Accurate delineation of the prostate and surrounding pelvic structures is critical to successful treatment planning, accurate identification, and staging of prostate cancer. Segmentation of anatomically complex regions surrounding the prostate in CT imaging can be challenging due to low soft-tissue contrast and complex boundary delineations. In this work, we investigate three complementary paradigms of knowledge distillation-voxel-level, region-level, and a dynamically weighted combination of the two-to improve segmentation performance for the prostate and parailiac regions. The region-level approach imposes the semantic coherence of network predictions via the region-wise contrastive form of supervision, whereas the voxel-level distillation provides fine-tuned supervision in terms of Kullback-Leibler divergence on soft probabilistic outputs. We introduce a novel fusion approach that adds uncertainty-aware dynamic weighting, thus allowing the model to adjust the contribution of every distillation loss in an adaptive manner during training, taking advantage of the strengths of both approaches. The distillation methods are implemented within the dual-network architecture in terms of VNet (Milletari et al. in Proc. Int. Conf. 3D Vis. (3DV):565-571, 2016) and 3D-ResVNet (Wang et al. in Proc. IEEE/CVF Conf. Comput. Vis. Pattern Recognit. (CVPR)), thus allowing synergistic learning of different architectural biases. Experimental results on both an in-house collected and annotated CT dataset of prostate cancer patients-where parailiac regions and the prostate gland (including seminal vesicles) are manually segmented-and three public benchmark datasets demonstrate that each individual distillation method consistently improves segmentation accuracy over baseline models. These results indicate that the effectiveness of the proposed distillation strategies generalizes across different datasets and anatomical structures, highlighting their robustness and practical applicability. Complementary supervision at voxel and region levels can improve the delineation of complex pelvic structures in CT imaging of prostate cancer.
The distal-to-proximal pressure ratio (dpPR) has emerged as a superior indicator compared to the diameter stenosis rate (DSR) for assessing the functional severity of carotid artery stenosis (CAS). However, unlike DSR, dpPR cannot be directly determined by vascular imaging. In this study, we developed a hemodynamic modeling method to predict dpPR based on medical images available in clinical settings. A multiscale modeling method was employed to integrate a three-dimensional (3D) hemodynamic model of CAS into a lumped-parameter model of systemic hemodynamics, while incorporating patient-specific geometric information of large cerebral arteries derived from computed tomography angiography (CTA) images. The 3D modeling method was validated through in vitro fluid dynamics experiments, while the accuracy of the resulting multiscale model in predicting dpPR was evaluated by comparing model predictions with invasive pressure wire measurements. The model-predicted dpPR values for 27 carotid artery stenoses demonstrated strong agreement with invasive measurements, with a mean relative error of - 0.8% and a standard deviation of 2.5%. dpPR was only moderately correlated with DSR (r = - 0.55, p = 0.003). Further analysis revealed that the anatomical structure of the circle of Willis (CoW) is a major factor influencing the relationship between dpPR and DSR. Constructing a multiscale model based on CTA images provides a practical approach for assessing the hemodynamic impact of CAS. The significant influence of CoW's anatomical structure on the relationship between dpPR and DSR underscores the importance of considering systemic cerebral hemodynamics when evaluating the functional severity of CAS.
Tooth pattern and surrounding tissue can affect the complexity of third molar (3M) extraction surgery. This study aimed to develop a new, more precise 3M extraction difficulty assessment scoring system by applying image computational techniques and artificial intelligence (AI)-based technologies to panoramic radiography images. We used dental panoramic X-ray data of patients aged 16 to 86 years. The mandibular canal (MC), inner area of alveolar bone (IAAB), and 3M were detected and segmented using an AI-based deep learning model. We developed algorithms to evaluate the difficulty of 3M extraction and the risk of inferior alveolar nerve damage. The inclination of the 3M (1-4 points), impaction depth of the 3M (1-4 points), and proximity between the mandibular third molar (M3M) and MC (0-4) were classified and scored. The scores obtained from each algorithm were summed to classify the difficulty index as very easy (2-4), easy (5-6), slightly difficult (7-9), and very difficult (10-12). The average precisions of the maxillary 3M and M3M detection models were 0.93 and 0.97, respectively. Moreover, the average accuracies of the 3M inclination classification algorithm, 3M impaction depth calculation algorithm, and the proximity of M3M and MC algorithms were 0.8544, 0.9515, and 0.8991, respectively. The developed extraction difficulty scoring model can aid dentists in assessing the risk of 3M extraction and establish an appropriate surgical plan. Future studies should include more diverse patient data and improve the performance of the AI models to realize clinical implementation.
