Inside standard and hyperspectral low-dose CT variational imaging: parameter identification and material decomposition

The main contribution of this thesis is the proposal of novel strategies for the selection of parameters arising in variational models employed for the solution of inverse problems with data corrupted by Poisson noise. In light of the importance of using a significantly small dose of X-rays in Computed Tomography (CT), and its need of using advanced techniques to reconstruct the objects due to the high level of noise in the data, we will focus on parameter selection principles especially for low photon-counts, i.e. low dose Computed Tomography. For completeness, since such strategies can be adopted for various scenarios where the noise in the data typically follows a Poisson distribution, we will show their performance for other applications such as photography, astronomical and microscopy imaging. More specifically, in the first part of the thesis we will focus on low dose CT data corrupted only by Poisson noise by extending automatic selection strategies designed for Gaussian noise and improving the few existing ones for Poisson. The new approaches will show to outperform the state-of-the-art competitors especially in the low-counting regime. Moreover, we will propose to extend the best performing strategy to the hard task of multi-parameter selection showing promising results. Finally, in the last part of the thesis, we will introduce the problem of material decomposition for hyperspectral CT, which data encodes information of how different materials in the target attenuate X-rays in different ways according to the specific energy. We will conduct a preliminary comparative study to obtain accurate material decomposition starting from few noisy projection data.

Stereotactict body radiotherapy (SBRT)

Purpose: evaluation and comparison of volumetric modulated RapidarcTM radiotherapy (RA-IMRT) vs linac based Stereotactic body radiotherapy (SBRT) in the salvage treatment of isolated lymph node recurrences in patients affected by gynaecological cancer. Materials and Methods From January 2010 to September 2011, 15 patients affected by isolated lymph nodes recurrence of gynaecological cancer underwent salvage radiotherapy after conventional imaging staging with CT and 18-FDG-PET/CT. Two different radiotherapy techniques were used in this study: RA-IMRT (RapidarcTM implemented radiotherapy Varian Medical System, Palo Alto, CA, USA) or SBRT (BrainLAB, Feldkirchen, Germany). Five patients underwent CT scan and all patients underwent 18FDG-PET/CT for pre-treatment evaluation and staging. The mean total dose delivered was 54.3 Gy (range 50-60 Gy with conventional fractionation and 27.4 Gy (range 12-40 Gy hypofractionation) for RA-IMRT and SBRT respectively. The mean number of fractions was 27.6 fractions (range 25-31) and 3-4 fractions , the mean overall treatment duration was 40.5 days (range 36-45) and 6.5 days (range 5-8 days) for RA-IMRT and SBRT respectively. Results: At the time of the analysis, October 2011, the overall survival was 92.3 % (80% for RA-IMRT and 100% for SBRT). Six patients are alive with no evidence of disease and also six patients are alive with clinically evident disease in other sites (40% and 50% patients RA-IMRT vs SBRT respectively, one patient died for systemic progression of disease and two patient were not evaluable at this time. Conclusions: Our preliminary results showed that, the use of RA-IMRT and SBRT are an excellent local therapy for isolated lymph nodes recurrences of gynaecological cancer with a good toxicity profile and local control rate, even if any long term survivors would be expected. New treatment modalities like Cyberknife are also being implemented.

Ultrasuoni focalizzati guidati da imaging di risonanza magnetica: studio delle potenziali applicazioni in campo scheletrico, esempio n.1 - osteoma osteoide

