Right-Ventricular Remodeling Mechanics: From Fiber Architecture and Constitutive Modeling to Imaging Biomarkers and Clinical Endpoints

1. Introduction

The right ventricle is not a smaller left ventricle. It is a distinct pump evolved to deliver high flow against low impedance with minimal energy loss, and it remodels under overload in ways that are strongly shaped by geometry, wall thickness, fiber architecture, and boundary conditions. Clinically, RV function is a major driver of symptoms and survival in pulmonary arterial hypertension, chronic thromboembolic disease, and mixed-etiology pulmonary hypertension; it also predicts outcomes in congenital heart disease and in left-heart disease complicated by elevated pulmonary pressures. Despite this centrality, RV mechanics has historically been reviewed in fragments, separated into physiological coupling, imaging strain indices, tissue remodeling biology, or numerical modeling. The consequence is that mechanical quantities are often used as if they were interchangeable: a longitudinal strain value is interpreted as contractility, a change in TAPSE is interpreted as reverse remodeling, and a wall thickness measurement is interpreted as load compensation, even when the underlying determinants differ. This review aims to unify these fragments into a coherent mechanics perspective that connects measurable quantities across scales and modalities [1,2,3,4].

RV remodeling is most commonly discussed in the context of pressure overload and increased pulmonary vascular resistance, but mechanical remodeling is equally driven by changes in preload, pericardial constraint, interventricular interaction, and myocardial substrate. Post-MI RV remodeling spans several mechanisms: (i) primary RV infarction, usually associated with inferior MI; (ii) ischemia from right coronary disease with impaired RV perfusion; (iii) secondary RV afterload elevation due to LV failure and pulmonary venous hypertension; and (iv) chronic geometric interaction through the shared septum and pericardium. These processes produce overlapping phenotypes: chamber dilatation, wall thickening, increased diastolic stiffness, reduced systolic reserve, altered timing of contraction, and progressive tricuspid regurgitation. The mechanics question is not only which phenotype is present, but which load pathway produced it, and which measurable metrics can distinguish adaptation from impending failure [5,6,7,8,9,10,11,12,13].

Several factors explain why RV remodeling mechanics is under-reviewed compared with LV remodeling. The RV free wall is thin, highly trabeculated, and difficult to isolate for testing; imaging resolution and segmentation errors are proportionally larger; pressure-volume analysis is less routinely performed; and constitutive modeling is complicated by large deformation, heterogeneous fiber orientation, and strong boundary interaction with the septum. In addition, clinical practice historically relied on global and surrogate metrics such as TAPSE, fractional area change, and qualitative assessment, which have limitations under altered loading. Recent advances in 3D echocardiography, speckle tracking strain, feature-tracking cardiac magnetic resonance (CMR), and 4D flow CMR now enable richer kinematic descriptions, and the computational community has developed RV-specific finite element (FE) and inverse approaches. Yet, the translation between these imaging descriptors and classical mechanics parameters, and their linkage to endpoints, remains inconsistent [14,15,16,17,18,19,20,21,22,23].

Figure 1 summarises the multiscale pathway by which pressure overload and post-MI contexts can produce either adaptive RV remodelling or progressive maladaptation. At the system level, pulmonary vascular afterload (resistance, compliance, impedance, and pulsatility) governs the loading problem that determines RV–arterial coupling; this coupling, in turn, interacts with RV geometry (radius, wall thickness, curvature) to set a heterogeneous wall-stress landscape rather than a uniform “Laplace” state. The resulting stress gradients, shaped further by septal mechanics and pericardial constraint, provide the mechanobiological stimulus for microstructural remodelling, myocyte hypertrophy and changes in extracellular matrix quantity/quality (collagen accumulation, cross-linking) alongside altered fibre dispersion, that shifts passive stiffness and modifies active force transmission. Over time, these stress-driven tissue changes can create reinforcing feedback loops in which elevated metabolic demand and fibrosis reduce contractile reserve, promote functional tricuspid regurgitation, and accelerate RV–arterial uncoupling and dilatation. This framing also clarifies why standard clinical metrics are indispensable yet incomplete: they primarily report kinematics and coupled system behaviour, so mechanistic interpretation of “stiffness” or “contractility” typically requires a model-based bridge between measured motion/hemodynamics and underlying material and microstructural state

2. Scope, Terminology, and Literature Sampling

In this review, right-ventricular (RV) remodelling denotes the time-dependent evolution of RV structure and function arising from altered loading conditions and myocardial substrate, encompassing hypertrophy and/or dilation, fibrotic remodelling, changes in sarcomere and myofibre architecture, and shifts in electrical and electromechanical activation. “Mechanics” is used in a broad and integrative sense, including kinematics, forces, stresses, strains, constitutive material behaviour, and their coupling to growth-and-remodelling processes that link measurable deformation to underlying biological [24,25,26,27,28,29].

