Pattern recognition methods applied to medical imaging: lung nodule detection in computed tomography images

Lung cancer is one of the main public health issues in developed countries. The overall 5-year survival rate is only 10−16%, although the mortality rate among men in the United States has started to decrease by about 1.5% per year since 1991 and a similar trend for the male population has been observed in most European countries. By contrast, in the case of the female population, the survival rate is still decreasing, despite a decline in the mortality of young women has been ob- served over the last decade. Approximately 70% of lung cancers are diagnosed at too advanced stages for the treatments to be effective. The five-year survival rate for early-stage lung cancers (stage I), which can reach 70%, is sensibly higher than for cancers diagnosed at more advanced stages. Lung cancer most commonly manifests itself as non-calcified pulmonary nodules. The CT has been shown as the most sensitive imaging modality for the detection of small pulmonary nodules, particularly since the introduction of the multi-detector-row and helical CT technologies. Screening programs based on Low Dose Computed Tomography (LDCT) may be regarded as a promising technique for detecting small, early-stage lung cancers. The efficacy of screening programs based on CT in reducing the mortality rate for lung cancer has not been fully demonstrated yet, and different and opposing opinions are being pointed out on this topic by many experts. However, the recent results obtained by the National Lung Screening Trial (NLST), involving 53454 high risk patients, show a 20% reduction of mortality when the screening program was carried out with the helical CT, rather than with a conventional chest X-ray. LDCT settings are currently recommended by the screening trial protocols. However, it is not trivial in this case to identify small pulmonary nodules,due to the noisier appearance of the images in low-dose CT with respect to the standard-dose CT. Moreover, thin slices are generally used in screening programs, thus originating datasets of about 300 − 400 slices per study. De- pending on the screening trial protocol they joined, radiologists can be asked to identify even very small lung nodules, which is a very difficult and time- consuming task. Lung nodules are rather spherical objects, characterized by very low CT values and/or low contrast. Nodules may have CT values in the same range of those of blood vessels, airway walls, pleura and may be strongly connected to them. It has been demonstrated, that a large percent- age of nodules (20 − 35%) is actually missed in screening diagnoses. To support radiologists in the identification of early-stage pathological objects, about one decade ago, researchers started to develop CAD methods to be applied to CT examinations. Within this framework, two CAD sub-systems are proposed: CAD for internal nodules (CADI), devoted to the identification of small nodules embedded in the lung parenchyma, i.e. Internal Nodules (INs) and CADJP, devoted the identification of nodules originating on the pleura surface, i.e. Juxta-Pleural Nodules (JPNs) respectively. As the training and validation sets may drastically influence the performance of a CAD system, the presented approaches have been trained, developed and tested on different datasets of CT scans (Lung Image Database Consortium (LIDC), ITALUNG − CT) and finally blindly validated on the ANODE09 dataset. The two CAD sub-systems are implemented in the ITK framework, an open source C++ framework for segmentation and registration of medical im- ages, and the rendering of the obtained results are achieved using VTK, a freely available software system for 3D computer graphics, image processing and visualization. The Support Vector Machines (SVMs) are implemented in SVMLight. The two proposed approaches have been developed to detect solid nodules, since the number of Ground Glass Opacity (GGO) contained in the available datasets has been considered too low. This thesis is structured as follows: in the first chapter the basic concepts about CT and lung anatomy are explained. The second chapter deals with CAD systems and their evaluation methods. In the third chapter the datasets used for this work are described. In chapter 4 the lung segmentation algorithm is explained in details, and in chapter 5 and 6 the algorithms to detect internal and juxta-pleural candidates are discussed. In chapter 7 the reduction of false positives findings is explained. In chapter 8 results of the train and validation sessions are shown. Finally in the last chapter the conclusions are drawn

Evaluation of algorithms for photon depth of interaction estimation for the TRIMAGE PET component

The TRIMAGE consortium aims to develop a multimodal PET/MR/EEG brain scanner dedicated to the early diagnosis of schizophrenia and other mental health disorders. The PET component features a full ring made of 18 detectors, each one consisting of twelve 8x8 Silicon PhotoMultipliers (SiPMs) tiles coupled to two segmented LYSO crystal matrices with staggered layers. In each module, the crystals belonging to the bottom layer are coupled one to one to the SiPMs, while each crystal of the top layer is coupled to four crystals of the bottom layer. This configuration allows to increase the crystal thickness while reducing the depth of interaction uncertainty, as photons interacting in different layers are expected to produce different light patterns on the SiPMs. The PET scanner will implement the pixel/layer identification on a front-end FPGA. This will allow increasing the effective bandwidth, setting at the same time restrictions on the complexity of the algorithms to be implemented. In this work two algorithms whose implementation is feasible directly on an FPGA are presented and evaluated. The first algorithm implements a method based on adaptive thresholding, while the other uses a linear Support Vector Machine (SVM) trained to distinguish the light pattern coming from two different layers. The validation of the algorithm performance is carried out by using simulated data generated with the GAMOS Monte Carlo. The obtained results show that the achieved accuracy in layer and pixel identification is above the 90% for both the proposed approaches

