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.

Analisi preclinica di nuove strategie terapeutiche basate sull'inibizione di protein-chinasi nell'osteosarcoma.

Scopo: L’obiettivo del presente programma di studio è stato quello di identificare e validare nuovi possibili bersagli terapeutici per l’osteosarcoma (OS) partendo dall’analisi del chinoma umano. Risultati: L’analisi del profilo di espressione genica ottenuta su 21 campioni clinici di OS ad alto grado di malignità ha permesso di selezionare le seguenti chinasi di possibile rilevanza biologica per l’OS: AURK-A, AURK-B, CDK2, PIK3CA, PLK-1. Le chinasi selezionate sono state validate tramite RNA interference. Successivamente è stata valutata l’efficacia dei relativi inibitori specifici: VX-680 e ZM-447439 inibitori delle Aurora-chinasi, Roscovitina di CDK2 e NMS1 di PLK-1, già inclusi in studi clinici. In termini d’inibizione della crescita cellulare le linee sono risultate maggiomente sensibili ai farmaci VX-680 e NMS1. E’ stata osservata una minor sensibilità ai farmaci VX-680, ZM447439 e NMS1 nelle linee doxorubicina(DX)-resistenti (caratterizzate da elevati livelli di espressione di ABCB1), indicando questi farmaci come potenziali substrati di ABCB1. La Roscovitina, nonostante i valori di IC50 elevati, non sembrerebbe substrato di ABCB1. La validazione preclinica di VX-680 e ZM447439 è stata completata. La forte inibizione della crescita è causata da endoreduplicazione per mancata citodieresi con conseguente formazione di una popolazione iperploide e apoptosi. Inoltre, VX-680 inibisce la motilità e la capacità di formare colonie. Esperimenti di associazione farmacologica mostrano che VX-680 interagisce positivamente con tutti i chemioterapici convenzionali impiegati nel trattamento dell’OS. NMS-1 produce interazioni positive con la DX in linee cellulari DX-resistenti, probabilmente grazie all’effetto revertante esercitato su ABCB1. La Roscovitina produce interazioni positive con CDDP e DX nelle varianti resistenti, effetto probbilmente dovuto al ruolo di CDK2 nei meccanismi di riparo del DNA. Conclusioni: L’analisi in vitro dell’attività degli inibitori ha permesso di identificare VX-680 come nuovo farmaco di potenziale interesse clinico, soprattutto in virtù delle sue interazioni sinergiche con i chemioterapici di uso convenzionale nel trattamento dell’osteosarcoma.

Efficient ultrasonic signal processing techniques for aided medical diagnostics

Ultrasound imaging is widely used in medical diagnostics as it is the fastest, least invasive, and least expensive imaging modality. However, ultrasound images are intrinsically difficult to be interpreted. In this scenario, Computer Aided Detection (CAD) systems can be used to support physicians during diagnosis providing them a second opinion. This thesis discusses efficient ultrasound processing techniques for computer aided medical diagnostics, focusing on two major topics: (i) Ultrasound Tissue Characterization (UTC), aimed at characterizing and differentiating between healthy and diseased tissue; (ii) Ultrasound Image Segmentation (UIS), aimed at detecting the boundaries of anatomical structures to automatically measure organ dimensions and compute clinically relevant functional indices. Research on UTC produced a CAD tool for Prostate Cancer detection to improve the biopsy protocol. In particular, this thesis contributes with: (i) the development of a robust classification system; (ii) the exploitation of parallel computing on GPU for real-time performance; (iii) the introduction of both an innovative Semi-Supervised Learning algorithm and a novel supervised/semi-supervised learning scheme for CAD system training that improve system performance reducing data collection effort and avoiding collected data wasting. The tool provides physicians a risk map highlighting suspect tissue areas, allowing them to perform a lesion-directed biopsy. Clinical validation demonstrated the system validity as a diagnostic support tool and its effectiveness at reducing the number of biopsy cores requested for an accurate diagnosis. For UIS the research developed a heart disease diagnostic tool based on Real-Time 3D Echocardiography. Thesis contributions to this application are: (i) the development of an automated GPU based level-set segmentation framework for 3D images; (ii) the application of this framework to the myocardium segmentation. Experimental results showed the high efficiency and flexibility of the proposed framework. Its effectiveness as a tool for quantitative analysis of 3D cardiac morphology and function was demonstrated through clinical validation.