2.1. Why a Mechanics Unification Is Needed

A central challenge in RV remodeling research is that most clinical measurements are not direct mechanical properties but are outputs of an interacting system: myocardium as an active and passive material; geometry and wall thickness; ventricular-arterial coupling; heart rate and rhythm; and pericardial and septal constraints. Inverse interpretations are therefore ill-posed unless the measurement context is specified. For example, a reduction in RV longitudinal strain can reflect decreased contractility, increased afterload, altered fiber orientation, reduced preload, or imaging tracking bias. Conversely, a preserved ejection fraction can coexist with increased wall stress if afterload is underestimated, or with severe dysfunction if chamber size is small. A unified framework should make these dependencies explicit, treat each metric as a function of load, geometry, and material state, and encourage reproducible reporting [30,31,32,33,34,35,36,37,38,39,40].

2.2. Literature Sampling and Evidence Mapping

Right-ventricular (RV) remodelling is investigated across partially disconnected literatures spanning physiology, biomechanics, cardiovascular imaging, computational modelling, and clinical outcomes. To maintain coherence while reflecting this interdisciplinarity, the reference set underpinning this review was assembled using a purposive, evidence-mapping approach designed to ensure representation across these communities. Priority was given to studies that report at least one explicit mechanical observable or constraint relevant to RV remodelling—namely RV deformation (global or regional), loading/hemodynamics (including pressure–volume and coupling metrics), microstructural measurements, ex vivo or in situ tissue mechanical testing, model-based parameter estimation (forward or inverse), or associations between RV mechanical markers and clinical outcomes. Citations are thematically grouped to make the evidentiary basis traceable and to support readers who wish to construct focused bibliographies for specific mechanistic or translational sub-questions. The grouped evidence statements below should be interpreted as a transparent map of representative work rather than a formal systematic review [41,42,43,44,45,46,47].

Within this framework, the echocardiography-focused evidence slice was sampled to preserve breadth across deformation imaging and RV shape/size markers, particularly free-wall longitudinal strain, three-dimensional (3D) echo-derived volumes, and emerging transverse or area-strain indices, while remaining anchored in studies that explicitly report RV mechanics, geometry, deformation, and/or loading. Representative studies in this thematic slice include [5,6,7,8,9,10,11,13,14,15,48]. The cardiovascular magnetic resonance (CMR) evidence slice was sampled to capture CMR-derived RV geometry and strain alongside tissue-characterisation measures that act as proxies for myocardial substrate, including feature tracking, late gadolinium enhancement, and T1/ECV mapping. Selection remained centred on studies that provide explicit RV mechanics, geometry, deformation, and/or hemodynamic context. Representative studies in this thematic slice include [24,25,26,27,28,29,30,31,32,33,34,36,37,38,39,40,49,50,51].

The hemodynamics and pressure–volume evidence slice was sampled to preserve breadth across RV–arterial coupling, load sensitivity, and approaches that seek to separate contractile reserve from afterload, again prioritising studies with explicit mechanical or loading readouts. Representative studies in this thematic slice include [41,42,43,44,45,46,47,52]. The computational modelling evidence slice was sampled to represent patient-specific reconstructions, inverse parameter estimation, and finite-element (FE) pipelines used to infer RV stress/strain or regional material/contractile parameters, while remaining anchored in work that links modelling outputs to measured geometry, deformation, and/or hemodynamics. Representative studies in this thematic slice include [1,12,14,18,53,54,55,56,57,58,59,60,61,62,63,64,65,66]

The experimental and translational evidence slice was sampled to capture models of pressure overload, pulmonary vascular disease, and RV failure biology that include explicit mechanical readouts (e.g., deformation, loading, tissue properties, or mechanically interpretable phenotypes), providing mechanistic grounding for clinical observations. Representative studies in this thematic slice include [2,21,25,36,67,68,69,70,71,72,73,74,75,76,77,78,79]. Because RV remodelling is strongly modulated by ventricular interdependence, the septal mechanics evidence slice was sampled to reflect studies on septal deformation, pericardial constraint, and biventricular coupling as amplifiers or buffers of RV remodelling trajectories, with emphasis on work reporting explicit mechanics, deformation, and loading. Representative studies in this thematic slice include [35,61,62,71,80,81,82,83,84,85,86,87,88,89,90,91,92,93,94]

Congenital heart disease and repaired-lesion cohorts constitute long-horizon “natural experiments” in RV adaptation and maladaptation; accordingly, this evidence slice was sampled to include studies where RV geometry, deformation, and loading are tracked over extended time scales and linked to clinical trajectories. Representative studies in this thematic slice include [95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111]. To support clinical translation, the interventional and pharmacologic evidence slice was sampled to include studies where RV mechanics-related metrics are used as endpoints, mediators, or treatment-response markers, emphasising explicit deformation/hemodynamic readouts and interpretable changes in loading or coupling. Representative studies in this thematic slice include [16,112,113,114,115,116,117,118,119,120,121,122,123].

