Methods for the Quantification of Motor Stability for the Assessment of Fall Risk

The research field of the Thesis is the evaluation of motor variability and the analysis of motor stability for the assessment of fall risk. Since many falls occur during walking, a better understanding of motor stability could lead to the definition of a reliable fall risk index aiming at measuring and assessing the risk of fall in the elderly, in the attempt to prevent traumatic events. Several motor variability and stability measures are proposed in the literature, but still a proper methodological characterization is lacking. Moreover, the relationship between many of these measures and fall history or fall risk is still unknown, or not completely clear. The aim of this thesis is hence to: i) analyze the influence of experimental implementation parameters on variability/stability measures and understand how variations in these parameters affect the outputs; ii) assess the relationship between variability/stability measures and long- short-term fall history. Several implementation issues have been addressed. Following the need for a methodological standardization of gait variability/stability measures, highlighted in particular for orbital stability analysis through a systematic review, general indications about implementation of orbital stability analysis have been showed, together with an analysis of the number of strides and the test-retest reliability of several variability/stability numbers. Indications about the influence of directional changes on measures have been provided. The association between measures and long/short-term fall history has also been assessed. Of all the analyzed variability/stability measures, Multiscale entropy and Recurrence quantification analysis demonstrated particularly good results in terms of reliability, applicability and association with fall history. Therefore, these measures should be taken in consideration for the definition of a fall risk index.

Decoding complex flow phenomena via Dynamic Mode Decomposition

In this thesis, the viability of the Dynamic Mode Decomposition (DMD) as a technique to analyze and model complex dynamic real-world systems is presented. This method derives, directly from data, computationally efficient reduced-order models (ROMs) which can replace too onerous or unavailable high-fidelity physics-based models. Optimizations and extensions to the standard implementation of the methodology are proposed, investigating diverse case studies related to the decoding of complex flow phenomena. The flexibility of this data-driven technique allows its application to high-fidelity fluid dynamics simulations, as well as time series of real systems observations. The resulting ROMs are tested against two tasks: (i) reduction of the storage requirements of high-fidelity simulations or observations; (ii) interpolation and extrapolation of missing data. The capabilities of DMD can also be exploited to alleviate the cost of onerous studies that require many simulations, such as uncertainty quantification analysis, especially when dealing with complex high-dimensional systems. In this context, a novel approach to address parameter variability issues when modeling systems with space and time-variant response is proposed. Specifically, DMD is merged with another model-reduction technique, namely the Polynomial Chaos Expansion, for uncertainty quantification purposes. Useful guidelines for DMD deployment result from the study, together with the demonstration of its potential to ease diagnosis and scenario analysis when complex flow processes are involved.

Methodological improvement of 3D fluoroscopic analysis for the robust quantification of 3D kinematics of human joints

