Is there any objective and independent characterization and modeling of soft biological tissues?

The characterization of soft tissue raises several difficulties. Indeed, soft biological tissues usually shrink when dissected from their in vivo location. This shrinkage is characteristic of the release of residual stresses, since soft tissues are indeed often pre-stressed in their physiological configuration. During experimental loading, large extension at very low level of force are expected and assumed to be related to the progressive recruitment and stretching of fibers. However, the first phase of the mechanical test is also aiming at recovering the pre-stressed in vivo behavior. As a consequence, the initial phase, corresponding to the recovering of prestress and/or recruitment of fiberes, is questionable and frequently removed. One of the preferred methods to erase it consists in applying a preforce or prestress to the sample: this allows to easily get rid of the sample retensioning range. However this operation can impact the interpretation of the identified mechanical parameters. This study presents an evaluation of the impact of the data processing on the mechanical properties of a numerically defined material. For this purpose, a finite element simulation was performed to replicate a uniaxial tensile test on a biological soft tissue sample. The influence of different pre-stretches on the mechanical parameters of a second order Yeoh model was investigated. The Yeoh mechanical parameters, or any other strain energy density, depend strongly on any pre- and post-processing choices: they adapt to compensate the error made when choosing an arbitrary level of prestretch or prestress. This observation spreads to any modeling approach used in soft tissues. Mechanical parameters are indeed naturally bound to the choice of the pre-stretch (or pre-stress) through the elongation and the constitutive law. Regardless of the model, it would therefore be pointless to compare mechanical parameters if the conditions for the processing of experimental raw data are not fully documented.

Evolution of the mechanical properties of a medical device regarding implantation time.

BACKGROUND: Our study aimed at understanding the influence of healing time on the mechanical properties of meshes used in pelvic organ prolapse, once implanted in an animal model using the rat. METHODS: A standard polypropylene mesh was implanted in 42 rats in order to evaluate the mechanical properties of the implanted mesh. Explantation occurred at 1, 2, 3, 4 and 5 months and mechanical tests were performed. Each sample was mechanically evaluated by a uniaxial tensile test with a machine (BIOTENS). Biological tissues presented a nonlinear relation between stress and strain so it could be modeled by the 2 parameters C0 and C1 of a second-order Mooney-Rivlin law. RESULTS: The rigidity in small deformation might not be affected by healing time or the presence of the synthetic implant. On the contrary, changes seemed to occur on the stiffness in large deformation (C1). The stiffness with the mesh composite changed with healing time. The "two-month implantation" rat group was significantly more rigid than the two control groups (pcontrol/2months = 0,04 and pplacebo/2months = 0,04). The 2- and 3-month healing groups were significantly more rigid than the 1-month healing group (p1/2months = 0,01 and p1/3months = 0,003). After 2 months, the mechanical properties seemed to stabilize (p2/3months = 0,44, p2/5months = 0,16 et p3/5months = 0,3). CONCLUSION: In order to evaluate the mechanical properties of an implanted mesh, the optimal time for explantation seems to be 2 months. Once this period is over, a more physiological mesh will be developed in order to be similar to native vaginal tissue once implanted and colonized by scar tissue.

Experimental study of the mechanical behavior of an explanted mesh: The influence of healing.

