La lattatemia nel puledro neonato sottoposto a terapia intensiva

Admission blood lactate concentration has been shown to be a useful indicator of disease severity in human medicine and numerous studies have associated hyperlactatemia with patients at high risk of death who should be treated aggressively regardless of the cause of the lactate generation. The degree and duration of hyperlactacidaemia also have been correlated with the subsequent development of organ failure. Similarly, in a small number of studies about equine colic, blood lactate concentration has been investigated as a useful prognostic variable . In neonatal foals blood lactate was studied first by Magdesian (2003) who described venous blood lactate concentration in 14 normal foals during the initial 48 hours post-partum. A preliminary study about lactate concentration in foals presenting to a neonatal intensive care unit reported that surviving foals had earlier lactate clearance. The measurement of blood lactate concentration is traditionally available with a wet chemistry laboratory method or with blood-gas analyzers, for clinicians working at university or large private hospital. But this methods may not be easily accessible to many practitioners in field conditions. Several relatively inexpensive, easy to use and rapid pocket size monitors to measure lactate concentration have been validated in human patients and athletes. None of these portable lactate analyzer have been evaluated in clinically normal neonatal foals or in foals referred to a neonatal intensive care unit. The aims of this study were to validate the Lactate Scout analyzer in neonatal foals, investigating the correlation between lactate concentration in whole blood measured with the portable monitor and measured in plasma with the reference laboratory analyzer. The effect of hematocrit (Hct) on the accuracy of Lactate Scout was also evaluated. Further, we determined the utility of venous lactate measurement in critically-ill foals, describing lactate values in the most frequent neonatal pathologies, evaluating serial blood lactate measurements during hospitalization and investigating its prognostic value. The study also describes normal range for lactate in healthy neonatal foals during the first 72 hours of life.

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.