Ultrasound in Medicine & Biology

Background Perioperative incidents such as hypoxic cardiac injury often have subtle or nonspecific clinical manifestations. Reduction in myocardial oxygenation precedes biochemical changes, as well as electrical and functional changes. Photoacoustic imaging (PAI) is a modality that uses laser irradiation of tissue to generate ultrasonic waves, enabling spatially resolved quantitative mapping of oxygenated and deoxygenated haemoglobin. We investigated the utility of PAI for real-time monitoring of myocardial and great vessel oxygenation. Methods Male CD-1 mice were anaesthetised, and photoacoustic and simultaneous B-mode images were acquired of the myocardium and right ventricular outflow tract (RVOT), the pulmonary artery, and aorta. PAI was performed at fractional inspired oxygen levels (FiO2) of 100%, 21%, and then 10%. Separate cohorts of mice were exposed to increasing intravenous doses of either combined phenylephrine and isoprenaline, or individual administration of vasoactive or adrenergic agents. Results PAI reliably distinguished changes in oxygenation in the RVOT cavity, pulmonary artery, aorta, and myocardium. PAI detected hypoxia-induced changes in oxygenation, revealing greater desaturation in the myocardium than in the RVOT (-9.85%, 95% CI -14.94 to -4.77, P<0.0001). Escalating doses of phenylephrine and isoprenaline caused a progressive desaturation of the myocardium and RVOT (mean [95% CI]; myocardium 16 mg/kg: -14.64% [-27.62 to -1.65], P=0.0038 and RVOT 32 mg/kg: -18.71% [-32.15 to -5.27], P=0.0003). Myocardial deoxygenation was detected before changes in systolic function or electrical abnormalities. Conclusions This work demonstrates that PAI can reliably monitor cardiac oxygen desaturation, potentially offering an earlier warning of cardiac dysfunction and injury compared to existing monitoring tools. Keywords: Echocardiography, hypoxaemia, hypoxia, myocardial injury, oxygenation, perioperative monitoring, photoacoustic imaging

Skeletal muscle is a living, perfused soft tissue whose viscoelastic behavior is shaped by both voluntary contraction and hemodynamic state. However, the independent and superimposed contributions of contractile loading and blood flow restriction (BFR) have not been quantified simultaneously in real time. Twenty-six healthy adults underwent multi-frequency ultrasound time-harmonic elastography (THE, 60-80 Hz) of the vastus lateralis under six conditions: rest, 15% and 30% maximal voluntary contraction (MVC) before BFR, passive BFR after 4 min of cuff inflation, and 15% and 30% MVC shortly after cuff release. Shear wave speed (SWS), reflecting elasticity, and penetration rate (PR), reflecting inverse viscous damping, were extracted using the k-MDEV inversion algorithm. BFR significantly elevated SWS at all three contraction levels relative to the corresponding pre-BFR measurements (Holm-corrected p [&le;] 0.011; dz = 0.54-2.13). PR decreased during resting BFR (dz = 1.34, p < 0.001) and at 15% MVC after cuff release (dz = 0.94, p < 0.001), but not at 30% MVC (dz = 0.21, p = 0.294). BFR-related changes reduced the SWS-force slope by 14.5% and the PR-force slope by 40.7%. Men exhibited a greater BFR-induced increase in resting SWS than women. These findings show that THE can distinguish contractile and hemodynamic contributions to skeletal-muscle viscoelasticity and provide complementary information on elastic and dissipative tissue behavior in vivo.

