Pelvic organ prolapse (POP) is an abnormality of the female pelvic anatomy due to events, such as multiple child births, menopause, and morbid obesity, which may lead to weakening of the pelvic floor striated muscles and smooth musculo-connective tissues. POP leads to dropping of the pelvic organs, namely, the bladder, uterus, and rectum into the vaginal canal and eventual protrusion, causing vaginal pain, pressure, difficulty emptying the bladder and rectum, and sexual dysfunction. Each year, close to 300,000 POP surgeries are performed in the U.S., out of which more than 60% of patients may face relapse conditions. A closer look into the problem reveals that POP surgery failures may be attributed mainly to the lack of understanding among medical practitioners on the mechanics of prolapse. In the literature, there have been attempts in the engineering community to understand prolapse using phenomenological computational modeling. This paper reviews the development and study of these numerical models, aimed at understanding the mechanics of POP. The various computational challenges related to geometry creation, material modeling, finite-element (FE) modeling, and boundary conditions (BCs) will be discussed and significant future research directions will also be highlighted in this review.

Traumatic brain injury (TBI) due to blast exposure or head impacts in accidents or contact sports is one of the most critical and poorly understood areas of research in the 21st century. To date, the unavailability of human brain tissues (grey and white matter especially) due to ethical and biosafety issues has not allowed for much experimental research into the study of the mechanics of brain tissues under impact or dynamic loading. In the current work, for the first time, biofidelic brain tissue surrogates have been developed using a low cost, castable (to any shape or size), two-part silicone-based material system to precisely mimic the nonlinear mechanical properties of both the white and the grey matter. The fabrication methodology involves the iterative mixing of the two parts of silicone at certain mix ratios (by weight) to generate a biomechanical behavior similar to the white and the grey matter tissues, respectively, at two different strain rates (low and high). The nonlinear behavior of these novel brain tissue surrogates have been characterized using five hyperelastic material models. These brain tissue simulant materials would be indispensable not only for the study of TBI, but also to allow doctors to practice brain surgeries (for training purposes) in a clinical setting. Additionally, crucial brain tissue modifications in Alzheimer's disease and dementia can be studied in the future with such accessible biofidelic brain tissue surrogate materials.

Wounds or cuts are the most common form of skin injuries. While a shallow wound may heal over time, deep wounds often require clinical interventions such as suturing to ensure the wound closure and timely healing. To date, suturing practices are based on a surgeon's experience and there is no benchmark to what is right or wrong. In the literature, there have been few attempts to characterize wound closure and suture mechanics using simple 2D computational models. In our current work, for the first time, a realistic three-dimensional (3D) computational model of the skin with the two layers, namely the epidermis and dermis, have been developed. A 3D diamond shaped wound with a varying cross-section has been modeled, and interrupted sutures have been placed numerically in multiple steps to close the wound. Nonlinear hyperelastic material properties have been adopted for the skin and a skin pre-stress was applied bi-axially. The force requirements for each suture were estimated numerically using a novel suture pulling technique. The suture forces were found to lie in the range of 0–5 N with a maximum value at the center. Also, the center suture was observed to require an approximately four times pull force compared to the first end suture. All these findings provide important guidelines for suturing. Additionally, the suture force can be approximated as a polynomial function of the displacement. Given a wound geometry, wound depth, skin material properties, skin pre-stress, suture wire material and cross-sectional area, using our computational model, such a relationship can be used to estimate and characterize the suture force requirements accurately. To our knowledge, such a 3D computational model of skin wound closure with interrupted sutures have not been developed till date, and would be indispensable for planning robotic surgeries and improving clinical suturing practices in the future.

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The variations in mechanical properties of cells obtained from experimental and theoretical studies can be overcome only through the development of a sound mathematical framework correlating the derived mechanical property with the cellular structure. Such a formulation accounting for the inhomogeneity of the cytoplasm due to stress fibers and actin cortex is developed in this work. The proposed model is developed using the Mori-Tanaka method of homogenization by treating the cell as a fiber-reinforced composite medium satisfying the continuum hypothesis. The validation of the constitutive model using finite element analysis on atomic force microscopy (AFM) and magnetic twisting cytometry (MTC) has been carried out and is found to yield good correlation with reported experimental results. It is observed from the study that as the volume fraction of the stress fiber increases, the stiffness of the cell increases and it alters the force displacement behavior for the AFM and MTC experiments. Through this model, we have also been able to find the stress fiber as a likely cause of the differences in the derived mechanical property from the AFM and MTC experiments. The correlation of the mechanical behavior of the cell with the cell composition, as obtained through this study, is an important observation in cell mechanics.

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Treatment of anterior vaginal prolapse (AVP), suffered by over 500,000 women in the USA, is a challenge in urogynecology because of the poorly understood mechanics of AVP. Recently, computational modeling combined with finite element method has been used to model AVP through the study of pelvic floor muscle and connective tissue impairments on the anterior vaginal wall (AVW). Also, the effects of pelvic organ displacements on the AVW were studied numerically. In our current work, an MRI-based full-scale biofidelic computational model of the female pelvic system composed of the urinary bladder, vaginal canal, and the uterus was developed, and a novel finite element method framework was employed to simulate vaginal tissue stiffening and also bladder filling due to expansion for the first time. A mesh convergence study was conducted to choose a computationally efficient mesh, and a non-linear hyperelastic Yeoh's material model was adopted for the study. The AVW displacements, mechanical stresses, and strains were estimated at varying degrees of bladder fills and vaginal tissue stiffening. Both bladder filling and vaginal stiffening were found to increase the stress concentration on the AVW with varying trends, which have been discussed in detail in the paper. To our knowledge, this study is the first to estimate the individual and combined effects of bladder filling and vaginal tissue stiffening due to prolapse on the AVW. Copyright © 2016 John Wiley & Sons, Ltd.

Suturing is an acquired skill which is based on a surgeon's experience. To date, no two sutures are the same with respect to the type of knot, tension, or suture material. With advancement in medical technologies, robotic suturing is becoming more and more important to operate on complex and difficult to reach internal surgical sites. While it is very difficult to translate a surgeon's suturing expertise to an automated environment, computational models could be employed to estimate baseline suture force requirements for a given wound shape, size, and suture material, which could be subsequently processed by a robot. In the literature, there have been few attempts to characterize wound closure and suture mechanics using simple two- and three-dimensional computational models. Single and multiple skin layers (epidermis, dermis, and hypodermis) and tissues with different wound geometries and sizes have been simulated under simple wound flap displacements to estimate suture force requirements. Also, recently, sutures were modeled to simulate a realistic wound closure via suture pulling, and skin prestress effect due to the natural tension of skin was incorporated in a few models to understand its effects on wound closure mechanics. An extensive review of this literature on computational modeling of wound suture would provide valuable insights into the areas in which further research work is required. Discussion of various computational challenges in modeling sutures in a numerical environment will help in better understanding the roadblocks and the required advancements in suture modeling.