Personalized biomechanical insights in atrial fibrillation: opportunities & challenges

ABSTRACT

Introduction

Atrial fibrillation (AF) is an increasingly prevalent and significant worldwide health problem. Manifested as an irregular atrial electrophysiological activation, it is associated with many serious health complications. AF affects the biomechanical function of the heart as contraction follows the electrical activation, subsequently leading to reduced blood flow. The underlying mechanisms behind AF are not fully understood, but it is known that AF is highly correlated with the presence of atrial fibrosis, and with a manifold increase in risk of stroke.

Areas Covered

In this review, we focus on biomechanical aspects in atrial fibrillation, current and emerging use of clinical images, and personalized computational models. We also discuss how these can be used to provide patient-specific care.

Expert Opinion

Understanding the connection betweenatrial fibrillation and atrial remodeling might lead to valuable understanding of stroke and heart failure pathophysiology. Established and emerging imaging modalities can bring us closer to this understanding, especially with continued advancements in processing accuracy, reproducibility, and clinical relevance of the associated technologies. Computational models of cardiac electromechanics can be used to glean additional insights on the roles of AF and remodeling in heart function.

Plain Language Summary

People with atrial fibrillation (AF) experience a fast, chaotic heartbeat. AF greatly increases the risk of stroke. The hearts of AF patients often have an accumulation of fibrous tissue (fibrosis). Fibrosis patterns can be detected via medical imaging scans, like MRI. These images can be used to build patient-specific digital representations. These models can be used to explore how fibrosis might cause AF, stroke, and other health risks. Insights from imaging and modeling are becoming more and more useful as tools for personalizing AF treatment.

KEYWORDS:

• Atrial fibrillation
• atrial fibrosis
• biomechanics
• medical imaging
• multiphysics modeling
• patient-specific modeling
• patient-specific care

Article highlights

• AF is tightly connected to electrical and structural remodeling, which affects the biomechanical atrial function through various pathways.

• LGE-MRI is the most studied imaging modality for cardiac fibrosis assessment and can serve as an important aid in clinical decision-making. Better image processing tools and use of other imaging techniques, such as T₁ mapping, strain, elastography, and 4D flow MRI are expected to yield additional insights, especially when applied in combination.

• We anticipate that computational models will guide understanding of sub-mechanisms and facilitate quantifications that are not possible to perform with conventional experimental approaches. This will lead to deeper understanding of how AF, atrial fibrosis, and stroke are interconnected. Models are based on atrial geometries and incorporating additional clinical data should be immensely valuable, improving model usefulness and personalization.

• Few multi-physics models of the atria or the whole heart have been developed to date. Biomechanical models can borrow from the more advanced field of electrophysiological modeling, such as considering the same fibrosis patterns, but the need remains for independent experiments to determine biomechanical-specific quantities such as alterations in tissue stiffness and structural anisotropy.

• Augmenting clinical characteristics with advanced imaging and computational tools that are rooted in the mechanisms of arrhythmia, biomechanical, and hemostatic alterations will allow for a more personalized approach to patient care decisions.

Abbreviations and acronyms

4D – four-dimensional (3D + time = 4D); AF – atrial fibrillation; CFD – computational fluid dynamics; CT – computed tomography; ESUS – embolic stroke of undetermined source; ECG – electrocardiogram; IIR – image intensity ratio; LAA – left atrial appendage; LGE – late gadolinium enhancement; MRE – magnetic resonance elastography; MRI – magnetic resonance imaging; PACS – peak atrial contractile strain; PALS – peak atrial longitudinal strain; PIH – pixel intensity histogram; SD – standard deviation(s); STE – speckle-tracking echocardiography; SWE – shear wave elastography; TDI – tissue doppler imaging; TEE – transesophageal echocardiography

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial relationships or otherwise to disclose.

Additional information

Funding

The work was supported by the following grants: NIH R01-HL160024, NIH R01-HL158667, NIH R01-NS125635, the John Locke Charitable Trust, and the Catherine Holmes Wilkins Charitable Foundation.