Point-of-care ultrasound has transformed bedside diagnostics, yet current systems remain limited by rigid form factors, bulky external electronics and the need for skilled operators. Here we report a conformable ultrasound imaging patch that integrates a 1024-channel CMOS ultrasound application-specific integrated circuit (ASIC) directly beneath a conformable piezocomposite transducer array. The 10 mm X 8 mm, 1024-element ASIC contains on-chip transmit and receive beamforming, reducing the effective off-chip channel count by 16X while preserving image fidelity. Fabricated on a flexible polyimide substrate and bonded using anisotropic conductive film, the patch operates untethered from conventional ultrasound consoles and requires only a laptop for control and data acquisition. The device supports focused, plane-wave and diverging-wave transmission with steering over {+/-}30{degrees} in azimuth and {+/-}15{degrees} in elevation, achieving peak-to-peak acoustic pressures up to 7 MPa at a 4.4-MHz center frequency (mechanical index of 1.7), within diagnostic safety limits. Phantom experiments demonstrate three-dimensional imaging with axial and lateral resolutions (in both XZ and YZ planes) of 0.5 mm and 2 mm, respectively, and accurate contrast reproduction in tissue-mimicking phantoms. Human studies further demonstrate three-dimensional (3D) visualization of the internal jugular vein and carotid artery, as well as rib-shadow-free imaging of pleural motion during respiration. This work establishes a scalable architecture for chronic, wearable ultrasound imaging and highlights the potential of CMOS-integrated, conformable ultrasound systems for continuous physiological monitoring and remote diagnostics.

Background: Venous thromboembolism (VTE), including deep vein thrombosis (DVT), remains a major global health burden. Diagnostic pathways rely on ultrasound but are limited by availability and prolonged time-to-imaging. Novel artificial intelligence (AI) guidance systems have been designed to enable non-ultrasound-trained operators to acquire proximal lower extremity compression ultrasounds for remote clinician interpretation. Methods: This multicenter, double-blinded, prospective, nonrandomized study evaluated the performance of an AI guidance system (ThinkSono Guidance, ThinkSono, GmbH). Patients underwent AI-guided ultrasound(s) and standard of care ultrasound(s). Primary and secondary endpoints were image quality, sensitivity and specificity for proximal DVT, and prioritization specificity, a measure of specificity in identifying patients requiring standard of care ultrasound after AI-guided scan. Results: Of 634 recruited subjects, 594 were analyzed, with 67 DVTs across 700 scans. 86.83% of AI-guided scans achieved diagnostic image quality. Triage sensitivity was 92.86%, triage specificity 39.12%, prioritization specificity 97.96%. Standard of care ultrasounds could be avoided in 35.32% of patients. Total median AI-guided scan and review time was 7.57 minutes. Conclusions: Clinician-reviewed AI-guided scans were rapid, sensitive for DVT, and specific for prioritizing patients requiring standard of care ultrasounds. These findings suggest AI-guided ultrasound may be a scalable triage strategy to expand DVT evaluation access, particularly in resource-constrained and after-hours settings

Background: Epicardial adipose tissue (EAT) is a metabolically active fat depot adjacent to the myocardium and the coronary arteries that can be non-invasively assessed by cardiovascular magnetic resonance (CMR). Increased EAT volume quantified by CMR has been linked to adverse cardiac remodeling, atrial fibrillation, coronary artery disease, and heart failure. Among CMR techniques, isotropic three-dimensional (3D) Dixon imaging at 1.3 x 1.3 x 1.3 mm3 resolution was developed to improve tissue characterization, providing fat-water signal separation for precise volumetric EAT assessment. However, manual segmentation of 3D datasets is highly time-consuming. For integration into clinical and research CMR workflows, reliable and fast automated segmentation is needed. Purpose: To develop and evaluate an automated deep-learning-based pipeline for ventricular EAT quantification based on isotropic 3D Dixon CMR acquisitions. Methods: An nnU-Net model was trained on 165 3D Dixon CMR cases encompassing healthy individuals and patients with underlying cardiovascular disease. The model was trained using all four Dixon phase images (opposed-phase, in-phase, fat-phase, water-phase). Manual 3D ventricular EAT segmentations served as the ground truth for training and evaluation. Performance was evaluated in 30 independent cases using Dice similarity coefficient (DSC), 95th percentile Hausdorff distance (HD95), volumetric agreement, Pearson correlation, intraclass correlation (ICC), and Bland-Altman analysis. Model performance was benchmarked against interobserver and intraobserver variability. Results: Automated segmentation achieved a mean DSC of 0.896 {+/-} 0.039 and HD95 of 1.84 {+/-} 0.93 mm versus ground truth. Volumetric agreement with ground truth was high (r = 0.984, ICC = 0.988, p < 0.001; mean bias -0.70 mL, limits of agreement (LoA) [-10.31, 8.90] mL), exceeding interobserver agreement (bias -25.24 mL, LoA [-42.81, -7.66] mL) and comparable to intraobserver reproducibility (bias 2.72 mL, LoA [-8.73, 14.17] mL). Automated segmentation required less than one minute per case compared to 58.4 {+/-} 7.9 minutes for manual segmentation. Two of 30 cases (6.7%) required minor manual correction, both less than five minutes. Conclusion: Fully automated nnU-Net-based ventricular EAT segmentation from isotropic 3D Dixon CMR achieves accuracy comparable to intraobserver reproducibility while significantly reducing post-processing time. The approach may facilitate large-scale and longitudinal EAT quantification in CMR-based research workflows.

