Development of a patient-specific model for stroke risk assessment in atrial fibrillation patients

Atrial fibrillation is associated with a five-fold increase in the risk of cerebrovascular events,being responsible of 15-18% of all strokes.The morphological and functional remodelling of the left atrium caused by atrial fibrillation favours blood stasis and, consequently, stroke risk. In this context, several clinical studies suggest that stroke risk stratification could be improved by using haemodynamic information on the left atrium (LA) and the left atrial appendage (LAA). The goal of this study was to develop a personalized computational fluid-dynamics (CFD) model of the left atrium which could clarify the haemodynamic implications of atrial fibrillation on a patient specific basis. The developed CFD model was first applied to better understand the role of LAA in stroke risk. Infact, the interplay of the LAA geometric parameters such as LAA length, tortuosity, surface area and volume with the fluid-dynamics parameters and the effects of the LAA closure have not been investigated. Results demonstrated the capabilities of the CFD model to reproduce the real physiological behaviour of the blood flow dynamics inside the LA and the LAA. Finally, we determined that the fluid-dynamics parameters enhanced in this research project could be used as new quantitative indexes to describe the different types of AF and open new scenarios for the patient-specific stroke risk stratification.

Numerical simulations of the spine for patient-specific models of severe scoliosis

In silico methods, such as musculoskeletal modelling, may aid the selection of the optimal surgical treatment for highly complex pathologies such as scoliosis. Many musculoskeletal models use a generic, simplified representation of the intervertebral joints, which are fundamental to the flexibility of the spine. Therefore, to model and simulate the spine, a suitable representation of the intervertebral joint is crucial. The aim of this PhD was to characterise specimen-specific models of the intervertebral joint for multi-body models from experimental datasets. First, the project investigated the characterisation of a specimen-specific lumped parameter model of the intervertebral joint from an experimental dataset of a four-vertebra lumbar spine segment. Specimen-specific stiffnesses were determined with an optimisation method. The sensitivity of the parameters to the joint pose was investigate. Results showed the stiffnesses and predicted motions were highly depended on both the joint pose. Following the first study, the method was reapplied to another dataset that included six complete lumbar spine segments under three different loading conditions. Specimen-specific uniform stiffnesses across joint levels and level-dependent stiffnesses were calculated by optimisation. Specimen-specific stiffness show high inter-specimen variability and were also specific to the loading condition. Level-dependent stiffnesses are necessary for accurate kinematic predictions and should be determined independently of one another. Secondly, a framework to create subject-specific musculoskeletal models of individuals with severe scoliosis was developed. This resulted in a robust codified pipeline for creating subject-specific, severely scoliotic spine models from CT data. In conclusion, this thesis showed that specimen-specific intervertebral joint stiffnesses were highly sensitive to joint pose definition and the importance of level-dependent optimisation. Further, an open-source codified pipeline to create patient-specific scoliotic spine models from CT data was released. These studies and this pipeline can facilitate the specimen-specific characterisation of the scoliotic intervertebral joint and its incorporation into scoliotic musculoskeletal spine models.

Planning and assessment techniques for spine surgeries

The rate of diagnosis and treatment of degenerative spine disorders is increasing, increasing the need for surgical intervention. Posterior spine fusion is one surgical intervention used to treat various spine degeneration pathologies To minimize the risk of complications and provide patients with positive outcomes, preoperative planning and postsurgical assessment are necessary. This PhD aimed to investigate techniques for the surgical planning and assessment of spine surgeries. Three main techniques were assessed: stereophotogrammetric motion analysis, 3D printing of complex spine deformities and finite element analysis of the thoracolumbar spine. Upon reviewing the literature on currently available spine kinematics protocol, a comprehensive motion analysis protocol to measure the multi-segmental spine motion was developed. Using this protocol, the patterns of spine motion in patients before and after posterior spine fixation was mapped. The second part investigated the use of virtual and 3D printed spine models for the surgical planning of complex spine deformity correction. Compared to usual radiographic images, the printed model allowed optimal surgical intervention, reduced surgical time and provided better surgeon-patient communication. The third part assessed the use of polyetheretherketone rods auxiliary to titanium rods to reduce the stiffness of posterior spine fusion constructs. Using a finite element model of the thoracolumbar spine, the rods system showed a decrease in the overall stress of the uppermost instrumented vertebra when compared to regular fixation approaches. Finally, a retrospective biomechanical assessment of a lumbopelvic reconstruction technique was investigated to assess the patients' gait following the surgery, the implant deformation over the years and the extent of bony fusion between spine and implant. In conclusion, this thesis highlighted the need to provide surgeons with new planning and assessment techniques to better understand postsurgical complications. The methodologies investigated in this project can be used in the future to establish a patient-specific planning protocol.