3D video-fluoroscopy is an accurate but cumbersome technique to estimate natural or prosthetic human joint kinematics. This dissertation proposes innovative methodologies to improve the 3D fluoroscopic analysis reliability and usability. Being based on direct radiographic imaging of the joint, and avoiding soft tissue artefact that limits the accuracy of skin marker based techniques, the fluoroscopic analysis has a potential accuracy of the order of mm/deg or better. It can provide fundamental informations for clinical and methodological applications, but, notwithstanding the number of methodological protocols proposed in the literature, time consuming user interaction is exploited to obtain consistent results. The user-dependency prevented a reliable quantification of the actual accuracy and precision of the methods, and, consequently, slowed down the translation to the clinical practice. The objective of the present work was to speed up this process introducing methodological improvements in the analysis. In the thesis, the fluoroscopic analysis was characterized in depth, in order to evaluate its pros and cons, and to provide reliable solutions to overcome its limitations. To this aim, an analytical approach was followed. The major sources of error were isolated with in-silico preliminary studies as: (a) geometric distortion and calibration errors, (b) 2D images and 3D models resolutions, (c) incorrect contour extraction, (d) bone model symmetries, (e) optimization algorithm limitations, (f) user errors. The effect of each criticality was quantified, and verified with an in-vivo preliminary study on the elbow joint. The dominant source of error was identified in the limited extent of the convergence domain for the local optimization algorithms, which forced the user to manually specify the starting pose for the estimating process. To solve this problem, two different approaches were followed: to increase the optimal pose convergence basin, the local approach used sequential alignments of the 6 degrees of freedom in order of sensitivity, or a geometrical feature-based estimation of the initial conditions for the optimization; the global approach used an unsupervised memetic algorithm to optimally explore the search domain. The performances of the technique were evaluated with a series of in-silico studies and validated in-vitro with a phantom based comparison with a radiostereometric gold-standard. The accuracy of the method is joint-dependent, and for the intact knee joint, the new unsupervised algorithm guaranteed a maximum error lower than 0.5 mm for in-plane translations, 10 mm for out-of-plane translation, and of 3 deg for rotations in a mono-planar setup; and lower than 0.5 mm for translations and 1 deg for rotations in a bi-planar setups. The bi-planar setup is best suited when accurate results are needed, such as for methodological research studies. The mono-planar analysis may be enough for clinical application when the analysis time and cost may be an issue. A further reduction of the user interaction was obtained for prosthetic joints kinematics. A mixed region-growing and level-set segmentation method was proposed and halved the analysis time, delegating the computational burden to the machine. In-silico and in-vivo studies demonstrated that the reliability of the new semiautomatic method was comparable to a user defined manual gold-standard. The improved fluoroscopic analysis was finally applied to a first in-vivo methodological study on the foot kinematics. Preliminary evaluations showed that the presented methodology represents a feasible gold-standard for the validation of skin marker based foot kinematics protocols.

Data Mining in Clinical Practice for the Quantification of Motor Impairment in Parkinson's Disease

Advances in biomedical signal acquisition systems for motion analysis have led to lowcost and ubiquitous wearable sensors which can be used to record movement data in different settings. This implies the potential availability of large amounts of quantitative data. It is then crucial to identify and to extract the information of clinical relevance from the large amount of available data. This quantitative and objective information can be an important aid for clinical decision making. Data mining is the process of discovering such information in databases through data processing, selection of informative data, and identification of relevant patterns. The databases considered in this thesis store motion data from wearable sensors (specifically accelerometers) and clinical information (clinical data, scores, tests). The main goal of this thesis is to develop data mining tools which can provide quantitative information to the clinician in the field of movement disorders. This thesis will focus on motor impairment in Parkinson's disease (PD). Different databases related to Parkinson subjects in different stages of the disease were considered for this thesis. Each database is characterized by the data recorded during a specific motor task performed by different groups of subjects. The data mining techniques that were used in this thesis are feature selection (a technique which was used to find relevant information and to discard useless or redundant data), classification, clustering, and regression. The aims were to identify high risk subjects for PD, characterize the differences between early PD subjects and healthy ones, characterize PD subtypes and automatically assess the severity of symptoms in the home setting.

CT perfusion image processing: analysis of liver tumors

Perfusion CT imaging of the liver has potential to improve evaluation of tumour angiogenesis. Quantitative parameters can be obtained applying mathematical models to Time Attenuation Curve (TAC). However, there are still some difficulties for an accurate quantification of perfusion parameters due, for example, to algorithms employed, to mathematical model, to patient’s weight and cardiac output and to the acquisition system. In this thesis, new parameters and alternative methodologies about liver perfusion CT are presented in order to investigate the cause of variability of this technique. Firstly analysis were made to assess the variability related to the mathematical model used to compute arterial Blood Flow (BFa) values. Results were obtained implementing algorithms based on “ maximum slope method” and “Dual input one compartment model” . Statistical analysis on simulated data demonstrated that the two methods are not interchangeable. Anyway slope method is always applicable in clinical context. Then variability related to TAC processing in the application of slope method is analyzed. Results compared with manual selection allow to identify the best automatic algorithm to compute BFa. The consistency of a Standardized Perfusion Index (SPV) was evaluated and a simplified calibration procedure was proposed. At the end the quantitative value of perfusion map was analyzed. ROI approach and map approach provide related values of BFa and this means that pixel by pixel algorithm give reliable quantitative results. Also in pixel by pixel approach slope method give better results. In conclusion the development of new automatic algorithms for a consistent computation of BFa and the analysis and definition of simplified technique to compute SPV parameter, represent an improvement in the field of liver perfusion CT analysis.

