Mitral stenosis accounts for roughly twelve percent of patients with disease confined to a single heart valve, and it comes in two very different flavors. Rheumatic mitral stenosis, long the dominant form worldwide, arises from repeated group A streptococcal infections. Molecular mimicry between bacterial antigens and valve proteins triggers an autoimmune attack that fibroses the leaflets and fuses their commissures, sculpting the valve into a funnel whose tightest point sits at the leaflet tips. Mitral annular calcification, by contrast, is an inflammatory disease of aging in which calcium deposits build up in the fibrous ring anchoring the valve, sometimes extending onto the leaflet bases and forming a rigid calcific tunnel. In this condition the narrowest flow channel lies near the annulus rather than at the tips, and the entire valve apparatus takes on a shrunken appearance. In a large United States echocardiographic cohort, annular calcification was found in twenty-three percent of imaged patients, and stenosis was present in 6.6 percent of those with calcification compared with just 0.5 percent of those without. Prognosis is sobering: five-year survival in mitral stenosis associated with annular calcification has been reported below fifty percent.

Clinical imaging struggles to distinguish what these two diseases actually do to the blood. Doppler echocardiography measures velocities only along the ultrasound beam, so it cannot reconstruct the full three-dimensional velocity field inside the ventricle, and even four-dimensional flow magnetic resonance imaging lacks the resolution to capture the fine shear layers where viscous energy is dissipated. Earlier laboratory work using planar particle image velocimetry had hinted that calcific stenosis dissipates more energy than the rheumatic form, but a single imaging plane can miss out-of-plane velocities entirely. Because ventricular flow is inherently three-dimensional, the team turned to high-fidelity computation to see what planar measurements might be hiding.

The researchers built their virtual laboratory around real patients. Three mitral valve geometries, one healthy, one rheumatic, and one calcific, were digitally extracted from four-dimensional echocardiography at the moment of systolic closure, thickened to one millimeter, and embedded in a left ventricle model derived from a silicone phantom used in prior bench experiments. The calcific case included an additional rigid ring representing the annular calcium. Using an immersed finite element-finite difference fluid-structure interaction scheme with adaptive mesh refinement, the team simulated eight consecutive cardiac cycles at seventy beats per minute across cardiac outputs of 1.5, 3.0, 3.5, and 5.0 liters per minute, discarding the first three cycles so that statistics were drawn from a periodic steady state. Blood was modeled as an incompressible Newtonian fluid with a viscosity of 4.0 millipascal-seconds, and parallel simulations with water-like viscosity allowed direct comparison with the original in vitro platform.

The classic diagnostic numbers told a familiar but incomplete story. Both diseased valves produced elevated transmitral pressure gradients relative to the healthy valve, as expected. The rheumatic valve had the smallest geometric and effective orifice areas, yet the differences in mean pressure gradient and peak velocity between the two diseases flipped depending on cardiac output: peak velocity was higher in the rheumatic case at reduced flows, but the calcific valve took the lead at the physiologic 5.0 liters per minute. When the gradients were scaled by orifice area, however, the calcific valve carried the heavier effective hemodynamic burden, consistent with earlier bench findings.

The energetics told a sharper tale. Despite the rheumatic valve’s tighter orifice and higher velocities, the calcific case demanded the greatest pump stroke work, the mechanical energy the ventricle must expend to sustain each beat, and it also produced the highest three-dimensional ventricular kinetic energy and viscous energy dissipation across all equivalent flow conditions. The healthy valve sat lowest on every energetic measure. Crucially, the gap between the two diseases widened dramatically when the full three-dimensional velocity field was used instead of a single plane. At 3.5 liters per minute with blood-analog viscosity, planar measurements suggested only a twenty percent difference in total cycle dissipation between the calcific and rheumatic cases; the three-dimensional analysis put it at fifty-one percent. The discrepancy traces to large out-of-plane velocities in the calcific case that a planar laser sheet simply cannot see, a finding with direct implications for how laboratory flow studies of diseased hearts should be designed and interpreted.

Flow visualization and particle tracking revealed why the energy bills differ. In the healthy configuration, streamlines curled gracefully around the leaflets, forming the classic diastolic vortex ring that funnels blood toward the outflow tract. Both diseased valves destroyed this structure, but in characteristically different ways. The calcific jet drove straight toward the ventricular apex, scattering particles into the lower half of the chamber, while the rheumatic jet slammed into the inferolateral wall and sent particles crawling along the wall toward the apex, away from the exit. Of two thousand massless particles released upstream of the valve, seven hundred eight were ejected from the ventricle within three cycles in the healthy blood-analog simulation at 3.5 liters per minute, compared with 396 for the calcific valve and a mere 107 for the rheumatic valve, none of which had left the chamber by the third cycle in the water simulations. Retained particles in the calcific case traveled the longest total distances, a signature of inefficient recirculation, while ejected particles in the rheumatic case lingered longest inside the ventricle, indicating delayed filling and impaired mixing.

The clinical stakes are considerable. Breathlessness and exercise intolerance define valvular disease, and in rheumatic stenosis intervention is generally recommended once the orifice area falls below 1.5 square centimeters. Calcific stenosis is murkier: patients are older, carry more comorbidities, and it is often unclear whether their symptoms stem from the valve itself or from the stiff atrial and ventricular compliance that typically accompanies annular calcification. Intervention in this population is technically harder and riskier. If the valve’s geometric distortion is a primary driver of the physiological derangement, as these simulations suggest, then valve intervention may be justified even when conventional pressure gradients look unremarkable. Conversely, if chamber stiffness dominates, replacement could incur more risk than benefit. Etiology-specific hemodynamic signatures of the kind uncovered here could help clinicians make that distinction.

The authors are careful to frame the work as a proof of concept with real limitations. Each disease was represented by a single anonymized valve, so inter-patient variability remains unexplored; the leaflets were modeled as isotropic silicone, the calcification as fully rigid, and the subvalvular apparatus of chordae and papillary muscles was absent, which also limited loading conditions and caused the healthy valve model to invert at the highest flow rate. The ventricle was larger than physiological, yielding a reduced ejection fraction, and no direct volumetric validation against experiment or clinic was performed. Some quantitative discrepancies with the underlying bench study, including valve velocities and effective orifice areas, likely reflect unavailable pressure measurements used to set boundary conditions. Still, the qualitative vortex disruption and the comparative energetic rankings reproduced the in vitro observations, and extending them to three dimensions exposed differences no planar measurement could capture. The team calls for studies with larger valve cohorts, more physiological material models, and complementary validation data. If those confirm the pattern, the humble vortex, invisible to the stethoscope and only partially visible to the echocardiographer, may become a genuine target in the care of an aging population increasingly affected by calcified heart valves.

