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.

New approaches to open problems in gene expression microarray data

In the past decade, the advent of efficient genome sequencing tools and high-throughput experimental biotechnology has lead to enormous progress in the life science. Among the most important innovations is the microarray tecnology. It allows to quantify the expression for thousands of genes simultaneously by measurin the hybridization from a tissue of interest to probes on a small glass or plastic slide. The characteristics of these data include a fair amount of random noise, a predictor dimension in the thousand, and a sample noise in the dozens. One of the most exciting areas to which microarray technology has been applied is the challenge of deciphering complex disease such as cancer. In these studies, samples are taken from two or more groups of individuals with heterogeneous phenotypes, pathologies, or clinical outcomes. these samples are hybridized to microarrays in an effort to find a small number of genes which are strongly correlated with the group of individuals. Eventhough today methods to analyse the data are welle developed and close to reach a standard organization (through the effort of preposed International project like Microarray Gene Expression Data -MGED- Society [1]) it is not unfrequant to stumble in a clinician's question that do not have a compelling statistical method that could permit to answer it.The contribution of this dissertation in deciphering disease regards the development of new approaches aiming at handle open problems posed by clinicians in handle specific experimental designs. In Chapter 1 starting from a biological necessary introduction, we revise the microarray tecnologies and all the important steps that involve an experiment from the production of the array, to the quality controls ending with preprocessing steps that will be used into the data analysis in the rest of the dissertation. While in Chapter 2 a critical review of standard analysis methods are provided stressing most of problems that In Chapter 3 is introduced a method to adress the issue of unbalanced design of miacroarray experiments. In microarray experiments, experimental design is a crucial starting-point for obtaining reasonable results. In a two-class problem, an equal or similar number of samples it should be collected between the two classes. However in some cases, e.g. rare pathologies, the approach to be taken is less evident. We propose to address this issue by applying a modified version of SAM [2]. MultiSAM consists in a reiterated application of a SAM analysis, comparing the less populated class (LPC) with 1,000 random samplings of the same size from the more populated class (MPC) A list of the differentially expressed genes is generated for each SAM application. After 1,000 reiterations, each single probe given a "score" ranging from 0 to 1,000 based on its recurrence in the 1,000 lists as differentially expressed. The performance of MultiSAM was compared to the performance of SAM and LIMMA [3] over two simulated data sets via beta and exponential distribution. The results of all three algorithms over low- noise data sets seems acceptable However, on a real unbalanced two-channel data set reagardin Chronic Lymphocitic Leukemia, LIMMA finds no significant probe, SAM finds 23 significantly changed probes but cannot separate the two classes, while MultiSAM finds 122 probes with score >300 and separates the data into two clusters by hierarchical clustering. We also report extra-assay validation in terms of differentially expressed genes Although standard algorithms perform well over low-noise simulated data sets, multi-SAM seems to be the only one able to reveal subtle differences in gene expression profiles on real unbalanced data. In Chapter 4 a method to adress similarities evaluation in a three-class prblem by means of Relevance Vector Machine [4] is described. In fact, looking at microarray data in a prognostic and diagnostic clinical framework, not only differences could have a crucial role. In some cases similarities can give useful and, sometimes even more, important information. The goal, given three classes, could be to establish, with a certain level of confidence, if the third one is similar to the first or the second one. In this work we show that Relevance Vector Machine (RVM) [2] could be a possible solutions to the limitation of standard supervised classification. In fact, RVM offers many advantages compared, for example, with his well-known precursor (Support Vector Machine - SVM [3]). Among these advantages, the estimate of posterior probability of class membership represents a key feature to address the similarity issue. This is a highly important, but often overlooked, option of any practical pattern recognition system. We focused on Tumor-Grade-three-class problem, so we have 67 samples of grade I (G1), 54 samples of grade 3 (G3) and 100 samples of grade 2 (G2). The goal is to find a model able to separate G1 from G3, then evaluate the third class G2 as test-set to obtain the probability for samples of G2 to be member of class G1 or class G3. The analysis showed that breast cancer samples of grade II have a molecular profile more similar to breast cancer samples of grade I. Looking at the literature this result have been guessed, but no measure of significance was gived before.

Nuovo scaffold biomimetico per il trattamento delle lesioni osteocondrali: studio clinico pilota

Nel corso degli anni diverse sono le tecniche proposte per il trattamento delle lesioni osteocondrali, da quelle mini-invasive con stimolazione midollare fino a quelle più aggressive basate sul trapianto di tessuti autologhi o eterologhi. Tutti questi metodi hanno comunque dei difetti ed è questo il motivo per cui il trattamento delle lesioni osteocondrali rappresenta tuttora una sfida per il chirurgo ortopedico, in considerazione dell’alta specializzazione e del basso potere di guarigione del tessuto cartilagineo. Buoni risultati sono stati ottenuti con innesti bioingegnerizzati o matrici polimeriche impiantati nei siti danneggiati. La quantità di scaffolds in uso per la riparazione condrale ed osteocondrale è molto ampia; essi differiscono non solo per il tipo di materiali usati per la loro realizzazione, ma anche per la presenza di promotori di una o più linee cellulari , su base condrogenica o osteogenica. Quando ci si approccia ad una lesione condrale di grandi dimensioni, l’osso sub-condrale è anch’esso coinvolto e necessita di trattamento per ottenere il corretto ripristino degli strati articolari più superficiali. La scelta più giusta sembra essere un innesto osteocondrale bioingegnerizzato, pronto per l’uso ed immediatamente disponibile, che consenta di effettuare il trattamento in un unico tempo chirurgico. Sulla base di questo razionale, dopo uno studio preclinico animale e previa autorizzazione del comitato etico locale, abbiamo condotto uno studio clinico clinico pilota utilizzando un nuovo innesto biomimetico nanostrutturato per il trattamento di lesioni condrali ed osteocondrali del ginocchio; la sua sicurezza e maneggevolezza, così come la facile riproducibilità della tecnica chirurgica ed i risultati clinici ottenuti sono stati valutati nel tempo a 6, 12, 24, 36 e 48 mesi dall’impianto in modo da testare il suo potenziale intrinseco senza l’aggiunta di alcuna linea cellulare.

The medical management after surgery for advanced heart failure

The aim of the Research of this Ph D Project is to improve the medical management after surgery for advanced heart failure, both after left ventricular assist devices (LVAD) implantation, and after heart transplantation in the long-term. Regarding heart transplantation (HTx), the Research Project is focused on diagnostics, classification, prevention and treatment of cardiac allograft vasculopathy (CAV), and on treatment of post-HTx cancers; the results are presented in the first part of this Thesis. In particular, the main aspect investigated are the prognostic role of information derived from coronary angiography, coronary tomography and intravascular ultrasound, and the different sensitivity of these techniques in predicting outcomes and in diagnosing CAV. Moreover, the role of mTOR inhibitors on CAV prevention or treatment is investigated, both alone and in combination with different anti-CMV prevention strategies, as well as the impact of mTOR inhibitors on clinical outcomes in the long term. Regarding LVAD, the main focus is on the role of transthoracic echocardiography in the management of patients with a continuous-flow, centrifugal, intrapericardial pump (HVAD, Heartware); this section is reported in the second part of this Thesis. The main aspects investigated are the use of echocardiography in patients with HVAD device and its interaction with the information derived from pump curves' analysis in predicting aortic valve opening status, a surrogate of the condition of support provided by the LVAD.