Analysis of cerebral and autonomic response to respiratory events in patients with Sleep Apnea Syndrome

The arousal scoring in Obstructive Sleep Apnea Syndrome (OSAS) is important to clarify the impact of the disease on sleep but the currently applied American Academy of Sleep Medicine (AASM) definition may underestimate the subtle alterations of sleep. The aims of the present study were to evaluate the impact of respiratory events on cortical and autonomic arousal response and to quantify the additional value of cyclic alternating pattern (CAP) and pulse wave amplitude (PWA) for a more accurate detection of respiratory events and sleep alterations in OSAS patients. A retrospective revision of 19 polysomnographic recordings of OSAS patients was carried out. Analysis was focused on quantification of apneas (AP), hypopneas (H) and flow limitation (FL) events, and on investigation of cerebral and autonomic activity. Only 41.1% of FL events analyzed in non rapid eye movement met the AASM rules for the definition of respiratory event-related arousal (RERA), while 75.5% of FL events ended with a CAP A phase. The dual response (EEG-PWA) was the most frequent response for all subtypes of respiratory event with a progressive reduction from AP to H and FL. 87.7% of respiratory events with EEG activation showed also a PWA drop and 53,4% of the respiratory events without EEG activation presented a PWA drop. The relationship between the respiratory events and the arousal response is more complex than that suggested by the international classification. In the estimation of the response to respiratory events, the CAP scoring and PWA analysis can offer more extensive information compared to the AASM rules. Our data confirm also that the application of PWA scoring improves the detection of respiratory events and could reduce the underestimation of OSAS severity compared to AASM arousal.

Integrated molecular analysis of endometrial carcinoma: translation of biomarker profiles into the clinical practice

The Cancer Genome Atlas (TCGA) collaborative project identified four distinct prognostic groups of endometrial carcinoma (EC) based on molecular alterations: (i) the ultramutated subtype that encompassed POLE mutated (POLE) cases; (ii) the hypermutated subtype, characterized by MisMatch Repair deficiency (MMRd); (iii) the copy-number high subtype, with p53 abnormal/mutated features (p53abn); (iv) the copy-number low subtype, known as No Specific Molecular Profile (NSMP). Although the prognostic value of TCGA molecular classification, NSMP tumors present a wide variability in molecular alterations and biological aggressiveness. This study aims to investigate the impact of ARID1A and CTNNB1/β-catenin alterations by targeted Next-generation sequencing (NGS) and immunohistochemistry (IHC) in a consecutive series of 125 molecularly classified ECs. NGS and IHC were used to assign surrogate TCGA groups and to identify molecular alterations of multiple target genes including POLE, PTEN, ARID1A, CTNNB1, TP53. Associations with clinicopathologic parameters, molecular subtypes, and outcomes identified NSMP category as the most heterogeneous group in terms of clinicopathologic features and outcome. Integration of surrogate TCGA molecular classification with ARID1A and β-catenin analysis showed NSMP cases with ARID1A mutation characterized by the worst outcome with early recurrence, while NSMP tumors with ARID1A wild-type and β-catenin alteration had indolent clinicopathologic features and no recurrence. This study indicates how the identification of ARID1A and β-catenin alterations in EC represents a simple and effective way to characterize NSMP tumor aggressiveness and metastatic potential.

