Ultrasound in Medicine & Biology

BackgroundTumor progression is associated with alterations in tissue mechanical properties. Experimental studies in cancer mechanobiology suggest that increased viscosity of the tumor habitat can promote tumor growth, while malignant tumors often exhibit pronounced mechanical heterogeneity with coexisting soft and rigid regions that facilitate cell motility. Elastography enables noninvasive viscoelastic profiling of soft-tissue properties in vivo and may therefore detect tumor malignancy. PurposeTo investigate whether multiparametric external vibration-based ultrasound time-harmonic elastography (THE) can differentiate benign from malignant liver tumors and identify viscoelastic parameters associated with tumor malignancy. Materials and MethodsIn this prospective study conducted from January 2025 to March 2026, 94 patients with focal liver lesions underwent THE. Eighty-four patients were included in the final analysis (41 benign, 39 malignant; 45 women; age range 30-87 years). Liver and tumor stiffness (shear wave speed; SWS), viscosity (loss angle; {phi}), and spatial mechanical heterogeneity (spatial standard deviation, SWS-SD) were quantified. Diagnostic performance for differentiating benign and malignant tumors was assessed using the area under the receiver operating characteristic curve (AUC). ResultsTumor heterogeneity and surrounding habitat viscosity provided the most pronounced differentiation between malignant and benign lesions. Malignant tumors demonstrated higher SWS-SD (0.41{+/-}0.20 vs. 0.28{+/-}0.11 m/s) and increased {phi} (0.76{+/-}0.09 vs. 0.71{+/-}0.05 rad) with a combined discriminative power of AUC=0.72. These viscoelastic differences were more pronounced in larger tumors of [≥]2.5 cm2 area (SWS-SD: 0.47{+/-}0.19 vs. 0.32{+/-}0.11 m/s; {phi}: 0.78{+/-}0.10 vs 0.70{+/-}0.04 rad) yielding AUC=0.88 while excellent discriminative power of AUC=0.97 for [≥]6 cm2 tumor area. ConclusionElevated viscosity of the tumor habitat combined with increased tumor stiffness-heterogeneity measured by multiparametric THE can differentiate liver malignancies from benign liver lesions. THE may thus provide a rapid, cost-effective approach for viscoelastic profiling of liver tumors in clinical diagnostic imaging.

BackgroundBreast cancer-related lymphedema (BCRL) is a common complication following breast cancer treatment. While lymphoscintigraphy is considered the diagnostic gold standard, it is unsuitable for routine periodic monitoring or assessment of treatment efficacy. Shear wave elastography (SWE) offers a possible alternative, but traditional modes of operation limit its potential. Proposed SolutionsThe Holder-Optimized Elastography (HOE) method is introduced to eliminate pressure issues introduced by manual operation of ultrasound probes by stabilizing them above the cutis. MethodsThe HOE method was used to acquire ARFI images of high-velocity areas (HVAs, with shear wave velocity greater than 7 m/s) in limbs with and without BCRL (as confirmed and characterized by lymphoscintigraphy) in two cohorts of 15 and 125 patients. ResultsThe HOE method enabled ARFI elastography to directly and consistently visualize the effects caused by both obstructed lymphatic vessels and intraluminal lymphatic fluid as HVAs, whereas traditional hand-held methods did not. Inter-limb differences in HVA burden showed moderate diagnostic performance for detecting BCRL and grading obstruction with modest sensitivity. However, there was systematic underestimation of both early and confluent advanced lesions. ConclusionHOE-based HVA imaging has potential for rapid and non-invasive monitoring of lymphedema course and treatment response and may serve as a useful adjunct to existing diagnostic tools for BCRL. However, further technical refinements and quantitative analytic methods will be required to fully exploit the richer SWV information provided by HOE and to enhance the diagnostic utility of HVAs. Summary StatementThe Holder-Optimized Elastography method ("HOE" method) increases the diagnostic capability of ARFI elastography for breast cancer-related lymphedema, allowing for the non-invasive detection of some lymphatic obstructions but not all. Key ResultsThe Holder-Optimized Elastography (HOE) method revealed the effects caused by fluid-filled lymphatic vessels as "High-Velocity Areas" (HVAs), which are difficult to detect by conventional methods. HVA counts for detecting lymphedema (any obstruction vs. no obstruction) showed high specificity (0.86-1.00) but low sensitivity (0.57-0.67). Conversely, HVA counts for staging lymphedema (i.e. total vs. partial obstruction) showed high sensitivity (up to 1.00) but low specificity (0.48-0.66). The inter-limb difference of HVAs counted in whole-limb scans between affected and unaffected limbs (aka, the "Global Mean Difference") provided the most balanced diagnostic performance (sensitivity 0.67-0.79, specificity 0.88-0.89).