Model structure and parameter identifiability depend on microstructure; therefore, the microstructural evidence slice was sampled to represent studies of myofibre and collagen architecture, anisotropy, and regional heterogeneity that motivate constitutive assumptions and region definitions in RV modelling. Representative studies in this thematic slice include [65,100,124,125,126,127,128,129,130,131,132,133].

Finally, because RV mechanics measures are sensitive to acquisition, post-processing, and modelling choices, the methodological evidence slice was sampled to include work on reproducibility, cross-vendor comparability, and statistical handling of heterogeneity and uncertainty, with emphasis on implications for interpretation and synthesis across studies. Representative studies in this thematic slice include [134,135,136,137,138,139,140,141,142,143,144,145].

To make cross-study comparisons mechanistically interpretable, the key determinants of RV remodeling and the corresponding measurable metrics across length scales are summarized in Table 1. This multiscale mapping is motivated by the fact that most clinical observables (e.g., strain, ejection fraction, or coupling surrogates) are not direct mechanical properties, but emergent outputs of an interacting system that couples load, geometry, myocardial material state, rhythm, and septal/pericardial constraints; consequently, inverse interpretation is ill-posed unless the measurement context is made explicit. At the organ level, RV–arterial coupling metrics integrate contractile performance with afterload; at the chamber level, geometric adaptation and wall thickness influence stress proxies but are sensitive to segmentation uncertainty in a thin, trabeculated wall. Regional deformation metrics partition free-wall and septal contributions and can reveal dyssynchrony, yet remain sensitive to loading, tethering, and tracking algorithms. Tissue-scale stiffness and fibrosis are informed by ex-vivo testing, substrate imaging proxies, or model-inferred parameters, each carrying distinct identifiability and model-dependence risks. Finally, microstructural descriptors (fiber dispersion and collagen architecture) motivate anisotropic constitutive structure but are limited by in-vivo accessibility and sampling/region-definition bias.

3. RV Anatomy, Fiber Architecture, and the Mechanical Consequences of Geometry

The RV is a crescentic chamber wrapped around the LV, with a thin free wall, complex trabeculation, and a distinct inflow-outflow organization. This geometry is not an aesthetic detail; it sets the relationship between cavity pressure and wall stress and determines which regions carry load under pressure overload. Under Laplace-like reasoning, a thin wall implies high stress for a given pressure and radius, but the RV is not a thin-walled cylinder. Its curvature varies strongly from inflow to outflow, and the septal boundary shifts with LV pressure and pericardial constraint. Consequently, regional stress and strain can vary markedly even under uniform cavity pressure, and global metrics can miss localized failure. In pressure overload, the RV may increase wall thickness, reduce radius, and change curvature to restore stress; however, these geometric adaptations often lag behind afterload changes and may not prevent progressive dilation once coupling deteriorates [109,146,147,148,149,150,151,152,153].

Myofiber architecture in the RV differs from the LV in both orientation and transmural organization. The LV is often idealized as having a smooth transmural helix angle gradient, while the RV free wall exhibits more variable orientation with strong regional dependence and influence from trabecular bundles. Collagen architecture, including perimysial and endomysial networks, contributes to anisotropic stiffness and the recruitment of fibers with stretch. Remodeling alters both myocyte and collagen organization, typically increasing collagen content and cross-linking, thickening the wall, and changing fiber dispersion. These microstructural changes can increase passive stiffness and shift the operating point on the stress-strain curve, impairing diastolic filling and augmenting afterload sensitivity. Importantly, the same gross wall thickness can arise from different microstructural states, such as myocyte hypertrophy with limited fibrosis versus fibrosis-dominated stiffening, which have different reversibility and prognostic meaning [14,29,53,54,56,57,58,63,64,65,77].

Septal mechanics and pericardial constraint are often treated as boundary conditions in modeling, but they are mechanistic drivers of RV function. The septum is shared myocardium, and its curvature and fiber activation contribute to RV ejection, especially under increased afterload. In acute pressure overload, the septum can flatten or shift toward the LV, altering LV filling and generating a feedback loop that worsens overall cardiac output. The pericardium constrains diastolic volume and couples ventricles through external pressure, which means that RV dilation can impair LV filling even when LV contractility is preserved. These interactions are not fully captured by single-chamber metrics and are one reason why RV remodeling metrics require interpretation in a biventricular context [33,59,60,61,66,67,69,129,154,155,156].

