Analysis of morphological and functional heterogeneity in ct perfusion images of lung tumours

Questa tesi si propone di innovare lo stato dell’arte dei metodi di analisi dell’eterogeneità in lesioni polmonari attualmente utilizzati, affiancando l’analisi funzionale (emodinamica) a quella morfologica, grazie allo sviluppo di nuove feature specifiche. Grazie alla collaborazione tra il Computer Vision Group (CVG) dell’Università di Bologna e l’Unità Operativa di Radiologia dell’IRCCS-IRST di Meldola (Istituto di Ricovero e Cura a Carattere Scientifico – Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori), è stato possibile analizzare un adeguato numero di casi reali di pazienti affetti da lesioni polmonari primitive, effettuando un’analisi dell’eterogeneità sia su sequenze di immagini TC baseline sia contrast-enhanced, consentendo quindi un confronto tra eterogeneità morfologica e funzionale. I risultati ottenuti sono infine discussi sulla base del confronto con le considerazioni di natura clinica effettuate in cieco da due esperti radiologi dell’IRCCS-IRST.

A Reliable Downscaling of ECG Signals for the Detection of T wave Heterogeneity Features

In cardiovascular disease the definition and the detection of the ECG parameters related to repolarization dynamics in post MI patients is still a crucial unmet need. In addition, the use of a 3D sensor in the implantable medical devices would be a crucial mean in the assessment or prediction of Heart Failure status, but the inclusion of such feature is limited by hardware and firmware constraints. The aim of this thesis is the definition of a reliable surrogate of the 500 Hz ECG signal to reach the aforementioned objective. To evaluate the worsening of reliability due to sampling frequency reduction on delineation performance, the signals have been consecutively down sampled by a factor 2, 4, 8 thus obtaining the ECG signals sampled at 250, 125 and 62.5 Hz, respectively. The final goal is the feasibility assessment of the detection of the fiducial points in order to translate those parameters into meaningful clinical parameter for Heart Failure prediction, such as T waves intervals heterogeneity and variability of areas under T waves. An experimental setting for data collection on healthy volunteers has been set up at the Bakken Research Center in Maastricht. A 16 – channel ambulatory system, provided by TMSI, has recorded the standard 12 – Leads ECG, two 3D accelerometers and a respiration sensor. The collection platform has been set up by the TMSI property software Polybench, the data analysis of such signals has been performed with Matlab. The main results of this study show that the 125 Hz sampling rate has demonstrated to be a good candidate for a reliable detection of fiducial points. T wave intervals proved to be consistently stable, even at 62.5 Hz. Further studies would be needed to provide a better comparison between sampling at 250 Hz and 125 Hz for areas under the T waves.