The goal of optimizing electrogram acquisition in electrophysiology imaging is to minimize the number of electrodes used, determine their optimal placement, and ensure accurate imaging. We quantitatively evaluated the impact of the electrode number and placement on the accuracy of human uterine peristalsis imaging (UPI) using adapted minimum nonzero eigenvalue pursuit (MNEP), adapted maximal projection on minimum eigenspace (MPME), and a distance-based baseline method. Specifically, we assessed the accuracy of the uterine surface electrogram imaged by UPI while maintaining the original 128-electrode UPI placement as a constraint. Subsequently, we expanded our analysis to the entire body surface of the subjects, removing the constraint of the initial UPI electrode placement to explore a generalized optimized electrode placement strategy. The MPME method demonstrated superior performance compared to other approaches under both constrained and unconstrained optimization. For UPI, the optimal electrode configuration should prioritize a dense concentration of electrodes on the lower abdomen, close to the uterus, where the most informative bioelectrical signals are captured. At the same time, it is important to maintain a distribution of electrodes along the edges of the upper abdominal, lateral sides, and posterior regions. This spatial distribution preserves the geometric contour of the torso and supports comprehensive, multi-angle observation of uterine electrical activity. By combining signal fidelity with spatial coverage, this balanced placement strategy enhances the UPI accuracy. The adapted MPME method guided a novel electrode placement strategy for electrophysiological imaging, achieving substantial improvements in imaging accuracy while reducing system complexity and cost.
Deepfakes have posed severe challenges to healthcare systems as fake medical images and videos can be utilized to disseminate fake information about an organization or person. The challenges have open room for more solutions to address them. Therefore, this study provides a survey that highlights the considerable strides made in the development of deepfake detection technologies while showcasing various approaches, from advanced machine learning techniques to multi-modal systems. The progress made in identifying deepfakes, particularly with regard to deep learning and hybrid models, shows promise for detecting alterations in digital content and medical imaging. But the use of these technologies shows differing degrees of efficacy, suggesting the necessity for customized detection tactics that take into account the particular difficulties of certain domains, such as nuclear medicine and endoscopic videography. In addition, the application of these technologies raises significant ethical and legal questions, such as those pertaining to data security, privacy, and possible abuses of artificial intelligence. Therefore, it becomes critical to provide a survey on these issues in order to build and apply deepfake detection tools responsibly.
Although hypertension may affect the local biomechanical properties of ascending thoracic aortic aneurysms (ATAAs) with a bicuspid aortic valve (BAV), a comparison of the regional elastic properties of BAV-ATAAs between patients with and without hypertension is not yet available due to lack of biomechanical data. In this study, we collected 25 fresh ATAA samples from 17 hypertensive and 8 age-matched non-hypertensive patients who underwent elective aortic surgery. Biomechanical tests were executed to investigate the regional failure stresses and biaxial mechanical properties of BAV-ATAAs with and without hypertension. A material model was fitted to the biaxial experimental data to obtain model parameters in different regions. Histological analysis was performed to investigate the underlying microstructure and determine the percentages of elastic and collagen fibers. The circumferential failure stresses in the anterior, lateral, and posterior regions were significantly lower for the hypertensive group than in the non-hypertensive group. Regarding equibiaxial stresses, the hypertensive BAV-ATAAs showed significantly higher longitudinal tissue stiffness in the anterior and lateral regions than the non-hypertensive BAV-ATAAs. Collagen fiber hyperplasia was observed in the anterior and lateral regions of both the hypertensive and non-hypertensive BAV-ATAAs. However, in these regions the laminar structure of the elastic fibers was disrupted in several places and apoptotic smooth muscle cells were observed in the group with hypertension compared to the group without hypertension. In addition, the circumferential failure stresses in the anterior and lateral regions were significantly increased in the hypertensive group and strongly correlated with the collagen content. These results suggest that the regional elastic properties of the hypertensive BAV-ATAAs are more deteriorated than those of the non-hypertensive samples. Due to the significant impact on circumferential tensile strength, the hypertensive BAV patients may be at a higher risk of ATAA rupture than non-hypertensive BAV patients.