Accurate interpretation of planar ventilation-perfusion (V/Q) scintigraphy, used for diagnosing pulmonary embolism (PE) based on PIOPED/EANM guidelines, requires objective assessment of mismatched V/Q defects. Manual delineation of V/Q defects is time-consuming, subject to interobserver variability, and rarely performed in practice, limiting standardized reporting and quantification of disease burden. To address these challenges, we evaluated four modern AI models for automated segmentation of vascular perfusion defects in planar V/Q scans and compared their performance to human annotators. We retrospectively identified 2,118 patients who underwent planar V/Q scans at The Ottawa Hospital (June 2019-February 2023). Six standard projections (ANT, POST, LAO, RAO, LPO, RPO) were included. Four 2D neural networks (U-Net, nnU-Net, Swin UNETR, and a Bottleneck Transformer U-Net [BTU-Net]) were trained on 1,313 patients (7,878 projections) and validated on 329 (1,974 projections) using physician-annotated defects. A hold-out test set of 46 high probability patients was used to evaluate segmentation quality, and defect detection accuracy using free-response receiver operating characteristic (FROC) analysis, where BTU-Net was the only model performing on par with human readers, showing robust sensitivity across the entire range of segmentation probabilities. At 1.5 false positives per projection rate (FPPR), BTU-Net outperformed other models with a sensitivity of 0.529 {+/-} 0.026, On a separate hold-out set of low likelihood of disease patients (n=430), the lowest FPPR was 0.08 {+/-} 0.01 for BTU-Net (P<0.0001). BTU-Net enables rapid, consistent, and accurate interpretation of planar V/Q scans. Such tools may enhance diagnostic efficiency, standardize reporting, and support non-expert readers in evaluating PE.

PurposeComputational models of the uterus during pregnancy enable analysis of electro-chemo-mechanical pathways to predict labor timing and guide treatment planning. We aim to develop a robust image-based modeling pipeline to investigate uterine passive mechanics during late pregnancy. MethodsA parametric model of the uterus and cervix was created using a patients MRI measurements at 38 weeks of gestation. Inspired by advances in cardiac mechanics models, we created Laplace-Dirichlet solutions to inform tissue domains, fiber structure within the uterus and cervix, and spatially varying Robin boundary conditions. Prior imaging and mechanical testing data were used to fit material parameters. Boundary condition parameters were tuned to match the displacements of a previously established approach that employed contact with surrounding tissue. The tissue mechanical response to a physiologic load was assessed across varying material properties and fiber architectures. ResultsDiscrepancies in nodal displacements between the current approach and the contact-based model were limited to 3.4 {+/-} 1.8 mm, yielding nearly 90 % computational savings. Uterine tensile strains were more sensitive to ground substance elastic modulus (E) compared to fiber properties. Reduced E and fiber stiffness increased cervical strains and compression. Fiber dispersion and architecture modulated the opening of the cervical internal ostium but had a reduced impact on compression. ConclusionWe developed a novel workflow for modeling passive uterine mechanics, informed by patient-specific measurements and in vitro mechanical tests. The robust workflow may prove useful for studying labor progression and conducting longitudinal studies to enhance our understanding of normal and pathological pregnancies.

