O câncer de mama é a doença que mais acomete as mulheres em todo o mundo, sendo o tratamento mais eficaz se for diagnosticada em estágio inicial. A partir de 2011, nos programas de rastreamento de países desenvolvidos, vem sendo empregada uma nova modalidade de exame, a tomossíntese digital mamária (Digital Breast Tomosynthesis - DBT), que possui diversas vantagens se comparada à mamografia digital. No exame, o médico radiologista busca por sinais suspeitos na imagem, como: nódulos, microcalcificações e distorção arquitetural mamária (DAM). Sendo que, este último pode representar o estágio mais inicial de um câncer em formação, podendo se manifestar antes da formação de qualquer outra lesão. No entanto, a DAM é difícil de ser detectada pois modifica o tecido mamário de forma sutil, não havendo qualquer formação de massa ou a borda definida. Os sistemas computacionais de auxílio ao diagnóstico (Computer-Aided Detection - CAD) vêm apresentando alto desempenho na detecção de nódulos e microcalcificações mamárias, mas para o caso da DAM, o desempenho ainda é insatisfatório. Algumas limitações são normalmente reportadas nos algoritmos adotados para detectar automaticamente a DAM. O presente trabalho tem por objetivo propor novas abordagens para aumentar a precisão dos métodos computacionais de detecção: o uso de descritores de micro-padrões local para discriminação de áreas suspeitas; redução de falsos-positivos; uso do volume 3D fornecido pelo exame de DBT e; uso de arquitetura de aprendizagem profunda para discriminação e classificação de regiões suspeitas. Os diversos testes efetuados em cada proposta mostraram que é possível melhorar as taxas de detecção da DAM, mesmo para imagens de DBT onde ainda não há um esquema computacional de detecção bem estabelecido. / Breast cancer is the disease that most affects women worldwide and is the most effective treatment if it is diagnosed at early stages. Since 2011, in developed countries screening programs has been employed a new exam, the digital breast tomosynthesis (DBT), which has several advantages compared to the digital mammography. In the exam, the radiologist looks for suspicious signs in the image such as masses, microcalcifications and architectural distortion of breast (ADB). Since the later may represent the earliest sign of a cancer in formation, it may manifests before the formation of any other lesion. However, ADB is difficult to be detected due to its subtly changes the breast tissue, with no mass or defined shape. Computer-aided detection (CAD) systems have shown good results in the detection of masses and microcalcifications, however, for ADB the performance is still poor. Several weakness are reported in the pipeline adopted to automatic detection of ADB. The present work aims to propose new approaches to increase the accuracy of the current CAD pipeline: the use of local micro-pattern descriptors to discriminate suspicious areas; false-positives reduction; automatic detection of ADB in DBT images using and tridimensionality of the exam and; use of deep learning architecture to discriminate and classify suspicious regions. The several tests performed on each proposal showed that it is possible to improve the detection rates even for DBT images where there is no established CAD pipeline.