Evaluation of spinal mobility is essential for clinical assessment of spinal disorders and their treatment. Motion capture systems can offer intersegmental kinematic data for the spine, but results usually depend on marker placement, and the definition of reference frames can still pose a challenge for clinical relevance and data comparison. This pilot study aimed to propose a reduced marker set protocol to estimate thoracic, lumbar, and intervertebral ranges of motion (ROM) during functional trunk movements - flexion/extension (FE), lateral bending (LB), and axial rotation (AR). Fifteen asymptomatic young adults performed standardised trunk tasks, while a twenty-one-marker configuration and motion-capture system were used to capture their 3D spinal motion. Anatomical coordinate systems were constructed for pelvis, thoracic, and lumbar regions. Three models of intervertebral kinematic constraints were compared, implementing different degrees of freedom between intervertebral segments, and different distribution of ROM to individual spinal levels. The agreement among models was assessed, and ROM was compared to literature data. Results showed large differences in ROM between kinematic models, as well as differences with reference data in the literature. Furthermore, differences between models were not consistent across all movements (FE, LB, AR). This study highlights the need for in vivo data to reflect functional, coupled spinal motion. The choice of kinematic model had a large impact on ROM and segmental ROM. Nevertheless, the proposed recduced marker protocol combined with validated kinematic constraints could offer a feasible and anatomically plausible solution for clinical spine mobility assessment.
Clinical use of endovascular interventions has increased in recent decades for treatment of peripheral artery disease (PAD); however, molecular imaging paradigms for monitoring inflammatory responses or adverse remodeling in targeted arteries have not been validated. Therefore, this study tested the utility of positron emission tomography (PET) imaging with fluorine-18 (18F)-fluorodeoxyglucose (FDG) for in vivo detection of peripheral angioplasty-induced arterial remodeling. Yorkshire pigs (n = 8) underwent fluoroscopy-guided overdilation of the right femoral artery using a balloon catheter inflated 1.25-1.85X the arterial diameter. 18F-FDG PET/CT imaging was performed 14 days post-angioplasty. Injured and control arteries were harvested immediately after imaging and sectioned for gamma counting (18F-FDG uptake) and stained with hematoxylin and eosin (H&E), alpha-smooth muscle actin (α-SMA), and CD64 for evaluation of arterial thickness, smooth muscle cell area, and macrophage infiltration. In vivo PET/CT imaging detected a significant increase in 18F-FDG uptake in injured versus control femoral arteries 14 days post-angioplasty (p = 0.008) that was confirmed by ex vivo gamma counting of vessels (p = 0.02). Ex vivo gamma counting of 18F-FDG uptake demonstrated a significant association with in vivo 18F-FDG uptake measured by PET/CT imaging (r = 0.92; p = 0.004). Image analysis for H&E, α-SMA, and CD64 revealed significant relative increases in vessel wall thickness (p < 0.0001), smooth muscle cell area (p = 0.0001), and CD64 area (p = 0.04) that were each significantly associated with ex vivo measures of 18F-FDG uptake. 18F-FDG PET/CT quantifies remodeling characteristics associated with angioplasty-induced injury, thereby providing a potential in vivo paradigm for monitoring and testing of emerging devices for PAD treatment.
