搜索结果：Tissue barriers

Tissue deformation recovery based on stereo endoscopic images is crucial for tool-tissue interaction analysis and benefits surgical navigation and autonomous soft tissue manipulation. Previous research suffers from the problems raised from camera motion, occlusion, large tissue deformation, lack of tissue-specific biomechanical priors, and reliance on offline processing. Unlike previous studies where the tissue geometry and deformation are represented by 3D points and displacements, the proposed method models tissue geometry as the 3D point and derivative map and tissue deformation as the 3D displacement and local deformation map. For a single surface point, 6 parameters are used to describe its rigid motion and 3 parameters for its local deformation. The method is formulated under the camera-centric setting, where all motions are regarded as the scene motion with respect to the camera. Inter-frame alignment is realized by optimizing the inter-frame deformation, making it unnecessary to estimate camera pose. The concept of the canonical map is introduced to optimize tissue geometry and deformation in an online approach. Quantitative and qualitative experiments were conducted using

Tissue engineering technology and tissue cell-based stem cell research have made great strides in treating tissue and organ damage, correcting tissue and organ dysfunction, and reducing surgical complications. In the past, traditional methods have used biological substitutes for tissue repair materials, while tissue engineering technology has focused on merging sperm cells with biological materials to form biological tissues with the same structure and function as their own tissues. The advantage is that tissue engineering technology can overcome donors. Material procurement restrictions can effectively reduce complications. The aim of studying tissue engineering technology is to find sperm cells and suitable biological materials to replace the original biological functions of tissues and to establish a suitable in vivo microenvironment. This article mainly describes the current developments of tissue engineering in various fields of urology and discusses the future trends of tissue engineering technology in the treatment of complex diseases of the urinary system. The results of the research in this article indicate that while the current clinical studies are relatively few, the go

This paper is a contribution to the "BraTS 2023 Local Synthesis of Healthy Brain Tissue via Inpainting Challenge". The task of this challenge is to transform tumor tissue into healthy tissue in brain magnetic resonance (MR) images. This idea originates from the problem that MR images can be evaluated using automatic processing tools, however, many of these tools are optimized for the analysis of healthy tissue. By solving the given inpainting task, we enable the automatic analysis of images featuring lesions, and further downstream tasks. Our approach builds on denoising diffusion probabilistic models. We use a 2D model that is trained using slices in which healthy tissue was cropped out and is learned to be inpainted again. This allows us to use the ground truth healthy tissue during training. In the sampling stage, we replace the slices containing diseased tissue in the original 3D volume with the slices containing the healthy tissue inpainting. With our approach, we achieve comparable results to the competing methods. On the validation set our model achieves a mean SSIM of 0.7804, a PSNR of 20.3525 and a MSE of 0.0113. In future we plan to extend our 2D model to a 3D model, allo

Organogenesis involves large deformations and complex shape changes that require elaborate mechanical regulation. Models of tissue biomechanics have been introduced to account for the coupling between mechanical response and biochemical processes. Recent experimental evidence indicates that the mechanical response of epithelial tissue is strongly anisotropic, with the degree of anisotropy being correlated with the existence of long range orientational order of cytoskeletal organization across the tissue. A theoretical framework is introduced that captures the dynamic feedback between tissue elastic response and cytoskeletal reorganization under stress. Within the linear regime for small and uniform applied strains, the shear modulus is effectively reduced by the nematic order in cytoskeletal alignment induced by the applied strain. This prediction agrees with experimental observations of epithelial response in lithographically patterned micro tissues.

Cellular rearrangements, as primary sources of tissue fluidization, facilitate topological transitions during tissue morphogenesis. We study the role of intrinsic cell properties such as cell polarity and cell-cell adhesion in shaping epithelial tissues using a minimal model of interacting polarized cells. The presence of a vortex in the cell polarization poses the topological constraint that induces an inwards migration with the formation of a conical shape. Local rearrangements at the tip of the cone lead to the onset of tube formation. Switching between collective migration and structural rearrangements is key for balancing the contrasting tendencies, such as the tissue rigidity needed to preserve shape and the tissue fluidity allowing for topological transitions during tissue morphogenesis.

