Simulation of artificial anal sphincter motion and interaction with intestinal environment using SOFA.

BACKGROUND: Artificial anal sphincter is an implantable medical device for treating fecal incontinence. Reasonable simulation facilitates the advancement of research and reduces experiments on biological tissue. However, the device's clamping motion and sensor interaction with the intestine in the simulation still require further exploration. This article presents a simulation of the artificial anal sphincter's clamping and sensing and its interaction with the intestinal environment using the Simulation Open Framework Architecture (SOFA). METHODS: Firstly, the proposed simulation algorithm and its principles in SOFA are analyzed. Secondly, the clamping motion and sensor system of the artificial anal sphincter are simulated. Thirdly, a finite element model of intestine is established based on the properties of intestinal soft tissue. Finally, the in vitro experiments are performed. RESULTS: The simulation results indicate that the sensor system of the artificial anal sphincter has good sensing performance during the clamping motion and fecal accumulation process. Experiments have shown that optimal sensory capabilities can be achieved as the posture of the artificial anal sphincter with a roll angle between 20° and 40°. The comparison demonstrates a mean absolute error of 10%-20% between simulation and in vitro experimental results for sensor forces, which verifies the effectiveness of the simulation. CONCLUSION: The proposed novel simulation achieves a more comprehensive interaction between the artificial anal sphincter motion and intestinal environment. This study may provide more effective simulation data for guidance in improving the performance of sensor perception of artificial anal sphincter for further research.

Palpation simulator with stable haptic feedback.

BACKGROUND: The main difficulty in constructing palpation simulators is to compute and to generate stable and realistic haptic feedback without vibration. When a user haptically interacts with highly non-homogeneous soft tissues through a palpation simulator, a sudden change of stiffness in target tissues causes unstable interaction with the object. MATERIAL AND METHODS: We propose a model consisting of a virtual adjustable damper and an energy measuring element. The energy measuring element gauges energy which is stored in a palpation simulator and the virtual adjustable damper dissipates the energy to achieve stable haptic interaction. RESULTS: To investigate the haptic behavior of the proposed method, impulse and continuous inputs are provided to target tissues. If a haptic interface point meets with the hardest portion in the target tissues modeled with a conventional method, we observe unstable motion and feedback force. However, when the target tissues are modeled with the proposed method, a palpation simulator provides stable interaction without vibration. CONCLUSION: The proposed method overcomes a problem in conventional haptic palpation simulators where unstable force or vibration can be generated if there is a big discrepancy in material property between an element and its neighboring elements in target tissues.

Development of an Anisotropic Hyperelastic Material Model for Porcine Colorectal Tissues.

Many colonic surgeries include colorectal anastomoses whose leaks may be life-threatening, affecting thousands of patients annually. Various studies propose that mechanical interaction between the staples and neighboring tissues may play an important role in anastomotic leakage. Therefore, understanding the mechanical behavior of colorectal tissue is essential to characterizing the reasons for this type of failure. So far, experimental data characterizing the mechanical properties of colorectal tissue have been few and inconsistent, which has significantly limited understanding their behavior. This research proposes an approach to developing an anisotropic hyperelastic material model for colorectal tissues based on uniaxial testing of freshly harvested porcine specimens, which were collected from several age- and weight-matched pigs. The specimens were extracted from the same colon tract of each pig along their circumferential and longitudinal orientations. We propose a constitutive model combining Yeoh isotropic hyperelastic material with fibers oriented in two directions to account for the hyperelastic and anisotropic nature of colorectal tissues. Experimental data were used to accurately determine the model's coefficients (circumferential, R2 = 0.9968; longitudinal, R2 = 0.9675). The results show that the proposed model can be incorporated into a finite element model that can simulate procedures such as colorectal anastomoses reliably.

Personalized statistical modeling of soft tissue structures in the knee.