Subject of Research: Patient-specific fluid-structure interaction analysis of ventricular vortex formation and flow energetics in rheumatic versus calcific mitral stenosis

Article Title: Patient-Specific Analysis of Ventricular Vortex Formation and Flow Energetics in Rheumatic and Calcific Mitral Stenosis

Article References: Davey, M., Hashemi, M. S., Pressman, G. S., Kheradvar, A., & Griffith, B. E. (2026). Patient-Specific Analysis of Ventricular Vortex Formation and Flow Energetics in Rheumatic and Calcific Mitral Stenosis. Annals of Biomedical Engineering. https://doi.org/10.1007/s10439-026-04364-7

Image Credits: AI Generated

DOI: 10.1007/s10439-026-04364-7

Keywords: mitral stenosis, mitral annular calcification, rheumatic heart disease, fluid-structure interaction, ventricular vortex, cardiac fluid dynamics, flow energetics, viscous energy dissipation, echocardiography, left ventricle, biomedical engineering, computational modeling

The research team approached a problem that has long frustrated trauma researchers. Animal models of blunt chest trauma, while physiologically realistic, are difficult to control and raise ethical concerns, and they confound mechanical effects with inflammatory and neurological responses. Computational models, meanwhile, require validation against physical measurements. The solution adopted by the team was a laboratory left-heart simulator built around a transparent silicone left ventricle submerged in a water–glycerol mixture that mimics the density and viscosity of blood. The working fluid circulated through a left atrium, into the ventricle, and onward through an aortic section, with bioprosthetic valves installed at both the mitral and aortic positions to reproduce realistic valve opening and closing behavior.

The engineering centerpiece of the setup was a pair of linear motors. One drove the cyclic contraction and relaxation of the artificial ventricle, replicating the pumping action of the cardiac cycle. The second delivered precisely timed external impacts to the simulator, emulating the kind of short, low-velocity blow the chest might experience in a vehicle collision. Crucially, the researchers could trigger that impact at five different timings within the cardiac cycle, allowing them to test a central hypothesis of the study: that the heart’s hemodynamic response to trauma depends not just on the force of the blow, but on exactly when in the heartbeat it lands.

To visualize what happened inside the beating chamber, the team turned to particle image velocimetry, or PIV, a laser-based optical technique widely used in experimental fluid mechanics. Microscopic particles seeded in the blood-analog fluid were illuminated in a thin laser sheet, and high-speed cameras recorded their motion. By cross-correlating successive image frames, the researchers reconstructed the full two-dimensional velocity field of the flow inside the ventricle and the aorta. From those velocity fields they derived quantities of direct physiological relevance: vorticity, a measure of the local swirling rotation of the fluid; kinetic energy carried by the moving blood; and viscous energy dissipation, often abbreviated VED, which quantifies how much of the blood’s mechanical energy is irreversibly lost to friction as chaotic, poorly organized flow.

These energy metrics matter because the healthy heart is a remarkably efficient pump. Decades of work in cardiac fluid dynamics, including landmark studies showing that nature optimizes the swirling vortex flow inside the left ventricle, have established that organized vortical structures during filling and ejection minimize energy loss and smooth the redirection of blood through the asymmetric geometry of the heart. Elevated viscous energy dissipation is a recognized marker of abnormal flow, measurable in patients today with four-dimensional flow MRI, and it has been linked to pathological conditions in both the ventricle and the aorta. If a chest impact pushes the intracardiac flow toward a more dissipative state, that shift provides an objective, quantifiable signature of the disturbance—something clinicians could eventually look for in trauma patients.

The results revealed a striking phase dependence. In every impact condition except one, the velocity field inside the left ventricle was measurably altered by the blow. The single exception was early systole, the brief window just after the mitral valve closes and the ventricle begins to contract. At that moment, the heart appears to be momentarily insensitive to external perturbation, perhaps because the contracting muscle and the rapidly accelerating outflow dominate the local fluid dynamics. By contrast, impacts delivered during late systole produced the most pronounced reduction in vorticity, suggesting that a blow near the end of contraction disrupts the swirling structures that normally organize the blood for ejection.

Viscous energy dissipation told a complementary story. At the instant of impact, VED increased in all tested conditions, indicating that the external blow consistently injected disorder into the flow, converting organized kinetic energy into heat through viscous friction regardless of cardiac timing. The aorta, however, responded in a more selective fashion. Flow velocity, volumetric flow rate, kinetic energy, and viscous energy dissipation in the aortic section all increased primarily when the impact arrived during systolic phases of the cycle. This makes intuitive mechanical sense: during systole the aortic valve is open, so any sudden compression or acceleration of the ventricular contents is transmitted directly down the outflow tract, momentarily boosting the momentum of blood entering the aorta and simultaneously increasing the dissipative losses associated with that disturbed, high-velocity flow.

The authors emphasize that the impacts they imposed were short and sub-physiological in the sense of being brief, controlled laboratory perturbations rather than full crash-level loading events. Yet even these modest, millisecond-scale disturbances were sufficient to induce measurable flow disturbances whose magnitude and character depended on cardiac timing. That finding carries a provocative implication for trauma science: the severity of blunt cardiac injury may not be a simple function of impact energy alone, but of the interaction between the impact waveform and the dynamic mechanical state of the heart at the moment of contact. Two collisions delivering identical external loads could, in principle, produce very different intracardiac flow disturbances depending on where they fall within the roughly one-second span of the cardiac cycle.

The study builds on the team’s earlier work, including a companion paper in the Journal of Biomechanics describing the in-vitro simulator itself, and on a growing body of crash-injury research that seeks to connect vehicle crash data to virtual injury assessment through finite element modeling of the thorax. By anchoring those computational efforts with hard experimental numbers—velocity fields, vorticity distributions, kinetic energy, and dissipation budgets measured under controlled impact conditions—the new results provide validation data that numerical models of blunt aortic and cardiac injury have lacked. The researchers have also made the MATLAB post-processing code for their fluid dynamics analyses publicly available, lowering the barrier for other groups to adopt the same analytical framework.

