Total Bolus Transit Time Predicts Cardiac Dysfunction in Acute Ischemic Stroke and Transient Ischemic Attack Patients: A Retrospective Double Center Study.

Figures

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  FIGURE 1. Relationship between bolus‐tracking parameters and left ventricular ejection fraction (LVEF), and diagnostic accuracy for reduced ejection fraction. (A) Scatter plot depicting the inverse correlation between T40HU and LVEF (Spearman's ρ = −0.40; p < 0.01). (B) Scatter plot showing the inverse correlation between T100HU and LVEF (Spearman's ρ = −0.52; p < 0.01). In both panels, each point represents an individual patient, with orange circles indicating normal or mildly reduced ejection fraction (NoMrEF) and black triangles indicating reduced ejection fraction (rEF). The red line denotes the linear regression fit, and the shaded gray area represents the 95% confidence interval. (C) Receiver operating characteristic (ROC) curves for T40HU (blue) and T100HU (red) predicting heart failure with reduced ejection fraction (LVEF < 40%). The green diagonal represents the line of no discrimination (reference line). T100HU showed superior diagnostic performance (AUROC = 0.85; 95% CI: 0.79–0.91; p < 0.01) compared to T40HU (AUROC = 0.77; 95% CI: 0.72–0.85; p < 0.01). EF = ejection fraction; rEF = reduced ejection fraction; NoMrEF = normal or mildly reduced ejection fraction; HU = Hounsfield…

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  FIGURE 2. Relationship between ΔT100–T40HU and left ventricular ejection fraction (LVEF), and diagnostic accuracy for reduced ejection fraction (rEF). (A) Scatter plot showing a significant inverse correlation between ΔT100–T40HU and LVEF (Spearman's ρ = −0.54; p < 0.01). Orange dots represent patients with normal or mildly reduced ejection fraction (NoMrEF); black triangles indicate patients with reduced ejection fraction (rEF). The red line shows the linear regression fit with a 95% confidence interval in gray. (B) Receiver operating characteristic (ROC) curve assessing the diagnostic performance of ΔT100–T40HU as a continuous variable (red line) and stratified into three Δ‐groups (blue line) for the identification of rEF (LVEF < 40%). Both models showed good diagnostic accuracy (AUROC = 0.88). The green diagonal represents the line of no discrimination.

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  FIGURE 3. ΔT100–T40HU as an independent predictor of reduced ejection fraction (rEF) and cardioembolic stroke etiology. (A) Forest plot illustrating the results of the binary logistic regression analysis evaluating predictors of reduced ejection fraction (rEF) in ischemic stroke patients. Male sex, smoke, mitral‐valve failure, and ΔT100–T40HU were independently associated with rEF. (B) Forest plot showing the results of the binary logistic regression analysis for predictors of cardioembolic stroke etiology. Age, mitral‐valve failure, history of congestive heart failure, and ΔT100–T40HU were identified as independent predictors. Adjusted odds ratios (aORs) are represented with corresponding 95% confidence intervals (CIs). EF = ejection fraction; rEF = reduced ejection fraction; NoMrEF = normal or mildly reduced ejection fraction; HU = Hounsfield units.