<p>We present a new x-ray imaging technique, Correlation Imaging (CI), for improved breast and lung cancer detection. In CI, multiple low-dose radiographic images are acquired along a limited angular arc. Information from unreconstructed angular projections is directly combined to reduce the effect of overlying anatomy - the largest bottleneck in diagnosing cancer with projection imaging. In addition, CI avoids reconstruction artifacts that otherwise limit the performance of tomosynthesis. This work involved assessing the feasibility of the CI technique, its optimization, and its implementation for breast and chest imaging.</p><p>First a theoretical model was developed to determine the diagnostic information content of projection images using a mathematical observer. The model was benchmarked for a specific application in assessing the impact of reduced dose in mammography. Using this model, a multi-factorial task-based framework was developed to optimize the image acquisition of CI using existing low-dose clinical data. The framework was further validated using a CADe processor. Performance of CI was evaluated on mastectomy specimens at clinically relevant doses and further compared to tomosynthesis. Finally, leveraging on the expected improvement in breast imaging, a new hardware capable of CI acquisition for chest imaging was designed, prototyped, evaluated, and experimentally validated.</p><p>The theoretical model successfully predicted diagnostic performance on mammographic backgrounds, indicating a possible reduction in mammography dose by as much as 50% without adversely affecting lesion detection. Application of this model on low-dose clinical data showed that peak CI performance may be obtained with 15-17 projections. CAD results confirmed similar trends. Mastectomy specimen results at higher dose revealed that the performance of optimized breast CI may exceed that of mammography and tomosynthesis by 18% and 8%, respectively. Furthermore, for both CI and tomosynthesis, highest dose setting and maximum angular span with an angular separation of 2.75o was found to be optimum, indicating a threshold in the number of projections per angular span for optimum performance. </p><p>Finally, for the CI chest imaging system, the positional errors were found to be within 1% and motion blur to have minimal impact on the system MTF. The clinical images had excellent diagnostic quality for potentially improved lung cancer detection. The system was found to be robust and scalable to enable advanced applications for chest radiography, including novel tomosynthesis trajectories and stereoscopic imaging.</p> / Dissertation

<p>Digital tomosynthesis (DTS) is a quasi-three-dimensional (3D) imaging technique which reconstructs images from a limited angle of cone-beam projections with shorter acquisition time, lower imaging dose, and less mechanical constraint than full cone-beam CT (CBCT). However, DTS images reconstructed by the conventional filtered back projection method have low plane-to-plane resolution, and they do not provide full volumetric information for target localization due to the limited angle of the DTS acquisition. </p><p>This dissertation presents the optimization and clinical implementation of image guided radiation therapy using limited-angle projections.</p><p>A hybrid multiresolution rigid-body registration technique was developed to automatically register reference DTS images with on-board DTS images to guide patient positioning in radiation therapy. This hybrid registration technique uses a faster but less accurate static method to achieve an initial registration, followed by a slower but more accurate adaptive method to fine tune the registration. A multiresolution scheme is employed in the registration to further improve the registration accuracy, robustness and efficiency. Normalized mutual information is selected as the criterion for the similarity measure, and the downhill simplex method is used as the search engine. This technique was tested using image data both from an anthropomorphic chest phantom and from head-and-neck cancer patients. The effects of the scan angle and the region-of-interest size on the registration accuracy and robustness were investigated. The average capture ranges in single-axis simulations with a 44° scan angle and a large ROI covering the entire DTS volume were between -31 and +34 deg for rotations and between -89 and +78 mm for translations in the phantom study, and between -38 and +38 deg for rotations and between -58 and +65 mm for translations in the patient study.