Clinically, the work points toward a future in which the fluid-dynamic signature of cardiac trauma could complement electrocardiographic and imaging findings in emergency departments, where diagnosing blunt cardiac injury remains notoriously difficult and where systematic reviews have questioned the accuracy of current diagnostic tests. It may also inform the design of passive safety systems: if certain phases of the cardiac cycle render the heart more vulnerable to flow disruption, that knowledge could eventually feed into injury criteria used to evaluate restraint systems and vehicle structures. For now, the study’s most immediate contribution is conceptual—a demonstration that the biomechanical response of the heart to external impact is fundamentally phase-dependent, and that the invisible world of intracardiac fluid dynamics responds to trauma in ways that can now be measured, quantified, and modeled with laboratory precision.

Subject of Research: Experimental quantification of left ventricular blood flow and energy changes during timed external chest impacts

Article Title: Left Ventricle Velocity Patterns and Energy Changes During Controlled External Impact: A Quantitative Experimental Insight

Article References: Sweidy, D., Mathyssen, A., Teimouri, K., Maraouch, G., Wei, W., Saleh, W., Kadem, L., & Evin, M. (2026). Left Ventricle Velocity Patterns and Energy Changes During Controlled External Impact: A Quantitative Experimental Insight. Annals of Biomedical Engineering. https://doi.org/10.1007/s10439-026-04405-1

Image Credits: AI Generated

DOI: 10.1007/s10439-026-04405-1

Keywords: blunt chest trauma, left ventricle, cardiac fluid dynamics, particle image velocimetry, viscous energy dissipation, aorta, vorticity, motor vehicle crashes, biomechanics, heart simulator, cardiac cycle, hemodynamics

The research team, led by Jeffrey Ji-Peng Li and Patrick Doeblin, identified 132 patients with mitral valve prolapse among all individuals who underwent cardiac magnetic resonance imaging at their institution between 2013 and 2022. These patients were compared with 50 controls without any apparent cardiac disease, drawn from five previous prospective studies. The scans were performed on 1.5-Tesla and 3-Tesla scanners using standard cine imaging, and strain analysis was carried out semiautomatically with the MEDIS QStrain 4.1 software. Because feature tracking can be applied retrospectively to existing cine images, the method allowed the researchers to extract detailed deformation data from nearly a decade of routine clinical scans.

Strain analysis quantifies how much the heart muscle shortens, thickens, or lengthens during each heartbeat, expressed as a percentage change from its resting dimension. Longitudinal strain describes the shortening of the heart muscle along its long axis, and in a healthy ventricle the values are negative, becoming more negative with stronger contraction. Feature tracking works by identifying grayscale patterns on the endocardial and epicardial borders of cine images and following them frame by frame across the cardiac cycle. This differs fundamentally from echocardiographic speckle tracking, which follows acoustic markers within the tissue, meaning that strain values from the two modalities are not directly interchangeable, although global measures correlate reasonably well.

The headline result was a clear base-to-apex gradient in longitudinal strain. After adjusting for age and sex, patients with prolapse showed less negative, meaning impaired, strain values in all basal segments of the left ventricle, with the largest deficits in the basal anterolateral segment, where the adjusted difference reached 6.0 percentage points, followed by the basal inferior and basal anterior segments. Parts of the medial wall were also affected, particularly the medial anterior and medial anterolateral segments. In contrast, the apical segments showed more negative, meaning enhanced, strain values compared with controls, with differences of up to 5.4 percentage points in the apical inferior region. The apex itself and most of the remaining medial segments were similar between the two groups.

Crucially, this regional imbalance cancelled itself out at the global level. Left ventricular global longitudinal strain, global circumferential strain, and right ventricular free wall longitudinal strain were all statistically comparable between patients and controls. The only global parameter that stood apart was left atrial reservoir strain, which showed a trend toward reduction in the prolapse group, a notable finding because the researchers had deliberately excluded anyone with moderate or worse valve leakage. This hints at what the authors describe as a possible primary atriopathy, in which the abnormal motion of the prolapsing leaflets stretches the atrial walls and drives remodeling, independent of any regurgitant volume.

The mechanical explanation for the basal strain deficits likely lies in the peculiar anatomy of prolapse. In the Berlin cohort, 68 percent of patients showed systolic curling, an abnormal motion of the posterior mitral ring relative to the adjacent myocardium, and many had mitral annular disjunction, a separation of the valve annulus from the underlying heart muscle visible in both systole and diastole. These structural abnormalities alter how contractile forces are transmitted through the basal myocardium, and the reduced strain values there may reflect a combination of genuine contractile impairment and measurement effects arising from the distorted mechanics. Disentangling the two is precisely what the study set out to quantify, so that clinicians interpreting regional strain in prolapse patients can better judge when an abnormality signals true myocardial disease rather than a mechanical artifact.

Supporting the idea that at least part of the basal impairment is real, 19 of the 114 patients who received contrast-enhanced imaging showed signs of local myocardial fibrosis, concentrated in the basal and medial inferior and inferolateral walls, exactly the regions with the worst strain values. Fibrosis near the mitral annulus is a well-recognized feature of prolapse and is clinically important because of its association with ventricular arrhythmias and sudden cardiac death. The proportion observed here, roughly 17 percent, sits close to the 25 percent reported in earlier studies. Abnormal mechanical stress from the prolapsing leaflets may trigger remodeling processes that promote fibrosis, and fibrotic tissue in turn contracts poorly, creating a plausible feedback loop between valve mechanics and myocardial injury.

One of the most novel observations was a strain ratio comparing the basal anterolateral segment with the apical lateral segment. This ratio was significantly lower in prolapse patients than in controls, indicating a predominant apical deformation of the lateral wall, a pattern not previously described. Intriguingly, patients with mitral annular disjunction showed a slightly higher ratio than those without, suggesting that in disjunction the compensatory boost in apical contraction is blunted. The authors speculate that this loss of apical compensation could represent a mechanistic link between annular disjunction and the elevated arrhythmic risk reported in prior studies, although they caution that the fibrosis subgroup was small and not all patients underwent contrast imaging, so the interpretation remains provisional.

