Soft tissue modelling for applications in virtual surgery and surgical robotics

3D Ultrasound Shear Wave Elastography for Musculoskeletal Tissue Assessment Under Compressive Load: A Feasibility Study

Given its real-time capability to quantify mechanical tissue properties, ultrasound shear wave elastography holds significant promise in clinical musculoskeletal imaging. However, existing shear wave elastography methods fall short in enabling full-limb analysis of 3D anatomical structures under diverse loading conditions, and may introduce measurement bias due to sonographer-applied force on the transducer. These limitations pose numerous challenges, particularly for 3D computational biomechanical tissue modeling in areas like prosthetic socket design. In this feasibility study, a clinical linear ultrasound transducer system with integrated shear wave elastography capabilities was utilized to scan both a calibrated phantom and human limbs in a water tank imaging setup. By conducting 2D and 3D scans under varying compressive loads, this study demonstrates the feasibility of volumetric ultrasound shear wave elastography of human limbs. Our preliminary results showcase a potential method for evaluating 3D spatially varying tissue properties, offering future extensions to computational biomechanical modeling of tissue for various clinical scenarios.

Validating the measurement of passive Musculo-articular wrist stiffness without intentional or reactive contraction using axillary plexus block

BACKGROUND

Passive stiffness describes how easily a joint may move passively. To accurately measure wrist stiffness, an electro-oscillation device was developed. The objectives were to 1) ensuring that the measurement are free from intentional or reflex contraction, 2) analyzing how forearm anatomy affects the passive stiffness of the wrist and 3) determining the clinical practical relevance of the device.

METHODS

In this prospective study, the device generated low amplitude sinusoidal motions in flexion and extension on the wrist to quantify elastic and viscous passive stiffness in voluntary orthopaedic patients. The first series of measurements was carried out in the state of voluntary relaxation, the second series of measurements was carried out after an axillary plexus anesthetic block. A matched group of healthy subjects were use for control.

FINDINGS

The Electromechanical Oscillation methods effectively enable the measurement of passive joint stiffness since the stiffness values obtained show no statistically significant difference pre-post the anesthesia. The stiffness values are comparable to those of healthy subjects. The effect of forearm passive structure, estimated by the perimeter of the forearm, influences the passive stiffness of the wrist, mainly the viscous component.

INTERPRETATION

The use of sinusoidal oscillation was well accepted by the participants, demonstrating its usefulness and applicability in a clinical setting. This work serves as a foundation for future investigations of orthopaedic and/or neurological pathological conditions characterized by abnormal passive joint stiffness of the wrist. It paves the way for its use as a diagnostic, prognostic, and monitoring tool in these pathologies.

Maximum likelihood-based extended Kalman filter for soft tissue modelling

Realistic modelling of human soft tissue is very important in medical applications. This paper proposes a novel method by dynamically incorporating soft tissue characterisation in the process of soft tissue modelling to increase the modelling fidelity. This method defines nonlinear tissue deformation with unknown mechanical properties as a problem of nonlinear filtering identification to dynamically identify mechanical properties and further estimate nonlinear deformation behaviour of soft tissue. It combines maximum likelihood theory, nonlinear filtering and nonlinear finite element method (NFEM) for modelling of nonlinear tissue deformation behaviour based on dynamic identification of homogeneous tissue properties. On the basis of hyperelasticity, a nonlinear state-space equation is established by discretizing tissue deformation through NFEM for dynamic filtering. A maximum likelihood algorithm is also established to dynamically identify tissue mechanical properties during the deformation process. Upon above, a maximum likelihood-based extended Kalman filter is further developed for dynamically estimating tissue nonlinear deformation based on dynamic identification of tissue mechanical properties. Simulation and experimental analyses reveal that the proposed method not only overcomes the NFEM limitation of expensive computations, but also absorbs the NFEM merit of high accuracy for modelling of homogeneous tissue deformation. Further, the proposed method also effectively identifies tissue mechanical properties during the deformation modelling process.

