Combined ECG and Cardiac Imaging-Derived Radiomics Model Improves Detection of AF in Women
|
By HospiMedica International staff writers Posted on 05 Dec 2022 |

Atrial fibrillation (AF) is a heart condition characterized by an irregular and often abnormally fast heart rhythm. The most commonly encountered cardiac arrhythmia, it happens when abnormal electrical impulses suddenly occur in the heart’s upper chambers, or atria, causing them to beat out of sync with the heart’s lower chambers, or ventricles. AF can cause problems such as dizziness, shortness of breath and tiredness, and it also increases the risk of stroke and heart failure. The main clinical tool for diagnosing AF is the ECG. It is widely used to spot abnormalities in heart rhythms and waveforms. However, an ECG recorded at a single time point may not detect individuals with paroxysmal AF, which is intermittent AF episodes that end within seven days, either on their own or with treatment. Another tool, cardiovascular magnetic resonance (CMR) imaging, plays an important role in assessing the function and structure of the cardiovascular system. Additionally, CMR radiomics has attracted a lot of interest because of its potential to enhance diagnostic accuracy through its ability to extract a large number of features from medical images using data characterization algorithms. Now, if ECG features and CMR radiomics were to be combined, would this improve AF detection?
New research supported by euCanSHare (Barcelona, Spain) and HealthyCloudEU (Barcelona, Spain) has revealed that a model combining ECG features and cardiac imaging-derived radiomics data improves the detection of AF in women. The researchers used information from a large-scale health database called the UK Biobank. A total of 32 121 participants with an average age of 63 years were included in the study. An estimated 51 % were female. Of all the participants, 495 had prevalent AF. The research team found that their integrative model combining radiomics and ECG had better results than ECG alone, especially in women. Adding radiomics led to a considerable increase in sensitivity in the case of women, resulting in improved detection of AF events.
“ECG had a lower performance in women than men … but adding radiomics features, the accuracy of the model was able to improve significantly. Our findings provide novel insights into AF-related electro-anatomic remodelling and its variations by sex. The integrative radiomics-ECG model also presents a potential novel approach for earlier detection of AF,” the authors concluded.
Related Links:
euCanSHare
HealthyCloudEU
Latest Critical Care News
- Automated IV Labeling Solution Improves Infusion Safety and Efficiency
- First-Of-Its-Kind AI Tool Detects Pulmonary Hypertension from Standard ECGs
- 4D Digital Twin Heart Model Improves CRT Outcomes
- AI Turns Glucose Data Into Actionable Insights for Diabetes Care
- Microscale Wireless Implant Tracks Brain Activity Over Time
- Smart Mask Delivers Continuous, Battery-Free Breath Monitoring
- Routine Blood Pressure Readings May Identify Risk of Future Cognitive Decline
- CGM-Based Algorithm Enhances Insulin Dose Adjustment in Type 2 Diabetes
- Fish Scale–Based Implants Offer New Approach to Corneal Repair
- Dual-Function Wound Patch Combines Infection Sensing and Treatment
- Smartwatch Signals and Blood Tests Team Up for Early Warning on Insulin Resistance
- Smart Fabric Technology Aims to Prevent Pressure Injuries in Hospital Care
- Standardized Treatment Algorithm Improves Blood Pressure Control
- Combined Infection Control Strategy Limits Drug-Resistant Outbreak in NICU
- AI Helps Predict Which Heart-Failure Patients Will Worsen Within a Year
- Algorithm Allows Paramedics to Predict Brain Damage Risk After Cardiac Arrest
Channels
Artificial Intelligence
view channel
Machine Learning Approach Enhances Liver Cancer Risk Stratification
Hepatocellular carcinoma, the most common form of primary liver cancer, is often detected late despite targeted surveillance programs. Current screening guidelines emphasize patients with known cirrhosis,... Read more
New AI Approach Monitors Brain Health Using Passive Wearable Data
Brain health spans cognitive and emotional functions and can fluctuate even in adults without diagnosed disease. Detecting early changes remains difficult in routine care and burdens specialty services... Read moreCritical Care
view channel
Automated IV Labeling Solution Improves Infusion Safety and Efficiency
Medication administration in high-acuity settings is often complicated by multiple concurrent infusions, making accurate line identification essential. In a 10-hospital intensive care unit study, 60% of... Read more
First-Of-Its-Kind AI Tool Detects Pulmonary Hypertension from Standard ECGs
Pulmonary hypertension is a progressive, life‑threatening disease that is frequently missed early because symptoms such as dyspnea are nonspecific and diagnostic delays can exceed two years.... Read moreSurgical Techniques
view channel
Continuous Monitoring with Wearables Enhances Postoperative Patient Safety
Postoperative hypoxemia on general surgical wards is common and often missed by intermittent vital sign checks. Undetected low oxygen levels can delay recovery and raise the risk of complications that... Read more
New Approach Enables Customized Muscle Tissue Without Biomaterial Scaffolds
Volumetric muscle loss is a traumatic loss of skeletal muscle that often leads to permanent functional impairment and limited reconstructive options. Current experimental strategies struggle to deliver... Read morePatient Care
view channel
Wearable Sleep Data Predict Adherence to Pulmonary Rehabilitation
Chronic obstructive pulmonary disease (COPD) is a long-term lung disorder that makes breathing difficult and often disturbs sleep, reducing energy for daily activities. Limited engagement in pulmonary... Read more
Revolutionary Automatic IV-Line Flushing Device to Enhance Infusion Care
More than 80% of in-hospital patients receive intravenous (IV) therapy. Every dose of IV medicine delivered in a small volume (<250 mL) infusion bag should be followed by subsequent flushing to ensure... Read moreHealth IT
view channel
EMR-Based Tool Predicts Graft Failure After Kidney Transplant
Kidney transplantation offers patients with end-stage kidney disease longer survival and better quality of life than dialysis, yet graft failure remains a major challenge. Although a successful transplant... Read more
Printable Molecule-Selective Nanoparticles Enable Mass Production of Wearable Biosensors
The future of medicine is likely to focus on the personalization of healthcare—understanding exactly what an individual requires and delivering the appropriate combination of nutrients, metabolites, and... Read moreBusiness
view channel







