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




Diagnostic Technique Assesses Structural Changes in Cardiac Arrhythmia to Enable Personalized Treatment

By MedImaging International staff writers
Posted on 07 Aug 2023
Print article
Image: The new technique offers improved diagnostic precision and potential for personalized therapy for a common arrhythmia (Photo courtesy of Freepik)
Image: The new technique offers improved diagnostic precision and potential for personalized therapy for a common arrhythmia (Photo courtesy of Freepik)

Atrial fibrillation, one of the most common types of cardiac arrhythmia, is characterized by irregular and rapid heartbeats that can lead to the formation of blood clots in the heart. This increases the risk of stroke, heart failure, and other related complications. Currently, atrial fibrillation is classified based on the duration of the arrhythmia, but this temporal classification does not provide information about the extent of structural and electrophysiological changes, known as atrial remodeling, that occur in the hearts of patients with atrial fibrillation. Atrial remodeling is a crucial parameter, especially in the initial months of the condition, as the underlying disease processes can progress at different rates. Now, a new diagnostic method allows for the simultaneous assessment of both electrical and mechanical (contractile) activity in the heart atria during atrial fibrillation, enabling timely intervention and better management of the condition.

Over the past 10 years, a team of national and international experts led by scientists at the Centro Nacional de Investigaciones Cardiovasculares (CNIC, Madrid, Spain) has been collaborating to integrate electrical and mechanical cardiac data in order to enable personalized characterization of the pathological changes associated with the progression of atrial fibrillation. The researchers were successful in achieving this through a multidisciplinary approach. Engineers and physicists worked together in the initial phase to devise the most suitable strategy for integrating the electrical and mechanical data. They found a solution to measure mechanical activity by using Doppler imaging, which offers a noninvasive method of providing information on atrial tissue movements, and to measure electrical activity by utilizing surface electrocardiography.

Both approaches are easy to implement in a clinical setting since they are noninvasive and can be performed during a transthoracic ultrasound examination, a routine study of the heart's shape and function along with some internal structures. The second phase involved experts in biology, biotechnology, biochemistry, and biomedical engineering working in collaboration with the CNIC Proteomics Unit and clinical cardiologists. Experimental studies in this phase correlated the information obtained through the new approach with underlying pathological changes in atrial tissue. This led to the development of advanced mapping techniques and computer simulations that shed light on the mechanisms underlying electrical and mechanical remodeling during the progression of atrial fibrillation.

In the final phase, a multicenter prospective study involving 83 patients in the early stages of atrial fibrillation was conducted to determine the prognostic value of simultaneously assessing electrical and mechanical activity in the atria of these patients. The experimental and clinical findings revealed an imbalance between electrical and mechanical activation in the atria during the early stages of the disease. This causes dissociation between the two parameters, termed "atrial electromechanical dissociation," where the contractile activation cannot keep up with the electrical activation. This phenomenon is specific to each individual patient and is usually observed within the first 2-3 months after an uninterrupted atrial fibrillation episode. A key advantage of this new approach is that it identifies atrial electromechanical dissociation before overt clinical signs of structural atrial remodeling appear. This early detection could be crucial for timely intervention and better management of the condition.

“The use of this new diagnostic approach allows early characterization of the underlying remodeling in patients with atrial fibrillation,” said study leader David Filgueiras. “The study shows that it is possible to integrate electrical and mechanical data from the atria of patients with atrial fibrillation to obtain personalized prognostic information about the clinical progression of the disease.”

Related Links:
CNIC

New
Gold Member
X-Ray QA Meter
T3 AD Pro
New
Transducer Covers
Surgi Intraoperative Covers
New
DRF DR & Remote Fluoroscopy Solution
CombiDiagnost R90
Ultrasound Color LCD
U156W

Print article
Radcal

Channels

Radiography

view channel
Image: The new X-ray detector produces a high-quality radiograph (Photo courtesy of ACS Central Science 2024, DOI: https://doi.org/10.1021/acscentsci.4c01296)

Highly Sensitive, Foldable Detector to Make X-Rays Safer

X-rays are widely used in diagnostic testing and industrial monitoring, from dental checkups to airport luggage scans. However, these high-energy rays emit ionizing radiation, which can pose risks after... Read more

MRI

view channel
Image: Artificial intelligence models can be trained to distinguish brain tumors from healthy tissue (Photo courtesy of 123RF)

AI Can Distinguish Brain Tumors from Healthy Tissue

Researchers have made significant advancements in artificial intelligence (AI) for medical applications. AI holds particular promise in radiology, where delays in processing medical images can often postpone... Read more

Nuclear Medicine

view channel
Image: Example of AI analysis of PET/CT images (Photo courtesy of Academic Radiology; DOI: 10.1016/j.acra.2024.08.043)

AI Analysis of PET/CT Images Predicts Side Effects of Immunotherapy in Lung Cancer

Immunotherapy has significantly advanced the treatment of primary lung cancer, but it can sometimes lead to a severe side effect known as interstitial lung disease. This condition is characterized by lung... Read more

General/Advanced Imaging

view channel
Image: Cleerly offers an AI-enabled CCTA solution for personalized, precise and measurable assessment of plaque, stenosis and ischemia (Photo courtesy of Cleerly)

AI-Enabled Plaque Assessments Help Cardiologists Identify High-Risk CAD Patients

Groundbreaking research has shown that a non-invasive, artificial intelligence (AI)-based analysis of cardiac computed tomography (CT) can predict severe heart-related events in patients exhibiting symptoms... 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
Copyright © 2000-2024 Globetech Media. All rights reserved.