A Physics-Guided Neural Operator Learning Approach to Model Biological Tissues From Digital Image Correlation Measurements

We present a data-driven workflow to biological tissue modeling, which aims to predict the displacement field based on digital image correlation (DIC) measurements under unseen loading scenarios, without postulating a specific constitutive model form nor possessing knowledge of the material microstructure. To this end, a material database is constructed from the DIC displacement tracking measurements of multiple biaxial stretching protocols on a porcine tricuspid valve anterior leaflet, with which we build a neural operator learning model. The material response is modeled as a solution operator from the loading to the resultant displacement field, with the material microstructure properties learned implicitly from the data and naturally embedded in the network parameters. Using various combinations of loading protocols, we compare the predictivity of this framework with finite element analysis based on three conventional constitutive models. From in-distribution tests, the predictivity of our approach presents good generalizability to different loading conditions and outperforms the conventional constitutive modeling at approximately one order of magnitude. When tested on out-of-distribution loading ratios, the neural operator learning approach becomes less effective. To improve the generalizability of our framework, we propose a physics-guided neural operator learning model via imposing partial physics knowledge. This method is shown to improve the model's extrapolative performance in the small-deformation regime. Our results demonstrate that with sufficient data coverage and/or guidance from partial physics constraints, the data-driven approach can be a more effective method for modeling biological materials than the traditional constitutive modeling.

Bayesian inference on a microstructural, hyperelastic model of tendon deformation

Microstructural models of soft-tissue deformation are important in applications including artificial tissue design and surgical planning. The basis of these models, and their advantage over their phenomenological counterparts, is that they incorporate parameters that are directly linked to the tissue's microscale structure and constitutive behaviour and can therefore be used to predict the effects of structural changes to the tissue. Although studies have attempted to determine such parameters using diverse, state-of-the-art, experimental techniques, values ranging over several orders of magnitude have been reported, leading to uncertainty in the true parameter values and creating a need for models that can handle such uncertainty. We derive a new microstructural, hyperelastic model for transversely isotropic soft tissues and use it to model the mechanical behaviour of tendons. To account for parameter uncertainty, we employ a Bayesian approach and apply an adaptive Markov chain Monte Carlo algorithm to determine posterior probability distributions for the model parameters. The obtained posterior distributions are consistent with parameter measurements previously reported and enable us to quantify the uncertainty in their values for each tendon sample that was modelled. This approach could serve as a prototype for quantifying parameter uncertainty in other soft tissues.

Personalised statistical modelling of soft tissue structures in the ankle

BACKGROUND AND OBJECTIVE

Revealing the complexity behind subject-specific ankle joint mechanics requires simultaneous analysis of three-dimensional bony and soft-tissue structures. 3D musculoskeletal models have become pivotal in orthopedic treatment planning and biomechanical research. Since manual segmentation of these models is time-consuming and subject to manual errors, (semi-) automatic methods could improve the accuracy and enlarge the sample size of personalised 'in silico' biomechanical experiments and computer-assisted treatment planning. Therefore, our aim was to automatically predict ligament paths, cartilage topography and thickness in the ankle joint based on statistical shape modelling.

METHODS

A personalised cartilage and ligamentous prediction algorithm was established using geometric morphometrics, based on an 'in-house' generated lower limb skeletal model (N = 542), tibiotalar cartilage (N = 60) and ankle ligament segmentations (N = 10). For cartilage, a population-averaged thickness map was determined by use of partial least-squares regression. Ligaments were wrapped around bony contours based on iterative shortest path calculation. Accuracy of ligament path and cartilage thickness prediction was quantified using leave-one-out experiments. The novel personalised thickness prediction was compared with a constant cartilage thickness of 1.50 mm by use of a paired sample T-test.

RESULTS

Mean distance error of cartilage and ligament prediction was 0.12 mm (SD 0.04 mm) and 0.54 mm (SD 0.05 mm), respectively. No significant differences were found between the personalised thickness cartilage and segmented cartilage of the tibia (p = 0.73, CI [-1.60 .10^-17, 1.13 .10^-17]) and talus (p = 0.95, CI[ -1.35 .10^-17, 1.28 .10^-17]). For the constant thickness cartilage, a statistically significant difference was found in 89% and 92% of the tibial (p < 0.001, CI [0.51, 0.58]) and talar (p < 0.001, CI [0.33, 0.40]) cartilage area.

CONCLUSIONS

In this study, we described a personalised prediction algorithm of cartilage and ligaments in the ankle joint. We were able to predict cartilage and main ankle ligaments with submillimeter accuracy. The proposed method has a high potential for generating large (virtual) sample sizes in biomechanical research and mitigates technological advances in computer-assisted orthopaedic surgery.