First full-beam PET acquisitions in proton therapy with a modular dual-head dedicated system

During particle therapy irradiation, positron emitters with half-lives ranging from 2 to 20 min are generated from nuclear processes. The half-lives are such that it is possible either to detect the positron signal in the treatment room using an in-beam positron emission tomography (PET) system, right after the irradiation, or to quickly transfer the patient to a close PET/CT scanner. Since the activity distribution is spatially correlated with the dose, it is possible to use PET imaging as an indirect method to assure the quality of the dose delivery. In this work, we present a new dedicated PET system able to operate in-beam. The PET apparatus consists in two 10 cm × 10 cm detector heads. Each detector is composed of four scintillating matrices of 23 × 23 LYSO crystals. The crystal size is 1.9 mm × 1.9 mm × 16 mm. Each scintillation matrix is read out independently with a modularized acquisition system. The distance between the two opposing detector heads was set to 20 cm. The system has very low dead time per detector area and a 3 ns coincidence window, which is capable to sustain high single count rates and to keep the random counts relatively low. This allows a new full-beam monitoring modality that includes data acquisition also while the beam is on. The PET system was tested during the irradiation at the CATANA (INFN, Catania, Italy) cyclotron-based proton therapy facility. Four acquisitions with different doses and dose rates were analysed. In all cases the random to total coincidences ratio was equal or less than 25%. For each measurement we estimated the accuracy and precision of the activity range on a set of voxel lines within an irradiated PMMA phantom. Results show that the inclusion of data acquired during the irradiation, referred to as beam-on data, improves both the precision and accuracy of the range measurement with respect to data acquired only after irradiation. Beam-on data alone are enough to give precisions better than 1 mm when at least 5 Gy are delivered

Online monitoring for proton therapy: A real-time procedure using a planar PET system

In this study a procedure for range verification in proton therapy by means of a planar in-beam PET system is presented. The procedure consists of two steps: the measurement of the β+-activity induced in the irradiated body by the proton beam and the comparison of these distributions with simulations. The experimental data taking was performed at the CNAO center in Pavia, Italy, irradiating plastic phantoms. For two different cases we demonstrate how a real-time feedback of the delivered treatment plan can be obtained with in-beam PET imaging

Full-beam performances of a PET detector with synchrotron therapeutic proton beams

Treatment quality assessment is a crucial feature for both present and nextgeneration ion therapy facilities. Several approaches are being explored, based on prompt radiation emission or on PET signals by β+;-decaying isotopes generated by beam interactions with the body. In-beam PET monitoring at synchrotron-based ion therapy facilities has already been performed, either based on inter-spill data only, to avoid the influence of the prompt radiation, or including both in-spill and inter-spill data. However, the PET images either suffer of poor statistics (inter-spill) or are more influenced by the background induced by prompt radiation (in-spill). Both those problems are expected to worsen for accelerators with improved duty cycle where the inter-spill interval is reduced to shorten the treatment time. With the aim of assessing the detector performance and developing techniques for background reduction, a test of an in-beam PET detector prototype was performed at the CNAO synchrotron-based ion therapy facility in full-beam acquisition modality. Data taken with proton beams impinging on PMMA phantoms showed the system acquisition capability and the resulting activity distribution, separately reconstructed for the in-spill and the inter-spill data. The coincidence time resolution for in-spill and inter-spill data shows a good agreement, with a slight deterioration during the spill. The data selection technique allows the identification and rejection of most of the background originated during the beam delivery. The activity range difference between two different proton beam energies (68 and 72 MeV) was measured and found to be in submillimeter agreement with the expected result. However, a slightly longer (2 mm) absolute profile length is obtained for in-spill data when compared to inter-spill data

A new PET prototype for proton therapy: comparison of data and Monte Carlo simulations