Cardiac fibrosis is a key contributor to cardiomyopathy after myocardial infarction (MI). Existing imaging techniques can detect established fibrotic changes; however, they lack sensitivity for ongoing collagen turnover--a dynamic process involving the denaturation of collagen triple helix. Molecular imaging of this process could enhance risk assessment and aid in the development of anti-fibrotic treatments. This study aimed to evaluate 99mTc-(HE)-(GPO), a radiotracer designed to target denatured collagen, as a biomarker of collagen turnover after MI. Methods99mTc-(HE)-(GPO) incorporates glycine-proline-hydroxyproline (GPO) repeats and can hybridize with denatured single- or double-stranded collagen. MI was induced in mice by ligation of the left anterior descending artery; sham-operated animals served as controls. At 2 weeks post-MI, animals underwent myocardial perfusion imaging or contrast-enhanced CT to detect the infarct zone, followed by SPECT/CT imaging using 99mTc-(HE)-(GPO) or a control scrambled tracer. Tracer uptake was quantified in vivo and ex vivo with gamma counting and autoradiography. Different aspects of fibrosis were examined by tissue analysis, along with autoradiography with a matrix metalloproteinase-targeted radiotracer, 99mTc-RYM1. Tracer binding was also assessed in human cardiac tissue through ex vivo autoradiography. Results99mTc-(HE)-(GPO) SPECT/CT revealed significantly higher tracer uptake in the infarct zone of MI mice compared to the remote zone and sham controls (P < 0.0001 for both). Tracer uptake was confirmed by autoradiography, which showed a strong correlation between SPECT and autoradiography (R = 0.81, P < 0.01). The scrambled tracer exhibited minimal cardiac uptake, demonstrating the specificity of 99mTc-(HE)-(GPO) signal. Denatured collagen staining and 99mTc-RYM1 autoradiography showed similar patterns as ex vivo 99mTc-(HE)-(GPO) autoradiography, while the ratio of denatured collagen to procollagen in the infarct zone significantly increased from day 3 to 2 weeks post-MI. Finally, 99mTc-(HE)-(GPO) bound to human fibrotic (but not normal) cardiac tissue. Conclusion99mTc-(HE)-(GPO) enables non-invasive detection of denatured collagen as a marker of collagen remodeling in vivo, offering a promising tool for assessing fibrotic remodeling after MI. Collagen, procollagen, and denatured collagen, along with MMP activation, exhibit distinct patterns, and their combined imaging may provide a comprehensive molecular fingerprint of cardiac fibrosis, advancing personalized management of cardiomyopathy.

ObjectivePulsed field ablation (PFA) relies on irreversible electroporation to create nonthermal cardiac lesions, yet real-time indicators of electroporation progression and validated lethal electric field thresholds remain limited. This study aimed to develop a bioimpedance-based metric for real-time monitoring of cardiac electroporation, evaluate the impact of myocardial anisotropy under electroporation conditions, and derive waveform-specific lethal electric field thresholds. IntroductionCurrent PFA procedures lack direct intraoperative feedback on lesion formation, and uncertainty remains regarding the role of myocardial fiber orientation in shaping electric field distributions. Because electroporation dynamically alters tissue electrical properties, monitoring these changes during treatment may improve prediction of ablation outcomes. MethodsPFA was delivered to fresh ex vivo porcine ventricular tissue using clinically relevant and energy-matched waveforms with pulse widths from 1 to 100 {micro}s. Inter-burst broadband electrical impedance spectroscopy was performed using a low-voltage diagnostic waveform to quantify burst-resolved impedance changes. Lesions were visualized using metabolic staining, then finite element models incorporating nonlinear electroporation-dependent conductivity were used to compare anisotropic and homogenized electric field distributions. Lethal electric field thresholds were estimated by fitting simulated contours to measured lesion areas and validated using uniform electric fields generated by a parallel electrode array. ResultsAcross all waveforms, impedance measurements showed a rapid initial decrease followed by stabilization, indicating early electroporation saturation. Burst-to-burst percent change in impedance slope provided a consistent, waveform-agnostic metric of electroporation progression. Lesion morphology was not systematically influenced by fiber orientation, and modeling demonstrated that electroporation-induced conductivity increases homogenized tissue anisotropy. Lethal electric field thresholds increased with decreasing pulse width, ranging from 517 {+/-} 46 V/cm (100 {micro}s) to 1405 {+/-} 55 V/cm (1 {micro}s), and were validated under uniform field conditions. ConclusionBioimpedance-assisted monitoring enables real-time assessment of cardiac electroporation, while electroporation-induced homogenization supports simplified modeling and standardized PFA treatment design.