Modeling biomechanical interaction between soft tissue and soft robotic instruments: importance of constitutive anisotropic hyperelastic formulations

Cardiovascular diseases are the leading cause of death in the western countries. Robotic surgery recently emerged as a confirmed strategy in the cardiovascular field, especially thanks to the improvement of soft robotics. These techniques have demonstrated their potential in terms of speed of execution and precision. In this context, a deeper knowledge of the material properties of the blood vessels is required, especially for computational soft robotics applications. A constitutive model including the contribution of the collagen fibers families is needed to take hyperelasticity and anisotropy into account. For this purpose, four different models are presented: two fiber families with dispersion (2FFD), two fiber families without dispersion (2FF), four fiber families with dispersion (4FFD), and four fiber families without dispersion (4FF). A set of experimental biaxial data obtained from ex-vivo specimens was used to assess the model performances. Two fitting procedures were imposed: a procedure with no weighting of scores and a procedure with a weight set to enhance the model performances in the contact range. A finite element simulation of a contact procedure was developed to evaluate the effect on the contact pressures and forces according to the different model implementations. In particular, a minimally invasive aortic valve positioning process through a previously designed soft robot was simulated. The results confirmed the overall fitting procedure. The adoption of the weighting process for the fitting was successful, as it permitted an accurate prediction in the region of interest through models with less parameters.

Effect of Age and Body Size on the Wrist's Viscoelasticity in Healthy Participants From 3 to 90 Years Old and Reliability Assessment

Excessive or insufficient levels of passive musculoarticular stiffness (PMAS) can lead to joint impairment or instability. Quantifying the PMAS may provide a better understanding of neurological or musculoskeletal disorders. The aims of the present study were multiple: first, to assess the reliability of quantifying PMAS and to collect normative data on the wrist in healthy participants, and second, to assess the effect of age and body size on PMAS. For this purpose, a total of 458 participants from 3 to 90 years old were analyzed with an electromechanical oscillation device (EOD). Passive sinusoidal movements were induced in a flexion/extension pattern in the participants' wrists, enabling an objective measurement of elastic stiffness (EL) and viscous stiffness (VI). Both the dominant and non-dominant wrists were assessed. Two-way repeated-measures ANOVA revealed a sex differentiation from puberty (12-18 years old) and an increase of EL and VI from childhood to adulthood and a decrease of stiffness at old age. EL and VI values were associated with body size characteristics and age. After body size normalization, EL was no longer influenced by the variables measured. On the other hand, VI remained moderately influenced by age and body size. The current study was able to provide normative data of PMAS in the wrist of healthy participants.

Systematic Review of Virtual Haptics in Surgical Simulation: A Valid Educational Tool?

BACKGROUND

Virtual reality (VR)-based surgical simulation is an expanding and rapidly advancing modality which aims to serve the increasing demand to acquire surgical skills outside the live operating room. Haptic, or "force-feedback" technology in VR simulation is a rapidly developing field, however the role of haptics in surgical education and its efficacy is unclear.

METHODS

A systematic literature search was carried out until September 2018 in MEDLINE, Embase, and Cochrane Library using the following keywords: (VR OR VR OR simulation OR simulator) AND (Haptic feedback OR Haptics OR Force feedback) AND (Surgery). All randomized controlled studies comparing VR training with and without haptics were included. PRISMA guidelines were adhered to RESULTS: Eight randomized controlled trials that compare VR training with and without haptics were included and 1 survey study with a total of 215 participants, 116 of which received haptic feedback and 99 were assigned to nonhaptic feedback group. Training tasks included basic proficiency based laparoscopic tasks such as object translocation, cutting, camera navigation, and more complex tasks including diathermy, suturing, dissection, knot tying, and operative maneuvers. Six randomized controlled trials demonstrated that haptic enhanced VR simulation is significantly more effective than without haptics for skill training with a reduced learning curve and faster time to proficiency and task completion, particularly in novice learners. Two studies showed no significant differences in task-assessed parameters between the haptics and nonhaptics cohorts, whereas 1 survey study suggested haptics negatively affected training with decreased realism.

CONCLUSION

Haptic feedback has been shown to improve the fidelity, realism and thus the training effect of VR simulators. However, at present haptic simulators are expensive and in a nascent stage and further research as well as cost-benefit analyses of such tools must be considered to determine whether haptics is truly a surgical necessity.

Real-time inextensible surgical thread simulation

Purpose

This paper discusses a real-time simulation method of inextensible surgical thread based on the Cosserat rod theory using position-based dynamics (PBD). The method realizes stable twining and knotting of surgical thread while including inextensibility, bending, twisting and coupling effects.