To better understand the in vivo mechanical behavior of synthetic mesh implants, we designed a specific experimental protocol for the mechanical characterization of explanted mesh under uniaxial tension. The implantation of a mesh leads to the development of scar tissue and the formation of a new composite made of native tissue, a mesh implant and scar tissues. This study focused on three points: determining the minimum representative size of mesh implants required for mechanical test samples, highlighting the influence of healing, and defining the healing time required to ensure stabilized mechanical properties. First, we determined the minimum representative size of mesh implants for the mechanical characterization with a study on a synthetic composite made of mesh and an elastomeric matrix mimicking the biological tissues. The size of the samples tested was gradually decreased. The downsizing process was stopped, when the mechanical properties of the composite were not preserved under uniaxial tension. It led to a sample representative size 3cm long and 2cm wide between the grips. Then an animal study was conducted on Wistar rats divided into eight groups. One group was set as control, consisting of the healthy abdominal wall. The other seven groups underwent surgery as follows: one placebo (i.e., without mesh placement), and six with a mesh installation on the abdominal wall and healing time. The rats were sacrificed after different healing times ranging from 1 to 5 months. We observed the influence of healing and healing time on the mechanical response under uniaxial tension of the new composite formed by scar, native tissue, and textile. It seems that 2 months are required to ensure the stabilization of the mechanical properties of the implanted mesh. We were not able to tell the control group (native abdominal wall) from the placebo group (native and scar tissue). This protocol was tested on two different prostheses after 3 months of healing. With this protocol, we were able to differentiate one mesh from another after host integration.

Biomechanical pregnant pelvic system model and numerical simulation of childbirth: impact of delivery on the uterosacral ligaments, preliminary results.

INTRODUCTION AND HYPOTHESIS: We created a pregnant woman pelvic model to perform a simulation of delivery to understand the pathophysiology of urogenital prolapse by studying the constraints on the pelvic components (muscles, ligaments, pelvic organs) during childbirth. These simulations will also provide valuable tools to understand and teach obstetrical mechanics. METHODS: We built a numerical model of the pelvic system from a term pregnant woman, using the finite element method on a mesh built from magnetic resonance images of a nulliparous pregnant woman. Mechanical properties of pelvic tissues already determined by the team were adapted to account for pregnancy. RESULTS: The system allows delivery to be simulated. When a fetal head at the 50th percentile for the term goes through the pelvic system, uterosacral ligaments undergo a deformation of around 30 %. Uterosacral ligaments are the major pelvic sustaining structures, their lesion may be a potential cause of urogenital prolapse. We built a model of childbirth as a function of pregnancy term by varying volumes of fetal head and uterus. The impact on uterosacral ligaments is higher when the fetal head is larger. CONCLUSIONS: Our modelling is rather complete considering that it involves many organs including ligaments. It allows us to analyse the effect of childbirth on uterosacral ligaments and to understand how they impact on pelvic statics. First results are promising, but optimisation and future simulations will be needed. We also plan to simulate various delivery scenarios (cephalic, breech presentation, instrumental extraction), which will be useful to study perineal lesions and also to teach obstetrical mechanics.

3D simulation of pelvic system numerical simulation for a better understanding of the contribution of the uterine ligaments.

INTRODUCTION AND HYPOTHESIS: Genital prolapse remains a complex pathological condition. Physiopathology remains poorly understood, aetiology is multi-factorial, surgery is not always satisfying, as the rate of relapse cannot be overlooked. More over a good anatomical result will not always guarantee functional satisfaction. The aim of our study is to have a better understanding of the involvement of uterine ligaments in pelvic statics via 3D simulation. METHODS: Simulation of pelvic mobility is performed with a validated numerical model in a normal situation (standing up to lying down) or induced pathological ones where parts of the constitutive elements of the model are virtually "cut" independently. Displacements are then discussed. RESULTS: Numerical results have been compared with dynamic MRI for two volunteers. Dynamic sequences had 90 images, and 180 simulations have been validated. Results are coherent with clinical data and the literature, thus validating our mechanical approach. Uterine ligaments are involved in pelvic statics, but their lesions are not sufficient to generate a genital prolapse. Round ligaments play a part in uterine orientation; the utero-sacral ligaments support the uterus when standing up. CONCLUSIONS: Pelvic normal and pathological mobility study via modelling and 3D simulation is a new strategy in understanding the complex multifactorial physiopathology of genital prolapse. This approach must be validated in a larger series of patients. Nevertheless, pelvic ligaments seem to play an important role in statics, especially, in agreement with a literature survey, utero-sacral ligaments in a standing position.