Stem Cells as a therapy for myocardial infarction in animal models

Advances in stem cell biology have challenged the notion that infarcted myocardium is irreparable. The pluripotent ability of stem cells to differentiate into specialized cell lines began to garner intense interest within cardiology when it was shown in animal models that intramyocardial injection of bone marrow stem cells (MSCs), or the mobilization of bone marrow stem cells with spontaneous homing to myocardium, could improve cardiac function and survival after induced myocardial infarction (MI) [1, 2]. Furthermore, the existence of stem cells in myocardium has been identified in animal heart [3, 4], and intense research is under way in an attempt to clarify their potential clinical application for patients with myocardial infarction. To date, in order to identify the best one, different kinds of stem cells have been studied; these have been derived from embryo or adult tissues (i.e. bone marrow, heart, peripheral blood etc.). Currently, three different biologic therapies for cardiovascular diseases are under investigation: cell therapy, gene therapy and the more recent “tissue-engineering” therapy . During my Ph.D. course, first I focalised my study on the isolation and characterization of Cardiac Stem Cells (CSCs) in wild-type and transgenic mice and for this purpose I attended, for more than one year, the Cardiovascular Research Institute of the New York Medical College, in Valhalla (NY, USA) under the direction of Doctor Piero Anversa. During this period I learnt different Immunohistochemical and Biomolecular techniques, useful for investigating the regenerative potential of stem cells. Then, during the next two years, I studied the new approach of cardiac regenerative medicine based on “tissue-engineering” in order to investigate a new strategy to regenerate the infracted myocardium. Tissue-engineering is a promising approach that makes possible the creation of new functional tissue to replace lost or failing tissue. This new discipline combines isolated functioning cells and biodegradable 3-dimensional (3D) polymeric scaffolds. The scaffold temporarily provides the biomechanical support for the cells until they produce their own extracellular matrix. Because tissue-engineering constructs contain living cells, they may have the potential for growth and cellular self-repair and remodeling. In the present study, I examined whether the tissue-engineering strategy within hyaluron-based scaffolds would result in the formation of alternative cardiac tissue that could replace the scar and improve cardiac function after MI in syngeneic heterotopic rat hearts. Rat hearts were explanted, subjected to left coronary descending artery occlusion, and then grafted into the abdomen (aorta-aorta anastomosis) of receiving syngeneic rat. After 2 weeks, a pouch of 3 mm2 was made in the thickness of the ventricular wall at the level of the post-infarction scar. The hyaluronic scaffold, previously engineered for 3 weeks with rat MSCs, was introduced into the pouch and the myocardial edges sutured with few stitches. Two weeks later we evaluated the cardiac function by M-Mode echocardiography and the myocardial morphology by microscope analysis. We chose bone marrow-derived mensenchymal stem cells (MSCs) because they have shown great signaling and regenerative properties when delivered to heart tissue following a myocardial infarction (MI). However, while the object of cell transplantation is to improve ventricular function, cardiac cell transplantation has had limited success because of poor graft viability and low cell retention, that’s why we decided to combine MSCs with a biopolimeric scaffold. At the end of the experiments we observed that the hyaluronan fibres had not been substantially degraded 2 weeks after heart-transplantation. Most MSCs had migrated to the surrounding infarcted area where they were especially found close to small-sized vessels. Scar tissue was moderated in the engrafted region and the thickness of the corresponding ventricular wall was comparable to that of the non-infarcted remote area. Also, the left ventricular shortening fraction, evaluated by M-Mode echocardiography, was found a little bit increased when compared to that measured just before construct transplantation. Therefore, this study suggests that post-infarction myocardial remodelling can be favourably affected by the grafting of MSCs delivered through a hyaluron-based scaffold

Statistical methods for analysis and processing of medical ultrasound: applications to segmentation and restoration

In this thesis two major topics inherent with medical ultrasound images are addressed: deconvolution and segmentation. In the first case a deconvolution algorithm is described allowing statistically consistent maximum a posteriori estimates of the tissue reflectivity to be restored. These estimates are proven to provide a reliable source of information for achieving an accurate characterization of biological tissues through the ultrasound echo. The second topic involves the definition of a semi automatic algorithm for myocardium segmentation in 2D echocardiographic images. The results show that the proposed method can reduce inter- and intra observer variability in myocardial contours delineation and is feasible and accurate even on clinical data.