Background and Objective: As in vivo measurements of knee joint contact forces remain challenging, computational musculoskeletal modeling has been popularized as an encouraging solution for non-invasive estimation of joint mechanical loading. Computational musculoskeletal modeling typically relies on laborious manual segmentation as it requires reliable osseous and soft tissue geometry. To improve on feasibility and accuracy of patient-specific geometry predictions, a generic computational approach that can easily be scaled, morphed and fitted to patient-specific knee joint anatomy is presented. Methods: A personalized prediction algorithm was established to derive soft tissue geometry of the knee, originating solely from skeletal anatomy. Based on a MRI dataset (n = 53), manual identification of soft-tissue anatomy and landmarks served as input for our model by use of geometric morphometrics. Topographic distance maps were generated for cartilage thickness predictions. Meniscal modeling relied on wrapping a triangular geometry with varying height and width from the anterior to the posterior root. Elastic mesh wrapping was applied for ligamentous and patellar tendon path modeling. Leave-one-out validation experiments were conducted for accuracy assessment. Results: The Root Mean Square Error (RMSE) for the cartilage layers of the medial tibial plateau, the lateral tibial plateau, the femur and the patella equaled respectively 0.32 mm (range 0.14-0.48), 0.35 mm (range 0.16-0.53), 0.39 mm (range 0.15-0.80) and 0.75 mm (range 0.16-1.11). Similarly, the RMSE equaled respectively 1.16 mm (range 0.99-1.59), 0.91 mm (0.75-1.33), 2.93 mm (range 1.85-4.66) and 2.04 mm (1.88-3.29), calculated over the course of the anterior cruciate ligament, posterior cruciate ligament, the medial and the lateral meniscus. Conclusion: A methodological workflow is presented for patient-specific, morphological knee joint modeling that avoids laborious segmentation. By allowing to accurately predict personalized geometry this method has the potential for generating large (virtual) sample sizes applicable for biomechanical research and improving personalized, computer-assisted medicine.

Subcutaneous adipose tissue thickness around the ASIS area for human body models in reclined positions.

OBJECTIVE: Subcutaneous adipose tissue (SAT) thickness above the anterior superior iliac spine (ASIS) influences belt fit of a vehicle occupant. To improve finite element (FE) human body models and their application assessing future seating positions in cars, there is a need for more detailed data. METHODS: Anthropometric input data were used to statistically model a lower limit of the SAT thickness in the area around the ASIS (at the ASIS or in the groin) extracted from 102 postmortem computed tomography (pmCT) data sets (56 males and 46 females). Additionally, 2 pmCT scans of 1 male individual in both supine and sitting conditions were used to estimate change in SAT thickness by position. RESULTS: Distributions and locations of minimum values for SAT thickness were derived for males and females. Sex, age, and body mass index (BMI) remained in a linear regression model for the minimum SAT thickness in the ASIS area. Thirty-seven percent of the variance in the SAT distribution of the sample can be explained by these input variables. The individual with data in supine and sitting positions showed an SAT thickness value above the ASIS 6 times higher in the sitting position than in the supine position. CONCLUSIONS: Individual factors influence SAT thickness around the ASIS in addition to BMI, sex, and age. The presented values need to be regarded as a lower limit of SAT thickness, because in 63% the minimum was found in the groin area and the measurements were performed in a supine position. The increase in SAT thickness in a sitting position compared to supine seen in the case example shows the need for further data acquisition to establish a transfer function interpolating between both positions. The SAT thickness minimum values in the ASIS area shown in this study can provide valuable input for soft tissue modeling in human body models with the aim to analyze seat belt fit and to computationally assess lap belt and occupant interaction sensitivity to SAT tissue thickness under load. This might be crucial in reclined sitting positions in automated driving.

Analyzing Liver Surface Indentation for In Vivo Refinement of Tumor Location in Minimally Invasive Surgery.

Manual palpation to update the position of subsurface tumor(s) is a normal practice in open surgery, but is not possible through the small incisions of minimally invasive surgery (MIS). This paper proposes a method that has the potential to use a simple constant-force indenter and the existing laparoscopic camera for tumor location refinement in MIS. The indenter floats with organ movement to generate a static surface deformation on the soft tissue, resolving problems of previous studies that require complicated measurement of force and displacement during indentation. By analyzing the deformation profile, we can intraoperatively update the tumor's location in real-time. Indentation experiments were conducted on healthy and "diseased" porcine liver specimens to obtain the deformation surrounding the indenter site. An inverse finite element (FE) algorithm was developed to determine the optimal material parameters of the healthy liver tissue. With these parameters, a computational model of tumorous tissue was constructed to quantitatively evaluate the effects of the tumor location on the induced deformation. By relating the experimental data from the "diseased" liver specimen to the computational results, we estimated the radial distance between the tumor and the indenter, as well as the angular position of the tumor relative to the indenter.