Handheld ultrasound devices have revolutionized point-of-care diagnostics, but their effectiveness remains limited by operator dependency and the need for specialized training. This paper presents an intelligent guidance and diagnostic assistance system for the handheld wireless ultrasound device, enabling automated carotid artery and thyroid examinations through handheld operation. Drawing inspiration from the Actor-Critic framework, we implement a simulation-based reinforcement learning approach for real-time probe navigation toward standard anatomical views. The system integrates YOLOv8n-based detection networks for carotid plaque and thyroid nodule identification, achieving real-time inference at 30 frames per second. Furthermore, we propose a hybrid measurement approach combining UNet segmentation with the Snake algorithm for precise biometric quantification, including carotid intima-media thickness (IMT), lumen diameter, and lesion dimensions. Experimental validation on clinical datasets demonstrates that the proposed system achieves 91.2% accuracy in standard plane acquisition, 87.5% mean average precision (mAP) for plaque detection, and 89.3% mAP for nodule identification. Measurement results show excellent agreement with expert sonographers, with IMT measurements exhibiting a mean absolute difference of 0.08 mm. These findings demonstrate the feasibility of intelligent handheld ultrasound examination, significantly reducing operator dependency while maintaining diagnostic accuracy comparable to experienced clinicians.

BackgroundTranscranial focused ultrasound (tFUS) is an emerging noninvasive neuromodulation modality with the ability to target deep brain structures with high spatial precision. Despite its promise, rigorous evaluation of its efficacy is limited by the absence of reliable, fully double-blind sham methodologies. ObjectiveTo develop and validate a pair of visually and mechanically indistinguishable acoustic coupling pads that enable true double-blind tFUS neuromodulation studies by providing either efficient ultrasound transmission or robust ultrasound blocking without altering participant or operator experience. MethodsTwo coupling pads were engineered: a transmitting pad designed to allow <5% pressure amplitude loss relative to free-water propagation, and a non-transmitting pad designed to attenuate ultrasound by [&ge;]40 dB. Both pads used a Dragon Skin 10 NV silicone base and were identical in size, appearance, flexibility, and handling. The non-transmitting pad incorporated an encapsulated air-based blocking layer using an open-cell polyethylene foam insert. Acoustic performance was evaluated in a water tank using a 650 kHz BrainSonix transducer and a calibrated needle hydrophone. Sound speed of the silicone material was measured using pulse-echo techniques. ResultsTwenty-three matched transmitting and non-transmitting pad pairs were fabricated and tested. Transmitting pads demonstrated a mean attenuation of -0.41 {+/-} 0.53 dB, satisfying the design criterion of minimal acoustic loss.Non-transmitting pads demonstrated a mean attenuation of -48.61 {+/-} 4.33 dB, exceeding the required -40 dB threshold for effective sham conditions. The Dragon Skin 10 NV substrate exhibited a sound speed of 964.72 m/s and produced <2 mm axial focal shift for standard pad thicknesses, with no measurable change in focal width. Both pad types were visually and tactually indistinguishable, could not be differentiated by experienced operators or participants, and maintained mechanical integrity after repeated cleaning ConclusionThese acoustically engineered coupling pads provide a practical and validated solution for achieving true single- and double-blind conditions in tFUS neuromodulation studies. By preserving identical sensory and procedural experiences while enabling precise control over ultrasound transmission, this approach addresses a critical methodological gap in human ultrasound neuromodulation research.

Myocaridum biomechanics are a biomarker for multiple cardiac pathologies. However the rapid and complex heart motion hampers accurate measurements of the tissue stiffness. Current in vivo methods for the evaluation of myocardium mechanical health are either highly invasive or can only provide with a global surrogate of heart function as they suffer from poor spatiotemporal resolution. We propose a new in vivo technique, transient magnetic resonance elastography (tMRE), to assess the dynamic cardiac biomechanics. tMRE is able to quantify local shear wave speed as a proxy for myocardial stiffness at user-defined times within the cardiac cycle. We report proof-of-concept results where we probe the septum of 4 different healthy rat specimens at 3 physiologically distinct cardiac phases. We provide with apparent speed measurements for early systole, mid-late systole and early diastole that match the expected values from the cardiac cycle physiological mechanics. We correct for non-negligible geometrical biases using literature results and report true stiffness values where possible. Finally, we validate tMRE in phantom experiments.