Automated Segmentation and Non-Rigid Registration for the Quantitative Evaluation of Myocardial Perfusion from Magnetic Resonance Images

Myocardial perfusion quantification by means of Contrast-Enhanced Cardiac Magnetic Resonance images relies on time consuming frame-by-frame manual tracing of regions of interest. In this Thesis, a novel automated technique for myocardial segmentation and non-rigid registration as a basis for perfusion quantification is presented. The proposed technique is based on three steps: reference frame selection, myocardial segmentation and non-rigid registration. In the first step, the reference frame in which both endo- and epicardial segmentation will be performed is chosen. Endocardial segmentation is achieved by means of a statistical region-based level-set technique followed by a curvature-based regularization motion. Epicardial segmentation is achieved by means of an edge-based level-set technique followed again by a regularization motion. To take into account the changes in position, size and shape of myocardium throughout the sequence due to out of plane respiratory motion, a non-rigid registration algorithm is required. The proposed non-rigid registration scheme consists in a novel multiscale extension of the normalized cross-correlation algorithm in combination with level-set methods. The myocardium is then divided into standard segments. Contrast enhancement curves are computed measuring the mean pixel intensity of each segment over time, and perfusion indices are extracted from each curve. The overall approach has been tested on synthetic and real datasets. For validation purposes, the sequences have been manually traced by an experienced interpreter, and contrast enhancement curves as well as perfusion indices have been computed. Comparisons between automatically extracted and manually obtained contours and enhancement curves showed high inter-technique agreement. Comparisons of perfusion indices computed using both approaches against quantitative coronary angiography and visual interpretation demonstrated that the two technique have similar diagnostic accuracy. In conclusion, the proposed technique allows fast, automated and accurate measurement of intra-myocardial contrast dynamics, and may thus address the strong clinical need for quantitative evaluation of myocardial perfusion.

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.

Sistemi endorfinergici e modulazione di segnali molecolari e profili trascrizionali coinvolti in processi di protezione e autoriparazione del miocardio danneggiato

Con il termine IPC (precondizionamento ischemico) si indica un fenomeno per il quale, esponendo il cuore a brevi cicli di ischemie subletali prima di un danno ischemico prolungato, si conferisce una profonda resistenza all’infarto, una delle principali cause di invalidità e mortalità a livello mondiale. Studi recenti hanno suggerito che l’IPC sia in grado di migliorare la sopravvivenza, la mobilizzazione e l’integrazione di cellule staminali in aree ischemiche e che possa fornire una nuova strategia per potenziare l’efficacia della terapia cellulare cardiaca, un’area della ricerca in continuo sviluppo. L’IPC è difficilmente trasferibile nella pratica clinica ma, da anni, è ben documentato che gli oppioidi e i loro recettori hanno un ruolo cardioprotettivo e che attivano le vie di segnale coinvolte nell’IPC: sono quindi candidati ideali per una possibile terapia farmacologica alternativa all’IPC. Il trattamento di cardiomiociti con gli agonisti dei recettori oppioidi Dinorfina B, DADLE e Met-Encefalina potrebbe proteggere, quindi, le cellule dall’apoptosi causata da un ambiente ischemico ma potrebbe anche indurle a produrre fattori che richiamino elementi staminali. Per testare quest’ipotesi è stato messo a punto un modello di “microambiente ischemico” in vitro sui cardiomioblasti di ratto H9c2 ed è stato dimostrato che precondizionando le cellule in modo “continuativo” (ventiquattro ore di precondizionamento con oppioidi e successivamente ventiquattro ore di induzione del danno, continuando a somministrare i peptidi oppioidi) con Dinorfina B e DADLE si verifica una protezione diretta dall’apoptosi. Successivamente, saggi di migrazione e adesione hanno mostrato che DADLE agisce sulle H9c2 “ischemiche” spronandole a creare un microambiente capace di attirare cellule staminali mesenchimali umane (FMhMSC) e di potenziare le capacità adesive delle FMhMSC. I dati ottenuti suggeriscono, inoltre, che la capacità del microambiente ischemico trattato con DADLE di attirare le cellule staminali possa essere imputabile alla maggiore espressione di chemochine da parte delle H9c2.