The perineum is a layered soft tissue structure with mechanical properties that maintain the integrity of the pelvic floor. During childbirth, the perineum undergoes significant deformation that ...often results in tears of various degrees of severity. To better understand the mechanisms underlying perineal tears, it is crucial to consider the mechanical properties of the different tissues that make up the perineum. Unfortunately, there is a lack of data on the mechanical properties of the perineum in the literature. The objective of this study is to partly fill these gaps. Hence sow perineums were dissected and the five perineal tissues involved in tears were characterized by uniaxial tension tests: Skin, Vagina, External Anal Sphincter, Internal Anal Sphincter and Anal Mucosa. From our knowledge, this study is the first to investigate all these tissues and to design a testing protocol to characterize their material properties. Six material models were used to fit the experimental data and the correlation between experimental and predicted data was evaluated for comparison. As a result, even if the tissues are of different nature, the best correlation was obtained with the Yeoh and Martins material models for all tissues. Moreover, these preliminary results show the difference in stiffness between the tissues which indicates that they might have different roles in the structure. These obtained results will serve as a basis to design an improved experimental protocol for a more robust structural model of the porcine perineum that can be used for the human perineum to predict perineal tears.
This article reviews some of the recent advances on FTIR spectroscopy in areas related to natural tissues and cell biology. It is an update on our previously published review on the applications of ...spectroscopic methods employed for the analysis of biological molecules, and summarizes some of the most widely used peak frequencies and their assignments. The aim of this review is to update and consolidate our previously published spectral database, which will help researchers in defining the chemical structure of the biological tissues introducing most of the important peaks present in the natural tissues more precisely and accurately. In spite of applying different methods, there seems to be a considerable similarity in defining the peaks of identical areas of the FTIR spectra. As a result, it is believed that preparing a unique collection of the frequencies encountered in FTIR spectroscopic studies can provide substantial help for future studies. In this article, we have included recent studies that have been reported since previous publication that will be of considerable assistance and added value to those who are focusing their research on defining chemical pathway to the progression of different diseases.
Soft structures are capable of undergoing reversible large strains and deformations when facing different types of loadings. Due to the limitations of linear elastic models, researchers have ...developed and employed different nonlinear elastic models capable of accurately modelling large deformations and strains. These models are significantly different in formulation and application. As hyperelastic strain energy density models provide researchers with a good fit for the mechanical behaviour of biological tissues, research studies on using these constitutive models together with different continuum-mechanics-based formulations have reached notable outcomes. With the improvements in biomechanical devices, in-vivo and in-vitro studies have increased significantly in the past few years which emphasises the importance of reviewing the latest works in this field. Besides, since soft structures are used for different mechanical and biomechanical applications such as prosthetics, soft robots, packaging, and wearing devices, the application of a proper hyperelastic strain energy density law in modelling the structure is of high importance. Therefore, in this review, a detailed classified analysis of the mechanics of hyperelastic structures is presented by focusing on the application of different hyperelastic strain energy density models. Previous studies on biological soft parts of the body (brain, artery, cartilage, liver, skeletal muscle, ligament, skin, tongue, heel pad and adipose tissue) are presented in detail and the hyperelastic strain energy models used for each biological tissue is discussed. Besides, the mechanics (deformation, buckling, inflation, etc.) of polymeric structures in different mechanical conditions is presented using previous studies in this field and the strength of hyperelastic strain energy density models in analysing their mechanics is presented.
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•Laser-induced breakdown spectroscopy is a major tool for imaging chemical elements in tissues.•Imaging of trace, minor or major elements with LIBS requires minor sample ...preparation.•Both endogenous and exogenous metal elements from the tissues are simultaneously detectable.•Tissue imaging with LIBS has straightforward applications for preclinical and medical studies.
Biological tissues contain various metal and metalloid ions that play different roles in the structure and function of proteins and are therefore indispensable to several vital biochemical processes. In this review, we discuss the broad capability of laser-induced breakdown spectroscopy (LIBS) for in situ elemental profiling and mapping of metals in biological materials such as plant, animal and human specimens. These biological samples contain or accumulate metal species and metal-containing compounds that can be detected, quantified, and imaged. LIBS enables performing microanalysis, mapping and depth profiling of endogenous and exogenous elements contained in the tissues with a parts-per-million scale sensitivity and microscopic resolution. In addition, this technology generally requires minimal sample preparation. Moreover, its tabletop instrumentation is compatible with optical microscopy and most elements from the periodic table. Specifically, low- and high-atomic-number elements can be detected simultaneously. Recent advances in space-resolved LIBS are reviewed with various examples from vegetable, animal and human specimens. Overall, the performance offered by this new technology along with its ease of operation suggest innumerable applications in biology, such as for the preclinical evaluation of metal-based nanoparticles and in medicine, where it could broaden the horizons of medical diagnostics for all pathologies involving metals.
We previously published a comprehensive review paper reviewing the Raman spectroscopy of biological molecules. This research area has expanded rapidly, which warranted an update to the existing ...review paper by adding the recently reported studies in literature. This article reviews some of the recent advances of Raman spectroscopy in relation to biomedical applications starting from natural tissues to cancer biology. Raman spectroscopy, an optical molecular detective, is a vibrational spectroscopic technique that has potential not only in cancer diagnosis but also in understanding progression of the disease. This article summarizes some of the most widely observed peak frequencies and their assignments. The aim of this review is to develop a database of molecular fingerprints, which will facilitate researchers in identifying the chemical structure of the biological tissues including most of the significant peaks reported both in the normal and cancerous tissues. It has covered a variety of Raman approaches and its quantitative and qualitative biochemical information. In addition, it covers the use of Raman spectroscopy to analyse a variety of different malignancies including breast, brain, cervical, gastrointestinal, lung, oral, and skin cancer. Multivariate analysis approaches used in these studies have also been covered.