Urinary stone disease is a common urological condition with increasing incidence, particularly in developed countries. Laser lithotripsy (LL) has become a preferred minimally invasive treatment due to its high precision and low tissue damage. Recent studies suggest that cavitation plays a critical role in stone damage during LL, and three-dimensional passive cavitation mapping (3D-PCM) has emerged as a promising tool for detecting these events. However, clinical translation of 3D-PCM remains challenging due to limitations in imaging depth, field of view (FOV), and procedural compatibility. Here, we present a large-FOV dual-modality imaging system (3D-PCM and B-mode ultrasound) based on a large-aperture planar ultrasound array. Through array optimization and model-based reconstruction, our system achieves an expanded FOV of ~40*40mm^2 at a clinically relevant imaging depth of ~110mm, while maintaining high spatial resolution of ~0.6 mm laterally and ~0.4 mm axially. In vivo experiments in a porcine model demonstrate that the reconstructed cavitation distribution correlates well with stone damage. Our technology has the potential to provide real-time treatment feedback during LL without disrupting the standard workflow.

BackgroundQuantitative dynamic contrast-enhanced myocardial perfusion cardiovascular magnetic resonance (CMR) enables estimation of myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). These measurements require an arterial input function (AIF), which is typically derived from the left ventricular blood pool. However, the contrast agent bolus undergoes dispersion during transport through the coronary vasculature before reaching the myocardial microcirculation. This may introduce systematic and spatially heterogeneous errors in MBF and MPR estimates. PurposeThis work provides an extended segmental analysis of bolus-dispersion-induced errors in quantitative myocardial perfusion MRI using previously established computational fluid dynamics (CFD) simulations in realistic porcine coronary artery models. The focus of the present analysis is the assignment of coronary outlets to myocardial segments and the resulting segmental variability of MBF and MPR errors. MethodsRealistic three-dimensional models of the left and right coronary arteries were extracted from an ex-vivo porcine imaging cryomicrotome dataset. The models extended down to the pre-arteriolar level and included 364 outlets for the left coronary artery and 104 outlets for the right coronary artery, with an average outlet diameter of 383 {+/-} 85 {micro}m. Blood flow was simulated under rest and stress conditions using OpenFOAM. Contrast agent transport was then modeled by solving the advection-diffusion equation using a gamma-variate bolus as input. Outlet concentration-time curves were analyzed using an indicator-dilution model to estimate MBF and MPR errors. Outlets were assigned to standardized myocardial segments, and segmental averages were evaluated with respect to coronary supply territory and travel distance from the model inlet. ResultsThe simulations demonstrated marked segmental heterogeneity of volume blood flow and bolus-dispersion-induced MBF and MPR errors. Errors increased with travel distance from the coronary artery inlet and were more pronounced in regions supplied by the right coronary artery, consistent with lower flow velocities and stronger bolus dispersion. The resulting systematic errors led to underestimation of MBF and overestimation of MPR, with segmental deviations reaching up to approximately 60%. ConclusionBolus dispersion in the coronary vasculature may lead to substantial segmental and location-dependent errors in quantitative myocardial perfusion MRI. This extended analysis indicates that dispersion-related bias is not spatially uniform, but depends on coronary supply territory, travel distance, and flow conditions. These effects should be considered when interpreting regional MBF and MPR estimates, particularly as automated quantitative myocardial perfusion CMR becomes more widely used.

