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Background: Fragmented QRS complex (f-QRS) on a 12-lead electrocardiogram (ECG) has been associated with myocardial scars. However, its diagnostic accuracy for detecting myocardial scars assessed by cardiac magnetic resonance (CMR) imaging remains uncertain.
Objective: To evaluate the diagnostic performance of f-QRS for detecting myocardial scars assessed by 3.0 CMR.
Methods: Patients who underwent 3.0 Tesla CMR between May 2020 and May 2023 were included. A 12-lead ECG was assessed for f-QRS, defined as the presence of an R' wave or notching in the nadir of the S wave in at least 2 contiguous leads. The diagnostic performance of f-QRS in detecting myocardial scars in corresponding left ventricular segments was analyzed.
Results: Overall, 1692 patients were included. f-QRS presented in 826 (49%) participants which were more prevalent in men (59.4% vs 46.0%), those with a history of coronary artery disease (26.4% vs 20.6%), and those with myocardial scars (48.9% vs 37.3). The sensitivity and specificity of f-QRS from ECG were 25.6% and 88.7% for anterior; 22.1% and 91.5%, for lateral; and 42.9% and 63.4% for inferior segments.
Conclusion: f-QRS demonstrates high specificity for detecting myocardial scars on CMR, though its sensitivity is limited.
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http://dx.doi.org/10.1016/j.hroo.2025.05.014 | DOI Listing |
Heart Rhythm O2
August 2025
Division of Cardiovascular Medicine, Department of Medicine, Faculty of Medicine, Chulalongkorn University, King Chulalongkorn Memorial Hospital, Bangkok, Thailand.
Background: Fragmented QRS complex (f-QRS) on a 12-lead electrocardiogram (ECG) has been associated with myocardial scars. However, its diagnostic accuracy for detecting myocardial scars assessed by cardiac magnetic resonance (CMR) imaging remains uncertain.
Objective: To evaluate the diagnostic performance of f-QRS for detecting myocardial scars assessed by 3.
Stem Cell Res Ther
September 2025
Armed Forces Bone Marrow Transplant Center, Rawalpindi, Pakistan.
Background: Myocardial infarction (MI) results in loss of cardiomyocytes leading to heart failure. Despite advancements in pharmacotherapy and interventions such as revascularization, ischemic heart failure remains a challenge. Recent advancements in stem cell therapies, genetic engineering and bioengineering have shown to improve cardiac function and quality of life.
View Article and Find Full Text PDFBiomedicines
August 2025
Humanitas Gavazzeni, Via Mauro Gavazzeni, 21, 24125 Bergamo, BG, Italy.
The widespread use of cardiac magnetic resonance imaging (MRI) in clinical practice has enabled the identification of numerous patients with evident damage from previous myocarditis, whether known or unknown. For years, myocardial fibrosis has been a topic of interest due to its established correlation with arrhythmic events in various clinical settings, including ischemic heart disease, dilated cardiomyopathy, and hypertrophic cardiomyopathy. MIBG scintigraphy is a method widely used in patients who are candidates for defibrillator implantation or have experienced heart failure.
View Article and Find Full Text PDFCirc Arrhythm Electrophysiol
August 2025
Instituto de Investigación Sanitaria Gregorio Marañón (IiSGM), Servicio de Cardiología, Hospital General Universitario Gregorio Marañón, Madrid, Spain (A.C.-B., J.B., A.A.-M.).
Background: Identification of fast ventricular tachycardia (FVT; cycle length <320 ms) isthmuses is often hindered by hemodynamic instability during sustained FVT and by rate-dependent (functional) scar properties. Comparing ultra-high-density voltage heterogeneity maps (0.1-1.
View Article and Find Full Text PDFJ Cardiovasc Magn Reson
August 2025
Department of Radiology, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
Background: Late Gadolinium Enhancement (LGE) imaging remains the gold standard for assessing myocardial fibrosis and scarring, with left ventricular (LV) LGE presence and extent serving as a predictor of major adverse cardiac events (MACE). Despite its clinical significance, LGE-based LV scar quantification is not used routinely due to the labor-intensive manual segmentation and substantial inter-observer variability.
Methods: We developed ScarNet that synergistically combines a transformer-based encoder in Medical Segment Anything Model (MedSAM), which we fine-tuned with our dataset, and a convolution-based decoder in U-Net with tailored attention blocks to automatically segment myocardial scar boundaries while maintaining anatomical context.