</p><p>Additionally, a novel limited-angle CBCT estimation method using a deformation field map was developed to optimally estimate volumetric information of organ deformation for soft tissue alignment in image guided radiation therapy. The deformation field map is solved by using prior information, a deformation model, and new projection data. Patients' previous CBCT data are used as the prior information, and the new patient volume to be estimated is considered as a deformation of the prior patient volume. The deformation field is solved by minimizing bending energy and maintaining new projection data fidelity using a nonlinear conjugate gradient method. The new patient CBCT volume is then obtained by deforming the prior patient CBCT volume according to the solution to the deformation field. The method was tested for different scan angles in 2D and 3D cases using simulated and real projections of a Shepp-Logan phantom, liver, prostate and head-and-neck patient data. Hardware acceleration and multiresolution scheme are used to accelerate the 3D estimation process. The accuracy of the estimation was evaluated by comparing organ volume, similarity and pixel value differences between limited-angle CBCT and full-rotation CBCT images. Results showed that the respiratory motion in the liver patient, rectum volume change in the prostate patient, and the weight loss and airway volume change in the head-and-neck patient were accurately estimated in the 60° CBCT images. This new estimation method is able to optimally estimate the volumetric information using 60-degree projection images. It is both technically and clinically feasible for image-guidance in radiation therapy.</p> / Dissertation

The current thesis is focused on the study of tomosynthesis techniques applied on breast imaging, in order to improve the detection of breast lesions. Breast Tomosynthesis (BT) is a pseudo-three-dimensional (3D) x-ray imaging technique that provides reconstructed tomographic images from a set of angular projections taken in a limited arc around the breast, with dose levels similar to those of a two-view conventional mammography. Simulation studies and clinical trials suggest that BT is very useful for imaging the breast in an attempt to optimize the detection and characterization of lesions particularly in dense breasts and has the potential to reduce the recall rate. Reconstruction algorithms and acquisition parameters are critical for the quality of reconstructed slices. The aim of this research is to explore tomosynthesis modalities for breast imaging and evaluate them against existing mammographic techniques as well as to investigate the effect of reconstruction algorithms and acquisition parameters on the image quality of tomosynthetic slices. A specific aim and innovation of the study was to demonstrate the feasibility of combining BT and monochromatic radiation for 3D breast imaging, an approach that had not been studied thoroughly yet. For the purposes of this study a computer-based platform has been developed in Matlab incorporating reconstruction algorithms and filtering techniques for BT applications. It is fully parameterized and has a modular architecture for easy addition of new algorithms. Simulations studies with the XRayImaging Simulator and experimental work at ELETTRA Synchrotron facilities in Trieste, Italy, have been performed using software and complex hardware phantoms, of realistic shape and size, consisting of materials mimicking the breast tissue. The work has been carried out in comparison to conventional BT and mammography and demonstrates the feasibility of the studied new technique and the potential advantages of using BT with synchrotron modality for the detection of breast low- and high-contrast breast lesions such as masses and microcalcifications (μCs). Evaluations of both simulation and experimental tomograms demonstrated superior visibility of all reconstructed features using appropriately optimized filtered algorithms. Moreover, image quality and evaluation metrics are improved with extending the acquisition length for the masses. The visualization of μCs was found less sensitive to this parameter due to their high inherent contrast. Breast tomosynthesis shows advantages in visualizing features of small size within phantoms of increased thickness and especially in bringing into focus and localizing low-contrast masses hidden in a highly heterogeneous background with superimposed structures. Monochromatic beams can result in better tissue differentiation and in combination with BT can lead to improvement of features’ visibility, better detail and higher contrast. Monochromatic BT provided improved image quality at lower incident exposures, compared to conventional mammography, concerning mass detection and visibility of borders, which is important for their