A methodological approach for the performance optimization of transient seepage models through inverse analysis

The topic of the Ph.D project focuses on the modelling of the soil-water dynamics inside an instrumented embankment section along Secchia River (Cavezzo (MO)) in the period from 2017 to 2018 and the quantification of the performance of the direct and indirect simulations . The commercial code Hydrus2D by Pc-Progress has been chosen to run the direct simulations. Different soil-hydraulic models have been adopted and compared. The parameters of the different hydraulic models are calibrated using a local optimization method based on the Levenberg - Marquardt algorithm implemented in the Hydrus package. The calibration program is carried out using different types of dataset of observation points, different weighting distributions, different combinations of optimized parameters and different initial sets of parameters. The final goal is an in-depth study of the potentialities and limits of the inverse analysis when applied to a complex geotechnical problem as the case study. The second part of the research focuses on the effects of plant roots and soil-vegetation-atmosphere interaction on the spatial and temporal distribution of pore water pressure in soil. The investigated soil belongs to the West Charlestown Bypass embankment, Newcastle, Australia, that showed in the past years shallow instabilities and the use of long stem planting is intended to stabilize the slope. The chosen plant species is the Malaleuca Styphelioides, native of eastern Australia. The research activity included the design and realization of a specific large scale apparatus for laboratory experiments. Local suction measurements at certain intervals of depth and radial distances from the root bulb are recorded within the vegetated soil mass under controlled boundary conditions. The experiments are then reproduced numerically using the commercial code Hydrus 2D. Laboratory data are used to calibrate the RWU parameters and the parameters of the hydraulic model.

Modelling and Uncertainty Quantification application to SA simulation codes in advanced SMR

In the framework of a global transition to a low-carbon energy mix, the interest in advanced nuclear Small Modular Reactors (SMRs) has been growing at the international level. Due to the high level of maturity reached by Severe Accident Codes for currently operating rectors, their applicability to advanced SMRs is starting to be studied. Within the present work of thesis and in the framework of a collaboration between ENEA, UNIBO and IRSN, an ASTEC code model of a generic IRIS reactor has been developed. The simulation of a DBA sequence involving the operation of all the passive safety systems of the generic IRIS has been carried out to investigate the code model capability in the prediction of the thermal-hydraulics characterizing an integral SMR adopting a passive mitigation strategy. The following simulation of 4 BDBAs sequences explores the applicability of Severe Accident Codes to advance SMRs in beyond-design and core-degradation conditions. The uncertainty affecting a code simulation can be estimated by using the method of Input Uncertainty Propagation, whose application has been realized through the RAVEN-ASTEC coupling and implementation on an HPC platform. This probabilistic methodology has been employed in a study of the uncertainty affecting the passive safety system operation in the DBA simulation of ASTEC, providing a further characterization of the thermal-hydraulics of this sequence. The application of the Uncertainty Quantification method to early core-melt phenomena has been investigated in the framework of a BEPU analysis of the ASTEC simulation of the QUENCH test-6 experiment. A possible solution to the encountered challenges has been proposed through the application of a Limit Surface search algorithm.

Content-aware approach for improving biomedical image analysis: an interdisciplinary study series

Biomedicine is a highly interdisciplinary research area at the interface of sciences, anatomy, physiology, and medicine. In the last decade, biomedical studies have been greatly enhanced by the introduction of new technologies and techniques for automated quantitative imaging, thus considerably advancing the possibility to investigate biological phenomena through image analysis. However, the effectiveness of this interdisciplinary approach is bounded by the limited knowledge that a biologist and a computer scientist, by professional training, have of each other’s fields. The possible solution to make up for both these lacks lies in training biologists to make them interdisciplinary researchers able to develop dedicated image processing and analysis tools by exploiting a content-aware approach. The aim of this Thesis is to show the effectiveness of a content-aware approach to automated quantitative imaging, by its application to different biomedical studies, with the secondary desirable purpose of motivating researchers to invest in interdisciplinarity. Such content-aware approach has been applied firstly to the phenomization of tumour cell response to stress by confocal fluorescent imaging, and secondly, to the texture analysis of trabecular bone microarchitecture in micro-CT scans. Third, this approach served the characterization of new 3-D multicellular spheroids of human stem cells, and the investigation of the role of the Nogo-A protein in tooth innervation. Finally, the content-aware approach also prompted to the development of two novel methods for local image analysis and colocalization quantification. In conclusion, the content-aware approach has proved its benefit through building new approaches that have improved the quality of image analysis, strengthening the statistical significance to allow unveiling biological phenomena. Hopefully, this Thesis will contribute to inspire researchers to striving hard for pursuing interdisciplinarity.