From fall-risk assessment to fall detection: inertial sensors in the clinical routine and daily life

Falls are caused by complex interaction between multiple risk factors which may be modified by age, disease and environment. A variety of methods and tools for fall risk assessment have been proposed, but none of which is universally accepted. Existing tools are generally not capable of providing a quantitative predictive assessment of fall risk. The need for objective, cost-effective and clinically applicable methods would enable quantitative assessment of fall risk on a subject-specific basis. Tracking objectively falls risk could provide timely feedback about the effectiveness of administered interventions enabling intervention strategies to be modified or changed if found to be ineffective. Moreover, some of the fundamental factors leading to falls and what actually happens during a fall remain unclear. Objectively documented and measured falls are needed to improve knowledge of fall in order to develop more effective prevention strategies and prolong independent living. In the last decade, several research groups have developed sensor-based automatic or semi-automatic fall risk assessment tools using wearable inertial sensors. This approach may also serve to detect falls. At the moment, i) several fall-risk assessment studies based on inertial sensors, even if promising, lack of a biomechanical model-based approach which could provide accurate and more detailed measurements of interests (e.g., joint moments, forces) and ii) the number of published real-world fall data of older people in a real-world environment is minimal since most authors have used simulations with healthy volunteers as a surrogate for real-world falls. With these limitations in mind, this thesis aims i) to suggest a novel method for the kinematics and dynamics evaluation of functional motor tasks, often used in clinics for the fall-risk evaluation, through a body sensor network and a biomechanical approach and ii) to define the guidelines for a fall detection algorithm based on a real-world fall database availability.

Context detection and abstraction in smart environments

Context-aware computing is currently considered the most promising approach to overcome information overload and to speed up access to relevant information and services. Context-awareness may be derived from many sources, including user profile and preferences, network information, sensor analysis; usually context-awareness relies on the ability of computing devices to interact with the physical world, i.e. with the natural and artificial objects hosted within the "environment”. Ideally, context-aware applications should not be intrusive and should be able to react according to user’s context, with minimum user effort. Context is an application dependent multidimensional space and the location is an important part of it since the very beginning. Location can be used to guide applications, in providing information or functions that are most appropriate for a specific position. Hence location systems play a crucial role. There are several technologies and systems for computing location to a vary degree of accuracy and tailored for specific space model, i.e. indoors or outdoors, structured spaces or unstructured spaces. The research challenge faced by this thesis is related to pedestrian positioning in heterogeneous environments. Particularly, the focus will be on pedestrian identification, localization, orientation and activity recognition. This research was mainly carried out within the “mobile and ambient systems” workgroup of EPOCH, a 6FP NoE on the application of ICT to Cultural Heritage. Therefore applications in Cultural Heritage sites were the main target of the context-aware services discussed. Cultural Heritage sites are considered significant test-beds in Context-aware computing for many reasons. For example building a smart environment in museums or in protected sites is a challenging task, because localization and tracking are usually based on technologies that are difficult to hide or harmonize within the environment. Therefore it is expected that the experience made with this research may be useful also in domains other than Cultural Heritage. This work presents three different approaches to the pedestrian identification, positioning and tracking: Pedestrian navigation by means of a wearable inertial sensing platform assisted by the vision based tracking system for initial settings an real-time calibration; Pedestrian navigation by means of a wearable inertial sensing platform augmented with GPS measurements; Pedestrian identification and tracking, combining the vision based tracking system with WiFi localization. The proposed localization systems have been mainly used to enhance Cultural Heritage applications in providing information and services depending on the user’s actual context, in particular depending on the user’s location.

