesota)

Soft Robotic System Can Grow Like Plants to Allow Surgical Access to Hard-To-Reach Areas

Soft robotics is an emerging field where robots are made of soft, pliable materials as opposed to rigid ones. Soft growing robots can create new material and “grow” as they move. These machines could be... Read more

Health IT

view channel
Image: Using digital data can improve health outcomes (Photo courtesy of Unsplash)

Electronic Health Records May Be Key to Improving Patient Care, Study Finds

When a patient gets transferred from a hospital to a nearby specialist or rehabilitation facility, it is often difficult for personnel at the new facility to access the patient’s electronic health records... Read more

Business

view channel
Image: Differentiated stapling technology for bariatric surgery (Photo courtesy of Standard Bariatrics)

Teleflex Completes Acquisition of Bariatric Stapling Technology Innovator

Teleflex Incorporated (Wayne, PA, USA), a leading global provider of medical technologies, has completed the previously announced acquisition of Standard Bariatrics, Inc. (Cincinnati, OH, USA), which has... Read more
Copyright © 2000-2022 Globetech Media. All rights reserved.