Key result
Normalizing hemodynamic features based on stroke volume, rather than ejection fraction, provided a clear and clinically significant distinction between stroke and control patients.
Why the study?
Existing clinical stroke risk scores often lack the granularity required for personalized predictions.
Does combining atrial computational fluid dynamics simulations and functional patient data improve the differentiation between stroke and control patients?
Case-Control (n=8)
Does combining atrial computational fluid dynamics simulations and functional patient data improve the differentiation between stroke and control patients?
Normalizing atrial hemodynamic features by stroke volume using patient-specific CFD and CMR data successfully differentiates stroke from control patients, offering a novel approach to personalized stroke risk assessment.
Hypothesis-generating for personalized stroke risk models; requires validation in larger prospective trials before clinical use.
-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.
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Zingaro et al. (2024) conducted a case-control in Stroke (n=8). History of stroke vs. Control (no history of stroke) was evaluated on Differentiation of hemodynamic features (Flow Stasis, TAWSS, OSI, RRT, ECAP) normalized by stroke volume. Normalizing hemodynamic features based on stroke volume, rather than ejection fraction, provided a clear and clinically significant distinction between stroke and control patients.
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