Objective: This study aims to develop and validate a quantitative, depth-resolved anisotropy imaging framework that extends ARFI-based focal degree-of-anisotropy (DoA) estimation into two-dimensional mapping by modeling the depth-dependent relationship between shear modulus ratio (SMR) and peak displacement ratio (PDR). Methods: We propose APRIL (Adaptive Polynomial Regression for anisotropy Imaging via ARFI-induced DispLacements), a framework for quantitative, depth-resolved DoA imaging that adaptively selects polynomial regression or shape-preserving spline interpolation based on excitation PSF asymmetry. Training data were generated using an LS-DYNA3D + Field II simulation pipeline in homogeneous transversely isotropic media (SMR 0.9-4.9). Testing included shifted SMRs under varied acoustic conditions and three heterogeneous inclusion configurations (anisotropic inclusion in isotropic background and vice versa). Experimental validation was performed in an in-vivo murine tumor model over the time, ex-vivo chicken breast, and tissue-mimicking gelatin phantoms, using a Verasonics system with an L11-5v transducer. Results: APRIL achieved depth-resolved SMR prediction errors below 9% over 10-30 mm, with highest accuracy in the focal region (MAE 2.3%, RMSE < 0.1) and stable performance across PSF transition zones. In heterogeneous phantoms, it reconstructed anisotropy maps with SSIM up to 86% and MPE below 7%, accurately delineating inclusion boundaries. Under acoustic parameter variations, mean absolute errors remained below 10%, demonstrating robustness to system and tissue heterogeneity. Conclusion: APRIL enables robust, two-dimensional anisotropy imaging beyond focal estimates. Significance: The method provides a physically grounded and generalizable framework for clinically viable anisotropy biomarkers in muscle, tendon, kidney, tumor and breast tissues.

This study presents the use of sub-micron nanobubbles (NBs) as contrast agents for ultrasound localization microscopy (ULM), a super-resolution imaging technique that visualizes microvascular structure and flow beyond the acoustic diffraction limit. While ULM has traditionally relied on micron-sized microbubbles (MBs), the reduced dimensions and prolonged circulation times of NBs make them attractive candidates for localization-based imaging. However, their weaker acoustic responses present significant challenges for reliable detection and tracking. To address this challenge, we developed the ULM Master GUI, an interactive framework for optimization of the complete ULM processing pipeline. Using custom ultrasound-compatible wall-less gelatin flow phantoms containing vessel-mimicking channels and bifurcations ranging from 100 to 500 m, we demonstrate that NB-based ULM achieves velocity reconstruction and flow partitioning measurements comparable to conventional MB-based ULM. Across all investigated geometries, NBs faithfully reproduced the underlying flow patterns and hemodynamic behavior despite their substantially reduced acoustic scattering. These findings establish the feasibility of NB-based ULM, expand the range of contrast agents available for localization microscopy, and provide a foundation for future super-resolution ultrasound imaging using nanoscale acoustic contrast agents. The ULM processing GUI is publicly available at https://github.com/grisha1998/ulm-super-resolution-toolbox.

PurposeFunctional tricuspid regurgitation (FTR) is driven by right ventricular (RV) remodeling, annular dilation, and papillary muscle dislocation. Free wall approximation (FWA) has been proposed to treat FTR by addressing RV dilation, but its effects on tricuspid valve (TV) biomechanics remain unclear. We present a real-time 3D echocardiographic (rt3DE)-based finite element framework to quantify TV biomechanics under FTR, and preliminarily apply it to assess FWA effects. MethodsSubject-specific models were developed from rt3DE data of three dilated porcine hearts in an ex-vivo mock-loop. TV geometries at end-diastole and peak systole (PS) were complemented by parametric chordae tendineae and hyperelastic tissue properties. TV closure was simulated under a standard pressure load and image-based annular motion. After tuning chordae length to replicate the PS ground truth in FTR, FWA was simulated as 30% and 60% approximations along three anatomical directions (anterior-posterior, A-P; anterior-septal, A-S; anterior-septal wall, A-SW). ResultsIn FTR simulations, median geometric errors ranged from 1.16 to 1.26 mm; median stress ranged from 56.4 to 74.7 kPa. FWA simulations predicted regurgitant orifice area (ROA) reductions by 53-99%, albeit overestimating the residual ROA vs. in vitro ground truth when starting from particularly extreme FTR conditions; concomitantly, a median stress reduction by 8-43% vs. FTR conditions was predicted. ConclusionPreliminary data suggest that our rt3DE-based framework can reliably quantify FTR-related TV biomechanics and that post-FWA biomechanics depends on initial FTR conditions. A larger cohort is required to verify the method and obtain statistically significant results.