Figure 2 motivates a regional (rather than global) interpretation of RV mechanics by making explicit how segmentation choices and septal interaction shape both measured deformation and inferred stresses under pressure overload. Because the RV is geometrically complex and mechanically anisotropic, partitioning into inflow–apex–outflow regions and distinguishing free wall from septum is not merely descriptive; it defines the spatial units over which fiber orientation, dispersion, and constitutive parameters are assumed constant and therefore determines where heterogeneity can be detected. The figure further highlights ventricular interdependence: as RV pressure rises, septal flattening changes septal curvature and constraint, reduces LV filling, and alters load sharing, such that the apparent location of peak RV stress may shift even when pulmonary afterload is unchanged. Finally, the tricuspid regurgitation subpanel shows why deformation metrics require loading context—regurgitation can change effective afterload and stroke work, producing strain patterns that may not map uniquely to intrinsic contractility or stiffness. Taken together, these effects explain why rigorous reporting of region definition, reference configuration (including the assumed stress-free or diastatic baseline), and boundary conditions (septal coupling, pericardial constraint, and valve competence) is essential when comparing studies, calibrating models, or constructing normative and pathological envelopes for regional RV mechanics.

4. Mechanobiology of RV Remodeling Under Pressure Overload and Post-MI Contexts

RV remodeling is a mechanobiological process in which cells and extracellular matrix (ECM) respond to changes in strain, stress, and metabolic demand. Pressure overload increases systolic wall stress, augments myocyte work, and can induce capillary rarefaction, ischemia, and metabolic shifts. Mechanotransduction pathways link these stimuli to hypertrophy, fibrosis, inflammation, and changes in titin phosphorylation and ECM cross-linking. The result is a material state change: passive stiffness increases, active force generation may initially rise via hypertrophy and altered calcium handling, and then declines as fibrosis, ischemia, and maladaptive signaling dominate. The temporal sequence matters: the same afterload can produce different remodeling trajectories depending on the speed of afterload increase, the presence of comorbidities, and baseline myocardial substrate [2,68,71,74,76,78,79,82,157,158,159].

In post-MI settings, RV remodeling may be driven by infarction in the RV free wall, by chronic elevation in pulmonary pressures from LV dysfunction, and by altered septal mechanics due to LV remodeling. Even when RV infarction is absent, the RV can experience increased afterload through pulmonary venous hypertension and reactive pulmonary vasoconstriction. This coupled remodeling can lead to a phenotype resembling pressure-overload RV failure but with additional contributions from ventricular interdependence and neurohormonal activation. Mechanically, these contexts emphasize that RV remodeling cannot be categorized solely by the presence of pulmonary arterial disease; the same RV phenotype can be produced by different pathways, and the mechanical signature should be used to infer pathway when possible [62,70,72,75,80,81,88,90,92,160,161].

An important translation point is that microstructural remodeling changes not only stiffness but also the mapping between measured strains and underlying stresses. When collagen recruitment increases, small changes in strain correspond to larger stress changes, which may explain why some imaging strain metrics show early prognostic signals even when conventional metrics remain preserved. Conversely, fibrosis can reduce strain magnitudes while leaving stresses high, potentially masking ongoing mechanical injury if strain is interpreted alone. These nuances motivate combined reporting of geometry, pressure, strain, and, when possible, coupling indices [71,73,83,84,85,86,87,89,93,94,162,163].

5. Mechanical Characterization: From Pressure-Volume Loops to Ex-Vivo Tissue Testing

Mechanical characterization of the RV can be approached at organ scale via pressure-volume (PV) analysis and at tissue scale via mechanical testing. PV loops provide a direct framework for separating load from contractility through end-systolic elastance and for quantifying afterload via effective arterial elastance. Their ratio, often used as an index of ventricular-arterial coupling, captures whether the RV can generate sufficient pressure and stroke volume for a given afterload. Importantly, coupling is a system property, not a myocardial property, and can deteriorate because of rising afterload, falling contractility, or both. PV analysis also yields diastolic stiffness metrics, such as end-diastolic elastance or the exponential coefficient of the diastolic PV relationship, which may increase with fibrosis and titin changes. Despite its conceptual clarity, PV loop acquisition in clinical RV practice is limited, and studies vary in methodology and assumptions [95,96,97,98,101,102,103,104,164,165,166,167].

Tissue-level testing of RV myocardium, including uniaxial tension, biaxial extension, shear, and indentation, is less common than LV testing and is complicated by specimen size, fiber dispersion, and trabecular content. Nevertheless, these tests are essential because imaging strain alone cannot identify material parameters without assumptions. RV tissue testing must contend with viscoelasticity, anisotropy, and active contraction; it is therefore sensitive to preconditioning protocols, strain rate, temperature, and post-mortem delay. When RV tissue is tested, results can vary depending on whether samples are taken from free wall versus outflow tract, whether fibers are aligned, and whether ECM remodeling is present. A key message for the field is that RV mechanical property datasets are not inconsistent because the myocardium is unknowable, but because experimental metadata and region definitions are often insufficient for cross-study equivalence [105,106,107,108,110,111,112,121,168,169,170,171].