characterization, especially when they are spiculated. Overall it has been proved that while reducing the radiation dose, monochromatic beams combined with BT, result in an improvement of image quality. These findings are encouraging for the development of a tomosynthesis system based on monochromatic beams. / Η συγκεκριμένη διατριβή εστιάζει στη μελέτη των τεχνικών της τομοσύνθεσης όπως αυτές εφαρμόζονται στην απεικόνιση του μαστού, με στόχο την βελτίωση της ανίχνευσης των αλλοιώσεων του μαστού. Η τομοσύνθεση του μαστού είναι μια τεχνική ψευδό-τρισδιάστατης απεικόνισης με ακτίνες-χ που ανακατασκευάζει τομογραφικές εικόνες χρησιμοποιώντας μια σειρά προβολικών λήψεων υπό διαφορετικές γωνίες σε περιορισμένο τόξο γύρω από το μαστό και με δόσεις ακτινοβολίας παρόμοιες με εκείνες που απαιτούνται για τις δύο τυπικές λήψεις της κλασικής μαστογραφία. Μελέτες προσομοίωσης και κλινικές δοκιμές δείχνουν πως η τομοσύνθεση του μαστού βελτιώνει την απεικόνιση του μαστού, με αποτέλεσμα την καλύτερη ανίχνευση των αλλοιώσεων ειδικά σε πυκνούς μαστούς και αναμένεται ότι η εφαρμογή της θα μπορούσε να μειώσει την ανάγκη επανάληψης της εξέτασης. Οι αλγόριθμοι ανακατασκευής και οι παράμετροι λήψης των προβολικών εικόνων είναι μεγάλης σημασίας για την ποιότητα των ανακατασκευασμένων τομογραφικών εικόνων. Ο στόχος αυτής της έρευνας είναι να μελετήσει τεχνικές που βασίζονται στην τομογραφική απεικόνιση του μαστού και να τις συγκρίνει με υπάρχουσες τεχνικές μαστογραφίας καθώς και να διερευνήσει την επίδραση των αλγορίθμων ανακατασκευής και των παραμέτρων λήψης στην ποιότητα της ανακατασκευασμένης τομογραφικής εικόνας. Ένας συγκεκριμένος στόχος και καινοτομία αυτής της μελέτης ήταν να διερευνήσει πιθανά πλεονεκτήματα και να επιδείξει την σκοπιμότητα του συνδυασμού της τομοσύνθεσης του μαστού με μονοχρωματική ακτινοβολία που παράγεται από σύγχροτρον για την τρισδιάστατη απεικόνιση του μαστού, μία προσέγγιση που δεν είχε ακόμα μελετηθεί εκτενώς. Για τις ανάγκες αυτής της μελέτης αναπτύχθηκε στο Matlab μια πλατφόρμα που ενσωματώνει αλγορίθμους ανακατασκευής και τεχνικές φιλτραρίσματος για τομοσύνθεση μαστού. Η εφαρμογή είναι πλήρως παραμετροποιημένη και σχεδιασμένη ώστε να είναι εύκολη η προσθήκη νέων αλγορίθμων. Προσομοιώσεις με τη χρήση του προσομοιωτή XRayImagingSimulator καθώς και πειραματικές μελέτες στις εγκαταστάσεις σύγχροτρον ELETΤRA, στην Τεργέστη της Ιταλίας έχουν πραγματοποιηθεί, με χρήση απλών και σύνθετων ομοιωμάτων μαστού, μιμούμενα τις ιδιότητες του ιστού του μαστού, με ρεαλιστικό μέγεθος και σχήμα. Οι μελέτες έχουν πραγματοποιηθεί σε σύγκριση με την τυπική τομοσύνθεση μαστογραφία και δείχνουν πόσο εφικτή είναι η νέα τεχνική και τα δυνητικά πλεονεκτήματα της τομοσύνθεσης του μαστού με χρήση μονοχρωματικής ακτινοβολίας για την εύρεση χαμηλής και υψηλής αντίθεσης αλλοιώσεων όπως μάζες και μικροαποτιτανώσεις. Εκτιμήσεις των τομογραφικών εικόνων που έχουν προκύψει τόσο από προσομοιώσεις όσο και από πειράματα δείχνουν βελτιωμένη απεικόνιση όλων των ανακατασκευασμένων στοιχείων ενδιαφέροντος με χρήση κατάλληλων βελτιστοποιημένων φίλτρων. Επιπλέον, η ποιότητα της εικόνας βελτιώνεται με τη διεύρυνση του τόξου λήψης για τις μάζες, ενώ η απεικόνιση των μικροαποτιτανώσεων βρέθηκε να είναι λιγότερο ευαίσθητη σε αυτή τη παράμετρο λόγω της υψηλότερης αντίθεσης που έχουν σε σχέση με τον περιβάλλοντα φυσιολογικό ιστό του μαστού. Η τομοσύνθεση του μαστού φάνηκε να έχει πλεονεκτήματα στην απεικόνιση αλλοιώσεων μικρού μεγέθους και πιο συγκεκριμένα στο να διακρίνει και να ανιχνεύει χαμηλής αντίθεσης μάζες, μέσα σε πυκνούς μαστούς με έντονα ετερογενή σύσταση, μετριάζοντας τα προβλήματα επικάλυψης. Η μονοχρωματική ακτινοβολία μπορεί να προσφέρει καλύτερη διαφοροποίηση των ιστών του μαστού και σε συνδυασμό με την τομοσύνθεση μπορεί να οδηγήσει στην βελτίωση της απεικόνισης των αλλοιώσεων και στην παραγωγή εικόνων με καλύτερη λεπτομέρεια και υψηλότερη αντίθεση. Γενικά βρέθηκε ότι η μονοχρωματική τομοσύνθεση του μαστού παρέχει βελτιωμένη ποιότητα εικόνας, σε σύγκριση με την κλασική μαστογραφία, όσον αφορά την ανίχνευση όγκων και την ορατότητα των περιγραμμάτων τους, που είναι σημαντική για τον χαρακτηρισμό των μαζών, ειδικά όταν δεν έχουν καλώς καθορισμένα όρια. Συνολικά η μελέτη αυτή έδειξε ότι ακόμα και με μικρότερη δόση ακτινοβολίας, η χρήση μονοχρωματικής ακτινοβολίας σε συνδυασμό με την τομοσύνθεση του μαστού, έχουν ως αποτέλεσμα την βελτίωση της εικόνας, γεγονός που είναι ενθαρρυντικό για την ανάπτυξη ενός συστήματος τομοσύνθεσης βασισμένο σε ακτίνες-χ μονοχρωματικής δέσμης.