Background: Iatrogenic atrial septal defect (iASD) is a known consequence of transseptal catheterization. Left atrial intracardiac echocardiography (LA ICE) requires additional septal instrumentation, yet data on persistent iASD after pulsed field ablation (PFA) with an LA ICE workflow remain limited. We evaluated the incidence, predictors, and one-year clinical significance of persistent iASD in this setting. Methods: Consecutive patients undergoing PFA for atrial fibrillation with LA ICE were prospectively evaluated with transthoracic echocardiography before ablation and at one year, including systematic agitated saline contrast. Persistent iASD was defined as residual interatrial shunting on color Doppler at follow-up, classified as small (<3 mm), moderate (3-5 mm), or large (>5 mm). Groups were compared by t-test and chi-square test. Results: Among 850 patients, persistent iASD was identified in 153 (18.0%) at one year; 97 (63.4%) were small and 56 (36.6%) moderate, with no large defects. All shunts were left-to-right. No stroke or transient ischemic attack, paradoxical embolism, hypoxemia, right-heart enlargement, or septal closure occurred. Persistent iASD was associated with female sex (64.7% vs 48.1%), longer septal dwell time (52{+/-}12 vs 31{+/-}11 min), higher left atrial pressure (28{+/-}4 vs 12{+/-}3 mmHg), lower LVEF (32{+/-}11% vs 54{+/-}14%), and larger-caliber sheaths ([&ge;]17 Fr; 80.4% vs 48.2%; all p<0.001). Conclusions: Persistent iASD following PFA with LA ICE occurs in approximately one in five patients but is predominantly small, exclusively left-to-right, and clinically benign at one year. Persistence is associated with mechanical and hemodynamic factors, particularly sheath caliber, rather than the ablation energy source.

Background: Acute pulmonary embolism (PE) is a leading cause of morbidity and mortality with persistent difficulties in choosing interventions and predicting outcomes for patients defined clinically as intermediate risk. Computational fluid dynamics (CFD) tools have been used to understand the hemodynamic environment and plan interventions in the pulmonary arteries across a variety of disease conditions. Several biomechanical metrics have been used to evaluate risk in narrowed vessels, including hemodynamic resistance, power dissipation, and fractional flow reserve (FFR). In this study, we evaluate differences in these CFD-derived biomarkers between healthy controls (HC) and intermediate risk, acute PE patients. Additionally, we examine the response of patient hemodynamics to mechanical thrombectomy and compare values of these biomarkers across post-intervention pressure status. Methods: A CFD framework was developed to simulate patient-specific hemodynamics within the pulmonary vasculature identifiable from clinical imaging. The pipeline involved reconstructing three-dimensional (3D) structures of the pulmonary arteries and modeling blood flow with the finite element method. Patient-specific boundary conditions were derived from matching pre-intervention inlet mPAP to the patient's measured value given their measured CO as steady inflow. Converged simulations allowed for precise quantification of primary hemodynamic characteristics (flow and pressure) as well as secondary flow phenomena, primarily wall shear stress (WSS) and simulated pressure metrics such as fractional flow reserve (FFR). Results: Our simulations revealed significant elevations in resistance, power dissipation, and the number of vessels with low FFR in those patients with acute PE (n=6) compared to HC (n=3). Occlusions of hemodynamic significance were generally found in segmental pulmonary arteries. For patients with normalized pulmonary pressures post-thrombectomy (n=3), we found significantly higher proximal power dissipation and counts of low FFR vessels in comparison to those with elevated pressures after intervention (n=3). Distal resistance, which was derived from the portion of resistance attributed to the outflow boundary conditions, was significantly higher in patients with elevated pressures post-intervention. Across all PE patients, FFR count was significantly correlated with post-thrombectomy pulmonary pressure and cardiac index. Discussion: CFD-derived biomarkers offer a promising tool for understanding disease severity in acute PE. Differences between HCs and acute PE patients reveal expected increases in metrics associated with proximal disease burden. Yet, in examining acute PE patients with varying post-intervention hemodynamics, we found that these metrics of proximal disease burden could also be useful to predict the efficacy of mechanical thrombectomy. Those patients with normalized pressures had higher values for proximal disease metrics and lower values for distal disease metrics than those with continued elevations in pressure. This suggests that accessibility of hemodynamically-significant emboli to thrombectomy may be useful as a predictor for outcomes.

