Niema Mohammed Pahlevan

Background: Restoration of cerebral blood flow (CBF) after ischemic stroke does not necessarily indicate recovery of cerebrovascular regulation. We tested whether myogenic‐band dynamics derived directly from CBF signals provide information beyond mean perfusion during cerebral ischemia and after acute stroke. Methods: Transient focal cerebral ischemia was induced in 29 Sprague–Dawley rats using middle cerebral artery occlusion/reperfusion. Bilateral laser‐Doppler flowmetry (LDF)‐derived CBF signals were decomposed using empirical mode decomposition and Hilbert transform, and myogenic‐band activity (0.15–0.4 Hz) was quantified by absolute and relative power. Cross‐validated logistic regression models were used to evaluate whether myogenic‐band power provided discriminative information beyond mean CBF alone. Results: Ipsilateral mean CBF fell from 73.5±51.8 p.u. at baseline to 52.2±38.0 p.u. during late ischemia (P=0.0088), then increased to 126.6±91.5 p.u. after 3 hours of reperfusion (P=0.0050 versus baseline). Relative myogenic‐band power decreased from 37.43±14.65% to 13.35±7.51% during ischemia (P<0.0001) and remained below baseline after reperfusion (20.74±12.02%, P=0.00033 versus baseline); contralateral relative power was comparatively preserved. Combining mean CBF and myogenic‐band power improved discrimination of baseline from late ischemia (AUC, 0.99 versus 0.70 for mean CBF alone) and late reperfusion (AUC, 0.88 versus 0.70). Conclusions: Frequency‐specific analysis of LDF‐derived CBF reveals persistent, lateralized abnormalities in myogenic‐band dynamics that are not captured by mean perfusion alone. The persistence of depressed myogenic activity despite restored or elevated mean CBF demonstrates incomplete recovery of frequency‐specific oscillatory dynamics after reperfusion. These findings support myogenic‐band power as a potential functional measure of persistent postischemic cerebrovascular dysfunction.

Diastolic dysfunction is a central driver of heart failure, yet the fluid-dynamic mechanisms underlying altered left ventricular (LV) filling are not fully understood. In this study, we characterize intraventricular vortex dynamics and hemodynamic performance across diastolic function inflow patterns using a physiologically accurate in vitro LV simulator. Diastolic function inflow patterns (impaired relaxation, normal, restrictive filling) were modeled by independently varying the E/A ratio (ratio of the early and late diastolic peak inflows), diastasis duration (0–20% of the cardiac cycle), heart rate (60–90 bpm), and stroke volume while maintaining clinically relevant inflow velocities (0.5–0.9 m/s). Quantitative flow analysis was performed using phase-locked particle image velocimetry. Hemodynamic metrics of two-dimensional viscous energy dissipation (VED), shear rate, and turbulent kinetic energy (TKE) were calculated from planar velocity field measurements. Abnormal inflow patterns exhibited higher energy losses than normal inflow patterns. Restrictive filling inflow patterns produced the highest peak VED (50% greater than normal) and increased TKE (38% greater), whereas impaired relaxation inflow patterns led to pronounced vortex pair merging, yielding the highest peak TKE (57% greater than normal). A moderate diastasis duration minimized VED across E/A ratios, identifying a local energetic optimum at 3.3 L/min, which was not observed under low-cardiac output conditions. In impaired relaxation inflow patterns, diastole-averaged VED scaled nonlinearly with stroke volume and linearly with heart rate at a constant cardiac output. These results characterize how the E/A ratio and diastasis independently govern LV vortex interactions and energetic efficiency, providing insights into the hemodynamic mechanisms of diastolic dysfunction, and may motivate future clinical studies to identify potential markers of disease severity.

Increased blood pressure variability (BPV) is associated with increased risk for dementia, independent of hypertension. The increased risk for dementia associated with high BPV includes probable Alzheimer disease (AD) dementia, but high BPV is also associated with increased risk of stroke and cerebral small vessel disease, which are commonly comorbid with AD. This raises the question of whether high BPV is independently predictive of AD-specific pathophysiology and neurodegeneration, which could have significant clinical implications. Fewer studies have directly addressed this question by examining whether higher BPV predicts future AD biomarker abnormalities that are specific to AD pathophysiology within the amyloid/tau/neurodegeneration framework. This narrative review summarizes current studies on this topic and discusses future directions in the investigation of elevated BPV as a risk factor for AD, the most common cause of dementia in older adults.

The electrocardiogram (ECG) contains rich nonlinear and non-stationary dynamic information that is only partly captured by conventional ECG interpretation and beat-to-beat metrics, and is increasingly analyzed using black-box artificial intelligence models that often lack interpretability. Here, we introduce the ECG time–frequency “eyeball”, an interpretable framework that transforms a brief single-lead ECG recording into a geometric signature and a set of low-dimensional rotational and geometrical features using empirical mode decomposition and Hilbert-based analytic signal mapping. In 30-second Lead I–equivalent recordings from 170 healthy subjects and 80 patients with acute myocardial infarction (AMI), the proposed “eyeball” metrics significantly differentiated groups, with AMI associated with higher rotational frequency metrics, lower envelope metrics, and displaced centroid location. Representative examples revealed a coherent morphologic spectrum from normal patterns to geometries consistent with myocardial ischemia, injury, and infarction. The representation remained stable across recording windows from 30 seconds to 5 minutes, and individual “eyeball” features achieved areas under the receiver operating characteristic curve (AUCs) of up to 0.78 for AMI detection. These findings suggest that the ECG time–frequency “eyeball” condenses clinically relevant nonlinear ECG dynamics into an interpretable representation that may reveal hidden AMI signatures, complement conventional ECG interpretation, and provide a foundation for accessible single-lead cardiovascular screening using future smart wearables.