A clinically validated prediction method for facial soft-tissue changes following double-jaw surgery.

PURPOSE: It is clinically important to accurately predict facial soft-tissue changes prior to orthognathic surgery. However, the current simulation methods are problematic, especially in anatomic regions of clinical significance, e.g., the nose, lips, and chin. We developed a new 3-stage finite element method (FEM) approach that incorporates realistic tissue sliding to improve such prediction. METHODS: In Stage One, soft-tissue change was simulated, using FEM with patient-specific mesh models generated from our previously developed eFace template. Postoperative bone movement was applied on the patient mesh model with standard FEM boundary conditions. In Stage Two, the simulation was improved by implementing sliding effects between gum tissue and teeth using a nodal force constraint scheme. In Stage Three, the result of the tissue sliding effect was further enhanced by reassigning the soft-tissue-bone mapping and boundary conditions using nodal spatial constraint. Finally, our methods have been quantitatively and qualitatively validated using 40 retrospectively evaluated patient cases by comparing it to the traditional FEM method and the FEM with sliding effect, using a nodal force constraint method. RESULTS: The results showed that our method was better than the other two methods. Using our method, the quantitative distance errors between predicted and actual patient surfaces for the entire face and any subregions thereof were below 1.5 mm. The overall soft-tissue change prediction was accurate to within 1.1 ± 0.3 mm, with the accuracy around the upper and lower lip regions of 1.2 ± 0.7 mm and 1.5 ± 0.7 mm, respectively. The results of qualitative evaluation completed by clinical experts showed an improvement of 46% in acceptance rate compared to the traditional FEM simulation. More than 80% of the result of our approach was considered acceptable in comparison with 55% and 50% following the other two methods. CONCLUSION: The FEM simulation method with improved sliding effect showed significant accuracy improvement in the whole face and the clinically significant regions (i.e., nose and lips) in comparison with the other published FEM methods, with or without sliding effect using a nodal force constraint. The qualitative validation also proved the clinical feasibility of the developed approach.

Surface deformation and reaction force estimation of liver tissue based on a novel nonlinear mass-spring-damper viscoelastic model.

Rheological soft tissue models play an important role in designing control methods for modern teleoperation systems. In the meanwhile, these models are also essential for creating a realistic virtual environment for surgical training. The implementation of model-based control in teleoperation has been a frequently discussed topic in the past decades, offering solutions for the loss of stability caused by time delay, which is one of the major issues in long-distance force control. In this paper, mass-spring-damper soft tissue models are investigated, showing that the widely used linear models do not represent realistic behavior under surgical manipulations. A novel, nonlinear model is proposed, where mechanical parameters are estimated using curve fitting methods. Theoretical reaction force curves are estimated using the proposed model, and the results are verified using measurement results from uniaxial indentation. The model is extended with force estimation by nonuniform surface deformation, where the surface deformation function is approximated according to visual data. Results show that using the proposed nonlinear model, a good estimation of reaction force can be achieved within the range of 0-4 mm, provided that the tissue deformation shape function is appropriately approximated.

Local deformation for soft tissue simulation.

This paper presents a new methodology to localize the deformation range to improve the computational efficiency for soft tissue simulation. This methodology identifies the local deformation range from the stress distribution in soft tissues due to an external force. A stress estimation method is used based on elastic theory to estimate the stress in soft tissues according to a depth from the contact surface. The proposed methodology can be used with both mass-spring and finite element modeling approaches for soft tissue deformation. Experimental results show that the proposed methodology can improve the computational efficiency while maintaining the modeling realism.

In Vivo Evaluation of Wearable Head Impact Sensors.