Identification and treatment of pregnancies at risk for preterm birth is a central challenge in obstetric research. Many of the known causes of preterm birth originate from mechanical failure in reproductive tissues. To better understand the biomechanical environment of the gravid uterus and its potential contribution to preterm birth, this computational study presents a parametric method for modeling maternal reproductive anatomy during the early second trimester. A finite element modeling approach was built using existing sonographic measurements from early second-trimester maternal anatomy and material properties from published mechanical tests. We applied the same physiologically relevant intrauterine pressure to all models and quantified the resulting tissue stretch. The sensitivity of the stretch in the proximal cervix was explored by varying material properties and sonographic maternal anatomy dimensions. Cervical material properties, particularly the fiber stiffness modulus and ground substance Youngs modulus, were found to have the greatest effect on proximal cervix stretch compared to other material properties and sonographic dimensions. Among the sonographic dimension measurements, those defining the region surrounding the proximal cervix had the greatest effect on proximal cervix stretch, including the curvature of the posterior uterine wall and the thickness of the lower uterine segment. The computational modeling approach presented here enables future patient-specific studies of gravid reproductive tissues to elucidate differences between individuals who do and do not deliver preterm. Additionally, this study is foundational for building digital twins to support future virtual clinical studies on diagnostic and therapeutic device design to prevent preterm birth.

Atrial fibrillation (AF) is associated with an increased risk of neurological morbidity, yet its impact on cerebral perfusion and neuro-cardiorespiratory regulation remains incompletely understood. We used arterial spin labeling, blood oxygenation level-dependent functional MRI (BOLD-fMRI), and a breath-hold challenge to characterize alterations in 14 AF patients compared with 14 age-matched healthy controls. We also examined the changes after catheter ablation with pulmonary vein isolation (PVI) in a subset of patients. Compared with controls, AF patients exhibited widespread reductions in basal cerebral perfusion, including in brainstem regions involved in cardiorespiratory regulation, and a higher prevalence of periodic breathing during wakeful rest. During breath-hold challenge, the coupling between heart rate and BOLD signal changes ({Delta}BOLD) was smaller in AF, whereas {Delta}BOLD coupling with breath-by-breath O2-CO2 exchange ratio was greater at rest within pontine respiratory centers, indicating altered cardiac and respiratory contributions to cerebral hemodynamic regulation. Follow-up MRI scans 1-6 months after PVI demonstrated that restoration of sinus rhythm was associated with stronger heart rate-{Delta}BOLD coupling during breath-hold challenge, whereas basal cerebral perfusion showed no significant change. This dissociation suggests distinct temporal responses of neuro-cardiorespiratory coupling and cerebral perfusion after sinus rhythm restoration, while the timing of cerebral perfusion recovery remains unresolved.

Minimally invasive surgery is a powerful technique that enables operations deep within the body while minimizing patient trauma and recovery time. Optical endoscopes are key to providing intraoperative vision but still face challenges due to the loss of essential senses, including depth perception and tactile feedback for tissue evaluation. Thus, it is critical to develop endoscopic imaging technologies that can augment operators with critical information. In this work, we explore a prototype multimodal 3D imaging endoscope that integrates volumetric light-field imaging with laser-speckle contrast imaging to simultaneously capture 3D structure and blood-flow information in a clinically relevant form factor.

