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.

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.

New methodologies in CT perfusion and MRI analysis to develop cancer imaging biomarkers

Quantitative imaging in oncology aims at developing imaging biomarkers for diagnosis and prediction of cancer aggressiveness and therapy response before any morphological change become visible. This Thesis exploits Computed Tomography perfusion (CTp) and multiparametric Magnetic Resonance Imaging (mpMRI) for investigating diverse cancer features on different organs. I developed a voxel-based image analysis methodology in CTp and extended its use to mpMRI, for performing precise and accurate analyses at single-voxel level. This is expected to improve reproducibility of measurements and cancer mechanisms’ comprehension and clinical interpretability. CTp has not entered the clinical routine yet, although its usefulness in the monitoring of cancer angiogenesis, due to different perfusion computing methods yielding unreproducible results. Instead, machine learning applications in mpMRI, useful to detect imaging features representative of cancer heterogeneity, are mostly limited to clinical research, because of results’ variability and difficult interpretability, which make clinicians not confident in clinical applications. In hepatic CTp, I investigated whether, and under what conditions, two widely adopted perfusion methods, Maximum Slope (MS) and Deconvolution (DV), could yield reproducible parameters. To this end, I developed signal processing methods to model the first pass kinetics and remove any numerical cause hampering the reproducibility. In mpMRI, I proposed a new approach to extract local first-order features, aiming at preserving spatial reference and making their interpretation easier. In CTp, I found out the cause of MS and DV non-reproducibility: MS and DV represent two different states of the system. Transport delays invalidate MS assumptions and, by correcting MS formulation, I have obtained the voxel-based equivalence of the two methods. In mpMRI, the developed predictive models allowed (i) detecting rectal cancers responding to neoadjuvant chemoradiation showing, at pre-therapy, sparse coarse subregions with altered density, and (ii) predicting clinically significant prostate cancers stemming from the disproportion between high- and low- diffusivity gland components.

Effetto dell' ormone tiroideo (T3) durante ex vivo lung perfusion (EVLP) sul polmone di ratto: valutazione dell'azione protettiva nel danno da ischemia riperfusione.

La perfusione polmonare extracorporea (EVLP) è una tecnica utilizzata dal 2010 per valutare e migliorare la qualità dell'organo da trapiantare e il danno da ischemia-ripefusione (IRI). Tale perfusione utilizza la soluzione di Steen, la cui composizione è solo parzialmente nota. Lo scopo è quello di identificare gli effetti di T3 su IRI polmonare ex vivo, in un modello di ratto di donatore a cuore non battente. Animali (40) randomizzati in otto gruppi e il protocollo EVLP sono stati standardizzati nel nostro centro. Sono state valutate la funzione polmonare, PEEP, la resistenza vascolare polmonare totale a 45, 60, 120 e 180 minuti di EVLP per eseguire analisi di gas, dosaggio del mediatore di infiammazione, mitocondriale libero DNA, freeT3 e freeT4. Alla fine dei campioni di tessuto polmonare sono stati congelati dal dosaggio ATP, espressione genica, DNA mitocondriale, T3. Non date le concentrazioni del produttore, abbiamo analizzato gli acidi grassi liberi, vitamine, ormoni e composizione della soluzione Steen. Risultati La soluzione di steen contiene albumina umana x2 nel siero umano (7,5-8 g/dl): le concentrazioni di ft4 e ft3 sono x2 quelle nel siero umano e vengono rilasciati dall'albumina. La concentrazione di ft4 e ft3 non è cambiata durante l'EVLP. La Steen ha alta fluorescenza per l'alta concentrazione delle molecole aromatiche (ormoni) mai descritto in precedenza. NADH e mtDNA nel perfused aumenta con danno ischemico e nel gruppo trattato con T3 Conclusione Il modello EVLP è già convalidato nella perfusione nel trapianto polmonare, ma è necessario approfondire l'effetto della Steen in termini di ormoni e analiti. L'effetto sull'IRI dell'EVLP sembra essere influenzato negativamente da un T3 troppo alto in Steen, cosa che descriviamo per la prima volta. L'ulteriore aggiunta di T3 provoca disfunzione mitocondriale e infiammazione.