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.

Valutazione precoce della risposta a Sorafenib nel Carcinoma Epatocellulare mediante quantificazione dell'Ecografia con contrasto con software Sonotumor

Scopo dello studio: Stabilire se cambiamenti della perfusione di una lesione target di epatocarcinoma (HCC), valutati quantitativamente mediante ecografia con contrasto (CE-US) alla settimana 2 e 4 di terapia con sorafenib, possono predire la progressione di malattia alla settimana 8, valutata con la tomografia computerizzata o la risonanza magnetica con mezzo di contrasto (TC-RM) usando i criteri RECIST/RECIST modificati (response evaluation criteria in solid tumors). Pazienti e metodi: Il comitato etico ha approvato lo studio ed i pazienti hanno fornito un consenso informato scritto prima dell’arruolamento. Lo studio è stato effettuato su un campione di soggetti con epatocarcinoma avanzato o non suscettibile di trattamento curativo, in monoterapia con sorafenib. La valutazione della risposta tumorale è stata effettuata con TC o RM a 2 mesi usando i criteri RECIST/RECIST modificati. La CE-US è stata effettuata entro 1 settimana prima dell’inizio del trattamento con sorafenib e durante la terapia alla settimana 2, 4, 8, 16 e 32. I parametri quantitativi funzionali sono stati ottenuti impiegando un software dedicato. I cambiamenti dei valori dei parametri suddetti tra il tempo zero ed i punti temporali successivi sono stati confrontati con la risposta tumorale basata sui criteri RECIST/RECIST modificati. Risultati: La riduzione dei valori dei parametri relativi alla perfusione tumorale, in particolare di WiAUC e PE (parametri correlati con il volume ematico), al T2/T4 (settimana 2, 4), predice la risposta tumorale a 2 mesi, valutata secondo i criteri RECIST e RECIST modificati, risultata indicativa di malattia stabile (responders). Conclusione: L’ecografia con contrasto può essere impiegata per quantificare i cambiamenti della vascolarizzazione tumorale già alla settimana 2, 4 dopo la somministrazione di sorafenib nei pazienti con HCC. Questi precoci cambiamenti della perfusione tumorale possono essere predittivi della risposta tumorale a 2 mesi e possono avere un potenziale nella valutazione precoce dell'efficacia della terapia antiangiogenica nell’epatocarcinoma.

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.

Valorization of pomaces from the mechanical extraction of virgin olive oils in dairy animal feeding

This research work is aimed at the valorization of two types of pomace deriving from the extra virgin olive oil mechanical extraction process, such as olive pomace and a new by-product named “paté”, in the livestock sector as important sources of antioxidants and unsaturated fatty acids. In the first research the suitability of dried stoned olive pomace as a dietary supplement for dairy buffaloes was evaluated. The effectiveness of this utilization in modifying fatty acid composition and improving the oxidative stability of buffalo milk and mozzarella cheese have been proven by means of the analysis of qualitative and quantitative parameters. In the second research the use of paté as a new by-product in dietary feed supplementation for dairy ewes, already fed with a source of unsaturated fatty acids such as extruded linseed, was studied in order to assess the effect of this combination on the dairy products obtained. The characterization of paté as a new by-product was also carried out, studying the optimal conditions of its stabilization and preservation at the same time. The main results, common to both researches, have been the detection and the characterization of hydrophilic phenols in the milk. The analytical detection of hydroxytyrosol and tyrosol in the ewes’ milk fed with the paté and hydroxytyrosol in buffalo fed with pomace showed for the first time the presence in the milk of hydroxytyrosol, which is one of the most important bioactive compounds of the oil industry products; the transfer of these antioxidants and the proven improvement of the quality of milk fat could positively interact in the prevention of some human cardiovascular diseases and some tumours, increasing in this manner the quality of dairy products, also improving their shelf-life. These results also provide important information on the bioavailability of these phenolic compounds.