Quantify the long-term mechanical durability of Abbott stylet-driven leads for left bundle branch area pacing (LBBAP) using a combination of computational modeling and fatigue bench test. Intracardiac lead curvatures were simulated in a 3D computational heart model across a range of lead implant scenarios and cardiac electro-mechanical scenarios over a complete cardiac cycle to determine the range of induced stresses. Safety factor was determined using the bending curvature and mechanical properties of the conductor. A benchtop fatigue physical test was implemented at higher stress levels, thus lower safety factors, than the computational modeling cohort. Computer simulation modeling showed that maximum curvature and safety factor (SF) were comparable for LBBA implants (0.06 ± 0.02 mm-1 and 4.7 ± 1.6) vs. other traditional implant locations (0.05 ± 0.03 mm-1 and 5.0 ± 0.7). Lead durability was verified through successful fatigue bench testing at max curvatures of 0.12 ± 0.01 mm-1 and safety factor of 2.2 ± 0.2. These test conditions represented approximately a twofold increase in maximum curvature and a 2.1-fold reduction in safety factor relative to simulated cases, over a test duration representative of 10 years of service. Abbott stylet-driven leads were demonstrated to be safe for LBBAP, even at stresses far exceeding those which may be clinically observed for 400 million cardiac cycles. No differences in long-term safety were observed between LBBAP and traditional pacing locations.
The growing global burden of ischemic stroke highlights the need for a deeper understanding of its pathogenic mechanisms. Although carotid plaque destabilization driven by intraplaque neovascularization is recognized as a critical factor of cerebrovascular disease, therapeutic strategies targeting this mechanobiological process remains inadequately explored. This study aims to develop and validate a noninvasive, portable ultrasound-guided nanotherapy system for enhancing the stability of early carotid artery plaques. We investigated a theranostic approach combining ultrasound-mediated microbubble cavitation with nanoliposomal drug delivery, a strategy that requires precise parameter optimization to achieve localized anti-angiogenic effects within unstable plaques. By engineering a flexible ultrasound device with adjustable power settings, we systematically demonstrated that combinatorial microbubble-nanoliposome treatment produces power-dependent therapeutic outcomes. Compared to the other groups, the microbubble-targeted liposome complex with ultrasound (MLCP + US) group demonstrated a marked reduction in necrotic core area, accompanied by increased collagen deposition and a pronounced decrease in intraplaque hemorrhage. Quantification of neovascularization via CD31 immunohistochemistry revealed near-complete suppression of intraplaque microvessels in the MLCP + US group. Western blot analysis further showed that the MLCP + US treatment significantly downregulated the expression levels of the examined signaling proteins. Multimodal analysis elucidated the mechanotransductive pathways by which ultrasound enhances drug penetration and promotes neovessel regression in preclinical models of carotid atherosclerosis. This study establishes a parameter-optimized, noninvasive platform for plaque stabilization and provides mechanistic insights that may inform the development of translationally relevant preventive strategies in stroke medicine.
Hepatocellular carcinoma (HCC) is the most common primary liver cancer and the third leading cause of cancer-related mortality worldwide. Despite advances in detection and treatment, prognosis remains poor, with incidence projected to surpass one million cases annually by 2025. Current loco-regional therapies, such as surgical resection, radiofrequency ablation, and transarterial chemoembolization, are often limited by anatomical or clinical constraints, leaving many patients without viable options. This study aims to develop and experimentally characterize a synthetic liver phantom with tunable mechanical and permeability properties for preclinical testing and protocol optimization of injectable loco-regional therapies, including emerging alternatives such as YntraDose. Porcine liver tissue was experimentally characterized to establish benchmark values for compression modulus and permeability. Based on these data, a 3D-printed phantom was designed using controlled microstructures to independently tune stiffness and permeability of parenchyma and tumor-mimicking regions. Compression testing, Darcy-based permeability experiments, and T2-weighted MRI were used for validation. The literature review revealed significant gaps in experimental permeability data, emphasizing the need for physical liver models to validate novel therapies. Preliminary design parameters were established for fabricating biomimetic liver phantoms with realistic mechanical and flow characteristics. Porcine liver permeability was measured in the order of 10⁻12 m2, while the selected parenchyma-mimicking material exhibited a compression modulus of approximately 22 kPa. Tumor-mimicking inclusions reached compression moduli of approximately 185 kPa. Injection experiments demonstrated reproducible diffusion patterns, confirmed by mass balance and MRI visualization. The proposed phantom provides a controlled experimental platform for investigating the mechanical and transport behavior of injectable agents in liver-mimicking tissue. While not intended for clinical or regulatory equivalence, this research-grade model bridges the gap between simplified in vitro systems and in vivo studies, supporting preclinical research and device development.