A key process during animal morphogenesis is oriented tissue deformation, which is often driven by internally generated active stresses. Yet, such active oriented materials are prone to well-known instabilities, raising the question of how oriented tissue deformation can be robust during morphogenesis. Here we study under which conditions active oriented deformation can be stabilized by the concentration pattern of a signaling molecule, which is secreted by a localized source region, diffuses across the tissue, and degrades. Consistent with earlier results, we find that oriented tissue deformation is always unstable in the gradient-contractile case, i.e. when active stresses act to contract the tissue along the direction of the signaling gradient, and we now show that this is true even in the limit of large diffusion. However, active deformation can be stabilized in the gradient-extensile case, i.e. when active stresses act to extend the tissue along the direction of the signaling gradient. Specifically, we show that gradient-extensile systems can be stable when the tissue is already elongated in the direction of the gradient. We moreover point out the existence of a formerly unkno

The self-organization of cells into complex tissues relies on a tight coordination of cell behavior. Identifying the cellular processes driving tissue growth is key to understanding the emergence of tissue forms and devising targeted therapies for aberrant growth, such as in cancer. Inferring the mode of tissue growth, whether it is driven by cells on the surface or cells in the bulk, is possible in cell culture experiments, but difficult in most tissues in living organisms (in vivo). Genetic tracing experiments, where a subset of cells is labeled with inheritable markers have become important experimental tools to study cell fate in vivo. Here, we show that the mode of tissue growth is reflected in the size distribution of the progeny of marked cells. To this end, we derive the clone-size distributions using analytical calculations in the limit of negligible cell migration and cell death, and we test our predictions with an agent-based stochastic sampling technique. We show that for surface-driven growth the clone-size distribution takes a characteristic power-law form with an exponent determined by fluctuations of the tissue surface. Our results show how the mode of tissue growth

Conventional imaging of diagnostic ultrasound is widely used. Although it makes the differences in the soft tissues echogenicities' apparent and clear, it fails in describing and estimating the soft tissue mechanical properties. It cannot portray their mechanical properties, such as the elasticity and stiffness. Estimating the mechanical properties increases chances of the identification of lesions or any pathological changes. Physicians are now characterizing the tissue's mechanical properties as diagnostic metrics. Estimating the tissue's mechanical properties is achieved by applying an Acoustic Radiation Force Impulse (ARFI) on the tissue and calculating the resulted shear wave speed. Due to the difficulty of calculating the shear wave speed precisely inside the tissue, it is estimated by analyzing ultrasound images of the tissue at a very high frame rate. In this study, the shear wave speed is estimated using finite element analysis. A two-dimensional model is constructed to simulate the tissue's mechanical properties. For a generalized soft tissue model, Agar-gelatine model is used because it has similar properties to the soft tissue. A point force is applied at the center of

In tissue engineering, we seek to address comprehensive tissue repair and regeneration needs. Aligned nanofibers have emerged as powerful and versatile tools, attributable to their structural and biochemical congruence with the natural extracellular matrix (ECM). This review delineates the contemporary applications of aligned nanofibers in tissue engineering, spotlighting their implementation across musculoskeletal, neural, and cardiovascular tissue domains. The influence of fiber alignment on critical cellular behaviors - cell adhesion, migration, orientation, and differentiation - is reviewed. We also discuss how nanofibers are improved by adding growth factors, peptides, and drugs to help tissues regenerate better. Comprehensive analyses of in vivo trials and clinical studies corroborate the efficacy and safety of these fibers in tissue engineering applications. The review culminates with exploring extant challenges, concurrently charting prospective avenues in aligned nanofiber-centric tissue engineering.

In animals, epithelial tissues are barriers against the external environment, providing protection against biological, chemical, and physical damage. Depending on the animal's physiology and behavior, these tissues encounter different types of mechanical forces and need to provide a suitable adaptive response to ensure success. Therefore, understanding tissue mechanics in different contexts is an important research area. Here, we review recent tissue mechanics discoveries in a few early-divergent non-bilaterian animals -- Trichoplax adhaerens, Hydra vulgaris, and Aurelia aurita. We highlight each animal's simple body plan and biology, and unique, rapid tissue remodeling phenomena that play a crucial role in its physiology. We also discuss the emergent large-scale mechanics that arise from small-scale phenomena. Finally, we emphasize the enormous potential of these non-bilaterian animals to be model systems for further investigation in tissue mechanics.