Exploratory analysis of the role of circulating microRNA in metastatic melanoma patients

MicroRNAs act as oncogene or tumor suppressor gene regulators and are actively released from tumor cells in the circulation. Specific microRNAs can be isolated and quantified in the blood, usually in serum or plasma fractions, where they are uncommonly stable. Cell-free microRNAs serve many, and possibly yet unexplored, functional roles and microRNA levels reflect underlying conditions and have been associated with skin cancer presence, stage and evolution. However, the clinical potential of circulating miRNAs in metastatic melanoma remains largely undefined. From May 2020 to September 2022, we conducted a spontaneous, monocentric, exploratory study on human tissues in vitro, which aimed to evaluate the prognostic and predictive role of circulating miRNAs in metastatic melanoma patients. At the Medical Oncology Unit of Policlinico Sant’Orsola-Malpighi of Bologna, peripheral venous blood samples from patients with metastatic melanoma treated with checkpoint inhibitors (CPI) were collected before the start of CPI (baseline, T0) and longitudinally, approximately every 3 months (T1, T2, etc). Circulating miRNA quantification was performed by droplet digital PCR (Biorad) using an EvaGreen and LNA primer-based assays. QuantaSoft Program (Biorad) calculated the absolute quantifications of each miRNA, indicated as copies/µL. After analysis of the literature, we chose to analyze miR-155-5p, miR-320a and miR-424-5p level. All miRNAs except miR-424-5p show a significantly higher level in plasma of patients who are alive after 1 year of follow-up. High/low levels of baseline miR-155-5p, miR-320a and miR-424-5p are significantly associated with overall survival and progression-free survival. Furthermore, a preliminary analysis on the group of patients who received first-line with anti-PD-1 (N=7), baseline miR-155-5p shows higher levels in responder vs. non responder patients (p 0.06). These data, though promising, are preliminary and need to be further investigated in a larger cohort of patients.

Contributions to the performance analysis of continuum parallel robots

Continuum parallel robots (CPRs) are manipulators employing multiple flexible beams arranged in parallel and connected to a rigid end-effector. CPRs promise higher payload and accuracy than serial CRs while keeping great flexibility. As the risk of injury during accidental contacts between a human and a CPR should be reduced, CPRs may be used in large-scale collaborative tasks or assisted robotic surgery. There exist various CPR designs, but the prototype conception is rarely based on performance considerations, and the CPRs realization in mainly based on intuitions or rigid-link parallel manipulators architectures. This thesis focuses on the performance analysis of CPRs, and the tools needed for such evaluation, such as workspace computation algorithms. In particular, workspace computation strategies for CPRs are essential for the performance assessment, since the CPRs workspace may be used as a performance index or it can serve for optimal-design tools. Two new workspace computation algorithms are proposed in this manuscript, the former focusing on the workspace volume computation and the certification of its numerical results, while the latter aims at computing the workspace boundary only. Due to the elastic nature of CPRs, a key performance indicator for these robots is the stability of their equilibrium configurations. This thesis proposes the experimental validation of the equilibrium stability assessment on a real prototype, demonstrating limitations of some commonly used assumptions. Additionally, a performance index measuring the distance to instability is originally proposed in this manuscript. Differently from the majority of the existing approaches, the clear advantage of the proposed index is a sound physical meaning; accordingly, the index can be used for a more straightforward performance quantification, and to derive robot specifications.