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Updated: Jul 10, 2026
Computerized Adaptive Testing System of Functional Assessment of Stroke
Published on: January 7, 2019
A comprehensive stroke risk assessment by combining atrial computational fluid dynamics simulations and functional
Alberto Zingaro1,2,3, Zan Ahmad1,4, Eugene Kholmovski1,5
1ADVANCE, Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, 3400 N. Charles St., 21218, Baltimore, MD, USA.
Insights
Integrating cardiac magnetic resonance (CMR) and computational fluid dynamics (CFD) offers personalized stroke risk assessment. Normalizing hemodynamic features by stroke volume, not ejection fraction, significantly distinguishes stroke patients.
Area of Science:
- Cardiovascular Medicine
- Biomedical Engineering
- Medical Imaging
Background:
- Stroke is a leading cause of death and disability globally, necessitating improved risk prediction.
- Existing stroke risk scores, such as CHA2DS2-VASc, may lack personalized predictive power.
- Cardiac dynamics play a crucial role in stroke etiology, yet are not fully integrated into risk models.
Conclusions:
- The synergistic fusion of CMR-derived functional data and patient-specific CFD simulations provides a personalized and mechanistic understanding of stroke risk.
- Motion-informed, personalized risk assessments are crucial for improved stroke prediction.
- This novel framework enhances stroke risk stratification, offering valuable clinical implications.
Abstract:
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.