Ion beam therapy is a valuable method for the treatment of deep-seated and radio-resistant tumors thanks to the favorable depth-dose distribution characterized by the Bragg peak. Hadrontherapy facilities take advantage of the specific ion range, resulting in a highly conformal dose in the target volume, while the dose in critical organs is reduced as compared to photon therapy. The necessity to monitor the delivery precision, i.e. the ion range, is unquestionable, thus different approaches have been investigated, such as the detection of prompt photons or annihilation photons of positron emitter nuclei created during the therapeutic treatment. Based on the measurement of the induced β+ activity, our group has developed various in-beam PET prototypes: the one under test is composed by two planar detector heads, each one consisting of four modules with a total active area of 10 × 10 cm2. A single detector module is made of a LYSO crystal matrix coupled to a position sensitive photomultiplier and is read-out by dedicated frontend electronics. A preliminary data taking was performed at the Italian National Centre for Oncological Hadron Therapy (CNAO, Pavia), using proton beams in the energy range of 93–112 MeV impinging on a plastic phantom. The measured activity profiles are presented and compared with the simulated ones based on the Monte Carlo FLUKA package

Particle beam microstructure reconstruction and coincidence discrimination in PET monitoring for hadron therapy

Positron emission tomography is one of the most mature techniques for monitoring the particles range in hadron therapy, aiming to reduce treatment uncertainties and therefore the extent of safety margins in the treatment plan. In-beam PET monitoring has been already performed using inter-spill and post-irradiation data, i.e., while the particle beam is off or paused. The full beam acquisition procedure is commonly discarded because the particle spills abruptly increase the random coincidence rates and therefore the image noise. This is because random coincidences cannot be separated by annihilation photons originating from radioactive decays and cannot be corrected with standard random coincidence techniques due to the time correlation of the beam-induced background with the ion beam microstructure. The aim of this paper is to provide a new method to recover in-spill data to improve the images obtained with full-beam PET acquisitions. This is done by estimating the temporal microstructure of the beam and thus selecting input PET events that are less likely to be random ones. The PET detector we used was the one developed within the INSIDE project and tested at the CNAO synchrotron-based facility. The data were taken on a PMMA phantom irradiated with 72 MeV proton pencil beams. The obtained results confirm the possibility of improving the acquired PET data without any external signal coming from the synchrotron or ad-hoc detectors

Online proton therapy monitoring: Clinical test of a Silicon-photodetector-based in-beam PET

Particle therapy exploits the energy deposition pattern of hadron beams. The narrow Bragg Peak at the end of range is a major advantage but range uncertainties can cause severe damage and require online verification to maximise the effectiveness in clinics. In-beam Positron Emission Tomography (PET) is a non-invasive, promising in-vivo technique, which consists in the measurement of the β+ activity induced by beam-tissue interactions during treatment, and presents the highest correlation of the measured activity distribution with the deposited dose, since it is not much influenced by biological washout. Here we report the first clinical results obtained with a state-of-the-art in-beam PET scanner, with on-the-fly reconstruction of the activity distribution during irradiation. An automated time-resolved quantitative analysis was tested on a lacrimal gland carcinoma case, monitored during two consecutive treatment sessions. The 3D activity map was reconstructed every 10 s, with an average delay between beam delivery and image availability of about 6 s. The correlation coefficient of 3D activity maps for the two sessions (above 0.9 after 120 s) and the range agreement (within 1 mm) prove the suitability of in-beam PET for online range verification during treatment, a crucial step towards adaptive strategies in particle therapy