Background: Empagliflozin, a sodium–glucose cotransporter 2 inhibitor, has demonstrated cardioprotective and neuroprotective effects in preclinical myocardial infarction (MI) and ischemic stroke settings by reducing acute myocardial and cerebral infarction sizes. However, the optimal administration for acute protection remains unclear. Particularly, empagliflozin effects when administered after ischemia onset but before reperfusion have not been systematically evaluated for acute MI and stroke models. Methods: Sprague–Dawley rats underwent either middle cerebral artery occlusion/reperfusion to induce acute ischemic stroke (n=25), or left coronary artery occlusion/reperfusion to induce acute MI (n=29). Empagliflozin (20 mg/kg) or saline was administered 10 minutes after ischemia onset. Outcomes included brain/heart injury sizes and cardiac hemodynamics were quantified after 3 hours of reperfusion. Results: In the stroke model, postocclusion empagliflozin administration significantly reduced cerebral total infarct volume compared with controls (80.83±16.59 versus 164.10±26.23 mm ³ , P =0.014), corresponding to ≈50% reduction in the infarct volume percentage, while edema was unchanged. In the MI model, empagliflozin did not reduce myocardial infarct size, ischemic risk area, or no‐reflow zone when given after occlusion/before reperfusion. Conclusions: Our findings highlight that empagliflozin, when administered after ischemia onset but before reperfusion, provides robust neuroprotection in acute ischemic stroke but fails to limit myocardial injury in acute MI. The divergent outcomes may reflect organ‐specific pathophysiology; for example, cerebral collaterals preserve residual perfusion and drug delivery, whereas limited cardiac collateralization leads to rapid necrosis and poor drug access. Clinically, these findings suggest that early postocclusion empagliflozin therapy may be beneficial in ischemic stroke, whereas comparable early administration appears insufficient in MI.

Background: Clinical studies have shown that aortic arch pulse‐wave velocity (PWV _aa ), a measure of local aortic stiffness, is a strong independent predictor of subsequent white matter hyperintensity volume and white matter integrity, both associated with cognitive decline, elevated stroke risk, vascular dementia, and neurodegenerative diseases. Total arterial compliance (TAC), a measure of global arterial stiffness, has been recognized as a marker of preclinical vascular disease. This study introduces a smartphone‐based method for the noninvasive measurement of PWV _aa and TAC using carotid pressure waveforms acquired via smartphone. Methods: This method uses intrinsic frequency analysis of smartphone‐acquired (iPhone) carotid pressure waveforms to assess PWV _aa and TAC. The method was trained, validated, and blind‐tested on a cohort of 132 participants aged 20 to 90 years, including both healthy individuals and those with cardiovascular disease, all of whom underwent cardiac magnetic resonance imaging, tonometry, and iPhone waveform measurements. Results: In the blind test set, our method achieved Pearson correlations of 0.81 and 0.80 for PWV _aa and TAC, with biases of −0.20 m/s and −0.06 mL/mm Hg and limits of agreement of −4.09 to 3.68 m/s and −0.52 to 0.40 mL/mm Hg, respectively. In the heart failure population, correlations were 0.81 for both, with a PWV _aa a bias of −1.07 m/s and TAC bias of −0.06 mL/mm Hg. Conclusions: Our smartphone‐based method enables accurate assessment of local and global arterial stiffness metrics (PWV _aa and TAC). It offers easy‐to‐use monitoring of vascular aging and arterial health, with important implications for identifying patients at higher risk of neurodegenerative and cardiovascular diseases. Registration: URL: clinicaltrials.org ; Unique Identifier: NCT02240979.

Background: Measurement of left ventricular end‐diastolic pressure (LVEDP) is an established diagnostic method to evaluate heart failure but requires an invasive procedure. A noninvasive technique for detecting elevated LVEDP would improve the diagnosis of heart failure. Herein, we present the results of a multicenter study to validate a noninvasive system to detect elevated LVEDP. Methods: The Vivio System includes a modified blood pressure cuff and single‐lead ECG to capture brachial artery waveforms. A model was created to identify patients with elevated LVEDP (>18 mm Hg). For the invasive cohort, all patients were referred for coronary angiography and left heart catheterization for clinical indications. A group of 321 patients with no significant health problems were enrolled as a control cohort. Invasive LVEDP measurements were performed using Millar catheters. The training data set (n=262) contained 101 patients with LVEDP measurements (n=44 with LVEDP >18 mm Hg) and 161 controls. The validation data set (n=155) contained 75 patients with LVEDP measurements (n=40 with LVEDP >18 mm Hg) and 80 controls. Results: Leave‐one‐out cross‐validation on the training data set yielded a sensitivity of 0.84 (95% CI, 0.70–0.93]) and a specificity of 0.84 (95% CI, 0.79–0.89). The validation data set showed a sensitivity of 0.80 (95% CI, 0.64–0.91) and a specificity of 0.83 (95% CI, 0.75–0.90). Conclusions: The Vivio System can accurately detect elevated LVEDP and has the potential to significantly improve early detection of heart failure in the outpatient setting.

This study addresses discrepancies in the literature regarding the measurement of vortex formation time (VFT) as an index of diastolic function. We evaluate the clinical relevance of three existing VFT formulations and introduce a novel, fluid dynamics-based method (VFT_piston) that models the left ventricular base as a moving piston. Using healthy and heart-failure participants, we demonstrate that each VFT formulation captures distinct aspects of ventricular mechanics and VFT_piston offers physiologically meaningful correlations with diastolic metrics.