Methods

The Cosserat rod theory is used to model the nonlinear elastic behavior of surgical thread. The surgical thread model is solved with PBD to achieve a real-time, extremely stable simulation. Due to the one-dimensional linear structure of surgical thread, the direct solution of the distance constraint based on tridiagonal matrix algorithm is used to enhance stretching resistance in every constraint projection iteration. In addition, continuous collision detection and collision response guarantee a large time step and high performance. Furthermore, friction is integrated into the constraint projection process to stabilize the twining of multiple threads and complex contact situations.

Results

Through comparisons with existing methods, the surgical thread maintains constant length under large deformation after applying the direct distance constraint in our method. The twining and knotting of multiple threads correspond to stable solutions to contact and friction forces. A surgical suture scene is also modeled to demonstrate the practicality and simplicity of our method.

Conclusions

Our method achieves stable and fast simulation of inextensible surgical thread. Benefiting from the unified particle framework, the rigid body, elastic rod, and soft body can be simultaneously simulated. The method is appropriate for applications in virtual surgery that require multiple dynamic bodies.

Simple empirical model for identifying rheological properties of soft biological tissues

Understanding the rheological properties of soft biological tissue is a key issue for mechanical systems used in the health care field. We propose a simple empirical model using fractional dynamics and exponential nonlinearity (FDEN) to identify the rheological properties of soft biological tissue. The model is derived from detailed material measurements using samples isolated from porcine liver. We conducted dynamic viscoelastic and creep tests on liver samples using a plate-plate rheometer. The experimental results indicated that biological tissue has specific properties: (i) power law increase in the storage elastic modulus and the loss elastic modulus of the same slope; (ii) power law compliance (gain) decrease and constant phase delay in the frequency domain; (iii) power law dependence between time and strain relationships in the time domain; and (iv) linear dependence in the low strain range and exponential law dependence in the high strain range between stress-strain relationships. Our simple FDEN model uses only three dependent parameters and represents the specific properties of soft biological tissue.

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.

Patient specific modeling of palpation-based prostate cancer diagnosis: effects of pelvic cavity anatomy and intrabladder pressure

Computational modeling has become a successful tool for scientific advances including understanding the behavior of biological and biomedical systems as well as improving clinical practice. In most cases, only general models are used without taking into account patient-specific features. However, patient specificity has proven to be crucial in guiding clinical practice because of disastrous consequences that can arise should the model be inaccurate. This paper proposes a framework for the computational modeling applied to the example of the male pelvic cavity for the purpose of prostate cancer diagnostics using palpation. The effects of patient specific structural features on palpation response are studied in three selected patients with very different pathophysiological conditions whose pelvic cavities are reconstructed from MRI scans. In particular, the role of intrabladder pressure in the outcome of digital rectal examination is investigated with the objective of providing guidelines to practitioners to enhance the effectiveness of diagnosis. Furthermore, the presence of the pelvic bone in the model is assessed to determine the pathophysiological conditions in which it has to be modeled. The conclusions and suggestions of this work have potential use not only in clinical practice and also for biomechanical modeling where structural patient-specificity needs to be considered. © 2015 The Authors. International Journal for Numerical Methods in Biomedical Engineering published by John Wiley & Sons Ltd.

The Incompatibility of Living Systems: Characterizing Growth-Induced Incompatibilities in Expanded Skin

Skin expansion is a common surgical technique to correct large cutaneous defects. Selecting a successful expansion protocol is solely based on the experience and personal preference of the operating surgeon. Skin expansion could be improved by predictive computational simulations. Towards this goal, we model skin expansion using the continuum framework of finite growth. This approach crucially relies on the concept of incompatible configurations. However, aside from the classical opening angle experiment, our current understanding of growth-induced incompatibilities remains rather vague. Here we visualize and characterize incompatibilities in living systems using skin expansion in a porcine model: We implanted and inflated two expanders, crescent, and spherical, and filled them to 225 cc throughout a period of 21 days. To quantify the residual strains developed during this period, we excised the expanded skin patches and subdivided them into smaller pieces. Skin growth averaged 1.17 times the original area for the spherical and 1.10 for the crescent expander, and displayed significant regional variations. When subdivided into smaller pieces, the grown skin patches retracted heterogeneously and confirmed the existence of incompatibilities. Understanding skin growth through mechanical stretch will allow surgeons to improve-and ultimately personalize-preoperative treatment planning in plastic and reconstructive surgery.