Three-dimensional joint kinematics of swimming using body-worn inertial and magnetic sensors

Wearable inertial and magnetic measurements units (IMMU) are an important tool for underwater motion analysis because they are swimmer-centric, they require only simple measurement set-up and they provide the performance results very quickly. In order to estimate 3D joint kinematics during motion, protocols were developed to transpose the IMMU orientation estimation to a biomechanical model. The aim of the thesis was to validate a protocol originally propositioned to estimate the joint angles of the upper limbs during one-degree-of-freedom movements in dry settings and herein modified to perform 3D kinematics analysis of shoulders, elbows and wrists during swimming. Eight high-level swimmers were assessed in the laboratory by means of an IMMU while simulating the front crawl and breaststroke movements. A stereo-photogrammetric system (SPS) was used as reference. The joint angles (in degrees) of the shoulders (flexion-extension, abduction-adduction and internal-external rotation), the elbows (flexion-extension and pronation-supination), and the wrists (flexion-extension and radial-ulnar deviation) were estimated with the two systems and compared by means of root mean square errors (RMSE), relative RMSE, Pearson’s product-moment coefficient correlation (R) and coefficient of multiple correlation (CMC). Subsequently, the athletes were assessed during pool swimming trials through the IMMU. Considering both swim styles and all joint degrees of freedom modeled, the comparison between the IMMU and the SPS showed median values of RMSE lower than 8°, representing 10% of overall joint range of motion, high median values of CMC (0.97) and R (0.96). These findings suggest that the protocol accurately estimated the 3D orientation of the shoulders, elbows and wrists joint during swimming with accuracy adequate for the purposes of research. In conclusion, the proposed method to evaluate the 3D joint kinematics through IMMU was revealed to be a useful tool for both sport and clinical contexts.

Studio e ottimizzazione del processo di fabbricazione additiva (SLM) per applicazioni in ambito biomedicale: produzione di protesi e strutture reticolari

Il progetto di dottorato che verrà presentato in questa tesi è focalizzato sullo sviluppo di un metodo sperimentale per la produzione di protesi personalizzate utilizzando il processo di fabbricazione additiva di Selective Laser Melting (SLM). L’obiettivo è quello di definire una condizione di processo ottimizzata per applicazioni in ambito chirurgico che possa essere generalizzabile, ovvero che ne garantisca la riproducibilità al variare dell’anatomia del paziente e che rappresenti la base per estendere il metodo ad altre componenti protesiche. Il lavoro si è sviluppato lungo due linee principali, la cui convergenza ha permesso di realizzare prototipi di protesi complete utilizzando un solo processo: da una parte la produzione di componenti a massima densità per il raggiungimento di elevate resistenze meccaniche, buona resistenza ad usura e corrosione e controllo di tensioni residue e deformazione delle parti stampate. Dall’altra si sono studiate strutture reticolari a geometria e porosità controllata per favorire l’osteointegrazione della componente protesica post impianto. In questo studio sono stati messe a confronto le possibili combinazioni tra parametri di processo e sono state individuate le correlazioni con le proprietà finali dei componenti stampati. Partendo da queste relazioni si sono sviluppate le strategie tecnologiche per la progettazione e la produzione dei componenti. I test sperimentali svolti e i risultati ottenuti hanno dimostrato la fattibilità dell’utilizzo del processo SLM per la produzione di protesi personalizzate e sono stati fabbricati i primi prototipi funzionali. La fabbricazione di protesi personalizzate richiede, però, anche la progettazione e la produzione di strumentario chirurgico ad hoc. Per questo motivo, parallelamente allo studio della lega di Cromo Cobalto, sono stati eseguiti i test anche su campioni in INOX 316L. Anche in questo caso è stato possibile individuare una finestra operativa di processo che garantisse proprietà meccaniche comparabili, e in alcuni casi superiori, a quelle ottenute con processi convenzionali.

