Lesion detection and classification in breast cancer: evaluation of approaches based on morphological features, tracer kinetic modelling and semi-quantitative parameters in MR functional imaging (DCE-MRI)

The diagnosis, grading and classification of tumours has benefited considerably from the development of DCE-MRI which is now essential to the adequate clinical management of many tumour types due to its capability in detecting active angiogenesis. Several strategies have been proposed for DCE-MRI evaluation. Visual inspection of contrast agent concentration curves vs time is a very simple yet operator dependent procedure, therefore more objective approaches have been developed in order to facilitate comparison between studies. In so called model free approaches, descriptive or heuristic information extracted from time series raw data have been used for tissue classification. The main issue concerning these schemes is that they have not a direct interpretation in terms of physiological properties of the tissues. On the other hand, model based investigations typically involve compartmental tracer kinetic modelling and pixel-by-pixel estimation of kinetic parameters via non-linear regression applied on region of interests opportunely selected by the physician. This approach has the advantage to provide parameters directly related to the pathophysiological properties of the tissue such as vessel permeability, local regional blood flow, extraction fraction, concentration gradient between plasma and extravascular-extracellular space. Anyway, nonlinear modelling is computational demanding and the accuracy of the estimates can be affected by the signal-to-noise ratio and by the initial solutions. The principal aim of this thesis is investigate the use of semi-quantitative and quantitative parameters for segmentation and classification of breast lesion. The objectives can be subdivided as follow: describe the principal techniques to evaluate time intensity curve in DCE-MRI with focus on kinetic model proposed in literature; to evaluate the influence in parametrization choice for a classic bi-compartmental kinetic models; to evaluate the performance of a method for simultaneous tracer kinetic modelling and pixel classification; to evaluate performance of machine learning techniques training for segmentation and classification of breast lesion.

Structural and kinetic characterization of DNA polymerases I and III from Escherichia coli

DNA elongation is performed by Pol III α subunit in E. coli, stimulated by the association with ε and θ subunits. These three subunits define the DNA Pol III catalytic core. There is controversy about the DNA Pol III assembly for the simultaneous control of lagging and leading strands replication, since some Authors propose a dimeric model with two cores, whereas others have assembled in vitro a trimeric DNA Pol III with a third catalytic core, which increases the efficiency of DNA replication. Moreover, the function of the PHP domain, located at the N-terminus of α subunit, is still unknown. Previous studies hypothesized a possible pyrophosphatase activity, not confirmed yet. The present Thesis highlights by the first time the production in vivo of a trimeric E. coli DNA Pol III by co-expressing α, τ, ε and θ subunits. This trimeric complex has been enzymatically characterized and a molecular model has been proposed, with 2 α subunits sustaining the lagging-strand replication whereas the third core replicates the leading strand. In addition, the pyrophosphatase activity of the PHP domain has been confirmed. This activity involves, at least, the H12 and the D19 residues, whereas the D201 regulates phosphate release. On the other hand, an artificial polymerase (HoLaMa), designed by deleting the exonuclease domain of Klenow Fragment, has been expressed, purified and characterized for a better understanding of bacterial polymerases mechanism. The absence of exonuclease domain impaired enzyme processivity, since this domain is involved in DNA binding. Finally, Klenow enzyme, HoLaMa, α subunit and DNA Pol III αεθ have been characterized at the single-molecule level by FRET analysis, combining ALEX and TIRF microscopy. Fluorescently-labeled DNA molecules were immobilized, and changes in FRET efficiency enabled us to study polymerase binding and DNA polymerization.