Design and finite element analysis of a novel smart clamper for aortic cross-clamping in minimally invasive surgery

Aortic cross-clamping is a critical action during heart surgeries which may cause some injuries to the wall of the artery. These injuries may have both short-term and long-term adverse effects on the artery function. Appropriate clampers can properly occlude the artery and decrease the extent of injury. Thus, developing a model for evaluation of such clampers is inevitable. In this paper, a finite element model of the aorta is presented; then, different mechanisms of clamping are investigated. In this regard, a numerical model of aortic cross-clamping by three types of clampers has been implemented with consideration of nonlinear behavior of two-layer artery, residual stress in aorta, and calcification. These three clamper models are commercial Chitwood clamper and linear mechanism clamper with and without balloon. Using the obtained results, comparative analysis was performed between the proposed clamper design and the commercial one. Based upon the analysis, it was concluded that the designed clamper, linear mechanism clamper with balloon, helps to distribute the stress uniformly in different layers of the aorta, which results in better performance of the clamping procedure and causes less injury in the aorta, especially when there is calcification.

Using preoperative imaging for intraoperative guidance: a case of mistaken identity

BACKGROUND

Surgical image guidance systems to date have tended to rely on reconstructions of preoperative datasets. This paper assesses the accuracy of these reconstructions to establish whether they are appropriate for use in image guidance platforms.

METHODS

Nine raters (two experts in image interpretation and preparation, three in image interpretation, and four in neither interpretation nor preparation) were asked to perform a segmentation of ten renal tumours (four cystic and six solid tumours). These segmentations were compared with a gold standard consensus segmentation generated using a previously validated algorithm.

RESULTS

Average sensitivity and positive predictive value (PPV) were 0.902 and 0.891, respectively. When assessing for variability between raters, significant differences were seen in the PPV, sensitivity and incursions and excursions from consensus tumour boundary.

CONCLUSIONS

This paper has demonstrated that the interpretation required for the segmentation of preoperative imaging of renal tumours introduces significant inconsistency and inaccuracy. Copyright © 2015 John Wiley & Sons, Ltd.

Structural and mechanical characterisation of bridging veins: A review

Bridging veins drain the venous blood from the cerebral cortex into the superior sagittal sinus (SSS) and doing so they bridge the subdural space. Despite their importance in head impact biomechanics, little is known about their properties with respect to histology, morphology and mechanical behaviour. Knowledge of these characteristics is essential for creating a biofidelic finite element model to study the biomechanics of head impact, ultimately leading to the improved design of protective devices by setting up tolerance criteria. This paper presents a comprehensive review of the state-of-the-art knowledge on bridging veins. Tolerance criteria to prevent head injury through impact have been set by a number of research groups, either directly through impact experiments or by means of finite element (FE) simulations. Current state-of-the-art FE head models still lack a biofidelic representation of the bridging veins. To achieve this, a thorough insight into their nature and behaviour is required. Therefore, an overview of the general morphology and histology is provided here, showing the clearly heterogeneous nature of the bridging vein complex, with its three different layers and distinct morphological and histological changes at the region of outflow into the superior sagittal sinus. Apart from a complex morphology, bridging veins also exhibit complex mechanical behaviour, being nonlinear, viscoelastic and prone to damage. Existing material models capable of capturing these properties, as well as methods for experimental characterisation, are discussed. Future work required in bridging vein research is firstly to achieve consensus on aspects regarding morphology and histology, especially in the outflow cuff segment. Secondly, the advised material models need to be populated with realistic parameters through biaxial mechanical experiments adapted to the dimensions of the bridging vein samples. Finally, updating the existing finite element head models with these parameters will render them truly biofidelic, allowing the establishment of accurate tolerance criteria and, ultimately, better head protection devices.

A structural approach including the behavior of collagen cross-links to model patient-specific human carotid arteries

In this work the mechanical response of the carotid arterial wall is studied. Some limitations of previous models of the arterial wall are overcomed and variability of the fitting problem is reduced. We review some experimental data from the literature and provide a constitutive model to characterize such data. A strain energy function is introduced including the behavior of cross-links between the main collagen fibers. With this function we are able to fit experimental data including information about the microstructure that previous models were not able to do. To demonstrate the applicability of the proposed model a patient-specific carotid artery geometry is reconstructed and simulated in a finite element framework, providing a microstructural description of the arterial wall. Our results qualitatively and quantitatively describe the experimental findings given in the literature fitting macroscopic mechanical tests and improving the features of previously developed models.

