High-Resolution 3D Cine MRI Analysis of Left Atrial Displacements and Strains using Online Learning Neural Networks

المفاهيم الأساسية

Aladdin, a novel end-to-end workflow, can reliably provide high-resolution 3D maps of left atrial displacements and strains from cardiac cine MRI, enabling comprehensive characterization of left atrial function.

الملخص

This study presents Aladdin, a novel workflow for the comprehensive analysis of left atrial (LA) motion and deformation using high-resolution 3D cardiac cine MRI. Aladdin includes:

An online learning segmentation neural network (nnU-Net) to accurately segment the LA across the cardiac cycle.
An online weakly supervised learning image registration neural network (Aladdin-R) to estimate the LA displacement vector fields (DVFs) across the cardiac cycle.
An algorithm to calculate regional LA principal strains from the estimated DVFs.
The construction of an atlas of LA DVFs and strains using data from 10 healthy volunteers.
Proof-of-concept characterization of regional LA strains in 8 cardiovascular disease (CVD) patients, including 2 with reduced left ventricular ejection fraction (LVEF↓).

The results show that Aladdin can accurately track the LA wall and characterize its motion and deformation. Global LA function markers assessed with Aladdin agree well with estimates from 2D cine MRI. A more marked active contraction phase was observed in the healthy cohort, while the CVD LVEF↓ group showed overall reduced LA function. Aladdin is uniquely able to identify LA regions with abnormal deformation metrics that may indicate focal pathology. This framework has the potential to provide novel clinical biomarkers of atrial pathophysiology.

الإحصائيات

"The healthy cohort had average DVF magnitudes of 0.67 ± 0.40 mm and principal strain values of 0.04 ± 0.04 across the cardiac cycle."
"The CVD cases had slightly higher averages of 0.71 ± 0.43 mm and 0.05 ± 0.04."
"The CVD LVEF↓ cases had much lower values of 0.34 ± 0.15 mm and 0.02 ± 0.02."

اقتباسات

"Aladdin is uniquely able to identify LA regions with abnormal deformation metrics that may indicate focal pathology."
"This framework has the potential to provide novel clinical biomarkers of atrial pathophysiology."

الرؤى الأساسية المستخلصة من

High-Resolution Maps of Left Atrial Displacements and Strains Estimated with 3D Cine MRI using Online Learning Neural Networks

by Chri... في arxiv.org 09-19-2024

https://arxiv.org/pdf/2312.09387.pdf

استفسارات أعمق

How can the Aladdin framework be extended to analyze the right atrium or right ventricle, which are also often approximated as thin surfaces?

The Aladdin framework, designed for the analysis of left atrial (LA) displacements and strains, can be effectively extended to analyze the right atrium (RA) and right ventricle (RV) by adapting its segmentation and image registration components to accommodate the unique anatomical and functional characteristics of these chambers.

Segmentation Adaptation: The existing nnU-Net segmentation network can be retrained or fine-tuned using annotated datasets specific to the RA and RV. Given that the RA and RV have different shapes and wall thicknesses compared to the LA, the training data should include a diverse range of cardiac morphologies to ensure robust performance across various patient populations.

Image Registration Modifications: The Aladdin-R image registration network can be modified to account for the distinct motion patterns and structural differences of the RA and RV. This may involve incorporating additional anatomical landmarks or features specific to these chambers to improve the accuracy of displacement vector field (DVF) estimations.

Biomechanical Modeling: The framework can integrate biomechanical models that account for the unique mechanical properties of the RA and RV myocardium. This would enhance the accuracy of strain calculations and provide insights into the regional mechanics of these chambers.

Data Integration: By leveraging multi-modal imaging data, such as combining Cine MRI with echocardiography or CT imaging, the Aladdin framework can enhance its analysis capabilities for the RA and RV, allowing for a more comprehensive assessment of their function and pathology.

Clinical Applications: Extending Aladdin to the RA and RV could facilitate the identification of regional motion abnormalities and strain patterns that are critical for understanding conditions such as right heart failure, pulmonary hypertension, and atrial fibrillation, thereby broadening its clinical utility.

What other biophysical variables beyond displacements and principal strains could be computed from the Aladdin outputs to provide additional insights into atrial function and pathology?

In addition to displacements and principal strains, several other biophysical variables can be derived from the Aladdin outputs to enhance the understanding of atrial function and pathology:

Shear Strains: By calculating shear strains, which quantify the deformation of the myocardium in response to applied stresses, clinicians can gain insights into the mechanical behavior of the atrial walls, particularly in regions susceptible to fibrosis or other pathological changes.

Strain Rate: The temporal derivative of strain, known as strain rate, can provide information on the speed of deformation during different cardiac phases. This metric is particularly useful for assessing the dynamic function of the atria and can be correlated with clinical outcomes in conditions like atrial fibrillation.

Ejection Fraction Metrics: Beyond the traditional left atrial ejection fraction (LAEF), metrics such as active ejection fraction (LAaEF) can be computed to evaluate the contractile function of the atrium during different phases of the cardiac cycle, offering insights into atrial performance.

Regional Wall Stress: By integrating the calculated strains with the geometry of the atrial walls, regional wall stress can be estimated. This is crucial for understanding the mechanical load experienced by the atrial myocardium, which can influence the development of atrial remodeling and fibrosis.

Tissue Elasticity and Compliance: Estimating the elastic properties of the atrial myocardium can provide valuable information about its stiffness and compliance, which are important factors in the pathophysiology of atrial fibrillation and other cardiovascular diseases.

3D Motion Patterns: Analyzing the 3D motion patterns of the atrial walls can reveal complex interactions between different regions of the atrium, which may be indicative of underlying pathologies or functional impairments.

Could the Aladdin-derived regional strain metrics be used to guide personalized catheter ablation procedures for atrial fibrillation treatment?

Yes, the Aladdin-derived regional strain metrics have the potential to significantly enhance personalized catheter ablation procedures for atrial fibrillation (AF) treatment. Here’s how:

Identification of Abnormal Regions: By utilizing the high-resolution maps of regional strains and displacements generated by Aladdin, clinicians can identify specific areas of the atrium that exhibit abnormal deformation patterns. These regions may correspond to areas of fibrosis or electrical conduction abnormalities, which are critical targets for catheter ablation.

Guiding Ablation Strategy: The detailed strain metrics can inform the selection of ablation sites by highlighting regions with reduced strain or abnormal motion, which are more likely to contribute to AF. This targeted approach can improve the efficacy of the procedure and reduce the risk of complications.

Monitoring Treatment Efficacy: Post-ablation, the Aladdin framework can be employed to reassess the regional strain metrics, allowing for the evaluation of treatment success. Changes in strain patterns can indicate whether the ablation has effectively modified the atrial substrate and improved function.

Personalized Treatment Plans: By integrating patient-specific strain data with clinical history and imaging findings, healthcare providers can develop tailored ablation strategies that consider the unique anatomical and functional characteristics of each patient’s atrium, potentially leading to better outcomes.

Predicting Recurrence: The ability to quantify regional strain metrics pre- and post-ablation can help in predicting the likelihood of AF recurrence. Patients with persistent abnormal strain patterns may require more aggressive or additional treatment strategies.

In summary, the Aladdin-derived regional strain metrics can provide valuable insights that enhance the precision and effectiveness of catheter ablation procedures for atrial fibrillation, ultimately leading to improved patient outcomes.