To test whether the pattern was an artifact of magnetic resonance feature tracking, the team repeated the analysis in a small subgroup of 19 patients and 9 controls who also had transthoracic echocardiograms suitable for speckle tracking. Despite the limited sample, the echocardiographic data reproduced the same regional signature, with worse strain at the base and better strain at the apex in prolapse patients. This cross-modality agreement strengthens the case that the pattern reflects a genuine mechanical phenomenon of the prolapsing heart rather than a quirk of one imaging technology, though the authors note that the choice of analysis software can itself influence strain results and may partly explain why earlier studies reached conflicting conclusions.

The study has limitations worth keeping in view. It was retrospective, and most patients were referred for magnetic resonance for reasons other than the valve condition itself, such as breathlessness or suspected cardiomyopathy, so the cohort may not perfectly represent the asymptomatic majority of prolapse cases. Images were acquired over ten years on scanners of two different field strengths, although prior work suggests this has minimal impact on strain measurements. The prolapse itself was generally mild, with an average displacement of the leaflets of only 4.4 millimeters, leaving open the question of whether more severe prolapse would push the strain abnormalities further toward the mid-ventricle and apex. Even so, as the largest cardiac magnetic resonance study of regional strain in mitral valve prolapse to date, the work provides a detailed reference map of how the prolapsing heart deforms, and it lays the groundwork for future studies testing whether these strain signatures can improve risk stratification for the arrhythmias and sudden cardiac death that remain the most feared complications of this common condition.

Subject of Research: Regional left ventricular strain patterns measured by cardiovascular magnetic resonance feature tracking in patients with mitral valve prolapse

Article Title: Regional strain patterns in patients with mitral valve prolapse

Article References: Li, J. J.-P., Ching, S., Aigner, A., Edelmann, F., Werhahn, S. M., Beyer, R., Schulz-Menger, J., Erley, J., Estepa, M., Meuwly, C., Eggers, A.-S., Stehning, C., Hashemi, D., Solowjowa, N., Klein, C., Hilgendorf, I., Kelle, S., & Doeblin, P. (2026). Regional strain patterns in patients with mitral valve prolapse. Clinical Research in Cardiology. https://doi.org/10.1007/s00392-026-03033-y

Image Credits: AI Generated

DOI: 10.1007/s00392-026-03033-y

Keywords: mitral valve prolapse, cardiac magnetic resonance, feature tracking, longitudinal strain, left ventricle, mitral annular disjunction, myocardial fibrosis, left atrial strain, ventricular arrhythmia, cardiology, strain analysis, valvular disease

The team, led by Kagan Ucak, Coskun Bilgi, and Niema M. Pahlevan, focused on diastole, the relaxation phase of the cardiac cycle when the left ventricle fills with blood returning from the lungs. Filling happens in two waves: an early passive rush of blood called the E-wave, driven by the ventricle’s own relaxation, and a later surge called the A-wave, produced when the atrium contracts. Between the two lies diastasis, a quiet interval in which little blood moves at all. Cardiologists have long used the ratio of the peak velocities of these two waves, the E/A ratio, to classify diastolic function into normal filling, impaired relaxation, and restrictive filling, the latter marking the most severe stage of dysfunction. What has remained murky is precisely how these different inflow patterns reshape the fluid dynamics inside the chamber and what that reshaping costs the heart in mechanical efficiency.

To find out, the researchers constructed a physiologically accurate left ventricle simulator: a compliant, transparent silicone sac submerged in a pressurized acrylic tank and driven by a programmable piston pump. The sac was fitted with artificial mitral and aortic valves and connected to a hydraulic circuit with adjustable resistance and compliance, allowing the team to tune afterload and preload independently. A blood-analog fluid, mixed from water, glycerol, and urea to match the viscosity and density of real blood, was seeded with tiny fluorescent microspheres. By illuminating a thin laser sheet through the ventricle’s mid-plane and capturing images with a 12.6-megapixel high-speed camera, the researchers performed phase-locked particle image velocimetry, or PIV, resolving velocity fields with a spatial resolution of roughly 0.4 millimeters across 29 repeated cardiac cycles for each experimental condition.

The elegance of the setup lies in its control. In patients, it is nearly impossible to isolate the effect of a single parameter, because heart rate, stroke volume, filling pressure, and ventricular geometry all change together as disease progresses. In the simulator, the team could dial in an E/A ratio below 0.8 to mimic impaired relaxation, above 2.0 to mimic restrictive filling, or an intermediate value for normal filling, while independently varying the duration of diastasis from zero to twenty percent of the cardiac cycle, the heart rate from 60 to 90 beats per minute, and the cardiac output from 2.0 to 3.3 liters per minute. Crucially, the resulting inflow velocities of 0.5 to 0.9 meters per second fell squarely within the range measured clinically by Doppler echocardiography, and the calculated vortex formation times matched values previously reported in patients.

What the camera revealed was striking. Under normal filling, the E-wave generates a pair of counter-rotating vortices that sweep toward the ventricular apex, settle near the walls, and gently fade as the A-wave delivers its own vortex pair into the center of the chamber. The two vortex systems coexist in an orderly, energy-efficient sequence. Under restrictive filling, by contrast, the E-wave arrives with far greater force, producing larger, more intense vortices that dominate the chamber, while the weakened A-wave enters without forming any coherent vortex structure at all. The result is a burst of intense dissipation early in diastole followed by an almost stagnant ventricle, with the velocity field nearly motionless by the time systole begins.

The quantitative consequences were dramatic. Restrictive filling patterns produced a peak viscous energy dissipation fifty percent higher than normal filling, along with a 38 percent increase in peak turbulent kinetic energy and a 21 percent higher peak shear rate. Impaired relaxation patterns told a different story: because the weak E-wave vortices linger in the chamber, the arriving A-wave vortices catch up and merge with them, creating a single, larger, tilted vortex structure that persists into early systole. This merging event drove the highest peak turbulent kinetic energy of all, 57 percent above normal, and pushed peak energy dissipation 46 percent above the healthy baseline. Elevated shear rates and turbulent kinetic energy are clinically meaningful because both have been linked to damage of blood cells and platelets, suggesting that severely diseased filling patterns may impose additional hemodynamic stress on the blood itself.