ImaGiNe Seldinger: first simulator for Seldinger technique and angiography training

In vascular interventional radiology, procedures generally start with the Seldinger technique to access the vasculature, using a needle through which a guidewire is inserted, followed by navigation of catheters within the vessels. Visual and tactile skills are learnt in a patient apprenticeship which is expensive and risky for patients. We propose a training alternative through a new virtual simulator supporting the Seldinger technique: ImaGiNe (imaging guided interventional needle) Seldinger. It is composed of two workstations: (1) a simulated pulse is palpated, in an immersive environment, to guide needle puncture and (2) two haptic devices provide a novel interface where a needle can direct a guidewire and catheter within the vessel lumen, using virtual fluoroscopy. Different complexities are provided by 28 real patient datasets. The feel of the simulation is enhanced by replicating, with the haptics, real force and flexibility measurements. A preliminary validation study has demonstrated training effectiveness for skills transfer.

HAPTIC MODELING OF STOMACH FOR REAL-TIME PROPERTY AND FORCE ESTIMATION

Robotic devices are being employed in gastrointestinal endoscopy procedures for diagnostics and surgery. However, force measurement, a very important factor for control and haptic feedback, becomes very challenging due to the strict size limitation of such devices and the flexible nature of the endoscope. This paper focuses on the modeling of the interior stomach wall for tool–tissue interactions from two perspectives: (1) If the interaction force between the robotic tool and the tissue can be measured, we utilize the force information to estimate the mechanical property of the stomach wall in real-time; given the force and position information, we would derive mathematically the only system model that can guarantee identifiability under arbitrary manipulation; (2) in the worst case scenario where force measurement is not available, we propose a viscoelastic model to restore force information solely based on position and motion information available from the robot. Ex-vivo experiments were performed on porcine stomach specimens to demonstrate the performance of the proposed models. Based on these findings, generalization and implementations of the modeling in real-time applications were discussed.

External aortic root support: a histological and mechanical study in sheep

OBJECTIVES

Personalized external aortic root support has completed initial evaluation and has technology appraisal in the UK for patients with Marfan syndrome for use as an alternative to root replacement. Its long-term success in preventing aortic dissection remains uncertain. Here, we report a study in sheep to establish whether the externally supporting mesh, as used clinically, is biologically incorporated. The strength of the resulting mesh/artery composite has been tested.

METHODS

The carotid artery of growing sheep (n=6) was enclosed in a mesh sleeve made of a polymer, polyethylene terephthalate. After a predefined interval of 4-6 months, a length of the artery was excised, including the sleeved and unsleeved portions, and was stress tested and examined histologically.

RESULTS

One animal died of pneumonia 7 days after implantation. Comparing sleeved with normal segments, the overall thickness was increased and there was a fibrotic sheet in the periarterial space. The overall vessel wall architecture was preserved in all specimens. Although media thickness of ensleeved arteries was smaller and in one animal mild oedema was found in one quadrant of the outer part of the media. There was a significant increase in stiffness and maximum tensile strength of the supported segments compared with normal arterial tissue.

CONCLUSIONS

Polyethylene terephthalate mesh, as used for the external support of the dilated aortic root in Marfan syndrome, becomes incorporated in the periadventitial tissue of the carotid artery of sheep. Limited thinning of the media, without any signs of inflammation or medial necrosis, was visible. There was a significantly greater tensile strength in the carotid artery/mesh composite compared with the unsleeved carotid artery.

Mathematical modeling of collagen turnover in biological tissue

We present a theoretical and computational model for collagen turnover in soft biological tissues. Driven by alterations in the mechanical environment, collagen fiber bundles may undergo important chronic changes, characterized primarily by alterations in collagen synthesis and degradation rates. In particular, hypertension triggers an increase in tropocollagen synthesis and a decrease in collagen degradation, which lead to the well-documented overall increase in collagen content. These changes are the result of a cascade of events, initiated mainly by the endothelial and smooth muscle cells. Here, we represent these events collectively in terms of two internal variables, the concentration of growth factor TGF-β and tissue inhibitors of metalloproteinases TIMP. The upregulation of TGF-β increases the collagen density. The upregulation of TIMP also increases the collagen density through decreasing matrix metalloproteinase MMP. We establish a mathematical theory for mechanically-induced collagen turnover and introduce a computational algorithm for its robust and efficient solution. We demonstrate that our model can accurately predict the experimentally observed collagen increase in response to hypertension reported in literature. Ultimately, the model can serve as a valuable tool to predict the chronic adaptation of collagen content to restore the homeostatic equilibrium state in vessels with arbitrary micro-structure and geometry.