Studio e modellizzazione di pattern nei cristalli liquidi nematici

La natura genera una numerosa quantita' di strutture organizzate, a partire dalle dune nella sabbia per finire alle impronte digitali e alle macchie sul manto sul pelo degli animali. Tutti questi fenomeni, a dispetto della loro diversa origine, hanno un meccanismo basilare in comune che e' l'oggetto di questa tesi. Gli strumenti utilizzati per modellare un tale comportamento sono la teoria dei sistemi dinamici non lineari e la teoria delle biforcazioni; di questi argomenti sara' data una breve descrizione nel capitolo iniziale di questo lavoro. Noi ci occuperemo solo di sistemi poco oltre la soglia dell'instabilita' primaria e per portare a termine questo obbiettivo useremo una teoria perturbativa che prende il nome di "espansione debolmente non lineare". In questo approccio e' cruciale la separazione delle scale che avviene alla soglia della biforcazione: le deformazioni che avvengono su scala "veloce" sono regolate dall'analisi lineare, mentre le variazioni su scala "lenta" evolvono secondo un'equazione di forma "universale" che chiameremo "equazione di ampiezza" . Tale equazione rappresenta indubbiamente un semplice modello che ci consente di studiare una grande quantita' di sistemi, che esibiscono pattern, vicino alla soglia della biforcazione primaria senza dover ricorrere alle equazioni complete del fenomeno che molto spesso, nel caso della formazione di pattern, sono fuori dalla portata numerica dei piu' potenti calcolatori oggi esistenti. Numerosi sistemi che esibiscono pattern nello spazio e nel tempo possono essere rappresentati da tale metodo, tuttavia il loro dettaglio microscopico non influisce sulla forma dell'equazione ma solo sui valori che assumono i suoi coefficienti. Nella fattispecie l'equazione di ampiezza ha la forma di un'equazione assai nota in letteratura, perche' utilizzata in molti altri ambiti della fisica: l'equazione di Landau-Ginzburg. In questo lavoro sono state impiegate due differenti equazioni di ampiezza : l'equazione a coefficienti reali (RGL) che descrive i pattern stazionari e quella a coefficienti complessi (CGL) che descrive pattern tempo dipendenti. In questa tesi faremo principalmente riferimento allo studio delle instabilita' elettroconvettive nei cristalli liquidi nematici (EHC), tuttavia bisogna sottolineare che l'interesse di questo lavoro di tesi non va in particolare al sistema sopra citato ma allo studio e alla modellazione degli aspetti universali che si presentano nell'ambito della formazione di pattern. Sara' esposta una breve fenomenologia della EHC e una descrizione basilare di un esperimento "ideale" volto a riprodurre il fenomeno della formazione di pattern. Le instabilita' elettroconvettive possono essere modellate con il formalismo dell'equazione di ampiezza dando una descrizione basilare di alcuni fenomeni e in buon accordo con le osservazioni sperimentali. In particolare la nostra attenzione si e' rivolta allo studio dei difetti topologici e al loro moto nei pattern spazialmente periodici. Lo studio del moto dei difetti e' stato svolto numericamente a causa della difficolta' nel risolvere analiticamente le equazioni di ampiezza; a questo proposito sono state scritte varie simulazioni unidimensionali e bidimensionali. Le simulazioni numeriche sono state implementate con algoritimi spettrali di tipo "leap frog" e "exponential-timestep" che hanno garantito buone prestazioni anche su un computer di tipo standard. La parte originale di questo lavoro consiste, oltre che nella scrittura delle simulazioni e nell'adattamento di alcuni algoritmi alle situazioni del caso, nello studio del moto dei difetti topologici e della loro interazione nei vari regimi dell'equazioni reali e complesse undimensionali e bidimensionali :sono stati esplorati vari regimi delle equazioni di ampiezza cercandone uno in cui fosse possibile osservare fenomeni di moto non banali dei difetti . E' importante sottolineare che l'intento di questo lavoro di tesi non e' studiare in particolare l'EHC quanto piuttosto analizzare una generica classe di sistemi che esibiscono una formazione di pattern di cui l'elettroconvezione nei cristalli liquidi e' uno degli esempi piu' semplici in natura

An automatic algorithm to exploit the symmetries of the system response matrix in PET iterative reconstruction

Positron emission tomography (PET) iterative 3D reconstruction is a very computational demanding task. One of the main issues of the iterative reconstruction concerns the management of the system response matrix (SRM). The SRM models the relationship between the projection and the voxel space and its memory footprint can easily exceed hundreds of GB. Moreover, in order to make the reconstruction fast enough not to hinder its practical application, the SRM must be stored in the random access memory of the workstation used for the reconstruction. This issue is normally solved by implementing efficient storage schemes and by reducing the number of redundant patterns in the SRM through symmetries. However, finding a sufficient number of symmetries is often non-trivial and is typically performed using dedicated solutions that cannot be exported to different detectors and geometries. In this paper, an automatic approach to reduce the memory footprint of a pre-computed SRM is described. The proposed approach was named symmetry search algorithm (SSA) and consists in an algorithm that searches for some of the redundant patterns present in the SRM, leading to its lossy compression. This approach was built to detect translations, reflections and coordinates swap in voxel space. Therefore, it is particularly well suited for those scanners where some of the rotational symmetries are broken, e.g. small animal scanner where the modules are arranged in a polygonal ring made of few elements, and dual head planar PET systems. In order to validate this approach, the SSA is applied to the SRM of a preclinical scanner (the IRIS PET/CT). The data acquired by the scanner were reconstructed with a dedicated maximum likelihood estimation maximization algorithm with both the uncompressed and the compressed SRMs. The results achieved show that the information lost due to the SSA compression is negligible. Compression factors up to 52 when using the SSA together with manually inserted symmetries and up to 204 when using the SSA alone, can be obtained for the IRIS SRM. These results come without significant differences in the values and in the main quality metrics of the reconstructed images, i.e. spatial resolution and noise. Although the compression factors depend on the system considered, the SSA is applicable to any SRM and therefore it can be considered a general tool to reduce the footprint of a pre-computed SRM