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - CAPES / The breast tomosynthesis is appearing in several studies that aim to investigate most appropriate parameters to obtaining images of high quality with dose values of ionizing radiation within the limits imposed for digital mammography. The parameters are related to an angular range limited used in examinations, the number of projections, the X-rays beam energies, and the reconstruction of projections, using specific algorithm, mainly. The advantage of tomosynthesis while a new mammographic technology in relation to the other techniques that employ X-rays is its potential to reduced overlap effect of breast tissue. The contribution of variation of the angle of the beams on the dose in breast examined, due to a change in the geometry used in the examination, should be investigated. To determine the impact that this variation has on the dose in the breast and in other organs and tissues of the human body, an important tool is the Computational Simulation by Monte Carlo. The main proposal of this work was to use the code of Monte Carlo N-Particle eXtended (MCNPX) to study absorbed doses in breast and other organs of the patient during the examination of digital tomosynthesis mammary glands. For this reason, it was used an anthropomorphic female adult phantom with representation of the body, tissues and internal structures and realistic adult patient incorporated in a scenario of radiation from a commercial model of equipment of each. The values of absorbed doses found with the AGMS-M tomosynthesis meter were lower than in digital mammography, the differences between tomosynthesis and mammography were 12.3% using 24 kVp, 10.74% for 28 kVp and 11.21% for 30 kVp. Comparing the experimental and that found in the simulation, the values of the absorbed doses had a smaller difference verified to 24 kVp, of 3.3% and a greater difference to 28 kVp, of 6.2%. The results obtained for the colon and brain have presented relative error (R) above 10% due to the occurrence of natural shielding and distance of these components of the primary beam of radiation. The CCs of equivalent dose in this study show that the estimated dose in the simulator anthropomorphic adult female is much greater in each of which in mammography, because the configuration of the acquisition of different geometry between digital mammography and tomosynthesis, and the sweep time which is higher in each. / A tomossíntese mamária vem aparecendo em vários estudos que buscam investigar tanto parâmetros mais adequados para obtenção de imagens de qualidade quanto valores de doses de radiação ionizante dentro dos limites impostos para mamografia digital. Os parâmetros estão relacionados às energias dos feixes de raios X nos exames, ao intervalo angular das projeções, ao número de projeções, e à reconstrução dessas, principalmente. A reconstrução das imagens é realizada utilizando-se algoritmos específicos. A vantagem da tomossíntese enquanto nova tecnologia em relação as outras técnicas mamográficas que empregam raios X é o seu potencial de imageamento com reduzido efeito de sobreposição do tecido mamário. A contribuição da variação angular dos feixes sobre a dose na mama examinada, devido à alteração na geometria do exame, deve ser investigada. Para determinar o impacto que essa variação exerce sobre a dose na mama e nos demais órgãos e tecidos do corpo humano, uma importante ferramenta é a simulação computacional por Monte Carlo. A proposta principal deste trabalho foi utilizar o código de Monte Carlo N-Particle eXtended (MCNPX) para estudar as doses absorvidas na mama e demais órgãos do paciente durante o exame de tomossíntese digital mamária. Para isso, foi utilizado um simulador antropomórfico adulto feminino com representação dos órgão, tecidos e estruturas internas bem realista de paciente adulto incorporado em cenário de radiação de um modelo comercial de equipamento de tomossíntese. Os valores das doses absorvidas encontrados com o medidor AGMSM em tomossíntese mostrou-se menor do que na mamografia digital, as diferenças entre a tomossíntese e a mamografia foram 12,3% empregando-se 24 kVp, 10,74% para 28 kVp e 11,21% para 30 kVp. Comparando o experimental e o encontrado na simulação, os valores das doses absorvidas teve uma menor diferença verificada para 24 kVp, de 3,3% e uma maior diferença para 28 kVp, de 6,2%. Os resultados obtidos para o cólon e cérebro apresentaram erro relativo (R) acima de 10%, isso devido a decorrência de blindagem natural e da distância desses órgãos ao feixe primário de radiação. Os Coeficientes de conversão de dose equivalente obtidos mostraram que a dose estimada no simulador antropomórfico adulto feminino é maior na tomossíntese do que na mamografia digital, devido a configuração de aquisição de geometria diferente entre a mamografia e tomossíntese, e ao tempo de varredura, que é maior na tomossíntese.