Background. Carotid webs (CaWs) are shelf-like protrusions in carotid bifurcation recognized as a potential cause of ischemic stroke. However, their impact on wall-based hemodynamic metrics (TAWSS, OSI, RRT) in distinguishing from normal bifurcations remains unclear. Methods. Carotid geometries were reconstructed from CT angiography in patients with CaWs, classified as symptomatic (with ischemic stroke) or asymptomatic (incidentally detected), and controls with normal bifurcations. Influence of three blood viscosity models (Newtonian, Carreau-Yasuda, Casson) was evaluated. Metrics were quantified using a Gaussian-weighted spatial averaging method and compared between groups. Results. CFD simulations were performed in 22 CaW cases (16 symptomatic, 6 asymptomatic) and 6 normal bifurcations. Simulations predicted recirculation corresponding to delayed contrast clearance on DSA. Viscosity models had minimal influence on flow patterns (<2% differences). CaWs showed greater inter-patient variability than normal bifurcations, but overlap remained (e.g., TAWSS 3.39 (2.72-8.96) vs 4.18 (3.09-4.56) Pa, p = 0.858). Symptomatic CaWs showed lower TAWSS and higher OSI and RRT than asymptomatic CaWs (TAWSS 3.39 vs 6.63 Pa), although did not reach statistical significance (p > 0.25). Conclusion. Symptomatic CaWs show lower shear stress and stronger oscillations than asymptomatic CaWs. However, wall-based hemodynamic metrics alone may not distinguish CaWs from normal carotid geometries.

BackgroundDynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) enables non-invasive characterization of carotid atherosclerotic plaque. PurposeTo evaluate the performance and reproducibility of a simplified DCE-MRI quantification method for carotid plaque assessment. MethodsT1-weighted black-blood DCE-MRI of the carotid arteries at 3T was performed at baseline and after six months in patients with mild-to-moderate atherosclerotic lesions in a pilot placebo-controlled randomized trial evaluating the effects of low-dose (0.5mg daily) colchicine therapy on carotid plaque volume. DCE-MRI signal intensity was measured in manually drawn regions of interest in the plaque core, remote non-atherosclerotic vessel wall, and skeletal muscle. Peak signal intensities were normalized to skeletal muscle signal in the same slice. ResultsIn patients (n=28, median [interquartile range] age 72 [64-74] years, 36% female, n=13/15 colchicine/placebo), normalized peak signal intensity was higher in the plaque core than in the remote vessel wall at both baseline (3.5 [2.3-4.1] vs 2.1 [1.7-2.5], p<0.001) and follow-up (3.2 [2.5-4.4] vs 2.0 [1.7-2.5], p<0.001). Measurements did not differ between baseline and follow-up for all patients (0.7{+/-}0.7 for plaque core, 0.6{+/-}0.4 for remote vessel wall, p>0.80 for both) nor between colchicine intervention and placebo control (p>0.35 for either region). ConclusionsNormalised peak signal intensity on DCE-MRI was consistently higher in the carotid plaque core than in the remote vessel wall, showed excellent reproducibility in both regions over six months, and was not altered by colchicine treatment. This simplified, muscle-normalised approach may facilitate future studies exploring DCE-MRI measures potentially related to plaque vulnerability.

PurposeTo evaluate the hemodynamic impact of restoring a normal sino-tubular junction (STJ) following a novel Hegar dilator-based procedure in patients undergoing root-sparing ascending thoracic aortic aneurysm (ATAA) repair using computational modeling. MethodsWe retrospectively selected an ATAA patient who underwent pre- and postoperative gated computed tomography angiography (CTA). We developed a novel workflow to segment the lumen, thick-walled aorta, and aortic valve from CTA images for subsequent blood flow analysis using computational fluid dynamics (CFD) and fluid-structure interaction (FSI). Morphological and hemodynamic characteristics of the root were quantified and compared against those of a control subject, with no noted ascending aortic dilation. The models sensitivity to graft properties and leaflet material heterogeneity was analyzed. ResultsBoth CFD and FSI results showed that the postoperative geometry reconstructed with a normal STJ profile reintroduces sinus vortices during peak systole, similar to the control subject, but were absent pre-surgery. Accounting for aortic valve leaflets in FSI studies yielded qualitatively similar results to the CFD cases, albeit with locally elevated velocities, time-averaged wall shear stress (TAWSS), and energy dissipation, likely due to the dynamically changing orifice area and differing profiles of the left ventricular outflow tract (LVOT). ConclusionWe demonstrated that the novel Hegar dilator-based STJ reconstruction restores normal blood flow patterns, highlighting the importance of reprofiling the aortic sinuses and STJ. The study also highlights the models sensitivities, particularly the LVOT shape and leaflet morphology and mobility, and may assist planning STJ reconstruction to yield optimal hemodynamics before intervention.