Abstract Raman spectroscopy is a popular tool for characterizing complex biological materials and their geological remains. Ordination methods, such as principal component analysis (PCA), use ...spectral variance to create a compositional space, the ChemoSpace, grouping samples based on spectroscopic manifestations reflecting different biological properties or geological processes. PCA allows to reduce the dimensionality of complex spectroscopic data and facilitates the extraction of informative features into formats suitable for downstream statistical analyses, thus representing a first step in the development of diagnostic biosignatures from complex modern and fossil tissues. For such samples, however, there is presently no systematic and accessible survey of the impact of sample, instrument, and spectral processing on the occupation of the ChemoSpace. Here, the influence of sample count, unwanted signals and different signal‐to‐noise ratios, spectrometer decalibration, baseline subtraction, and spectral normalization on ChemoSpace grouping is investigated and exemplified using synthetic spectra. Increase in sample size improves the dissociation of groups in the ChemoSpace, and our sample yields a representative and mostly stable pattern in occupation with less than 10 samples per group. The impact of systemic interference of different amplitude and frequency, periodical or random features that can be introduced by instrument or sample, on compositional biological signatures is reduced by PCA and allows to extract biological information even when spectra of differing signal‐to‐noise ratios are compared. Routine offsets ( 1 cm −1 ) in spectrometer calibration contribute in our sample to less than 0.1% of the total spectral variance captured in the ChemoSpace and do not obscure biological information. Standard adaptive baselining, together with normalization, increases spectral comparability and facilitates the extraction of informative features. The ChemoSpace approach to biosignatures represents a powerful tool for exploring, denoising, and integrating molecular information from modern and ancient organismal samples.
Minimally invasive surgery (MIS) remains technically demanding due to the difficulty of tracking hidden critical structures within the moving anatomy of the patient. In this study, we propose a soft ...tissue deformation tracking augmented reality (AR) navigation pipeline for laparoscopic surgery of the kidneys. The proposed navigation pipeline addresses two main sub-problems: the initial registration and deformation tracking. Our method utilizes preoperative MR or CT data and binocular laparoscopes without any additional interventional hardware. The initial registration is resolved through a probabilistic rigid registration algorithm and elastic compensation based on dense point cloud reconstruction. For deformation tracking, the sparse feature point displacement vector field continuously provides temporal boundary conditions for the biomechanical model. To enhance the accuracy of the displacement vector field, a novel feature points selection strategy based on deep learning is proposed. Moreover, an ex-vivo experimental method for internal structures error assessment is presented. The ex-vivo experiments indicate an external surface reprojection error of 4.07 ± 2.17mm and a maximum mean absolutely error for internal structures of 2.98mm. In-vivo experiments indicate mean absolutely error of 3.28 ± 0.40mm and 1.90±0.24mm, respectively. The combined qualitative and quantitative findings indicated the potential of our AR-assisted navigation system in improving the clinical application of laparoscopic kidney surgery.
Proximal femoral fracture segmentation in computed tomography (CT) is essential in the preoperative planning of orthopedic surgeons. Recently, numerous deep learning-based approaches have been ...proposed for segmenting various structures within CT scans. Nevertheless, distinguishing various attributes between fracture fragments and soft tissue regions in CT scans frequently poses challenges, which have received comparatively limited research attention. Besides, the cornerstone of contemporary deep learning methodologies is the availability of annotated data, while detailed CT annotations remain scarce. To address the challenge, we propose a novel weakly-supervised framework, namely Rough Turbo Net (RT-Net), for the segmentation of proximal femoral fractures. We emphasize the utilization of human resources to produce rough annotations on a substantial scale, as opposed to relying on limited fine-grained annotations that demand a substantial time to create. In RT-Net, rough annotations pose fractured-region constraints, which have demonstrated significant efficacy in enhancing the accuracy of the network. Conversely, the fine annotations can provide more details for recognizing edges and soft tissues. Besides, we design a spatial adaptive attention module (SAAM) that adapts to the spatial distribution of the fracture regions and align feature in each decoder. Moreover, we propose a fine-edge loss which is applied through an edge discrimination network to penalize the absence or imprecision edge features. Extensive quantitative and qualitative experiments demonstrate the superiority of RT-Net to state-of-the-art approaches. Furthermore, additional experiments show that RT-Net has the capability to produce pseudo labels for raw CT images that can further improve fracture segmentation performance and has the potential to improve segmentation performance on public datasets. The code is available at: https://github.com/zyairelu/RT-Net.
Robotized laser endoscopic tools provided surgeons with increased accuracy for ablating tissue. Here, a new modular endoscopic laser scanner system test-bed was designed and fabricated for conducting ...experiments into control strategies. This new system used a continuous wave (CW) laser system specifically designed for the task. Experiments into biological tissue ablation with this new system were compared with experiments previously conducted using a pulsed laser system. The torque required to accurately position the light beam of the flexible fiber optic cable was derived by solving Maxwell's equations. The new test-bed again included a photo-detector sensor, which was used to position the laser beam on the tissue and provide closed-loop feedback control. With this arrangement, laser beam tracking errors were shown to be smaller than in the original pulsed laser experiments, and the tissue ablation patterns were repeatable. Trials on biological tissue (chicken meat) with this new physical test-bed proved that the tissue ablation pattern experiments were consistent, robust, and accurate. A COMSOL simulation of heat propagation then showed that consistency between the experimental and the simulation results. It also gave indicators for additional test-bed design changes that are required for optimizing the control of laser beam/biological tissue ablation.
