AI-Derived Pericardial Effusion Volume and Long-Term Mortality After Transcatheter Aortic Valve Implantation

Background: Pericardial effusion is a common finding on pre-procedural computed tomography (CT) in patients undergoing transcatheter aortic valve implantation (TAVI). However, its clinical significance remains uncertain. Using artificial intelligence (AI)-based image analysis, we sought to determine whether pericardial effusion represents an incidental imaging finding, a marker of hemodynamic burden, or a prognostically relevant phenotype. Methods: This retrospective single-center study included 470 consecutive patients undergoing TAVI for severe aortic stenosis. Pericardial effusion volume was quantified using an AI-based CT segmentation workflow and categorized as no effusion (0 mL), trace effusion (>0–<5 mL), small effusion (5–<30 mL), or larger effusion (≥30 mL). Associations with baseline clinical and echocardiographic characteristics were assessed. Long-term mortality was evaluated using Kaplan–Meier analysis, Cox regression models, and restricted cubic spline analyses. Results: Detectable pericardial effusion was present in 276 patients (58.7%), although larger effusions were uncommon (5.1%). Increasing pericardial effusion volume was associated with a higher prevalence of atrial fibrillation (p = 0.001), higher systolic pulmonary artery pressure (p = 0.004), and lower TAPSE/sPAP ratios (p = 0.007). In contrast, left ventricular ejection fraction and transvalvular gradients did not differ across effusion categories. During long-term follow-up, no significant differences in mortality were observed between pericardial effusion groups (log-rank p = 0.46). Pericardial effusion volume was not associated with mortality when analyzed as a continuous variable (HR 1.00, 95% CI 0.996–1.01; p = 0.842), after logarithmic transformation (adjusted HR 0.91, 95% CI 0.76–1.08; p = 0.293), or in restricted cubic spline analyses. Conclusions: AI-derived pericardial effusion volume identifies a hemodynamic phenotype characterized by atrial fibrillation, pulmonary hypertension, and impaired right ventricular–pulmonary arterial coupling. Despite these associations, pericardial effusion volume does not independently predict long-term mortality after TAVI, suggesting that it reflects cardiovascular congestion and remodeling rather than a prognostically relevant phenotype.

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Journal
Journal of Clinical Medicine
Published
2026-08-18
DOI
https://doi.org/10.3390/jcm15166388
Primary Topic
Cardiac Valve Diseases and Treatments
Type
article
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article

AI-Derived Pericardial Effusion Volume and Long-Term Mortality After Transcatheter Aortic Valve Implantation

Bernhard Scharinger, Elke Boxhammer, Matthias Hammerer, Luther E. Preuss et al.
Journal of Clinical Medicine
Cardiac Valve Diseases and Treatments
article

AI-Derived Pericardial Effusion Volume and Long-Term Mortality After Transcatheter Aortic Valve Implantation

Bernhard Scharinger, Elke Boxhammer, Matthias Hammerer, Luther E. Preuss, Klaus Hergan, Nikolaos Schörghofer, Christoph Knapitsch, Gretha Hecke, Nikolaus Clodi, Uta C. Hoppe
article en

Abstract

Background: Pericardial effusion is a common finding on pre-procedural computed tomography (CT) in patients undergoing transcatheter aortic valve implantation (TAVI). However, its clinical significance remains uncertain. Using artificial intelligence (AI)-based image analysis, we sought to determine whether pericardial effusion represents an incidental imaging finding, a marker of hemodynamic burden, or a prognostically relevant phenotype. Methods: This retrospective single-center study included 470 consecutive patients undergoing TAVI for severe aortic stenosis. Pericardial effusion volume was quantified using an AI-based CT segmentation workflow and categorized as no effusion (0 mL), trace effusion (>0–<5 mL), small effusion (5–<30 mL), or larger effusion (≥30 mL). Associations with baseline clinical and echocardiographic characteristics were assessed. Long-term mortality was evaluated using Kaplan–Meier analysis, Cox regression models, and restricted cubic spline analyses. Results: Detectable pericardial effusion was present in 276 patients (58.7%), although larger effusions were uncommon (5.1%). Increasing pericardial effusion volume was associated with a higher prevalence of atrial fibrillation (p = 0.001), higher systolic pulmonary artery pressure (p = 0.004), and lower TAPSE/sPAP ratios (p = 0.007). In contrast, left ventricular ejection fraction and transvalvular gradients did not differ across effusion categories. During long-term follow-up, no significant differences in mortality were observed between pericardial effusion groups (log-rank p = 0.46). Pericardial effusion volume was not associated with mortality when analyzed as a continuous variable (HR 1.00, 95% CI 0.996–1.01; p = 0.842), after logarithmic transformation (adjusted HR 0.91, 95% CI 0.76–1.08; p = 0.293), or in restricted cubic spline analyses. Conclusions: AI-derived pericardial effusion volume identifies a hemodynamic phenotype characterized by atrial fibrillation, pulmonary hypertension, and impaired right ventricular–pulmonary arterial coupling. Despite these associations, pericardial effusion volume does not independently predict long-term mortality after TAVI, suggesting that it reflects cardiovascular congestion and remodeling rather than a prognostically relevant phenotype.

Journal of Clinical MedicineVol. 15(16)
Paracelsus Medical University (AT)
Good health and well-being
Openalex Percentile: Top 9%
Cardiac Valve Diseases and Treatments
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