Orientador: Denis Henrique Pinheiro Salvadeo / Resumo: Tomossíntese Mamária Digital (DBT) é uma técnica de imageamento radiográfico, com aquisição de projeções em ângulos limitados utilizando dose reduzida de radiação. Ela tem por objetivo reconstruir fatias tomográficas do interior da mama, possibilitando o diagnóstico precoce de possíveis lesões e aumentando, consequentemente, a probabilidade de cura do paciente. Contudo, devido ao fato de que DBT utiliza doses baixas de radiação, a imagem gerada contém mais ruído que a mamografia digital. Embora a qualidade do exame esteja diretamente relacionada com a dose utilizada, espera-se que a dose de radiação empregada no exame seja a mais baixa possível, mas ainda com qualidade suficiente para que o diagnóstico possa ser realizado, conforme o princípio As Low As Reasonably Achievable (ALARA). Uma das etapas importantes para se buscar o princípio ALARA é a reconstrução tomográfica, que consiste em um software que gera as fatias do interior da mama a partir de um conjunto de projeções 2D de DBT adquiridas. Por outro lado, técnicas de Aprendizado de Máquina, especialmente redes neurais com aprendizado profundo, que recentemente tem evoluído consideravelmente o estado da arte em diversos problemas de Visão Computacional e Processamento de Imagens, tem características adequadas para serem aplicadas também na etapa de reconstrução. Deste modo, este trabalho investigou uma arquitetura básica de rede neural artificial com aprendizado profundo que seja capaz de reconstruir imagens de DBT, espe... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: Digital Breast Tomosynthesis (DBT) is a technique of radiographic imaging, with acquisition of projections at limited angles using reduced dose of radiation. It aims to reconstruct tomographic slices inside the breast, making possible the early diagnosis of possible lesions and, consequently, increasing the probability of cure of the patient. However, due to the fact that DBT uses low doses of radiation, the generated image contains more noise than digital mammography. Although the quality of the exam is directly related to the dose applied, the radiation dose used in the examination is expected to be as low as possible, but still keeping enough quality for the diagnosis to be made, as determined by the As Low As Reasonably Achievable (ALARA) principle. One of the important steps to achieve the ALARA principle is the tomographic reconstruction, which consists of a software that generates slices inside the breast from an acquired set of 2D DBT projections. On the other hand, Machine Learning techniques, especially neural networks with deep learning, that have recently evolved considerably the state-of-the-art in several problems in Computer Vision and Image Processing areas, it has suitable characteristics to be applied also in the reconstruction step. Thus, this work investigated a basic architecture of artificial neural network with deep learning that is capable to reconstruct DBT images, especially focused on noise reduction. Furthermore, considering an additional filtering... (Complete abstract click electronic access below) / Mestre

Cette thèse avait deux buts principaux : a) l'implémentation et l'amélioration d'une méthode de calcul de densité volumique du sein (VBD), et b) la proposition d'une mesure d'irradiation utilisable pour l'évaluation du risque individuel en mammographie avec une méthode pour l'estimer. La densité du sein est connue comme indicateur de risque du cancer. Une méthode de quantification objective de la VBD a été développée, à partir d'approches existantes, et améliorée. La méthode a été implémentée pour deux systèmes de mammographie. Elle repose sur l'étalonnage du système de mammographie et la chaîne d'acquisition avec des fantômes équivalents aux tissus mammaires. Une carte de densité est calculée.La contribution majeure de la thèse consiste en une