Mitochondrial diseases are a diverse group of inherited neuromuscular disorders leading to progressive disability and early mortality. Mitochondrial myopathy is a common feature of mitochondrial disorders, affecting most patients. Assessment of disease progression and treatment efficacy in mitochondrial disease trials has often relied on muscle biopsies, however, these are increasingly considered unfavourable by patients. Imaging biomarkers of disease could reduce the patient burden, enabling non-invasive longitudinal monitoring of molecular information. Photoacoustic imaging combines the molecular sensitivity of light absorption with the deep tissue imaging capabilities of ultrasound, enabling a safe and fast imaging technique. Tuning the wavelength of light allows for the detection of molecular constituents such as oxy- and deoxy-haemoglobin, lipids, and water. These signatures may reflect underlying pathophysiological alterations and serve as valuable indicators of disease state and progression. We conducted an exploratory study of a photoacoustic imaging dataset in patients with mitochondrial myopathy due to the m.3243A>G mt-tRNALeu mutation and compared to healthy volunteers. We generated photoacoustic measurements at wavelengths in the near infrared, comparing absolute values and ratios derived in the bicep muscle. Confounding factors such as skin colour and sex were considered, and we ensured that these parameters were matched in healthy volunteers and patients. We identified significant differences between patients and controls, revealing changes in ratios between water and total haemoglobin, lipid and total haemoglobin, and lipid and water content. This study highlights the promise of photoacoustic imaging as a novel imaging biomarker in mitochondrial myopathies, paving the way for larger scale studies.

BackgroundAortic microstructure-function relationships and the pathophysiology of how medial degeneration leads to aortic dissection remain poorly defined. We aimed to determine how degeneration of individual components of the extracellular matrix (ECM), namely elastin, collagen, and proteoglycans, influence biomechanical properties of aortic tissue through an improved, disease-motivated enzymatic digestion framework. MethodsPorcine aortic tissue was sectioned into 200 {micro}m thick samples in the media, and progressively digested with elastase or collagenase for selective degradation of these ECM components. Full thickness human aortic tissues were treated with chondroitinase, hyaluronidase, and heparinase to completely remove proteoglycans. Biomechanical characterization was performed using planar biaxial tensile testing, from which low- and high-strain modulus, transition-zone behaviour, strain-energy density, and energy loss were derived. Degree of elastin fiber degradation was analyzed using two photon excitation fluorescence imaging. Analysis of collagen degradation was performed using picrosirius red staining under brightfield and polarized light. Alcian blue staining was used to evaluate proteoglycan content. ResultsInduced fragmentation and disorganization of elastin fibers reduced low-strain load bearing capacity, evidenced by reduced low-strain modulus, strain-energy density, and transition zone stress, along with reduced energy loss. Targeted collagen disorganization similarly reduced strain-energy density and decreased strain at the onset of transition, consistent with premature collagen recruitment, and was accompanied by reductions in high strain modulus and energy loss with increasing collagen degradation. Proteoglycan removal decreased energy loss and was found to modulate low- and high-strain behaviour, including reduced strain-energy density and strain at onset of transition, and increased high strain modulus. ConclusionsThrough targeted modelling of ECM degenerative features on aortic tissue mechanics, we have identified distinct disease-associated biomechanical roles for major matrix constituents, with overlapping effects. These findings delineate mechanical consequences of component-specific matrix degeneration while underscoring the complex, multifactorial nature of structure-function relationships in aortic disease.

ObjectiveSuper-resolution ultrasound (SR-US) reveals microvascular structures with exquisite resolution, but clinical translation remains limited by the need for ultrafast frame rates, massive data volumes, and long reconstruction times. This work proposes a deep learning framework that reconstructs microvascular maps from low-frame-rate enhanced ultrasound sequences, bypassing explicit microbubble localization and tracking. MethodsA transformer-decoder network with learned linear projections was designed to model spatiotemporal dependencies across sparse contrast-enhanced ultrasound sequences and reconstruct vessel probability maps, refined via a post-processing enhancement stage. Single-head self-attention captures temporal correlations under challenging conditions including overlapping microbubbles and low signal-to-noise ratios. Binary cross-entropy loss guided training to preserve vascular topology across synthetic and in vivo datasets. In vivo rat brain bolus data from the PALA challenge was used to evaluate this approach under up to 500 - fold data reduction (341 frames at 2 FPS vs. 170400 frames at 1000 FPS in standard ULM). ResultsDespite aggressive undersampling, the proposed pipeline recovered coherent microvascular architecture where conventional ULM pipelines applied to the same sparse data failed to produce continuous vascular networks. Major branches and higher-order microvessels remained visible with apparent vessel widths broadened by approximately three-fold relative to reference SR-US. End-to-end reconstruction completed in 28-133 seconds on an NVIDIA H100 GPU depending on the number of frames employed. ConclusionThe reported approach preserved vascular topology with fast reconstruction and low data overhead, albeit at lower resolution. The substantial reduction in frames and computation time highlights the translational potential of this SR-US-inspired microvascular imaging approach.

