Non-rigid registration of breast surfaces using the laplace and diffusion equations

A semi-automated, non-rigid breast surface registration method is presented that involves solving the Laplace or diffusion equations over undeformed and deformed breast surfaces. The resulting potential energy fields and isocontours are used to establish surface correspondence. This novel surface-based method, which does not require intensity images, anatomical landmarks, or fiducials, is compared to a gold standard of thin-plate spline (TPS) interpolation. Realistic finite element simulations of breast compression and further testing against a tissue-mimicking phantom demonstrate that this method is capable of registering surfaces experiencing 6 - 36 mm compression to within a mean error of 0.5 - 5.7 mm

Image-Guided Abdominal Surgery and Therapy Delivery

ABSTRACT Image-Guided Surgery has become the standard of care in intracranial neurosurgery providing more exact resections while minimizing damage to healthy tissue. Moving that process to abdominal organs presents additional challenges in the form of image segmentation, image to physical space registration, organ motion and deformation. In this paper, we present methodologies and results for addressing these challenges in two specific organs: the liver and the kidney

A finite element inverse analysis to assess functional improvement during the fracture healing process

Assessment of the restoration of load-bearing function is the central goal in the study of fracture healing process. During the fracture healing, two critical aspects affect its analysis: (1) material properties of the callus components, and (2) the spatio-temporal architecture of the callus with respect to cartilage and new bone formation. In this study, an inverse problem methodology is used which takes into account both features and yields material property estimates that can analyze the healing changes. Six stabilized fractured mouse tibias are obtained at two time points during the most active phase of the healing process, respectively 10 days (n=3), and 14 days (n=3) after fracture. Under the same displacement conditions, the inverse procedure estimations of the callus material properties are generated and compared to other fracture healing metrics. The FEA estimated property is the only metric shown to be statistically significant (p=0.0194) in detecting the changes in the stiffness that occur during the healing time points. In addition, simulation studies regarding sensitivity to initial guess and noise are presented; as well as the influence of callus architecture on the FEA estimated material property metric. The finite element model inverse analysis developed can be used to determine the effects of genetics or therapeutic manipulations on fracture healing in rodents

Sensitivity analysis and automation for intraoperative implementation of the atlas-based method for brain shift correction

ABSTRACT The use of biomechanical models to correct the misregistration due to deformation in image guided neurosurgical systems has been a growing area of investigation. In previous work, an atlas-based inverse model was developed to account for soft-tissue deformations during image-guided surgery. Central to that methodology is a considerable amount of pre-computation and planning. The goal of this work is to evaluate techniques that could potentially reduce that burden. Distinct from previous manual techniques, an automated segmentation technique is described for the cerebrum and dural septa. The shift correction results using this automated segmentation method were compared to those using the manual methods. In addition, the extent and distribution of the surgical parameters associated with the deformation atlas were investigated by a sensitivity analysis using simulation experiments and clinical data. The shift correction results did not change significantly using the automated method (correction of 73±13% ) as compared to the semi-automated method from previous work (correction of 76±13%). The results of the sensitivity analysis show that the atlas could be constructed by coarser sampling (six fold reduction) without substantial degradation in the shift reconstruction, a decrease in preoperative computational time from 13.1±3.5 hours to 2.2±0.6 hours. The automated segmentation technique and the findings of the sensitivity study have significant impact on the reduction of pre-operative computational time, improving the utility of the atlas-based method. The work in this paper suggests that the atlas-based technique can become a 'time of surgery' setup procedure rather than a pre-operative computing strategy

Comparison of microCT and an inverse finite element approach for biomechanical analysis: Results in a MSC therapeutic system for fracture healing

An important concern in the study of fracture healing is the ability to assess mechanical integrity in response to candidate therapeutics in small-animal systems. In recent reports, it has been proposed that microCT image-derived densitometric parameters could be used as a surrogate for mechanical property assessment. Recently, we have proposed an inverse methodology that iteratively reconstructs the modulus of elasticity of the lumped soft callus/hard callus region by integrating both intrinsic mechanical property (from biomechanical testing) and geometrical information (from microCT) within an inverse finite element analysis (FEA) to define a callus quality measure. In this paper, data from a therapeutic system involving mesenchymal stem cells is analyzed within the context of comparing traditional microCT densitometric and mechanical property metrics. In addition, a novel multi-parameter regression microCT parameter is analyzed as well as our inverse FEA metric. The results demonstrate that the inverse FEA approach was the only metric to successfully detect both longitudinal and therapeutic responses. While the most promising microCT-based metrics were adequate at early healing states, they failed to track late-stage mechanical integrity. In addition, our analysis added insight to the role of MSCs by demonstrating accelerated healing and was the only metric to demonstrate therapeutic benefits at late-stage healing. In conclusion, the work presented here indicates that microCT densitometric parameters are an incomplete surrogate for mechanical integrity. Additionally, our inverse FEA approach is shown to be very sensitive and may provide a first-step towards normalizing the often challenging process of assessing mechanical integrity of healing fractures

Regenerative Effects of Transplanted Mesenchymal Stem Cells in Fracture Healing

Mesenchymal stem cells (MSC) have a therapeutic potential in patients with fractures to reduce the time of healing and treat non-unions. The use of MSC to treat fractures is attractive as it would be implementing a reparative process that should be in place but occurs to be defective or protracted and MSC effects would be needed only for the repairing time that is relatively brief. However, an integrated approach to define the multiple regenerative contributions of MSC to the fracture repair process is necessary before clinical trials are initiated. In this study, using a stabilized tibia fracture mouse model, we determined the dynamic migration of transplanted MSC to the fracture site, their contributions to the repair process initiation and their role in modulating the injury-related inflammatory responses. Using MSC expressing luciferase, we determined by bioluminescence imaging that the MSC migration at the fracture site is time- and dose-dependent and, it is exclusively CXCR4-dependent. MSC improved the fracture healing affecting the callus biomechanical properties and such improvement correlated with an increase in cartilage and bone content, and changes in callus morphology as determined by micro-computed-tomography and histological studies. Transplanting CMV-Cre-R26R-LacZ-MSC, we found that MSC engrafted within the callus endosteal niche. Using MSC from BMP-2-Lac-Z mice genetically modified using a bacterial artificial chromosome system to be β-gal reporters for BMP-2 expression, we found that MSC contributed to the callus initiation by expressing BMP-2. The knowledge of the multiple MSC regenerative abilities in fracture healing will allow to design novel MSC-based therapies to treat fractures

Analysis of Model-Updated MR Images to Correct for Brain Deformation Due to Tissue Retraction

Surgical events such as retraction, resection, and gravitational sag often cause significant tissue movement that compromises the accuracy of neuronavigation systems that use a preoperative image display. Computational modeling has gained interest as a method for correcting registration errors that result from brain deformation by simulating surgical events and creating updated images. The success of simulating surgical events relies upon the application of surgical forces to a model of brain deformation physics. This paper analyzes the model simulation of retraction using a finite element model of the brain. To test the model, we conducted an ex vivo experiment on a porcine model using a retraction system in a MR scanner. The high-resolution images of retraction obtained from the sets of MR images were used to create the 3D volumetric model and serve as a basis of comparison to the model-updated images and calculations. The model is found to recapture 66 % of average tissue motion and reduce the maximum registration error by over 80%. The model-updated images are displayed along with the actual deformation images and show a strong potential for computational modeling as a means to compensate for brain shift and minimize registration errors