Analytical derivation of elasticity in breast phantoms for deformation tracking

Patient-specific biomedical modeling of the breast is of interest for medical applications such as image registration, image guided procedures and the alignment for biopsy or surgery purposes. The computation of elastic properties is essential to simulate deformations in a realistic way. This study presents an innovative analytical method to compute the elastic modulus and evaluate the elasticity of a breast using magnetic resonance (MRI) images of breast phantoms.An analytical method for elasticity computation was developed and subsequently validated on a series of geometric shapes, and on four physical breast phantoms that are supported by a planar frame. This method can compute the elasticity of a shape directly from a set of MRI scans. For comparison, elasticity values were also computed numerically using two different simulation software packages.Application of the different methods on the geometric shapes shows that the analytically derived elongation differs from simulated elongation by less than 9% for cylindrical shapes, and up to 18% for other shapes that are also substantially vertically supported by a planar base. For the four physical breast phantoms, the analytically derived elasticity differs from numeric elasticity by 18% on average, which is in accordance with the difference in elongation estimation for the geometric shapes. The analytic method has shown to be multiple orders of magnitude faster than the numerical methods.It can be concluded that the analytical elasticity computation method has good potential to supplement or replace numerical elasticity simulations in gravity-induced deformations, for shapes that are substantially supported by a planar base perpendicular to the gravitational field. The error is manageable, while the calculation procedure takes less than one second as opposed to multiple minutes with numerical methods. The results will be used in the MRI and Ultrasound Robotic Assisted Biopsy (MURAB) project

Iterative simulations to estimate the elastic properties from a series of MRI images followed by MRI-US validation

The modeling of breast deformations is of interest in medical applications such as image-guided biopsy, or image registration for diagnostic purposes. In order to have such information, it is needed to extract the mechanical properties of the tissues. In this work, we propose an iterative technique based on finite element analysis that estimates the elastic modulus of realistic breast phantoms, starting from MRI images acquired in different positions (prone and supine), when deformed only by the gravity force. We validated the method using both a single-modality evaluation in which we simulated the effect of the gravity force to generate four different configurations (prone, supine, lateral, and vertical) and a multi-modality evaluation in which we simulated a series of changes in orientation (prone to supine). Validation is performed, respectively, on surface points and lesions using as ground-truth data from MRI images, and on target lesions inside the breast phantom compared with the actual target segmented from the US image. The use of pre-operative images is limited at the moment to diagnostic purposes. By using our method we can compute patient-specific mechanical properties that allow compensating deformations

Supplementary files of pneumatic devices for Handbook of Robotic and Image-guided Surgery

STL files for 3D printing pneumatic devices Vector files for laser-cutting seals and teeth shape

Stormram 2: A MRI-compatible robotic system for breast biopsy

A novel MRI-compatible 5 DOF needle manipulator driven by custom pneumatic linear stepper motors has been developed. The robot's frame measures 185x160x100mm, making it small enough to fit inside the bore of the scanner together with the patient. It also has sufficient speed, force and dexterity to manipulate the needle towards a chosen target in a soft breast phantom

Design and implementation of autonomous robotic scanning of the breast

Breast cancer is the most common type of cancer in women worldwide, with nearly 1.7 million new cases diagnosed in 2012.[1] Improvement of breast biopsy methods, allowing early detection and reliable diagnosis, can reduce the mortality rate significantly.[2] The MURAB project stands for MRI and Ultrasound Robotic Assisted Biopsy and aims to improve breast biopsy. Image modalities such as ultrasound and MRI are used to locate the lesion. MRI breast biopsy provides higher resolution images but is significantly more complicated than ultrasound guided biopsy and causes increased discomfort for the patient and increased intervention time and costs. The MURAB project aims to reduce these drawbacks using the advantages of both imaging modalities. Images of both modalities will be registered and will provide input during the robotic assisted biopsy while using real-time ultrasound guidance to guide the biopsy needle to the lesion. The main aim of this research project is to design and implement the ultrasound scanning phase during which the breast of the patient is autonomously scanned by a LWR4+ lightweight robotic arm (KUKA industrial robots, Germany) in order to acquire 2D ultrasound images. The design and implementation in this study consists of 1) autonomous initialization of scanning using visual servoing, 2) automatic trajectory planning and 3) contact control using force feed-back to maintain a constant contact pressure between the robot probe and the patient while keeping the probe normal to the breast surface. Experiments were performed using breast phantoms. Results showed that during initialization of the scanning motion the robot is steered to the correct start position with an accuracy of 1.6 mm. It was possible to automatically plan the trajectory, after which the robotic arm made contact with the breast phantom. The contact pressure of 5N was maintained during the full scan and the probe was kept normal to the surface with an average deviation of seven degrees. These results are promising for further implementation and fine tuning of the scanning phase using a robot arm designed for breast biopsy applications. The MURAB project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 688188. References [1] World Cancer Research Fund International (2012), Breast cancer statistics. http://www.wcrf.org/int/cancer-facts-figures/ data-specific-cancers/breast-cancer-statistics [2] Khatib, Oussama MN, and Atord Modjtabai. "Guidelines for the early detection and screening of breast cancer." World Health Organization. Technical Publications Series 30 (2006)