A novel MRI compatible soft tissue indentor and fibre Bragg grating force sensor

MRI is an ideal method for non-invasive soft tissue mechanical properties investigation. This requires mechanical excitation of the body's tissues and measurement of the corresponding boundary conditions such as soft tissue deformation inside the MRI environment. However, this is technically difficult since load application and measurement of boundary conditions requires MRI compatible actuators and sensors. This paper describes a novel MRI compatible computer controlled soft tissue indentor and optical Fibre Bragg Grating (FBG) force sensor. The high acquisition rate (100Hz) force sensor was calibrated for forces up to 15N and demonstrated a maximum error of 0.043N. Performance and MRI compatibility of the devices was verified using indentation tests on a silicone gel phantom and the upper arm of a volunteer. The computer controlled indentor provided a highly repeatable tissue deformation. Since the indentor and force sensor are composed of non-ferromagnetic materials, they are MRI compatible and no artefacts or temporal SNR reductions were observed. In a phantom study the mean and standard deviation of the temporal SNR levels without the indentor present were 500.18 and 207.08, respectively. With the indentor present the mean and standard deviation were 501.95 and 200.45, respectively. This computer controlled MRI compatible soft tissue indentation system with an integrated force sensor has a broad range of applications and will be used in the future for the non-invasive analysis of the mechanical properties of skeletal muscle tissue.

Accounting for large deformations in real-time simulations of soft tissues based on reduced-order models

Model reduction techniques have shown to constitute a valuable tool for real-time simulation in surgical environments and other fields. However, some limitations, imposed by real-time constraints, have not yet been overcome. One of such limitations is the severe limitation in time (established in 500Hz of frequency for the resolution) that precludes the employ of Newton-like schemes for solving non-linear models as the ones usually employed for modeling biological tissues. In this work we present a technique able to deal with geometrically non-linear models, based on the employ of model reduction techniques, together with an efficient non-linear solver. Examples of the performance of the technique over some examples will be given.

Adaptive surrogate modeling for expedited estimation of nonlinear tissue properties through inverse finite element analysis

Simulation-based prediction of specimen-specific biomechanical behavior commonly requires inverse analysis using geometrically consistent finite element (FE) models. Optimization drives such analyses but previous studies have highlighted a large computational cost dictated by iterative use of nonlinear FE models. The goal of this study was to evaluate the performance of a local regression-based adaptive surrogate modeling approach to decrease computational cost for both global and local optimization approaches using an inverse FE application. Nonlinear elastic material parameters for patient-specific heel-pad tissue were found, both with and without the surrogate model. Surrogate prediction replaced a FE simulation using local regression of previous simulations when the corresponding error estimate was less than a given tolerance. Performance depended on optimization type and tolerance value. The surrogate reduced local optimization expense up to 68%, but achieved accurate results for only 1 of 20 initial conditions. Conversely, up to a tolerance value of 20 N(2), global optimization with the surrogate yielded consistent parameter predictions with a concurrent decrease in computational cost (up to 77%). However, the local optimization method without the surrogate, although sensitive to the initial conditions, was still on average seven times faster than the global approach. Our results help establish guidelines for setting acceptable tolerance values while using an adaptive surrogate model for inverse FE analysis. Most important, the study demonstrates the benefits of a surrogate modeling approach for intensive FE-based iterative analysis.

Haptic Simulator for Prostate Brachytherapy with Simulated Needle and Probe Interaction

This paper presents a haptic simulator for prostate brachytherapy. Both needle insertion and the manipulation of the transrectal ultrasound (TRUS) probe are controlled via haptic devices. Tissue interaction forces that are computed by a deformable tissue model based on the finite element method (FEM) are rendered to the user by these devices. The needle insertion simulation employs 3D models of needle flexibility and asymmetric tip bevel. The needle-tissue simulation allows a trainee to practice needle insertion and targeting. The TRUS-tissue interaction simulation allows a trainee to practice the 3D intraoperative TRUS placement for registration with the preoperative volume study and to practice TRUS axial translation and rotation for imaging needles during insertions. Approaches to computational acceleration for realtime haptic performance are presented. Trade-offs between accuracy and speed are discussed. A graphics-card implementation of the numerically intensive mesh-adaptation operation is also presented. The simulator can be used for training, rehearsal, and treatment planning.

Modelling of non-linear elastic tissues for surgical simulation

Realistic modelling of the interaction between surgical instruments and human organs has been recognised as a key requirement in the development of high-fidelity surgical simulators. Primarily due to computational considerations, most of the past real-time surgical simulation research has assumed linear elastic behaviour for modelling tissues, even though human soft tissues generally possess non-linear properties. For a non-linear model, the well-known Poynting effect developed during shearing of the tissue results in normal forces not seen in a linear elastic model. Using constitutive equations of non-linear tissue models together with experiments, we show that the Poynting effect results in differences in force magnitude larger than the absolute human perception threshold for force discrimination in some tissues (e.g. myocardial tissues) but not in others (e.g. brain tissue simulants).