Perhaps the most surprising discovery concerned diastasis, the quiet pause between the filling waves, which had never been systematically studied before. The researchers found that a moderate diastasis duration, around ten percent of the cardiac cycle, minimized viscous energy dissipation across all E/A ratios, revealing a local energetic optimum that corresponds precisely to the normal filling pattern with an E/A ratio near 1.5. Too little diastasis forces the filling waves to collide and interact chaotically; too much allows the E-wave vortices to dissipate completely before the A-wave arrives, forfeiting any beneficial interaction. Intriguingly, this optimum vanished under low-cardiac-output conditions, hinting that the energetic landscape of the ventricle shifts with the heart’s overall workload.

The team also uncovered distinct scaling laws for the impaired relaxation pattern. When stroke volume was varied from 27 to 53 milliliters at a fixed heart rate, diastole-averaged energy dissipation rose nonlinearly, following a second-order polynomial trend. When heart rate was varied from 60 to 90 beats per minute at constant cardiac output, dissipation per cycle stayed essentially constant, meaning total wasted energy scaled linearly with heart rate. The authors note an intriguing parallel with exercise physiology: stroke volume and heart rate both rise linearly with exercise intensity up to a threshold, beyond which stroke volume plateaus and falls while heart rate keeps climbing. The nonlinear energy penalty associated with increasing stroke volume may help explain why the heart sheds stroke volume at high exertion, particularly in patients whose ventricles are already filling inefficiently.

More than 6.7 million adults in the United States live with heart failure, and elevated left ventricular filling pressure is a central driver of the disease. Current diagnosis of diastolic dysfunction relies on Doppler indices such as the E/A ratio, mitral annular velocities, and estimates of filling pressure, but these provide only indirect glimpses of what the blood is actually doing inside the chamber. The USC team’s results suggest that flow-based energetic metrics, such as viscous energy dissipation, turbulent kinetic energy, and the presence of vortex merging, could serve as complementary markers of disease severity, potentially measurable at the bedside with echocardiographic particle image velocimetry, a technique already being explored in clinical settings.

The researchers are careful to note the limitations of their model. The simulator cannot replicate the full complexity of living myocardium, including fiber architecture, ventricular twist, and aortic root recoil, and its two-dimensional imaging cannot capture out-of-plane velocities in an inherently three-dimensional flow. The reported turbulent kinetic energy values, computed from 29 phase-locked cycles, should be read as comparative measures of flow fluctuation rather than direct measurements of fully developed turbulence. Still, as a controlled mechanistic study, the work delivers something clinical imaging cannot: a clean, parameter-by-parameter demonstration that the balance between early and late filling is not merely a diagnostic curiosity but a genuine determinant of the heart’s hydraulic efficiency. If future clinical studies confirm that these vortex signatures track with disease progression, the humble whirlpool inside the beating heart could become a powerful new window into heart failure, one that physicians could watch swirl, merge, and dissipate in real time.

Subject of Research: In vitro analysis of left ventricular vortex dynamics and energy dissipation across diastolic function filling patterns

Article Title: Vortex Dynamics and Energy Dissipation in Left Ventricular Diastolic Filling Across Diastolic Function Inflow Patterns: An In Vitro Quantitative Flow Analysis

Article References: Ucak, K., Bilgi, C., & Pahlevan, N. M. (2026). Vortex Dynamics and Energy Dissipation in Left Ventricular Diastolic Filling Across Diastolic Function Inflow Patterns: An In Vitro Quantitative Flow Analysis. Annals of Biomedical Engineering. https://doi.org/10.1007/s10439-026-04369-2

Image Credits: AI Generated

DOI: 10.1007/s10439-026-04369-2

Keywords: diastolic dysfunction, left ventricle, vortex dynamics, particle image velocimetry, energy dissipation, turbulent kinetic energy, heart failure, E/A ratio, diastasis, hemodynamics, in vitro model, cardiac fluid mechanics

The research team, based at Brigham and Women’s Hospital, followed thirty wild-type pups from three litters through four developmental milestones: postnatal day 0 (P0), day 8 (P8), day 21 (P21), and eight weeks of age. Using the VisualSonics Vevo F2 high-frequency ultrasound system with transducers operating between 25 and 71 MHz, the investigators captured images of hearts beating at rates of 400 to 600 beats per minute with exceptional spatial and temporal resolution. At birth, when a pup weighs barely more than a gram and its left ventricle measures roughly 1.5 millimeters across, imaging was performed without anesthesia or hair removal, with animals gently restrained on a heated platform. From P8 onward, a standardized isoflurane protocol maintained heart rates above 400 beats per minute while body temperature was held at 37 degrees Celsius, minimizing the hemodynamic variability that anesthesia can otherwise introduce.

The structural findings chart an astonishing trajectory of growth. Body weight rose from 1.25 grams at birth to nearly 21 grams at adulthood, while the left ventricular end-diastolic volume expanded almost tenfold, from about 6.4 microliters to 59 microliters. Ventricular walls thickened in parallel, with the systolic anterior wall more than doubling from birth to weaning and continuing to grow into adulthood. Perhaps most intriguing was the behavior of body-weight-indexed left ventricular mass, which surged during the early postnatal and juvenile periods before declining toward adult values. This transient overshoot, the authors note, mirrors the well-described postnatal transition in which cardiomyocytes shift from proliferative expansion to hypertrophic growth, with the heart briefly outpacing the body before mass and body weight rescale proportionally at maturity.

Counterintuitively, conventional indices of pumping performance declined steadily across development. Ejection fraction fell from 69 percent at birth to 60 percent at eight weeks, and fractional shortening followed a similar downward path. Rather than signaling weakening hearts, the authors explain, this decline reflects geometry and loading: as the ventricular cavity expands disproportionately relative to stroke volume, and as systemic afterload rises with maturation, volumetric efficiency measures naturally decrease even as the heart muscle itself grows stronger. Crucially, the strain measurements told a different story. Global circumferential strain, endocardial circumferential strain, and global radial strain all remained statistically stable from P8 through adulthood, indicating that the intrinsic contractile machinery of the myocardium is established early and preserved intact through the storms of growth and remodeling.

Strain analysis, enabled by speckle-tracking software that follows the natural acoustic markers within heart tissue frame by frame, quantifies how much the ventricular wall deforms during each beat. Longitudinal strain captures shortening along the base-to-apex axis, circumferential strain measures shortening around the chamber’s circumference, and radial strain records wall thickening toward the cavity. Because these indices depend on the coordinated behavior of individual contractile units rather than on chamber geometry, they are considered exquisitely sensitive detectors of early dysfunction, often flagging impairment in disease models long before ejection fraction budges. The one strain parameter that did change was myocardial global longitudinal strain, which became significantly more negative, from minus 8.8 percent at P8 to minus 11.9 percent at P21, suggesting selective maturation of the longitudinal contractile pathway during the juvenile period.

