Assessing model credibility of CT-Based finite element model to predict bone strength

Osteoporosis is one of the major causes of mortality among the elderly. Nowadays, areal bone mineral density (aBMD) is used as diagnostic criteria for osteoporosis; however, this is a moderate predictor of the femur fracture risk and does not capture the effect of some anatomical and physiological properties on the bone strength estimation. Data from past research suggest that most fragility femur fractures occur in patients with aBMD values outside the pathological range. Subject-specific finite element models derived from computed tomography data are considered better tools to non-invasively assess hip fracture risk. In particular, the Bologna Biomechanical Computed Tomography (BBCT) is an In Silico methodology that uses a subject specific FE model to predict bone strength. Different studies demonstrated that the modeling pipeline can increase predictive accuracy of osteoporosis detection and assess the efficacy of new antiresorptive drugs. However, one critical aspect that must be properly addressed before using the technology in the clinical practice, is the assessment of the model credibility. The aim of this study was to define and perform verification and uncertainty quantification analyses on the BBCT methodology following the risk-based credibility assessment framework recently proposed in the VV-40 standard. The analyses focused on the main verification tests used in computational solid mechanics: force and moment equilibrium check, mesh convergence analyses, mesh quality metrics study, evaluation of the uncertainties associated to the definition of the boundary conditions and material properties mapping. Results of these analyses showed that the FE model is correctly implemented and solved. The operation that mostly affect the model results is the material properties mapping step. This work represents an important step that, together with the ongoing clinical validation activities, will contribute to demonstrate the credibility of the BBCT methodology.

Micro-FEM models based on micro-CT reconstructions for the in vitro characterization of the elastic properties of trabecular bone tissue.

This master’s thesis describes the research done at the Medical Technology Laboratory (LTM) of the Rizzoli Orthopedic Institute (IOR, Bologna, Italy), which focused on the characterization of the elastic properties of the trabecular bone tissue, starting from october 2012 to present. The approach uses computed microtomography to characterize the architecture of trabecular bone specimens. With the information obtained from the scanner, specimen-specific models of trabecular bone are generated for the solution with the Finite Element Method (FEM). Along with the FEM modelling, mechanical tests are performed over the same reconstructed bone portions. From the linear-elastic stage of mechanical tests presented by experimental results, it is possible to estimate the mechanical properties of the trabecular bone tissue. After a brief introduction on the biomechanics of the trabecular bone (chapter 1) and on the characterization of the mechanics of its tissue using FEM models (chapter 2), the reliability analysis of an experimental procedure is explained (chapter 3), based on the high-scalable numerical solver ParFE. In chapter 4, the sensitivity analyses on two different parameters for micro-FEM model’s reconstruction are presented. Once the reliability of the modeling strategy has been shown, a recent layout for experimental test, developed in LTM, is presented (chapter 5). Moreover, the results of the application of the new layout are discussed, with a stress on the difficulties connected to it and observed during the tests. Finally, a prototype experimental layout for the measure of deformations in trabecular bone specimens is presented (chapter 6). This procedure is based on the Digital Image Correlation method and is currently under development in LTM.

Analysis of cone-beam ct dose in image-guided radiation therapy for brain and prostate cancer patients via gpu-based Monte Carlo simulations