To develop an endoscope reprocessing system using ozonated water jets. The system features a jet head with concentric orifices that moves vertically to disinfect the external surface of the endoscope. Simultaneously, ozonated water is injected into the internal channel to ensure complete disinfection. Endoscopes were experimentally contaminated with Staphylococcus aureus and Escherichia coli. Quantitative and qualitative microbiological analyses were performed to evaluate the effectiveness of enzymatic detergent washing followed by ozonated water disinfection. The system achieved uniform disinfection across all endoscope surfaces. Quantitative analysis demonstrated a 4-log (99.99%) reduction in colony-forming units (CFU/mL) on the endoscope and in the post-disinfection water. Qualitative analysis showed no turbidity, indicating the absence of bacterial growth. This preliminary study presents the development of an endoscope reprocessor capable of achieving a 99.99% reduction in bacterial load using ozonated water jets. The system may represent a more resource-efficient alternative to conventional methods, consuming only 8 liters of water per cycle through recirculation and re-ozonation. The combined mechanical action of the water jets and the antimicrobial properties of ozone resulted in effective disinfection under the experimental conditions, reducing the processing time to 15 minutes compared to conventional methods.
This letter to the editor comments on a recent computational fluid dynamics study by You et al. on hemodynamic features of offending arteries in hemifacial spasm (HFS). While the original study provides valuable insights into arterial compression, it omits venous offenders and multi-vessel compression scenarios. Drawing on clinical cases and surgical evidence, this letter highlights the independent role of veins (e.g., the vein of the middle cerebellar peduncle) and the complexity of vertebral artery involvement. It argues that future CFD studies should include venous etiologies and multi-vessel configurations to improve diagnostic accuracy and surgical planning. The hemodynamic differences between arterial and venous compression are discussed, and the potential utility of parameters such as TAWSSR for venous offenders is proposed.
A left ventricular assist device (LVAD) is a mechanical pump that provides circulatory support as a bridge-to-cardiac transplantation or as a destination therapy in patients with advanced heart failure. A potential adverse event of LVAD support is thrombus ingestion or formation, which may then travel through the device into the cerebral arteries, causing ischemic strokes. Previous numerical simulations of embolus transport within LVAD systems have exhibited inconsistencies in the results in assessing the fate of emboli in LVAD settings. These disparities prompted the development of an experimental framework tailored for a systematic measurement of particle transport in the context of LVADs. In this in vitro study, we utilized a nearly refractive-index-matched time-resolved particle tracking velocimetry (PTV) system to resolve and visualize particle trajectories within each aortic model, complemented by particle image velocimetry (PIV) measurements. We also conducted a meticulous measurement of particle weight in each individual branch by collecting the particles from each outlet. Four LVAD patients, as well as two idealized models of the human aorta, each featuring a cannula grafted at an anastomosis angle of 45 degrees, were considered. Thin-wall high-resolution phantoms of these models were 3D-printed with precision and placed in a flow loop that provided physiological flow conditions. Three different sizes of precision fluorescent beads (neutrally buoyant) with particle-to-cannula diameter ratios of d p / D = 0.031, 0.053, 0.075 were used to replicate emboli at two clinically relevant flow rates, spanning over 50 experimental cases combined. This systematic investigation reveals that particle distributions largely follow the branchwise flow split, nearly independent of the range of Stokes numbers and inlet Reynolds numbers examined. This finding partially challenges commonly held assumptions in LVAD studies.
Early detection of right ventricular (RV) dysfunction is essential in pulmonary arterial hypertension (PAH) but remains challenging using conventional echocardiography. This study investigates the feasibility of a noninvasive, physics-based framework using three-dimensional (3D) echocardiography that integrates myocardial strain and volumetric flow analysis to characterize RV mechanical performance across stages of PAH. A prospective pilot study (N = 15) enrolled healthy controls, PAH patients with preserved RV size, and PAH patients with RV dysfunction. Deformation was evaluated by principal strain analysis and by conventional (longitudinal, circumferential) components. Hemodynamic metrics included hemodynamic forces and energetic properties that were derived using a physics-informed volumetric echocardiographic particle image velocimetry (V-Echo-PIV) method applied to contrast-enhanced acquisitions. Deformation analysis revealed that longitudinal strain was significantly reduced even in PAH patients with preserved RV dimensions, while second principal (secondary) strain showed a distinctive sign reversal, indicating a paradoxical systolic lengthening, early in the disease. The analysis of hemodynamic forces showed a marked reduction in systolic propulsion across all PAH stages. In contrast, energetic abnormalities were predominantly observed at later stage of the disease. The integration of 3D myocardial strain with fluid dynamics provides a comprehensive physiological assessment of RV remodeling. While strain and systolic propulsion appear as sensitive markers for early dysfunction, diastolic energetics may support disease staging. This noninvasive framework shows promise for early detection and longitudinal monitoring of PAH patients.
