Po-01-210 Stroke Risk Is Identified by Slow Blood Flow and Stagnant Blood Particles in the Left Atrium

Zingaro, Alberto; Ahmad, Zaheer; Pinto, Carolyna Yamamoto Alves; Sakata, Kensuke; Kholmovski, Eugene; Dedè, Luca; Quarteroni, Alfio; Trayanova, Natalia A.

doi:10.1016/j.hrthm.2023.03.528

Cited by 2 publications

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“…This gap in current risk stratification models underscores an urgent need for a more nuanced, individualized approach that encapsulates the hemodynamic intricacies and geometric variabilities inherent within the LA. This need can be addressed by the use of in-silico methodologies as a noninvasive tool to predict the likelihood of thrombus formation and stroke risk in an individual subject [20][21][22][23][24][25][26][27][28][29][30][31][32] .…”

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confidence: 99%

A comprehensive stroke risk assessment by combining atrial computational fluid dynamics simulations and functional patient data

Zingaro,

Ahmad,

Kholmovski

et al. 2024

Preprint

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Stroke, a major global health concern often rooted in cardiac dynamics, demands precise risk evaluation for targeted intervention. Current risk models, like the CHA2DS2-VASc score, often lack the granularity required for personalized predictions. In this study, we present a nuanced and thorough stroke risk assessment by integrating functional insights from cardiac magnetic resonance (CMR) with patient-specific computational fluid dynamics (CFD) simulations. Our cohort, evenly split between control and stroke groups, comprises eight patients. Utilizing CINE CMR, we compute kinematic features, revealing smaller left atrial volumes for stroke patients. The incorporation of patient-specific atrial displacement into our hemodynamic simulations unveils the influence of atrial compliance on the flow fields, emphasizing the importance of LA motion in CFD simulations and challenging the conventional rigid wall assumption in hemodynamics models. Standardizing hemodynamic features with functional metrics enhances the differentiation between stroke and control cases. While standalone assessments provide limited clarity, the synergistic fusion of CMR-derived functional data and patient-informed CFD simulations offers a personalized and mechanistic understanding, distinctly segregating stroke from control cases. Specifically, our investigation reveals a crucial clinical insight: normalizing hemodynamic features based on ejection fraction fails to differentiate between stroke and control patients. Differently, when normalized with stroke volume, a clear and clinically significant distinction emerges and this holds true for both the left atrium and its appendage, providing valuable implications for precise stroke risk assessment in clinical settings. This work introduces a novel framework for seamlessly integrating hemodynamic and functional metrics, laying the groundwork for improved predictive models, and highlighting the significance of motion-informed, personalized risk assessments.

show abstract

Section: Introductionmentioning

confidence: 99%

A comprehensive stroke risk assessment by combining atrial computational fluid dynamics simulations and functional patient data

Zingaro,

Ahmad,

Kholmovski

et al. 2024

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

A comprehensive stroke risk assessment by combining atrial computational fluid dynamics simulations and functional patient data

Zingaro,

Ahmad,

Kholmovski

et al. 2024

Sci Rep

View full text Add to dashboard Cite

Stroke, a major global health concern often rooted in cardiac dynamics, demands precise risk evaluation for targeted intervention. Current risk models, like the $$\text {CHA}_2\text {DS}_2\text {-VASc}$$ CHA 2 DS 2 -VASc score, often lack the granularity required for personalized predictions. In this study, we present a nuanced and thorough stroke risk assessment by integrating functional insights from cardiac magnetic resonance (CMR) with patient-specific computational fluid dynamics (CFD) simulations. Our cohort, evenly split between control and stroke groups, comprises eight patients. Utilizing CINE CMR, we compute kinematic features, revealing smaller left atrial volumes for stroke patients. The incorporation of patient-specific atrial displacement into our hemodynamic simulations unveils the influence of atrial compliance on the flow fields, emphasizing the importance of LA motion in CFD simulations and challenging the conventional rigid wall assumption in hemodynamics models. Standardizing hemodynamic features with functional metrics enhances the differentiation between stroke and control cases. While standalone assessments provide limited clarity, the synergistic fusion of CMR-derived functional data and patient-informed CFD simulations offers a personalized and mechanistic understanding, distinctly segregating stroke from control cases. Specifically, our investigation reveals a crucial clinical insight: normalizing hemodynamic features based on ejection fraction fails to differentiate between stroke and control patients. Differently, when normalized with stroke volume, a clear and clinically significant distinction emerges and this holds true for both the left atrium and its appendage, providing valuable implications for precise stroke risk assessment in clinical settings. This work introduces a novel framework for seamlessly integrating hemodynamic and functional metrics, laying the groundwork for improved predictive models, and highlighting the significance of motion-informed, personalized risk assessments.

show abstract

Po-01-210 Stroke Risk Is Identified by Slow Blood Flow and Stagnant Blood Particles in the Left Atrium

Cited by 2 publications

References 0 publications

A comprehensive stroke risk assessment by combining atrial computational fluid dynamics simulations and functional patient data

A comprehensive stroke risk assessment by combining atrial computational fluid dynamics simulations and functional patient data

A comprehensive stroke risk assessment by combining atrial computational fluid dynamics simulations and functional patient data

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