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

Unveiling professional development: A critical review of stage models

In research across professions, the development of professional skill traditionally was seen as a process of accumulation of knowledge and skills, promoted by practical experience. More recently, this view has been modified to incorporate skillful know-how that is progressively acquired by passing through developmental stages, such as novice, competent, and expert. The authors of this article critically review contemporary stage models that are typically applied across professions. Their principal critique is that a focus on stages veils or conceals more fundamental aspects of professional skill development. On the basis of their critique, the authors propose an alternative model that builds on the strengths of previous models while seeking to overcome their main limitations. Finally, the authors outline the implications of their alternative model for professional education, workplace practices, and research on professional development

Student understandings of evidence-based management : ways of doing and being

This paper advances the literature on Evidence Based Management (EBMgt) by exploring how students understand EBMgt. We conduct a qualitative inductive study of undergraduate students who were introduced to EBMgt and applied evidence-based processes as part of an introductory management course. Our findings identify four qualitatively different student understandings of EBMgt: (1) EBMgt as an unrealistic way of doing management; (2) EBMgt as a way of doing management in particular situations; (3) EBMgt as a generally useful way of doing management; and (4) EBMgt as an ideal way of being a manager. We find that variations in student understanding are based upon perceptions of the utility of evidence-based processes, the stance taken towards scientific evidence as a form of knowledge, and the focus of reflection about the practice of EBMgt. By opening up insight into the how undergraduate students understand and make sense of EBMgt as ways of doing and being, we contribute to the theoretical literature on EBMgt and to the practice of EBMgt teaching and learning and offer new paths for future research.PostprintPeer reviewe

Real-time markerless trocar pose acquisition with RGB-D sensor

There is a crescent demand of transparent training programs based on an objective metrics to measure surgical skill. A fundamental source of objective parameters is the real-time analysis of positions, paths and movements of laparoscopic tools. Unfortunately, the equipment required to acquire accurate spatial measurements is expensive and specialized. In this work we address the problem of laparoscopic tools tracking, focusing on trocar tool. Trocar is the essential tool to guarantee the access to the surgical area during laparoscopic surgery, which is the most common minimally invasive technique performed in clinically practice. Currently researchers have predominantly employed rather expensive magnetic [1] or video based [2,3] tracking. The main limitations of the first approach is that it requires to fix an external sensor to measure the position of the instruments, while the second type of methods suffer from limited precision. The availability of light structured depth sensor, such as Microsoft's Kinect, allows to address tracking problems with a very compact and cheap device. The main contribution of this work is a method for markerless trocar tracking based on mixed depth and color information

Causal interaction modeling on ultra-processed food manufacturing

In recent years computer science theories have been applied to manufacturing improving products quality, fault detection and process monitoring. However, there is a lack of research in the identification of causal relationships among data. These associations of cause-effect are important since they allow root causes to be analysed, they highlight the most influential process variables and they embed a typical human reasoning model that is largely applied in manufacturing. Compared to knowledge-based approach, data driven causal discovery (DCD) enables causal modeling without overloading expert operators and scales faster. However, DCD is challenging to be applied especially in small-medium enterprises where machines raw data are stored without the support of specialized data analyst team. In this work, we aim to automatically reconstruct the causal interaction model of the production flow from raw data. We use PCMCI, a constraint-based causal discovery algorithm, that handles both linear and nonlinear relationships in time series. We validate our method on a synthetic realization that emulates manufacturing features and on real data with domain expert support. The obtained results confirm that PCMCI is able to recognize more than 50% of causal relationships without any false positives. The application of the PCMCI method in an ultra-processed food manufacturer allows to propose a novel causal interaction model integrating data-driven and expert's knowledge

A compact navigation system for free hand needle placement in percutaneos procedures

In this work we have designed and developed a new navigation system for interventional radiology, implemented in a light and compact device. The system attached to the needle is composed by a small screen that gives hints about the position and the orientation, a controller that commands the screen and interfaces with the computer, and a marker that communicates with a tracking system. By using a real time software the user is guided to move the needle along the desired position and orientation. To the best of our knowledges, this is the first system to have the navigation display integrated directly on the tool. The in-vitro tests we have performed, show how such a system yields a higher precision in the execution of the task and a reduction of the time required to complete the procedure

Multimodal Data Fusion and Registration for Needle Guidance in Percutaneous Procedures

Minimally invasive procedures, such as the percutaneous procedures, present more difficulties than the open approaches due to the limited access to the patient, the limited field of view and the difficult manipulation of the instruments. Navigation systems could help overcome these difficulties by providing additional information to the surgeon or the interventional radiologists during the procedure. In particular they can provide the exact localization of the instruments inside the patients body in relation to the tumor margins and risk structures. This work presents a method to track, register and integrate pre-operative images, with multimodal data acquired during the actual intervention, in a navigation system for percutaneous procedures. The goal of the navigation system is the virtual reconstruction of the operative scenario by the fusion of different images in the same reference system and the exact localization and tracking of the instruments used during the intervention, such as the ultrasound (US) probe and the needle. The proposed method focuses on the assistance of percutaneous cryoablation of renal tumors because this procedure requires the surgeon to translate the mental plan developed on the computer tomography (CT) images, acquired before the intervention, into the reality without any hint about internal structures position or only with the assistance of a 2D US image [1]. The success of a percutaneous intervention is bound to the precision of the needle insertion along the planned trajectory. Together with the registration and fusion of different image datasets, the needle used to accomplish the procedure is calibrated in the same reference system and is represented in the virtual environment. The use of virtual reconstruction increases the awareness of the on going procedure, by providing a rendering of the different tools and structures involved in the intervention and improves the positioning of the needle to be inserted