Quantitative, reproducible characterization of aortic microstructure is essential for advancing vascular biomechanics and mechanobiology. To address this need, we present a comprehensive image-analysis workflow that extracts quantitative descriptors of tissue microstructure from multiphoton microscopy stacks of the murine thoracic aorta. Channel-specific signals are acquired for fibrillar collagen (second harmonic generation), elastin (two-photon autofluorescence), and cell nuclei (two-photon excited fluorescence). Following reorientation into the XZ plane, individual elastic lamellae are traced to quantify lamellar thickness and interlamellar spacing using circle-based geometry (Taubin fitting). After correction for vessel wall curvature via a cylindrical transformation, segmented nuclei are assigned to medial or adventitial compartments based on visual estimates of adventitial volume fraction, and nuclear morphology is characterized via ellipsoidal fitting in terms of nuclear aspect ratio and major-axis orientation. Collagen organization is resolved in XY sections by extracting fiber centerlines to quantify straightness and amplitude; traces from serial sections are then combined to reconstruct the three-dimensional collagen network and estimate porosity and linear fiber density, while fiber orientation distributions are derived from principal component analysis-based angles and fit using a von Mises mixture model. Finally, collagen and elastin volume fractions are computed via a two-stage fixed-threshold approach calibrated on a balanced training subset. Overall, this modular and robust workflow provides an integrated framework for studying aortic wall remodeling across physiological and pathological processes. Non-Technical SummaryAs the main blood vessel in our body, the aorta needs to be both strong and flexible. This balance comes from three main parts: elastic layers that allow the aorta to stretch, strong fibers that prevent tearing, and cells that sense and respond to changes in blood pressure and other signals. When any of these components are altered, the aorta may stiffen or weaken, which can interfere with normal blood flow. In this study, we developed a clear and consistent way to measure the structure of the aortic wall using microscope images. The approach examines how thick the elastic layers are and how far apart they lie, the size and orientation of cell centers, and how straight or wavy structural fibers appear. It also estimates how much of each component is present in the aortic wall. Because the same steps are applied each time, results can be fairly compared across different conditions. Overall, this tool transforms detailed images into simple measurements, helping scientists understand how the aorta changes in health and disease.

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSIntroductionC_ST_ABSCardiovascular magnetic resonance (CMR) is the reference standard for quantifying cardiac structure and function, yet widely applicable population-based reference values remain limited. We derived age- and sex-specific reference ranges for ventricular volumes, mass, and function using data from the population-based German National Cohort (NAKO). MethodsShort-axis balanced steady-state free precession cine images from 3T CMR of 29,908 participants were analyzed using a validated deep learning segmentation pipeline with systematic quality control. From these, we defined a main reference cohort free of cardiovascular disease (CVD), and a healthy subcohort additionally free of cardiovascular risk factors. Standard left (LV) and right ventricular (RV) measures were quantified and indexed. Reference intervals (5th-95th percentiles) were modeled using additive models and quantile regression to capture non-linear age trends, stratified by sex, with formal testing for age-sex interactions. ResultsThe CVD-free reference cohort included 24,371 participants (mean age 43.8{+/-}12.2 years; age range 20-72 years, 44.7% women). LV and RV end-diastolic and end-systolic volumes declined with age, whereas LV ejection fraction remained stable and RV ejection fraction increased modestly. Sex differences were consistent across metrics and all major parameters demonstrated significant age-sex interactions; differences were most pronounced at younger ages and attenuated in later life. The healthy subcohort (n=5,550) showed similar structural and functional profiles, without clinically relevant deviations from the main reference cohort. ConclusionsThis study provides age- and sex-specific CMR reference ranges derived from a large, uniformly imaged national cohort. These data offer a population-based normative framework for clinical CMR interpretation and future research on sex-specific cardiac remodeling and healthy aging.