Diastolic function, the heart’s capacity to relax and fill, matured along its own timetable. From P8 onward, early and late transmitral filling velocities climbed steadily, with the E/A ratio peaking at day eight before stabilizing. Tissue Doppler velocities at the mitral annulus, including the early relaxation velocity e-prime, the late atrial contraction velocity a-prime, and the systolic annular velocity s-prime, all increased progressively into adulthood. Right ventricular function, tracked through tricuspid annular plane systolic excursion, nearly doubled from 0.40 millimeters at P8 to 0.78 millimeters at eight weeks. Left atrial areas grew in step with the rest of the heart, though fractional area change fluctuated without a consistent directional trend. These trajectories align with known postnatal refinements in calcium-handling proteins such as SERCA2a and ryanodine receptor 2, and with the metabolic switch from glycolysis to fatty-acid oxidation that newborn cardiomyocytes undergo shortly after birth.

One of the study’s most striking discoveries emerged when the data were split by sex. Most conventional parameters showed no sex-specific developmental patterns, but strain imaging revealed a clear divergence in late adolescence. By eight weeks, males exhibited significantly more negative longitudinal strain and higher radial strain than females, and systolic annular velocity showed the same pattern, with males reaching 21.5 millimeters per second versus 17.3 in females. Stroke volume also displayed a significant time-by-sex interaction. The timing is telling: the divergence between P21 and week eight coincides with pubertal maturation and the surge in circulating androgens, and it is consistent with prior work showing that isolated cardiomyocytes from adult male mice contract more vigorously than those from females, likely through testosterone-driven modulation of calcium handling and myofilament function.

Notably, this mouse pattern inverts the human picture, where women typically show greater myocardial strain values than men. The authors point to fundamental species differences as likely explanations: adult mouse ventricles predominantly express the fast-kinet ics alpha myosin heavy chain, whereas human ventricles express the slower beta isoform, and the tenfold difference in resting heart rate between the species fundamentally alters contraction-relaxation dynamics. Sex differences in cardiac function are also dynamic across the lifespan; aging studies suggest the male advantage seen at eight weeks may reverse later in life, with females maintaining better contractility into old age. For researchers translating murine findings to human cardiology, the message is unambiguous: sex- and species-specific normative values are essential, and extrapolating adult or human reference ranges to neonatal and juvenile mice risks misjudging both disease severity and therapeutic efficacy.

The study also functions as a technical manual for a notoriously difficult measurement. The authors document a systematic 12.3 percent overestimation of ejection fraction by short-axis M-mode derived from the Teichholz formula compared with B-mode Simpson’s monoplane volumetry, a bias that persisted at every developmental stage and that they recommend accounting for, particularly in disease models with regional wall motion abnormalities. They further emphasize maintaining normothermia in neonatal pups, which cannot thermoregulate and are prone to hypothermia-induced bradycardia, transferring maternal scent to gloved hands before handling to prevent rejection by dams, positioning the M-mode cursor perpendicular to the septum at the mid-papillary level while avoiding papillary muscle inclusion, and keeping Doppler angles below 45 degrees to prevent velocity underestimation. A printable echocardiography quicksheet summarizing key reference values accompanies the publication as a bench-side tool.

The limitations are candidly acknowledged: the data derive exclusively from Jackson Laboratory C57BL/6 mice, whose developmental trajectories may differ across strains; volumetric parameters rest on geometric assumptions that strain measurements avoid; and the extreme technical constraints of imaging newborn hearts meant that strain, Doppler, and right ventricular assessments could not be performed at P0. Future directions include comprehensive right ventricular and large-vessel characterization, integration with invasive pressure-volume loop analysis, and extending the serial observations into aging to trace how the early-life sex differences evolve across the lifespan. For now, the study stands as the definitive developmental atlas of the laboratory mouse heart, one that promises to sharpen the interpretation of countless cardiac disease models and, by reducing misclassification of phenotypes, to trim both animal usage and cost in preclinical research.

Subject of Research: Postnatal cardiac development and myocardial strain in C57BL/6 mice assessed by high-frequency echocardiography

Article Title: Prospective echocardiographic characterization of postnatal cardiac development in C57BL/6 mice: Strain analysis between birth and adulthood

Article References: Jo, S., Spyropoulos, G., Hart, L. G., Covington, T. A., Pandey, A. K., Michel, T., & Spyropoulos, F. (2026). Prospective echocardiographic characterization of postnatal cardiac development in C57BL/6 mice: Strain analysis between birth and adulthood. Physiological Reports, 14(18), Article e71113. https://doi.org/10.14814/phy2.71113

Image Credits: AI Generated

DOI: 10.14814/phy2.71113

Keywords: echocardiography, strain analysis, C57BL/6 mice, cardiac development, speckle-tracking, ejection fraction, diastolic function, sexual dimorphism, left ventricle, normative values, preclinical imaging, Physiological Reports

The new framework, called hierarchy-aware CT-driven constrained constructive optimization, or HCT-CCO, was developed by S. L. Vajire and Lik-Chuan Lee at Michigan State University together with Jenny S. Choy and Ghassan S. Kassab at the California Medical Innovations Institute. Writing in the Annals of Biomedical Engineering, the researchers describe how their method starts with a segmented epicardial coronary network, the visible large vessels such as the left anterior descending and left circumflex arteries, and grows a full arterial tree into the left ventricular myocardium, the thick muscular wall of the heart’s main pumping chamber. The result is a network spanning eleven hierarchical vessel orders, from vessels roughly three millimeters wide down to precapillary branches around eight micrometers in diameter.

The core idea builds on a decades-old technique known as constrained constructive optimization, or CCO, which grows synthetic vascular trees by repeatedly adding new terminal branches wherever they minimize the total hydraulic resistance of the network. Conventional CCO, however, has a fundamental limitation: it was designed for idealized geometric domains such as simple blocks or analytic shells, not for the complex, patient-specific anatomy of a real heart. When applied to a heart-shaped domain, conventional CCO fills the available space but produces vessels that bear little resemblance to the organized trunk-and-branch architecture of a genuine coronary tree. The generated hierarchies also vary wildly between repeated runs, making the method unreliable for physiological study.