Inertial sensors are commonly used to measure human head motion. Some sensors have been tested with dummy or cadaver experiments with mixed results, and methods to evaluate sensors in vivo are lacking. Here we present an in vivo method using high speed video to test teeth-mounted (mouthguard), soft tissue-mounted (skin patch), and headgear-mounted (skull cap) sensors during 6-13 g sagittal soccer head impacts. Sensor coupling to the skull was quantified by displacement from an ear-canal reference. Mouthguard displacements were within video measurement error (<1 mm), while the skin patch and skull cap displaced up to 4 and 13 mm from the ear-canal reference, respectively. We used the mouthguard, which had the least displacement from skull, as the reference to assess 6-degree-of-freedom skin patch and skull cap measurements. Linear and rotational acceleration magnitudes were over-predicted by both the skin patch (with 120% NRMS error for a(mag), 290% for α(mag)) and the skull cap (320% NRMS error for a(mag), 500% for α(mag)). Such over-predictions were largely due to out-of-plane motion. To model sensor error, we found that in-plane skin patch linear acceleration in the anterior-posterior direction could be modeled by an underdamped viscoelastic system. In summary, the mouthguard showed tighter skull coupling than the other sensor mounting approaches. Furthermore, the in vivo methods presented are valuable for investigating skull acceleration sensor technologies.

Viscoelastic model based force control for soft tissue interaction and its application in physiological motion compensation.

Controlling the interaction between robots and living soft tissues has become an important issue as the number of robotic systems inside the operating room increases. Many researches have been done on force control to help surgeons during medical procedures, such as physiological motion compensation and tele-operation systems with haptic feedback. In order to increase the performance of such controllers, this work presents a novel force control scheme using Active Observer (AOB) based on a viscoelastic interaction model. The control scheme has shown to be stable through theoretical analysis and its performance was evaluated by in vitro experiments. In order to evaluate how the force control scheme behaves under the presence of physiological motion, experiments considering breathing and beating heart disturbances are presented. The proposed control scheme presented a stable behavior in both static and moving environment. The viscoelastic AOB presented a compensation ratio of 87% for the breathing motion and 79% for the beating heart motion.

Material characterization of liver parenchyma using specimen-specific finite element models.

The liver is one of the most frequently injured abdominal organs during motor vehicle crashes. Realistic car crash simulations require incorporating strain-rate dependent mechanical properties of soft tissue in finite element (FE) material models. This study presents a total of 30 tension tests performed on fresh bovine liver parenchyma at various loading rates in order to characterize the biomechanical and failure properties of liver parenchyma. Each specimen, cut in a standard dog-bone shape, was tested until failure at one of three loading rates (0.01 s(-1), 0.1s(-1), 1 s(-1)) using a tensile testing setup. Load and acceleration recorded from each specimen grip were employed to calculate the time history of force at specimen ends. The shapes of all specimens were reconstructed from laser scans recorded prior to each test and then used to develop specimen-specific FE models. A first-order Ogden material model and the time histories of specimen end displacement were assigned to each specimen FE model. The failure Green-Lagrangian strain showed averages around 50% and no significant dependence on loading rates, but the failure 2nd Piola-Kirchhoff stress showed rate-dependence with average values ranging from 33 kPa to 94 kPa. The FE models with material model parameters identified using a simulation-based optimization replicated well the time history of load recorded during the test. The FE simulations with model parameters identified using an analytical approach or based on the displacement of optical markers showed a significantly stiffer response and lower failure stress/strain than the FE specimen-specific models. This study provides novel biomechanical and failure data which can be easily implemented in FE models and used to assess injury risk in automobile collisions.

Estimating zero-strain states of very soft tissue under gravity loading using digital image correlation.

This paper presents several experimental techniques and concepts in the process of measuring mechanical properties of very soft tissue in an ex vivo tensile test. Gravitational body force on very soft tissue causes pre-compression and results in a non-uniform initial deformation. The global digital image correlation technique is used to measure the full-field deformation behavior of liver tissue in uniaxial tension testing. A maximum stretching band is observed in the incremental strain field when a region of tissue passes from compression and enters a state of tension. A new method for estimating the zero-strain state is proposed: the zero strain position is close to, but ahead of the position of the maximum stretching band, or in other words, the tangent of a nominal stress-stretch curve reaches minimum at lambda greater or similar 1. The approach, to identify zero strain by using maximum incremental strain, can be implemented in other types of image-based soft tissue analysis. The experimental results of 10 samples from seven porcine livers are presented and material parameters for the Ogden model fit are obtained. The finite element simulation based on the fitted model confirms the effect of gravity on the deformation of very soft tissue and validates our approach.