Bridging organ-scale PV metrics to tissue-scale properties requires modeling. A PV loop does not directly reveal constitutive stiffness because geometry and boundary conditions influence the PV relationship. Similarly, a strain map does not directly reveal stress without pressure and wall thickness. Therefore, the most informative characterization studies combine imaging-derived geometry, pressure recordings, and deformation measures with FE-based inference of stress-strain behavior. Such studies can estimate passive stiffness parameters, active tension parameters, and, crucially, uncertainty bounds that quantify identifiability. The RV is an especially strong candidate for such integrative inference because wall thickness changes and septal interaction make purely geometric interpretations unreliable [113,116,117,118,120,122,123,151,172,173,174].

6. Constitutive and Electromechanical Models Tailored to the RV

Constitutive modeling of myocardium aims to encode passive anisotropic stiffness, active stress generation, and, in some cases, viscoelastic effects. For RV applications, transversely isotropic or orthotropic hyperelastic models are common, often using exponential strain-energy forms that separate fiber, sheet, and matrix contributions. Active contraction is frequently modeled as an additive stress along fibers, with activation timing and length dependence. The RV poses particular modeling challenges: the thin free wall experiences large curvature changes, the outflow tract has distinct structure, trabeculations complicate mesh generation, and regional fiber orientation can deviate from LV-based rules. Consequently, RV FE models often rely on rule-based fiber assignment or limited diffusion tensor data, and parameter estimation can be underdetermined unless multiple data types are combined [100,114,115,124,125,131,133,175,176,177,178,179].

Parameter identifiability is not a technical footnote; it is central to whether RV modeling can become clinically credible. Many combinations of passive stiffness parameters and active tension parameters can reproduce a given ejection fraction if afterload and preload are adjusted. Similarly, multiple fiber orientations can reproduce a surface strain field if the wall thickness and boundary conditions are uncertain. Modern RV modeling therefore increasingly uses inverse frameworks that estimate parameters by minimizing mismatch between measured and simulated strains, volumes, and pressures, often with regularization and Bayesian uncertainty quantification. A mechanics-aware review must emphasize that reporting a single parameter set without uncertainty can mislead readers into believing that a model is uniquely identified [29,126,127,128,129,130,132,180,181,182].

Growth and remodeling (G&R) modeling extends constitutive modeling by introducing time-dependent evolution laws for mass deposition, fiber reorientation, and ECM turnover in response to mechanical stimuli. In RV pressure overload, plausible G&R drivers include elevated fiber stress, altered strain energy density, and hypoxia-related signals. A key conceptual distinction is between homeostatic set points and pathological signaling: an RV may hypertrophy to restore stress toward a homeostatic target, but persistent afterload elevation, ischemia, or inflammation can shift the target or impair the remodeling capacity. A practical modeling goal is to predict when adaptation will transition to failure, which likely requires coupling mechanics to perfusion, metabolism, and fibrosis kinetics [134,135,136,137,138,139,140,141,142,143,144,145].

Electromechanical aspects are particularly relevant to the RV because conduction delays, dyssynchrony, and altered activation patterns can have disproportionate effects on a thin-walled chamber. In pressure overload, prolonged RV contraction and interventricular dyssynchrony can reduce effective stroke volume and increase myocardial work. Modeling frameworks that integrate activation timing with mechanics can, in principle, separate pure afterload effects from electromechanical inefficiency. Such models also provide a way to interpret pacing or resynchronization interventions and to quantify the mechanical cost of conduction abnormalities [48,99,183,184,185,186,187,188].

Because most clinical RV measurements provide kinematics and coupled system behaviour rather than intrinsic material properties, constitutive and electromechanical models are required to translate observed deformation and hemodynamics into interpretable descriptors such as passive stiffness, anisotropy, and contractile function.

Paper 90—Right-Ventricular Re…

Table 2 provides a structured overview of common model families and the practical implications of choosing each for RV applications. In brief, transversely isotropic hyperelastic laws offer a widely used baseline for anisotropic nonlinear stiffness, whereas orthotropic (fiber–sheet) formulations can represent richer directional behaviour but typically demand more informative deformation data and/or ex vivo calibration to avoid over-parameterization. Active stress models—most often implemented as an additive fibre-aligned stress with prescribed or estimated activation timing—enable separation of passive and active contributions, but introduce additional non-uniqueness when loading is uncertain. These identifiability challenges are amplified in the RV because thin-wall curvature changes, outflow-tract structural differences, trabeculations, and regionally variable fibre orientations increase sensitivity to geometric reconstruction and boundary-condition specification. Consequently, patient-specific inference increasingly relies on inverse frameworks that fit strains, volumes, and pressures with regularization and Bayesian/ensemble uncertainty quantification, since reporting a single “best-fit” parameter set can imply spurious uniqueness. Finally, G&R and electromechanical extensions formalize time-dependent adaptation (hypertrophy, ECM turnover, fibre reorientation) and the mechanical consequences of dyssynchrony, but generally require longitudinal or multi-modal constraints for credible calibration in pressure-overload settings.