The Michigan State and San Diego team attacked the problem from three directions. First, they anchored the entire growth process in real anatomy. The left ventricular wall segmented from CT images defines the admissible growth region, enforced through a Euclidean distance field that ensures every candidate vessel maintains a prescribed clearance from both the inner and outer surfaces of the heart wall. The segmented epicardial arteries serve as the proximal scaffold, so the algorithm does not regenerate what imaging already shows; it resumes growth directly from the imaged macrovasculature into the sub-resolution territory below.

Second, the researchers overhauled the local optimization that occurs every time a new branch is added. In conventional CCO, the bifurcation point where a new branch splits off is initialized at the geometric midpoint of the host segment with symmetric daughter radii, giving the nonlinear solver no physiological guidance. The new framework instead seeds each bifurcation with a flow-weighted position and daughter radii derived from a well-established coronary branching law with exponent 2.33, then refines the configuration by minimizing hydraulic resistance according to the Kamiya-Togawa optimality principle. This analytic initialization places the solver close to the true optimum from the start, accelerating convergence and preventing degenerate solutions under strong flow asymmetry.

The third and arguably most consequential innovation is the hierarchy-aware branching schedule. In conventional CCO, a new terminal segment can attach to any existing segment throughout growth. The HCT-CCO framework progressively restricts this choice in three stages tied to the fraction of target terminals reached. During the first ten percent of growth, branching is unrestricted, allowing coherent densification of intermediate vessel generations. From ten to thirty-five percent, new branches may attach only to terminal segments and a limited band of their ancestors. Beyond thirty-five percent, branching is confined to terminal segments and their immediate parents. This progressive narrowing mirrors how real coronary trees behave: proximal vessels show broadly distributed connectivity, while distal arterioles branch in an increasingly localized fashion.

To judge whether the synthetic trees are physiologically credible, the team turned to the gold-standard benchmark in the field: the detailed morphometric measurements of the pig coronary arterial tree published by Kassab and colleagues in 1993. Using the diameter-defined Strahler ordering scheme, which classifies vessels by both topology and diameter to reduce overlap between adjacent orders, they compared their generated networks against the experimental data across multiple measures. The results were striking. Across ten independent stochastic realizations on the same heart geometry, the HCT-CCO framework achieved a connectivity F1 score of 0.95 against the experimental order-to-order connectivity matrix, compared with 0.85 for conventional CCO. The diameter-order deviation from the porcine benchmark was 0.034 on a logarithmic scale for the new framework, corresponding to agreement within roughly eight percent, versus nearly a full order of magnitude for conventional CCO. Statistical testing showed complete separation between the two methods, with every HCT-CCO realization outperforming every conventional realization.

The researchers then applied the framework to five subject-specific CT-derived pig heart geometries plus one synthetic case. In every case, the generated trees reached the full eleven-order hierarchy, with mean vessel diameters increasing monotonically and quasi-exponentially with order, closely tracking the experimental curves. The transmural distribution of terminal vessels, those located in the inner versus outer halves of the heart wall, came out nearly balanced, with a slight epicardial predominance of about 52 percent versus 48 percent, a pattern qualitatively consistent with reported higher microvascular density near the outer wall, though the authors caution that the epicardial starting scaffold may contribute to this bias.

Crucially, the networks are not just geometrically plausible; they are hemodynamically workable. The team solved a representative generated network as a steady-state resistive model, calibrating total flow to a physiological vasodilated perfusion density of 3.5 milliliters per minute per gram of tissue under a 100 millimeter mercury inlet pressure. The computed wall shear stress remained approximately uniform across vessel calibers, with a median of 11 dynes per square centimeter, squarely within the physiological range that real coronary vessels maintain. Segment flows followed the expected power-law relationship with diameter. Generating a complete network of roughly 40,000 vessel segments took about twenty hours on a single processor with a modest 50 megabytes of memory, faster than comparable image-based methods that report multi-day generation times.

The implications extend well beyond an elegant piece of computational engineering. Subject-specific coronary trees of this fidelity could serve as substrates for simulating myocardial perfusion, studying ischemia mechanisms, computing fractional flow reserve, and testing therapies for coronary artery disease in settings where microcirculatory measurements are impossible to obtain in living patients. The team acknowledges limitations: the current pipeline relies on manual segmentation, terminal flows are prescribed uniformly rather than drawn from perfusion imaging, and validation rests on porcine rather than human morphometry. They are already developing a deep-learning pipeline to automate preprocessing directly from human CT angiography volumes, and the growth machinery itself is species-agnostic, ready to be re-parameterized with human reference data. The source code has been released openly on GitHub, inviting the broader cardiovascular modeling community to build on a framework that finally connects what scanners can see with what physiologists need to model.

Subject of Research: CT-driven constrained constructive optimization for generating subject-specific coronary arterial tree networks

Article Title: Hierarchy Aware CT-Driven Constrained Constructive Optimization: A Framework for Coronary Network Generation

Article References: Vajire, S. L., Choy, J. S., Kassab, G. S., & Lee, L.-C. (2026). Hierarchy Aware CT-Driven Constrained Constructive Optimization: A Framework for Coronary Network Generation. Annals of Biomedical Engineering. https://doi.org/10.1007/s10439-026-04383-4

Image Credits: AI Generated

DOI: 10.1007/s10439-026-04383-4

Keywords: coronary arterial tree, constrained constructive optimization, computed tomography, cardiovascular modeling, myocardial perfusion, Strahler ordering, coronary morphometry, hemodynamics, left ventricle, microvasculature, biomedical engineering, synthetic vascular networks

The team began with a strikingly simple question: if you look at the complete inventory of proteins in a failing left ventricle, do hearts that failed for different reasons actually look different from one another? To answer it, they used high-resolution mass spectrometry to quantify 3,788 proteins in cardiac tissue samples collected from patients undergoing advanced care, alongside non-failing control hearts. The patients spanned ischemic cardiomyopathy, dilated and hypertrophic cardiomyopathy, arrhythmogenic cardiomyopathy, myocarditis, adult congenital heart disease and non-ischemic dilated cardiomyopathy, among other diagnoses. Statistical models adjusted for age, sex and batch effects compared protein abundance in each etiology group against controls.