Today's mechanical tools for bone cutting (osteotomy) cause mechanical trauma that prolongs the healing process. Medical device manufacturers aim to minimize this trauma, with minimally invasive surgery using laser cutting as one innovation. This method ablates tissue using laser light instead of mechanical tools, reducing post-surgery healing time. A reliable feedback system is crucial during laser surgery to prevent damage to surrounding tissues. We propose a tissue classification method analyzing acoustic waves generated during laser ablation, demonstrating its applicability in an ex-vivo experiment. The ablation process with a microsecond pulsed Er:YAG laser produces acoustic waves, acquired with an air-coupled transducer. These waves were used to classify five porcine tissue types: hard bone, soft bone, muscle, fat, and skin. For automated tissue classification, we compared five Neural Network (NN) approaches: a one-dimensional Convolutional Neural Network (CNN) with time-dependent input, a Fully-connected Neural Network (FcNN) with either the frequency spectrum or principal components of the frequency spectrum as input, and a combination of a CNN and an FcNN with time-depende

The growth of several biological tissues is known to be controlled in part by local geometrical features, such as the curvature of the tissue interface. This control leads to changes in tissue shape that in turn can affect the tissue's evolution. Understanding the cellular basis of this control is highly significant for bioscaffold tissue engineering, the evolution of bone microarchitecture, wound healing, and tumour growth. While previous models have proposed geometrical relationships between tissue growth and curvature, the role of cell density and cell vigor remains poorly understood. We propose a cell-based mathematical model of tissue growth to investigate the systematic influence of curvature on the collective crowding or spreading of tissue-synthesising cells induced by changes in local tissue surface area during the motion of the interface. Depending on the strength of diffusive damping, the model exhibits complex growth patterns such as undulating motion, efficient smoothing of irregularities, and the generation of cusps. We compare this model with in-vitro experiments of tissue deposition in bioscaffolds of different geometries. By accounting for the depletion of active c

Interfaces in tissues are ubiquitous, both between tissue and environment as well as between populations of different cell types. The propagation of an interface can be driven mechanically. % e.g. by a difference in the respective homeostatic stress of the different cell types. Computer simulations of growing tissues are employed to study the stability of the interface between two tissues on a substrate. From a mechanical perspective, the dynamics and stability of this system is controlled mainly by four parameters of the respective tissues: (i) the homeostatic stress (ii) cell motility (iii) tissue viscosity and (iv) substrate friction. For propagation driven by a difference in homeostatic stress, the interface is stable for tissue-specific substrate friction even for very large differences of homeostatic stress; however, it becomes unstable above a critical stress difference when the tissue with the larger homeostatic stress has a higher viscosity. A small difference in directed bulk motility between the two tissues suffices to result in propagation with a stable interface, even for otherwise identical tissues. Larger differences in motility force, however, result in a finite-wav

Living tissues undergo wetting transitions: On a surface, they can either form a droplet-like cell aggregate or spread as a monolayer of migrating cells. Tissue wetting depends not only on the chemical but also on the mechanical properties of the substrate. Here, we study the role of substrate stiffness in tissue spreading, which we describe by means of an active polar fluid model. Taking into account that cells exert larger active traction forces on stiffer substrates, we predict a tissue wetting transition at a critical substrate stiffness that decreases with tissue size. On substrates with a stiffness gradient, we find that the tissue spreads faster on the stiffer side. Further, we show that the tissue can wet the substrate on the stiffer side while dewetting from the softer side. We also show that, by means of viscous forces transmitted across the tissue, the stiffer-side interface can transiently drag the softer-side interface towards increasing stiffness, against its spreading tendency. These two effects result in directed tissue migration up the stiffness gradient. This phenomenon -- tissue durotaxis -- can thus emerge both from dewetting at the soft side and from hydrodynam