Palpation nonlinear reaction force analysis for characterization of breast tissues

This paper addresses a diagnostic palpation system based on the measurement of nonlinear elasticity. An indentation probe is used to press against breast tissue. Then, the measured reaction force is used to estimate the parameters of nonlinear elasticity, which enables the identification of tissue type, such as fat, muscle, mammary gland or tumor. Here, we present the basic concept of our study and preliminary experimental and simulation results from pilot studies. More specifically, we measured the nonlinear response of reaction force using the breast of a goat. In addition, we also simulated the reaction force using nonlinear biomechanical simulation with several tissue types. Large differences in reaction force occur only in the nonlinear range in both experimental and simulation situations. Our results confirmed the feasibility of our concept.

The Role of Haptics in Medical Training Simulators: A Survey of the State of the Art

This review paper discusses the role of haptics within virtual medical training applications, particularly, where it can be used to aid a practitioner to learn and practice a task. The review summarizes aspects to be considered in the deployment of haptics technologies in medical training. First, both force/torque and tactile feedback hardware solutions that are currently produced commercially and in academia are reviewed, followed by the available haptics-related software and then an in-depth analysis of medical training simulations that include haptic feedback. The review is summarized with scrutiny of emerging technologies and discusses future directions in the field.

Cyclically stretching developing tissue in vivo enhances mechanical strength and organization of vascular grafts

Tissue-engineered vascular grafts must have qualities that rival native vasculature, specifically the ability to remodel, the expression of functional endothelial components and a dynamic and functional extracellular matrix (ECM) that resists the forces of the arterial circulation. We have developed a device that when inserted into the peritoneal cavity, attracts cells around a tubular scaffold to generate autologous arterial grafts. The device is capable of cyclically stretching (by means of a pulsatile pump) developing tissue to increase the mechanical strength of the graft. Pulsed (n=8) and unpulsed (n=8) devices were implanted for 10 days in Lovenaar sheep (n=8). Pulsation occurred for a period of 5-8 days before harvest. Thick unadhered autologous tissue with cells residing in a collagen ECM was produced in all devices. Collagen organization was greater in the circumferential direction of pulsed tissue. Immunohistochemical labelling revealed the hematopoietic origin of >90% cells and a significantly higher coexpression with vimentin in pulsed tissue. F-actin expression, mechanical failure strength and strain were also significantly increased by pulsation. Moreover, tissue could be grafted as carotid artery patches. This paper shows that unadhered tissue tubes with increased mechanical strength and differentiation in response to pulsation can be produced with every implant after a period of 10 days. However, these tissue tubes require a more fine-tuned exposure to pulsation to be suitable for use as vascular grafts.

Digital image correlation and finite element modelling as a method to determine mechanical properties of human soft tissue in vivo

The mechanical properties of human soft tissue are crucial for impact biomechanics, rehabilitation engineering, and surgical simulation. Validation of these constitutive models using human data remains challenging and often requires the use of non-invasive imaging and inverse finite element (FE) analysis. Post-processing data from imaging methods such as tagged magnetic resonance imaging (MRI) can be challenging. Digital image correlation (DIC), however, is a relatively straightforward imaging method. DIC has been used in the past to study the planar and superficial properties of soft tissue and excised soft tissue layers. However, DIC has not been used to non-invasive study of the bulk properties of human soft tissue in vivo. Thus, the goal of this study was to assess the use of DIC in combination with FE modelling to determine the bulk material properties of human soft tissue. Indentation experiments were performed on a silicone gel soft tissue phantom. A two camera DIC setup was then used to record the 3D surface deformation. The experiment was then simulated using a FE model. The gel was modelled as Neo-Hookean hyperelastic, and the material parameters were determined by minimising the error between the experimental and FE data. The iterative FE analysis determined material parameters (micro=1.80kPa, K=2999kPa) that were in close agreement with parameters derived independently from regression to uniaxial compression tests (micro=1.71kPa, K=2857kPa). Furthermore the FE model was capable of reproducing the experimental indentor force as well as the surface deformation found (R(2)=0.81). It was therefore concluded that a two camera DIC configuration combined with FE modelling can be used to determine the bulk mechanical properties of materials that can be represented using hyperelastic Neo-Hookean constitutive laws.