La radioterapia guidata da immagini (IGRT), grazie alle ripetute verifiche della posizione del paziente e della localizzazione del volume bersaglio, si è recentemente affermata come nuovo paradigma nella radioterapia, avendo migliorato radicalmente l’accuratezza nella somministrazione di dose a scopo terapeutico. Una promettente tecnica nel campo dell’IGRT è rappresentata dalla tomografia computerizzata a fascio conico (CBCT). La CBCT a kilovoltaggio, consente di fornire un’accurata mappatura tridimensionale dell’anatomia del paziente, in fase di pianificazione del trattamento e a ogni frazione del medisimo. Tuttavia, la dose da imaging attribuibile alle ripetute scansioni è diventata, negli ultimi anni, oggetto di una crescente preoccupazione nel contesto clinico. Lo scopo di questo lavoro è di valutare quantitativamente la dose addizionale somministrata da CBCT a kilovoltaggio, con riferimento a tre tipici protocolli di scansione per Varian OnBoard Imaging Systems (OBI, Palo Alto, California). A questo scopo sono state condotte simulazioni con codici Monte Carlo per il calcolo della dose, utilizzando il pacchetto gCTD, sviluppato sull’architettura della scheda grafica. L’utilizzo della GPU per sistemi server di calcolo ha permesso di raggiungere alte efficienze computazionali, accelerando le simulazioni Monte Carlo fino a raggiungere tempi di calcolo di ~1 min per un caso tipico. Inizialmente sono state condotte misure sperimentali di dose su un fantoccio d’acqua. I parametri necessari per la modellazione della sorgente di raggi X nel codice gCTD sono stati ottenuti attraverso un processo di validazione del codice al fine di accordare i valori di dose simulati in acqua con le misure nel fantoccio. Lo studio si concentra su cinquanta pazienti sottoposti a cicli di radioterapia a intensità modulata (IMRT). Venticinque pazienti con tumore al cervello sono utilizzati per studiare la dose nel protocollo standard-dose head e venticinque pazienti con tumore alla prostata sono selezionati per studiare la dose nei protocolli pelvis e pelvis spotlight. La dose media a ogni organo è calcolata. La dose media al 2% dei voxels con i valori più alti di dose è inoltre computata per ogni organo, al fine di caratterizzare l’omogeneità spaziale della distribuzione.

A ROS-based Workspace Control and Trajectory Planner for a seven degrees of freedom Robotic arm

In this Bachelor Thesis I want to provide readers with tools and scripts for the control of a 7DOF manipulator, backed up by some theory of Robotics and Computer Science, in order to better contextualize the work done. In practice, we will see most common software, and developing environments, used to cope with our task: these include ROS, along with visual simulation by VREP and RVIZ, and an almost "stand-alone" ROS extension called MoveIt!, a very complete programming interface for trajectory planning and obstacle avoidance. As we will better appreciate and understand in the introduction chapter, the capability of detecting collision objects through a camera sensor, and re-plan to the desired end-effector pose, are not enough. In fact, this work is implemented in a more complex system, where recognition of particular objects is needed. Through a package of ROS and customized scripts, a detailed procedure will be provided on how to distinguish a particular object, retrieve its reference frame with respect to a known one, and then allow navigation to that target. Together with technical details, the aim is also to report working scripts and a specific appendix (A) you can refer to, if desiring to put things together.

Performance Analysis of 5G based Positioning in Railway Applications

Rail transportation has significant importance in the future world. This importance is tightly bounded to accessible, sustainable, efficient and safe railway systems. Precise positioning in railway applications is essential for increasing railway traffic, train-track control, collision avoidance, train management and autonomous train driving. Hence, precise train positioning is a safety-critical application. Nowadays, positioning in railway applications highly depends on a cellular-based system called GSM-R, a railway-specific version of Global System for Mobile Communications (GSM). However, GSM-R is a relatively outdated technology and does not provide enough capacity and precision demanded by future railway networks. One option for positioning is mounting Global Navigation Satellite System (GNSS) receivers on trains as a low-cost solution. Nevertheless, GNSS can not provide continuous service due to signal interruption by harsh environments, tunnels etc. Another option is exploiting cellular-based positioning methods. The most recent cellular technology, 5G, provides high network capacity, low latency, high accuracy and high availability suitable for train positioning. In this thesis, an approach to 5G-based positioning for railway systems is discussed and simulated. Observed Time Difference of Arrival (OTDOA) method and 5G Positioning Reference Signal (PRS) are used. Simulations run using MATLAB, based on existing code developed for 5G positioning by extending it for Non Line of Sight (NLOS) link detection and base station exclusion algorithms. Performance analysis for different configurations is completed. Results show that efficient NLOS detection improves positioning accuracy and implementing a base station exclusion algorithm helps for further increase.