Epithelial morphogenesis, a signature problem of tissue biology and tissue mechanics, continues to inspire biologists and physicists alike. Many treatments focus on tissue fluidization, apical/basal ratio changes, or mechanical instabilities. In contrast to these approaches, shape-programmable materials, where the local lengths in the material change in a prescribed way, offer an appealing analogy. In this analogy, certain in-plane collective cell behaviors could also actively alter the local lengths in a tissue and therefore provide the ingredients necessary for shape programming. In this Letter we demonstrate that this is indeed the case for directed, active T1 rearrangements of cells. We determine the required shape programming parameters associated to tissue patches with both fixed numbers of rearrangements and patches at steady state between directed T1 events and counterbalancing randomly oriented ones using a simple free-boundary vertex model approach. Along the way we uncover a surprising connection between tissues with active T1 events and the central limit theorem, and through it, the physics of entropic springs.

In the context of surgery, robots can provide substantial assistance by performing small, repetitive tasks such as suturing, needle exchange, and tissue retraction, thereby enabling surgeons to concentrate on more complex aspects of the procedure. However, existing surgical task learning mainly pertains to rigid body interactions, whereas the advancement towards more sophisticated surgical robots necessitates the manipulation of soft bodies. Previous work focused on tissue phantoms for soft tissue task learning, which can be expensive and can be an entry barrier to research. Simulation environments present a safe and efficient way to learn surgical tasks before their application to actual tissue. In this study, we create a Robot Operating System (ROS)-compatible physics simulation environment with support for both rigid and soft body interactions within surgical tasks. Furthermore, we investigate the soft tissue interactions facilitated by the patient-side manipulator of the DaVinci surgical robot. Leveraging the pybullet physics engine, we simulate kinematics and establish anchor points to guide the robotic arm when manipulating soft tissue. Using demonstration-guided reinforcemen

In Minimally Invasive Surgery (MIS), tissue scanning with imaging probes is required for subsurface visualisation to characterise the state of the tissue. However, scanning of large tissue surfaces in the presence of deformation is a challenging task for the surgeon. Recently, robot-assisted local tissue scanning has been investigated for motion stabilisation of imaging probes to facilitate the capturing of good quality images and reduce the surgeon's cognitive load. Nonetheless, these approaches require the tissue surface to be static or deform with periodic motion. To eliminate these assumptions, we propose a visual servoing framework for autonomous tissue scanning, able to deal with free-form tissue deformation. The 3D structure of the surgical scene is recovered and a feature-based method is proposed to estimate the motion of the tissue in real-time. A desired scanning trajectory is manually defined on a reference frame and continuously updated using projective geometry to follow the tissue motion and control the movement of the robotic arm. The advantage of the proposed method is that it does not require the learning of the tissue motion prior to scanning and can deal with fre

Biological systems across various length and time scales are noisy, including tissues. Why are biological tissues inherently chaotic? Does heterogeneity play a role in determining the physiology and pathology of tissues? How do physical and biochemical heterogeneity crosstalk to dictate tissue function? In this review, we begin with a brief primer on heterogeneity in biological tissues. Then, we take examples from recent literature indicating functional relevance of biochemical and physical heterogeneity and discuss the impact of heterogeneity on tissue function and pathology. We take specific examples from studies on epithelial tissues to discuss the potential role of inherent tissue heterogeneity in tumorigenesis.

The promise of "free and open" multi-terabyte datasets often collides with harsh realities. While these datasets may be technically accessible, practical barriers -- from processing complexity to hidden costs -- create a system that primarily serves well-funded institutions. This study examines accessibility challenges across web crawls, satellite imagery, scientific data, and collaborative projects, revealing a consistent two-tier system where theoretical openness masks practical exclusivity. Our analysis demonstrates that datasets marketed as "publicly accessible" typically require minimum investments of \$1,000+ for meaningful analysis, with complex processing pipelines demanding \$10,000-100,000+ in infrastructure costs. The infrastructure requirements -- distributed computing knowledge, domain expertise, and substantial budgets -- effectively gatekeep these datasets despite their "open" status, limiting practical accessibility to those with institutional support or substantial resources.