The development of magnetoencephalography (MEG) based on optically pumped magnetometers (OPMs) has accelerated the evolution of brain imaging toward portable and movable configurations. Source localization using OPM-MEG plays a crucial role in both neuroscience and clinical applications. However, few studies have systematically evaluated localization performance under realistic measurement conditions that account for potential sensor errors. In this study, we simulated empirical OPM-MEG data with a biologically plausible model of ongoing brain activity to investigate the effects of calibration errors, specifically gain error, crosstalk, and angular misalignment, on the localization performance of three OPM array configurations: single-axis, dual-axis, and tri-axis sensors. We also compared four source inversion algorithms: Multiple Sparse Priors (MSP), Empirical Bayesian Beamformer (EBB), Minimum Norm (IID), and LORETA (COH). Our results indicate that gain error had minimal impact on localization accuracy, whereas crosstalk and angular error significantly degraded performance. These findings underscore the importance of OPM array calibration using reference magnetic fields, particularly for dual- and tri-axis configurations. Among the inversion methods tested, MSP demonstrated relative robustness to calibration errors and achieved the best overall performance, making it the most recommended approach. Furthermore, analysis of the relationship between cortical anatomy and localization accuracy revealed that deep neural sources are more susceptible to gain errors and thus require particular attention. To achieve accuracy comparable to an ideal OPM-MEG system, crosstalk should be kept below 2% and angular error under 2°.
Abnormalities in cardiac wall motion are strong predictors of cardiovascular risk, making their accurate detection essential for early diagnosis and effective clinical management. Traditional imaging modalities such as echocardiography, magnetic resonance imaging (MRI), and computed tomography (CT) provide valuable insights but face limitations related to accessibility, cost, and the complexity of spatiotemporal analysis. Recent advances in machine learning (ML), particularly deep learning (DL), have enabled automated extraction of spatial and temporal features from medical imaging. They improved accuracy in segmentation, motion estimation, and detection of regional wall motion abnormalities. This paper reviews state-of-the-art methods for predicting cardiac wall motion, with emphasis on DL applications across echocardiography, 4D CT, and cine MRI datasets. Representative studies demonstrate the potential of convolutional neural networks, recurrent neural networks, and transformers to achieve performance comparable to expert clinicians, while also highlighting challenges such as data scarcity, model interpretability, and limited external validation. Addressing these issues will be critical for translating ML-based approaches into routine practice, and integration of advanced imaging with robust ML frameworks helps in developing a reliable cardiac wall motion simulators for personalized treatment planning and improved cardiovascular care.
Cerebrospinal fluid (CSF) dynamics within the optic nerve subarachnoid space (ONSAS) are increasingly recognised as potential factors contributing to the pathogenesis of optic neuropathies, including normal-tension glaucoma (NTG) and idiopathic intracranial hypertension (IIH). In this study, high-resolution T2-weighted magnetic resonance imaging (MRI) data were manually segmented and processed for greyscale analysis and pixel-intensity mapping, enabling anatomically accurate three-dimensional reconstructions of the ONSAS. These reconstructions were imported into OpenFOAM software for computational fluid dynamics (CFD) simulations, incorporating physiologically realistic inlet pressure waveforms, boundary conditions, tissue porosity, and lymphatic drainage characteristics in the near optic nerve head portion of ONSAS, called the distal portion. Solver selection in OpenFOAM was optimised for the narrow geometry and unique boundary features of the ONSAS, yielding high-resolution maps of CSF flow dynamics. Multiple drainage scenarios were simulated to represent healthy, NTG, and IIH conditions. Area-averaged CSF velocities were quantified for each condition and compared with the scarce and available values reported in phase-contrast MRI (PC-MRI) studies. The results provide novel, physiologically relevant insights into CSF transport behaviour in the ONSAS under different physiological and pathophysiological conditions, with potential implications for the diagnosis, management, and treatment of optic neuropathies.