Biomechanical modelling of human knee during living activities

The knee joint is a key structure of the human locomotor system. The knowledge of how each single anatomical structure of the knee contributes to determine the physiological function of the knee, is of fundamental importance for the development of new prostheses and novel clinical, surgical, and rehabilitative procedures. In this context, a modelling approach is necessary to estimate the biomechanic function of each anatomical structure during daily living activities. The main aim of this study was to obtain a subject-specific model of the knee joint of a selected healthy subject. In particular, 3D models of the cruciate ligaments and of the tibio-femoral articular contact were proposed and developed using accurate bony geometries and kinematics reliably recorded by means of nuclear magnetic resonance and 3D video-fluoroscopy from the selected subject. Regarding the model of the cruciate ligaments, each ligament was modelled with 25 linear-elastic elements paying particular attention to the anatomical twisting of the fibres. The devised model was as subject-specific as possible. The geometrical parameters were directly estimated from the experimental measurements, whereas the only mechanical parameter of the model, the elastic modulus, had to be considered from the literature because of the invasiveness of the needed measurements. Thus, the developed model was employed for simulations of stability tests and during living activities. Physiologically meaningful results were always obtained. Nevertheless, the lack of subject-specific mechanical characterization induced to design and partially develop a novel experimental method to characterize the mechanics of the human cruciate ligaments in living healthy subjects. Moreover, using the same subject-specific data, the tibio-femoral articular interaction was modelled investigating the location of the contact point during the execution of daily motor tasks and the contact area at the full extension with and without the whole body weight of the subject. Two different approaches were implemented and their efficiency was evaluated. Thus, pros and cons of each approach were discussed in order to suggest future improvements of this methodologies. The final results of this study will contribute to produce useful methodologies for the investigation of the in-vivo function and pathology of the knee joint during the execution of daily living activities. Thus, the developed methodologies will be useful tools for the development of new prostheses, tools and procedures both in research field and in diagnostic, surgical and rehabilitative fields.

Development of musculoskeletal models for the design and the pre-clinical validation of hip resurfacing prosthesis

Background. The surgical treatment of dysfunctional hips is a severe condition for the patient and a costly therapy for the public health. Hip resurfacing techniques seem to hold the promise of various advantages over traditional THR, with particular attention to young and active patients. Although the lesson provided in the past by many branches of engineering is that success in designing competitive products can be achieved only by predicting the possible scenario of failure, to date the understanding of the implant quality is poorly pre-clinically addressed. Thus revision is the only delayed and reliable end point for assessment. The aim of the present work was to model the musculoskeletal system so as to develop a protocol for predicting failure of hip resurfacing prosthesis. Methods. Preliminary studies validated the technique for the generation of subject specific finite element (FE) models of long bones from Computed Thomography data. The proposed protocol consisted in the numerical analysis of the prosthesis biomechanics by deterministic and statistic studies so as to assess the risk of biomechanical failure on the different operative conditions the implant might face in a population of interest during various activities of daily living. Physiological conditions were defined including the variability of the anatomy, bone densitometry, surgery uncertainties and published boundary conditions at the hip. The protocol was tested by analysing a successful design on the market and a new prototype of a resurfacing prosthesis. Results. The intrinsic accuracy of models on bone stress predictions (RMSE < 10%) was aligned to the current state of the art in this field. The accuracy of prediction on the bone-prosthesis contact mechanics was also excellent (< 0.001 mm). The sensitivity of models prediction to uncertainties on modelling parameter was found below 8.4%. The analysis of the successful design resulted in a very good agreement with published retrospective studies. The geometry optimisation of the new prototype lead to a final design with a low risk of failure. The statistical analysis confirmed the minimal risk of the optimised design over the entire population of interest. The performances of the optimised design showed a significant improvement with respect to the first prototype (+35%). Limitations. On the authors opinion the major limitation of this study is on boundary conditions. The muscular forces and the hip joint reaction were derived from the few data available in the literature, which can be considered significant but hardly representative of the entire variability of boundary conditions the implant might face over the patients population. This moved the focus of the research on modelling the musculoskeletal system; the ongoing activity is to develop subject-specific musculoskeletal models of the lower limb from medical images. Conclusions. The developed protocol was able to accurately predict known clinical outcomes when applied to a well-established device and, to support the design optimisation phase providing important information on critical characteristics of the patients when applied to a new prosthesis. The presented approach does have a relevant generality that would allow the extension of the protocol to a large set of orthopaedic scenarios with minor changes. Hence, a failure mode analysis criterion can be considered a suitable tool in developing new orthopaedic devices.