La chirurgia con ultrasuoni focalizzati guidati da MRI (MR-g-FUS) è un trattamento di minima invasività, guidato dal più sofisticato strumento di imaging a disposizione, che utilizza a scopo diagnostico e terapeutico forme di energia non ionizzante. Le sue caratteristiche portano a pensare un suo possibile e promettente utilizzo in numerose aree della patologia umana, in particolare scheletrica. L'osteoma osteoide affligge frequentemente pazienti di giovane età, è una patologia benigna, con origine ed evoluzione non chiare, e trova nella termoablazione con radiofrequenza continua sotto guida CT (CT-g-RFA) il suo trattamento di elezione. Questo lavoro ha valutato l’efficacia, gli effetti e la sicurezza del trattamento dell’osteoma osteoide con MR-g-FUS. Sono stati presi in considerazione pazienti arruolati per MR-g-FUS e, come gruppo di controllo, pazienti sottoposti a CT-g-RFA, che hanno raggiunto un follow-up minimo di 18 mesi (rispettivamente 6 e 24 pazienti). Due pazienti erano stati esclusi dal trattamento MR-g-FUS per claustrofobia (2/8). Tutti i trattamenti sono stati portati a termine con successo tecnico e clinico. Non sono state registrate complicanze o eventi avversi correlati all’anestesia o alle procedure di trattamento, e tutti i pazienti sono stati dimessi regolarmente dopo 12-24 ore. La durata media dei trattamenti di MR-g-FUS è stata di 40±21 min. Da valori di score VAS pre-trattamento oscillanti tra 6 e 10 (su scala 0-10), i trattamenti hanno condotto tutti i pazienti a VAS 0 (senza integrazioni farmacologiche). Nessun paziente ha manifestato segni di persistenza di malattia o di recidiva al follow-up. Nonostante la neurolisi e la risoluzione dei sintomi, la perfusione del nidus è stata ritrovata ancora presente in oltre il 70% dei casi sottoposti a MR-g-FUS (4/6 pazienti). I risultati derivati da un'analisi estesa a pazienti più recentemente arruolati confermano questi dati. Il trattamento con MR-g-FUS sembra essere efficace e sicuro nel risolvere la sintomatologia dell'osteoma osteoide.

Applications of metrological techniques for clinical implementation of dosimetry and radiobiology in molecular radiotherapy

Molecular radiotherapy (MRT) is a fast developing and promising treatment for metastasised neuroendocrine tumours. Efficacy of MRT is based on the capability to selectively "deliver" radiation to tumour cells, minimizing administered dose to normal tissues. Outcome of MRT depends on the individual patient characteristics. For that reason, personalized treatment planning is important to improve outcomes of therapy. Dosimetry plays a key role in this setting, as it is the main physical quantity related to radiation effects on cells. Dosimetry in MRT consists in a complex series of procedures ranging from imaging quantification to dose calculation. This doctoral thesis focused on several aspects concerning the clinical implementation of absorbed dose calculations in MRT. Accuracy of SPECT/CT quantification was assessed in order to determine the optimal reconstruction parameters. A model of PVE correction was developed in order to improve the activity quantification in small volume, such us lesions in clinical patterns. Advanced dosimetric methods were compared with the aim of defining the most accurate modality, applicable in clinical routine. Also, for the first time on a large number of clinical cases, the overall uncertainty of tumour dose calculation was assessed. As part of the MRTDosimetry project, protocols for calibration of SPECT/CT systems and implementation of dosimetry were drawn up in order to provide standard guidelines to the clinics offering MRT. To estimate the risk of experiencing radio-toxicity side effects and the chance of inducing damage on neoplastic cells is crucial for patient selection and treatment planning. In this thesis, the NTCP and TCP models were derived based on clinical data as help to clinicians to decide the pharmaceutical dosage in relation to the therapy control and the limitation of damage to healthy tissues. Moreover, a model for tumour response prediction based on Machine Learning analysis was developed.

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.

Magnetic Resonance Imaging-Derived biomarkers of Isocitrate-Dehydrogenase mutation in diffuse gliomas: a conventional MR and Diffusion Weighted Imaging study.

The introduction of molecular criteria into the classification of diffuse gliomas has added interesting practical implications to glioma management. This has created a new clinical need for correlating imaging characteristics with glioma genotypes, also known as radiogenomics or imaging genomics. Whilst many studies have primarily focused on the use of advanced magnetic resonance imaging (MRI) techniques for radiogenomics purposes, conventional MRI sequences still remain the reference point in the study and characterization of brain tumours. Moreover, a different approach may rely on diffusion-weighted imaging (DWI) usage, which is considered a “conventional” sequence in line with recently published directions on glioma imaging. In a non-invasive way, it can provide direct insight into the microscopic physical properties of tissues. Considering that Isocitrate-Dehydrogenase gene mutations may reflect alterations in metabolism, cellularity, and angiogenesis, which may manifest characteristic features on an MRI, the identification of specific MRI biomarkers could be of great interest in managing patients with brain gliomas. My study aimed to evaluate the presence of specific MRI-derived biomarkers of IDH molecular status through conventional MRI and DWI sequences.