The first major finding was one of convergence. When patients were grouped by clinical diagnosis, the vast majority of significantly altered proteins were shared across etiologies rather than unique to any single one. Upset plots and enrichment analyses showed that common changes dwarfed diagnosis-specific ones, and functional enrichment mapped all the heart failure groups onto a shared landscape: metabolic reprogramming, altered contractile machinery, extracellular matrix remodeling and inflammatory signaling appeared everywhere. In other words, by the time the heart reaches end-stage failure, the terminal proteomic state looks remarkably similar regardless of what started the decline. This convergence echoes earlier single-nucleus RNA sequencing work, which likewise found common transcriptional signatures across cardiomyopathies, and it helps explain why a one-size-fits-all therapeutic approach has historically achieved only incremental gains.

But convergence at the disease endpoint was only half the story. When the researchers abandoned clinical labels altogether and let an unbiased computational method, non-negative matrix factorization, sort patients purely by proteomic similarity, the cohort split cleanly into two groups. Group 1 and Group 2, comprising 59 and 63 patients with reduced ejection fraction respectively, cut across every clinical etiology: a patient with ischemic disease and a patient with myocarditis could sit in the same molecular camp, while two patients with the same diagnosis could fall into opposing ones. The clustering was robust, reproducible in principal component analyses, and independent of demographic confounders.

What distinguished the two groups was not the cause of disease but the character of the heart’s remodeling response. Group 2 hearts were enriched for proteins derived from activated fibroblasts, smooth muscle cells and pro-inflammatory myeloid cells, signatures consistent with aggressive scar formation and immune infiltration. Overlaying the protein signatures onto a published atlas of 15 cardiac cell types from single-cell transcriptomics revealed that Group 2 mirrored the cellular states observed in dilated cardiomyopathy, including expansions of disease-associated cardiomyocyte populations, activated fibroblast states FB5 through FB9, and pro-inflammatory macrophages, monocytes and dendritic cells. Group 1, by contrast, retained a profile closer to non-failing tissue, relatively enriched for cardiomyocyte contractile and metabolic proteins. The subgrouping was independently validated in bulk RNA sequencing data from 198 heart failure samples in a public cohort, where the same protein signature reproduced the same molecular split at the transcript level.

The researchers then descended one level deeper into biology by profiling the phosphoproteome, the layer of phosphate tags that flip proteins on and off and transmit signals through kinases. From the same tissues they quantified 3,014 phosphosites, and the phosphorylation patterns reproduced the proteomic stratification, confirming that the two subgroups differ not only in which proteins they contain but in which signaling circuits are actually running. Critically, phosphoproteomics is where drug discovery lives: kinases, phosphatases and their downstream effectors are among the most pharmacologically tractable targets in medicine.

By integrating protein abundance, phosphosite regulation and prior knowledge networks of kinases, transcription factors and upstream regulators, the team identified selectively activated, druggable signaling networks confined to one molecular subgroup. Among the circuits implicated were RhoA and ROCK2 signaling, components of the actin cytoskeleton such as the Arp2/3 complex, and mitogen-activated protein kinase pathways including ERK1/2 and p38, alongside regulatory nodes such as glycogen synthase kinase 3 and RAF1. The researchers cross-referenced these targets against the Drug Repurposing Hub, ChEMBL, Open Targets and Mendelian randomization evidence for causal heart failure associations, filtering for known cardiac toxicity, and assembled a shortlist of candidate therapeutic entry points that would apply only to the molecularly defined patients whose networks show that activation. This is precision cardiology at the level of the cell’s control systems rather than its genome.

Perhaps the most clinically consequential result came from the UK Biobank. The remodeling-associated protein signature, originally discovered in end-stage explanted hearts, was tested against plasma proteomic data from an entirely independent cohort of heart failure patients who are, on average, at much earlier stages of disease and treated in the community rather than the transplant center. The signature stratified these patients into subgroups and predicted survival trajectories, with accelerated failure time modeling showing that the molecular group assignments carried prognostic information. This extends the relevance of the tissue-based findings far beyond the operating theater: a blood test grounded in the same biology may eventually help identify which ambulatory patients carry a fibrotic, inflammatory molecular phenotype and which do not.

The implications for drug development are considerable. Heart failure trials have long been plagued by modest average effect sizes, and a plausible explanation is that molecularly heterogeneous populations dilute real benefits among patients whose disease is not driven by the targeted pathway. If a candidate anti-fibrotic or kinase inhibitor benefits only Group 2 biology, enrolling an unstratified population would bury the signal. Stratifying trials by these protein-defined subgroups could sharpen effect estimates, reduce required sample sizes and rescue otherwise promising mechanisms. The prognostic signal in plasma also raises the prospect of patient stratification with routine blood draws rather than myocardial biopsy, something no clinician would contemplate for diagnosis in most heart failure settings.

The study also leaves open questions that will shape the next phase of work. The cohorts are dominated by end-stage disease and reduced ejection fraction, so the behavior of the subgrouping in heart failure with preserved ejection fraction remains untested. The two groups describe biology at a moment in time, and longitudinal studies will need to establish whether patients transition between molecular states as disease evolves, or whether subgroup membership is fixed from the outset. And while the plasma findings demonstrate prognostic value, translating them into a clinically deployable test will require targeted assays and prospective validation. Still, the message of the work is unambiguous: the failing heart’s molecular interior tells a story that diagnosis codes cannot, and listening to that story, in both tissue and blood, may finally make it possible to match heart failure therapies to the biology of the individual patient rather than the label on the chart.

Subject of Research: Molecular subgrouping of human heart failure by proteomic and phosphoproteomic profiling of cardiac tissue

Article Title: Cardiac proteomic and phosphoproteomic profiling defines clinically relevant molecular subgroups in human heart failure

Article References: Hamed, O., Reitz, C. J., Kuzmanov, U., Gramolini, S., Hu, M., Halpern, J., Billia, F., & Gramolini, A. O. (2026). Cardiac proteomic and phosphoproteomic profiling defines clinically relevant molecular subgroups in human heart failure. Nature Cardiovascular Research. https://doi.org/10.1038/s44161-026-00880-w

Image Credits: AI Generated

DOI: 10.1038/s44161-026-00880-w

Keywords: heart failure, proteomics, phosphoproteomics, cardiac remodeling, precision medicine, biomarkers, UK Biobank, fibrosis, kinase signaling, cardiomyopathy, left ventricle, mass spectrometry