Background and ObjectivesLeft ventricular pressure-strain loop (LV-PSL) analysis provides noninvasive myocardial work indices that may reflect ventricular-arterial (VA) coupling, but their behavior under controlled physiologic stressors is incompletely defined. We aimed to characterize directional changes in LV-PSL, derived indices during standardized interventions predominantly affecting preload, afterload, or contractility in healthy adults. MethodsIn this prospective, within-subject repeated-measures study, 61 healthy volunteers underwent interventions designed to elicit domain-specific hemodynamic perturbations. Group 1 (n=31) performed isotonic exercise (contractility-dominant). Group 2 (n=30) performed isometric handgrip (afterload-increasing) and passive leg raising (PLR; preload augmentation with concurrent afterload change). LV-PSL indices were assessed at baseline and during each intervention. Six co-primary endpoints were prespecified: Global Work Index (GWI), peak systolic strain, strain range, systolic strain rate (SSR), arterial elastance (Ea), and end-systolic pressure (ESP). Within-subject changes were analyzed using paired tests with multiplicity adjustment and determined effect sizes. Reproducibility was evaluated using intraclass correlation coefficients (ICC). ResultsLV-PSL responses were directionally consistent with established pressure-volume physiology. Isotonic exercise produced large increases in contractility-sensitive indices, including GWI (dz=1.03), peak systolic strain (dz=0.88), strain range (dz=1.10), SSR (dz=1.29), and ESP (r=1.26), all adjusted p<0.001, while Ea remained unchanged. In contrast, isometric handgrip and PLR elicited afterload-dominant responses, with significant increases in ESP (dz=1.11 and 1.21, respectively; adjusted p<0.001) and Ea (dz=0.79 and 0.77; adjusted p[&le;]0.001), without significant changes in GWI or strain-derived indices after adjustment. Intraobserver reproducibility was good-to-excellent (ICC 0.86-0.90), and interobserver reproducibility was moderate-to-good (ICC 0.72-0.87). ConclusionsIn healthy adults, LV-PSL indices demonstrate good reproducibility and appropriate sensitivity to hemodynamic perturbations. Exercise elicited contractility-dominant responses, whereas handgrip and PLR induced afterload-dominant changes. These physiologically coherent response patterns support LV-PSL as a practical non-invasive surrogate for invasive pressure-volume assessment. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/26347879v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@113c652org.highwire.dtl.DTLVardef@1413e5aorg.highwire.dtl.DTLVardef@64b898org.highwire.dtl.DTLVardef@930462_HPS_FORMAT_FIGEXP M_FIG Central Illustration - Validation of Non-Invasive Pressure-Strain Loops for Assessing Ventriculo-Arterial Coupling The study evaluated left ventricle pressure-strain loop (LV-PSL) derived indices during three hemodynamic interventions in healthy volunteers: Group 1 - exercise (contractility-dominant), Group 2 - isometric handgrip (afterload-dominant), and passive leg raising (preload/afterload modulation). Center heatmap shows effect sizes (Cohens dz or rank-biserial r) for six co-primary PSL endpoints. Color intensity indicates effect magnitude (red = positive, blue = negative); asterisks denote significance after Holm-Bonferroni correction (**p[&le;]0.001). Exercise produced robust responses in 5/6 parameters, while handgrip and passive leg raising showed intervention-specific patterns, particularly for afterload indices. PSL methodology demonstrates high reproducibility and physiological sensitivity for non-invasive ventriculo-arterial coupling assessment. Abbreviations: LV-PSL, Left ventricle pressure-strain loop; PLR, passive leg raising; VA, ventriculo-arterial C_FIG

Background: Late gadolinium enhancement (LGE) quantification by cardiovascular magnetic resonance is central to risk stratification in hypertrophic cardiomyopathy (HCM), yet conventional techniques require contour tracing and region-of-interest (ROI) placement, which may reduce reproducibility and increase analysis time. We developed a novel visual standardized approach, the Visual Standardized Quantification of LGE (VISTAQ), that does not require myocardial contouring, arbitrary ROI positioning, or dedicated post-processing software. Methods: In this multicenter, multivendor retrospective study, LGE images from 400 patients (100 prior myocardial infarction, 250 HCM, 50 other non-ischemic heart diseases) were analyzed. VISTAQ subdivides each myocardial segment into transmural mini-segments and classifies LGE visually using predefined criteria, expressing global LGE burden as the percentage of positive mini-segments. Reproducibility was assessed in 250 patients across different observer expertise levels using intraclass correlation coefficients (ICC) and Bland?Altman analysis. In 100 HCM patients, VISTAQ was compared with conventional methods (mean+2SD, +5SD, +6SD, FWHM, visual thresholding). Prognostic performance was evaluated in 250 HCM patients over a median 5-year follow-up. Results: VISTAQ demonstrated excellent intra- and inter-observer reproducibility (ICC up to 0.98 and 0.97, respectively), consistent across disease subtypes. Compared with conventional techniques, VISTAQ showed similar ICC to FWHM but significantly lower net and absolute inter-observer differences (median absolute difference 1.3%). Mean+2SD markedly overestimated LGE, whereas mean+6SD slightly underestimated LGE compared with VISTAQ, mean+5SD, FWHM, and visual thresholding. Analysis time was substantially shorter with VISTAQ (median 105 vs. 375 seconds, p<0.0001). During follow-up, 21 hard cardiac events occurred in HCM population. An LGE threshold >10% predicted events with higher accuracy using VISTAQ (AUC 0.90; sensitivity 85%; specificity 94%) compared with mean+6SD (AUC 0.75; sensitivity 57%; specificity 93%). Conclusions: VISTAQ provides highly reproducible, time-efficient LGE quantification without dedicated software and demonstrates non-inferior prognostic discrimination in HCM compared with conventional threshold-based techniques.