Minimally invasive endovascular procedures offer reduced surgical trauma, shorter recovery times, and improved outcomes, but rely on 2D fluoroscopic X-ray imaging, which provides limited depth perception and exposes patients and clinicians to ionizing radiation. Here we present an augmented reality (AR) system that fuses intravascular ultrasound (IVUS) and electromagnetic (EM) position tracking with preoperative computed tomography (CT) to produce an anatomically accurate, deformation-corrected navigational reference. A robotic device performs ECG-gated pullback of the IVUS probe, capturing 4D aortic motion across the cardiac cycle. We introduce a deep learning architecture for extracting vascular lumen boundaries and side-branch orifices from artifact-prone IVUS streams, and a semantically driven non-rigid CT-IVUS fusion pipeline robust to false positive landmarks. We evaluate the platform with trained surgeons in benchtop phantom studies and in-vivo ovine models, and demonstrate its application to fenestrated endovascular aneurysm repair (FEVAR). Compared to fluoroscopy alone, AR guidance significantly reduces cannulation time, radiation exposure, and cognitive workload, while improving procedural efficiency and safety. Our IVUS-EM and CT aortic datasets are released open source.

Effective modulation of cortical-subcortical motor circuits is essential for post-stroke recovery, yet progress has been constrained by the absence of non-invasive tools capable of precisely targeting deep brain structures. In this pilot proof of concept study, we explored the feasibility and preliminary neuromodulatory effects of a 12-minute transcranial focused ultrasound (tFUS) protocol targeting the ipsilesional ventral lateral posterior (VLp) thalamus in ischemic stroke patients. Six individuals with upper-limb hemiparesis received individualized, neuronavigation-guided tFUS. Sensorimotor tracking performance improved signiffcantly after a single session. Concurrent EEG revealed reversible beta-power suppression over the ipsilesional motor cortex and enhanced theta-phase synchronization in frontoparietal networks, both of which were associated with behavioral gains. Resting-state fMRI indicated rebalancing of inter-hemispheric motor networks. These preliminary ffndings suggest that thalamic tFUS can modulate both local and networklevel neural activity and is associated with immediate functional improvement, highlighting its potential as a feasible neuromodulation approach for deep motor circuit engagement in post-stroke rehabilitation.

Background: Cutaneous microvascular responses to local heating and acetylcholine perfusion are widely used to assess nitric oxide (NO)-mediated endothelium-dependent dilation in human health and disease. Despite the increasingly common usage of these approaches, no studies have directly compared responses to these stimuli within individuals. Therefore, we assessed endothelium- and NO-dependent dilation in 80 young adults (40 males/40 females; 22{+/-}3 years) to determine the extent to which microvascular responses to these endothelium-dependent stimuli are comparable within an individual. Methods: We examined cutaneous vascular conductance responses to (1) standardized local heating protocols to 39{degrees}C and 42{degrees}C, and (2) graded infusions of acetylcholine (10-10-10-1 M) alone or with 15 mM NG-nitro-l-arginine methyl ester (L-NAME; NO synthase inhibitor). Endothelium- and NO-dependent dilation were calculated and expressed in multiple ways based on commonly published analyses to allow for a thorough comparison within and between each stimulus. Results: Local heating-induced endothelium- and NO-dependent dilation were lower at 39{degrees}C compared with 42{degrees}C (P<0.001). The magnitude of local heating-induced endothelium-dependent dilation was significantly related to the NO-dependent contribution of that response at 39{degrees}C (R2= 0.79) and 42{degrees}C (R2= 0.56). Local heating-induced NO-dependent dilation at 39{degrees}C was not related to that at 42{degrees}C (P>0.05). Acetylcholine-induced endothelium- and NO-dependent dilation were not related to local heating-induced responses (all P>0.05). Conclusions: These data demonstrate that while local heating and acetylcholine perfusion produce robust endothelium- and NO-dependent cutaneous vasodilation, these responses are not comparable within an individual.