Osteoarthritis (OA) pain can arise from inflammatory cytokines sensitizing neurons that innervate the temporomandibular joint (TMJ) and knee. Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-based epigenome editing enables targeted repression of inflammatory receptors and offers a promising strategy to modify disease mechanisms. This study tested whether CRISPR epigenome editing of interleukin-1 receptor type 1 (IL1R1) in trigeminal ganglia (TG; TMJ-innervating) and dorsal root ganglia (DRG; knee-innervating) neurons could reduce OA-associated sensitization. OA cartilage was collected from knee replacement patients and compared with healthy cadaveric cartilage. Rat TG and DRG neurons were cultured with IL-1β on tissue culture plastic or cartilage explants, loaded with calcium dye, and subjected to thermal stimulation. Neurons were transduced with lentiviral CRISPR-dCas9-KRAB vectors targeting IL1R1 or with nontargeting controls, and heat-evoked calcium transients were measured. Exposure to IL-1β and OA cartilage both increased the proportion of TG and DRG neurons exhibiting heat-induced calcium transients compared with controls. CRISPR epigenome editing of IL1R1 abolished sensitization in DRG neurons, restoring responses to healthy cartilage levels. In TG neurons, editing reduced maximum calcium responses to baseline but did not fully normalize the percentage of sensitized cells, suggesting additional OA factors contribute to TMJ pain. CRISPR epigenome editing of IL1R1 in joint-innervating neurons reduces OA cartilage-induced sensitization. These results highlight differential mechanisms underlying OA cartilage driven DRG and TG neuron sensitization and establish epigenome editing as a potential therapeutic strategy to target OA-associated sensitization in the knee and TMJ.
As surgical practice has shifted from mechanical alignment toward kinematic alignment with growing interest in patient-specific soft-tissue laxity, we evaluated under dynamic, weight-bearing conditions-the relative impact of (1) soft-tissue laxity (modeled via MCL stiffness/compliance) and (2) the balanced medial collateral ligament (MCL) length achieved after soft-tissue balancing on tibiofemoral load sharing and kinematics in posterior-stabilized (PS) total knee arthroplasty (TKA). A validated, squat-based musculoskeletal model of mechanically aligned PS-TKA (0-120°) with anatomically segmented, nonlinear ligaments was used. Twenty-one simulations systematically varied soft-tissue laxity (± 20% change in MCL stiffness/compliance) and balanced MCL length (0-12% change in initial length). Outcomes included medial/lateral tibiofemoral contact forces, femoral internal-external and varus-valgus rotations, and compartmental rollback. Changes in balanced MCL length dominated knee mechanics. Lengthening the balanced MCL (greater final length/lower pre-tension) reduced medial contact force by up to 48% (0.76 BW), increased lateral loading, and increased femoral external rotation (+ 1.5°) and posterior rollback (up to 3.7 mm). Shortening (higher pre-tension) produced features of overconstraint with elevated medial pressures and diminished rollback. In contrast, modifying soft-tissue laxity alone (± 20% stiffness/compliance) had minimal effect on load sharing or kinematics unless the ligament was already tensioned. Across the flexion arc, the balanced MCL length (functional post-balancing length/pre-tension) has a substantially greater influence on tibiofemoral load distribution and kinematics than inherent soft-tissue laxity. Intraoperatively, prioritizing precise control of balanced MCL length-via selective release, preservation, or retensioning-may better normalize compartmental forces, mitigate midflexion instability, and avoid overconstraint than attempting to accommodate small variations in intrinsic laxity. These weight-bearing simulation data provide a practical baseline for integrating patient-specific laxity into alignment strategies and support targeting a physiologic, balanced MCL length as the primary means to achieve stability and near-native kinematics in PS-TKA.