7. Imaging-Derived RV Mechanics: What Is Measured, What Is Inferred, and What Is Comparable

The RV is increasingly assessed using deformation imaging, but a mechanics-aware interpretation requires careful distinction between measured kinematics and inferred mechanics. Echocardiography provides global surrogates such as TAPSE, S’ velocity, fractional area change, and estimates of pulmonary pressure; newer speckle-tracking approaches provide longitudinal strain of the free wall and, in some protocols, strain rate and transverse deformation. 3D echocardiography improves volume and ejection fraction estimates but remains sensitive to image quality and segmentation. CMR provides high-quality geometry and can measure strain via tagging, DENSE, SENC, or feature tracking, and can assess substrate via late gadolinium enhancement and T1 mapping. 4D flow CMR provides pulmonary artery flow patterns and may refine afterload estimation beyond pressure alone. Each modality has distinct error modes and dependencies, so cross-study comparability requires explicit reporting of acquisition, segmentation, tracking algorithms, and load context [5,6,7,8,9,10,11,13,14,15,48].

From a mechanics perspective, RV longitudinal strain is a kinematic measure of deformation along the long axis. Its magnitude depends on the projection of the underlying fiber shortening onto the imaging coordinate, on regional tethering, and on whether strain is computed in a Lagrangian or Eulerian frame. In the RV, longitudinal shortening of the free wall dominates in health, but under pressure overload the contribution of radial thickening and septal contraction may change, and the pattern of shortening can become heterogeneous. Therefore, changes in longitudinal strain should be interpreted together with geometry, RV outflow dynamics, and septal strain, rather than treated as a single contractility marker. Feature-tracking CMR strain and echo strain can correlate but are not interchangeable, and different vendors and algorithms can produce systematic biases [16,17,18,19,20,21,22,23,24,25,26,49,65,78,133].

Imaging-derived coupling metrics are an active area of translation. RV-arterial coupling can be approximated using PV analysis, but when PV loops are unavailable, surrogate indices such as TAPSE-to-pulmonary artery systolic pressure, or strain-to-afterload ratios, have been proposed. These surrogates embed assumptions about linearity and load estimation; they can be useful for risk stratification but should not be interpreted as direct elastance ratios. CMR-derived stroke volume combined with invasive or estimated pressures can provide improved coupling approximations, and 4D flow may refine pulmonary vascular impedance estimates. A consistent reporting standard should state the exact formulas and units used, the pressure estimation method, and whether the measurements were taken at rest or during stress [27,28,29,30,31,32,33,34,36,37,50,189].

Elastography and MR elastography offer the possibility of measuring shear-wave speed and viscoelastic moduli in vivo, but RV applications remain challenging because of wall thickness, motion, and adjacency to lung tissue. When used, elastography metrics must be interpreted as effective properties of a layered, moving, anisotropic structure, not as direct equivalents of small-strain shear modulus from ex-vivo tests. A realistic near-term role for RV elastography may be in tracking relative changes over time within individuals, rather than establishing absolute reference ranges across centers. Integrating elastography with FE models, where wave propagation is simulated in subject-specific geometry, may help convert measured wave properties into constitutive parameters, but this remains a research frontier [38,39,41,42,43,44,45,46,47,51].

To prevent over-interpretation of routinely reported RV “mechanics” readouts, Table 3 summarizes a set of commonly used imaging-derived metrics and separates (i) the quantity that is directly measured from (ii) the most defensible mechanical interpretation that can be supported without additional constraints. In particular, free-wall longitudinal strain should be treated as a kinematic measure of long-axis deformation whose magnitude depends on loading, tethering and methodological choices, including whether strain is computed in different reference frames and which tracking algorithm and vendor pipeline are used; consequently, it is better interpreted as a composite marker of systolic shortening under load rather than a standalone contractility surrogate. Global indices such as 3D RV volumes and ejection fraction provide pump performance but remain strongly load- and geometry-dependent, while low-dimensional surrogates (TAPSE, S′) are angle- and rhythm-sensitive and are insufficient in isolation for mechanistic inference. Tissue characterisation (LGE/T1) provides substrate proxies that may inform spatial priors on stiffness heterogeneity but is indirect and sequence-dependent, and 4D flow metrics offer an avenue to refine afterload characterisation and boundary conditions beyond pressure alone. Framed this way, Table 3 also clarifies how imaging outputs enter patient-specific modelling: strain fields can serve as objective functions for inverse estimation of active parameters, volumes provide pressure–volume consistency constraints, and flow-derived impedance proxies can strengthen coupling estimates—provided that acquisition, segmentation, tracking/sequence choices, and load context are explicitly reported to enable reproducible comparison and uncertainty-aware interpretation.

