LATEST TECHNOLOGIES IN THE DIAGNOSIS OF LEFT ATRIAL CARDIOMYOPATHY: FROM CONCEPT TO CLINICAL IMPLEMENTATION OF NON-INVASIVE IMAGING METHODS

Authors

DOI:

https://doi.org/10.30890/2567-5273.2025-40-02-042

Keywords:

left atrial cardiomyopathy, artificial intelligence, 4D echocardiography, parametric MRI mapping, aggressive course of atrial fibrillation.

Abstract

The paper analyzes the capabilities of the latest non-invasive imaging technologies for the diagnosis of left atrial cardiomyopathy in patients with atrial fibrillation and substantiates the feasibility of introducing these methods into clinical practice.

References

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Firouznia M, Feeny AK, LaBarbera MA, et al. Machine learning-derived fractal features of shape and texture of the left atrium and pulmonary veins from cardiac computed tomography scans are associated with risk of recurrence of atrial fibrillation post-ablation. Circ Arrhythm Electrophysiol. 2021;14(6):e009265.

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Published

2025-08-30

How to Cite

Кожин, М., & Ринчак, П. (2025). LATEST TECHNOLOGIES IN THE DIAGNOSIS OF LEFT ATRIAL CARDIOMYOPATHY: FROM CONCEPT TO CLINICAL IMPLEMENTATION OF NON-INVASIVE IMAGING METHODS. Modern Engineering and Innovative Technologies, 2(40-02), 212–219. https://doi.org/10.30890/2567-5273.2025-40-02-042

Issue

Section

Articles