A substantial body of evidence demonstrates that measures from mammograms are predictive of breast cancer risk. In this matched case-control study, mammograms acquired near the time of diagnosis were analyzed to investigate bilateral breast asymmetry as measure of short-term risk prediction. Specifically, contralateral breast images were compared with measures derived in the Fourier domain (FD); this technique summarizes power in concentric radial bands that cover the Fourier plane. Equivalently, this approach can be described as a multiscale characterization of the image. The summarized power difference between respective contralateral bands produces an asymmetry measure. Full field digital mammography (FFDM) and synthetic two-dimensional images from digital breast tomosynthesis (DBT) were investigated for women that had both types of mammograms acquired at the same time. Odds ratios (ORs) and the area under the receiver operating curves (Azs) were generated from conditional logistic regression modeling with 95% confidence intervals. Raw unprocessed FFDM images produced significant findings: OR = 1.90 (1.58, 2.29) and Az = 1.72 (0.67, 0.76) per one standard deviation unit. Associations were significant but attenuated for both clinical FFDM and DBT images: OR = 1.31 (1.11, 1.54) and Az = 0.63 (0.58, 0.67); and OR = 1.48 (1.25, 1.76) and Az = 0.65 (0.60, 0.70), respectively. Results suggest that clinical FFDM and DBT images are inferior to raw FFDM images in capturing breast asymmetry with information loss for breast cancer risk prediction. Moreover, these DBT images have lower spatial resolution but produced stronger associations than the clinical FFDM images.

BackgroundTricuspid transcatheter edge-to-edge repair (TEER) can induce an acute annuloplasty effect. While this has a therapeutic benefit, the mechanisms driving the reduction in annular size remain unclear. ObjectivesWe quantify the annular force induced by TEER in vitro in whole porcine heart preparations. We explore the impact of clipping different leaflet pairs on the TEER-induced annular forces. MethodsWe performed 49 interventions in 13 porcine hearts using a MitraClip XT. The clip was implanted between either the anterior-septal (AS), anterior-posterior (AP), or posterior-septal (SP) leaflet pairs. We also considered two-clip interventions between the combination of the AS-AP, AS-PS, or AP-PS leaflet pairs. For each intervention, we measured the right ventricular pressure, transvalvular flow rate, and force at eight locations around the annulus. ResultsTEER induced significant inward-pulling forces on the annulus. The maximum force was induced following an AS-PS two-clip intervention. A single AS clip induced the largest force among the one-clip interventions. Furthermore, the AP and AS-AP interventions induced the smallest annular forces. ConclusionsThe magnitude of the TEER-induced force depends on the intervention and number of clips implanted.

BackgroundVertebral artery calcification (VAC), a critical indicator of cerebrovascular disease, is often overlooked in head-and-neck imaging. Manual detection is time-consuming and prone to inter-observer variability. This study aimed to develop and validate a deep learning model for automated detection and quantitative risk assessment of VAC in non-contrast head-and-neck computed tomography (CT) images, bridging the diagnostic gap between dentistry and vascular medicine. MethodsWe developed a deep learning model based on the ResNet-18 architecture, designated as Grayscale ResNet, optimized for single-channel CT images. The development followed a two-phase strategy: initial training on 539 axial images from head-and-neck CT image followed by iterative refinement (fine-tuning) using a targeted dataset of clinically significant cases to ensure generalizability. The models performance was evaluated using patient-level Receiver Operating Characteristic (ROC) analysis and saliency map visualization for clinical interpretability. ResultsThe optimized model demonstrated a robust performance in distinguishing between cases with and without VAC. In the independent cohort, the model achieved an area under the curve (AUC) of 0.846. At a specific threshold value (98.6%), the system yielded a sensitivity of 80.0% and a specificity of 90.6%. A saliency map analysis confirmed that the model consistently focused on anatomically relevant vascular regions. ConclusionsThe proposed automated system provides an accurate and reliable method for VAC screening using routine head-and-neck CT scans. By transforming incidental imaging findings into a quantifiable risk index, this tool can serve as a vital decision-support system for dentists and radiologists, facilitating early patient referrals and contributing to global stroke prevention.