8. Patient-Specific Modeling Pipelines: Geometry, Fibers, Inference, and Uncertainty

Patient-specific RV modeling typically proceeds from imaging-derived geometry to mesh generation, fiber assignment, boundary condition specification, and parameter estimation. Each step introduces uncertainty that can dominate the final stress estimate. Geometry extraction is particularly sensitive in the RV because endocardial borders are trabeculated and the free wall is thin; small segmentation differences can change wall thickness estimates and therefore stress. Fiber assignment is often rule-based due to limited diffusion tensor data; errors in fiber orientation propagate directly into predicted strain patterns and inferred active tension. Boundary conditions include pericardial contact, septal coupling, and pulmonary artery impedance; simplifying these can bias predictions. Therefore, personalization pipelines should report not only the final parameters but also the sensitivity of key outputs to plausible variations in geometry and boundary assumptions [8,52,109,113,146,147,148,149,150,151,152,190].

Inverse modeling uses observed kinematics and hemodynamics to infer material parameters. In RV studies, inverse methods can fit passive stiffness parameters using diastolic filling data and active parameters using systolic deformation, often constrained by pressure recordings. When only noninvasive pressure estimates are available, parameter uncertainty increases, and models can become underdetermined. Bayesian approaches and ensemble methods provide a principled way to represent this uncertainty and to avoid overconfident conclusions. A further challenge is that many imaging strain measures are surface-based and do not uniquely determine transmural strain, yet constitutive models are volumetric. Regularization strategies, including smoothness priors and physiologically plausible parameter bounds, are therefore essential and should be explicitly reported [14,18,29,53,54,56,57,58,63,64,77].

Model validation is frequently claimed but rarely performed at the level needed for clinical translation. For RV mechanics, validation can occur at several levels: reproducing measured volumes and strains; predicting hemodynamic responses to known afterload changes; predicting regional stress patterns that correlate with known remodeling patterns; and prospective prediction of outcomes or intervention responses. Validation is complicated by the lack of a gold-standard stress measurement in vivo. Therefore, multi-modality consistency checks, such as agreement between CMR and echo volumes, or between modeled pressures and invasive measurements in subsets, are practical validation steps. Ultimately, clinical credibility will require pre-specified modeling protocols, cross-center reproducibility, and blinded prediction studies [33,59,60,61,62,66,67,69,154,156,191].

Figure 3 outlines an imaging-to-mechanics pipeline that treats RV remodeling inference as a patient-specific inverse problem rather than a direct readout from clinical images. Cine CMR and/or 3D echocardiography provide kinematic data, such as geometry, volumes, and deformation fields, which must be translated into intrinsic mechanical descriptors through mesh construction, fibre assignment, and explicit boundary condition specification. Passive stiffness and active tension are then estimated by fitting model predictions to measured motion and strain while enforcing pressure–volume consistency, but the figure makes clear that identifiability depends critically on where assumptions are injected: segmentation choices alter wall thickness and curvature; fiber rules shape directional stress and strain; and pressure specification (measured, estimated, or surrogate) controls the stiffness–pressure and stiffness–tension trade-offs. For this reason, uncertainty quantification is not optional: ensembles over segmentation, pressure estimation, and fiber architecture are propagated to yield parameter and prediction distributions, enabling sensitivity-aware interpretation of “stiffness” versus “contractility.” Finally, the workflow is anchored by validation beyond fit quality, including cross-modality agreement of volumes/strain, prediction of hemodynamic response to a known afterload perturbation, and assessment of whether inferred mechanics can predict subsequent regional remodeling patterns.

9. From Mechanics to Endpoints: What Should Be Predicted and How to Interpret Associations

Clinical endpoints in RV disease include functional capacity (such as six-minute walk distance and peak oxygen consumption), biomarkers (including natriuretic peptides), hospitalization, need for advanced therapies, and mortality or transplant-free survival. Imaging and hemodynamic metrics are often evaluated for prognostic value, but mechanistic interpretation requires caution. A strain metric that predicts survival may do so because it is a proxy for afterload, for myocardial fibrosis, or for reduced contractile reserve; without coupling measures, the mechanism remains ambiguous. Mechanics-based modeling can add value by decomposing observed function into contributions from afterload, contractility, geometry, and stiffness, and by producing mechanistically interpretable intermediate outcomes such as regional wall stress, myocardial work, or energetic cost. These intermediate outcomes may better explain why certain patients decompensate despite similar global ejection fractions [35,68,71,74,76,78,79,82,157,158].

A useful translation target is the prediction of response to therapy. In pulmonary arterial hypertension, vasodilator therapies reduce afterload, and reverse remodeling is expected if the RV retains contractile reserve and the myocardial substrate is not irreversibly fibrotic. Mechanical modeling can, in principle, distinguish patients whose poor strain is primarily load-driven from those with intrinsic contractile failure, thereby predicting who will respond to afterload reduction. Similarly, in tricuspid regurgitation and congenital lesions, interventions change loading and geometry; mechanical metrics that capture stress normalization or improved coupling may provide early indicators of durable benefit. To support such uses, studies should report pre- and post-intervention load, geometry, and deformation, and should avoid interpreting deformation changes without concurrent afterload assessment [61,62,70,72,75,80,81,88,90,92,160,161].

Post-MI and heart failure contexts add an additional layer: LV therapies can indirectly affect RV load through changes in pulmonary venous pressure and pulmonary vascular remodeling. Therefore, RV mechanics metrics may track both direct RV changes and secondary changes in pulmonary circulation. This reinforces the need for integrated RV-pulmonary and biventricular frameworks, particularly when evaluating therapies in mixed etiologies. In future clinical trials, RV modeling could be used to stratify patients by mechanical phenotype, such as predominantly afterload-driven dysfunction versus stiffness-dominated diastolic limitation, enabling more targeted interventions [71,73,83,84,86,87,89,93,94,95,162,163].

10. Towards Reference Ranges and Reproducible Reporting for RV Remodeling Mechanics

Reference ranges in RV mechanics cannot be defined as single numbers independent of context. A meaningful reference must specify the state variables and measurement conditions: heart rate, blood pressure, loading state, modality and algorithm, and geometric definitions. For example, a reference range for RV free-wall longitudinal strain should specify whether it is derived from 2D or 3D echocardiography, whether the region includes the outflow tract, the tracking algorithm, and whether pulmonary pressure is estimated or measured. Similarly, a reference range for coupling should specify the formula and afterload estimate. Without such specificity, reference ranges become artifacts of methodology rather than biology [95,96,97,98,101,102,103,104,164,165,166,167].

Reproducible reporting should therefore treat RV mechanics studies as multi-component experiments. At minimum, studies should report geometry acquisition and segmentation approach; definition of RV regions; method for estimating afterload; deformation metric definitions; and, when models are used, the constitutive law, fiber assignment method, boundary conditions, optimization procedure, and uncertainty reporting. Cross-vendor comparability remains a known challenge for strain imaging and for some CMR feature-tracking implementations. Multi-center initiatives that use standardized phantoms are not directly applicable to the heart, but cross-algorithm benchmarking on shared datasets with expert segmentations is feasible and should be prioritized [91,105,106,107,108,110,111,112,121,168,169,170,171,192,193,194].

For computational models [91,192,193,194,195,196], reproducibility requires code and mesh transparency. Small changes in mesh density or smoothing can influence regional strain and stress, and rule-based fiber assignment can vary across implementations. Therefore, model publications should provide sufficient detail to reproduce the pipeline, ideally with open-source code and example data. When patient data cannot be shared, synthetic benchmark cases and parameter files can still be provided. Such practices are standard in some fields of computational science and are increasingly expected for clinical translation [91,113,116,117,118,120,122,123,172,174,195,197,198,199,200,201,202,203].

11. Research Agenda: What to Measure Next

Several measurement gaps currently block mechanistic progress. First, the field needs more RV-specific tissue property datasets with standardized region definitions and metadata sufficient for constitutive fitting and model comparison. Second, in-vivo studies should more routinely combine deformation with contemporaneous afterload measurement or estimation beyond simple pulmonary artery systolic pressure, ideally incorporating impedance or flow-based descriptors. Third, microstructural imaging of fiber and collagen architecture in RV disease, linked to mechanical testing, would enable better-informed constitutive models and more credible mechanobiology. Fourth, modeling studies should embrace uncertainty quantification and identifiability analysis, reporting not only best-fit parameters but credible intervals and sensitivity to boundary conditions [100,114,115,124,125,131,133,175,176,177,178,179].

From a translational perspective, a practical near-term goal is to establish device-agnostic, physiology-aware mechanical phenotypes rather than fixed reference ranges. For example, patients might be classified by whether deformation impairment is disproportionate to afterload (suggesting intrinsic contractile limitation), whether diastolic stiffness is elevated relative to hypertrophy (suggesting fibrosis-dominant remodeling), or whether septal interaction dominates RV output. Such phenotypes would guide therapy selection and trial stratification, and could be validated against outcomes. Achieving this will require shared datasets, agreed-upon segmentation and metric definitions, and model repositories that enable independent replication [29,126,127,128,129,130,132,180,181,182].

12. Conclusions

RV remodeling mechanics is now positioned for rapid integration across imaging, modeling, and clinical science, but only if the community treats deformation and hemodynamic metrics as context-dependent mechanical outputs rather than stand-alone biomarkers. A unified framework that links fiber architecture, constitutive behavior, and coupling to measurable imaging and clinical endpoints can reduce contradictory interpretations and enable uncertainty-aware patient-specific prediction. By combining transparent reporting with integrative modeling and multi-modality validation, RV mechanics can mature into a clinically credible discipline parallel to, and not trailing, LV remodeling science.