nouvelle méthode de validation, applicable à tout calcul de VBD d'image de mammographie. Elle consiste à comparer les résultats aux valeurs de densité obtenues par des scanners thoraciques pour la même patiente. Cette validation a été appliquée à notre méthode de calcul et nous avons trouvé 10% d'écart moyen entre les deux méthodes, ce qui est comparable aux résultats de l'état de l'art. Pour le risque d'irradiation individuel, nous proposons de remplacer la dose glandulaire moyenne par l'énergie déposée, qui dépend de la quantité et de la distribution du tissu glandulaire, qui est le tissu à risque. L'énergie volumique déposée est calculée par simulation de Monte Carlo. Le VBD, calculé pour l'image de projection à 0° en tomosynthèse, aide à localiser le tissu glandulaire et à attribuer l'énergie déposée dans les tissus différents. Une proposition a été faite pour des fantômes géométriques, un fantôme texturé et un cas de patiente / In this research project the main goals were a) to implement a method for the computation of the volumetric breast density (VBD), and b) to propose an improved quantity for the assessment of individual radiation-induced risk, in particular during mammography, together with a method to quantify it. The breast density is known as a breast cancer risk factor. The objective quantification of the volumetric breast density was developed, based on already published methods, and improved. The method was implemented for two mammography systems. It is based on the calibration of the mammography system acquisition chain with breast equivalent phantoms and computes a breast density map. Our most important contribution resides in a new validation method applicable to any VBD computation, consisting in comparing its results with the VBD obtained from a thorax CT examination for the same patient. This validation method was applied to our VBD computation. We found an average deviation between mammography and CT of less than 10%. Our results are comparable to the state-of-the-art results for other validation methods. For the individual radiation risk, we proposed to replace the average glandular dose by the imparted energy, which depends on the quantity and distribution of the glandular tissue, which is the tissue at risk. The volumetric imparted energy is computed from Monte Carlo simulations. The VBD, computed for the 0° projection of tomosynthesis exams, helps us to localize the glandular tissue and to attribute the imparted energy to the different tissues. A proposition was implemented for geometric phantoms, a textured phantom and a patient case.

Objectifs : L’objectif a été de d’optimiser les protocoles d’acquisition des examens d’angiomammographie double-énergie, d’étudier la faisabilité de l’angiotomosynthèse pour la détection et la caractérisation des tumeurs mammaires, et d’étudier la faisabilité des biopsies stéréotaxiques sous guidage de l’angiomammographie. Méthodes : Une étude d’optimisation des paramètres d’acquisition de l’angiomammographie a été réalisée dans 4 situations cliniques pour lesquelles la qualité diagnostique requise des images de basse énergie et la dose totale délivrée à la patiente ne sont pas identiques. L’optimisation des paramètres d'exposition (anode/filtre, kVp, mAs) des images de basse énergie (BE) et haute énergie (HE) a été réalisée à partir d’une modélisation théorique de la chaîne d’acquisition. Une validation a été effectuée par mesures expérimentales sur des images de fantôme d’inserts d’iode. Nous avons ensuite étudié la technique d’angiotomosynthèse mammaire basée sur une approche double-énergie. Un nouveau fantôme anthropomorphique numérique du sein et de ses lésions, basé sur l’utilisation de primitives géométriques complexes et d’une technique de maillage surfacique, a été amélioré et utilisé pour évaluer les performances de l’angiomammographie optimisée, puis de l’angiotomosynthèse en comparaison à l’angiomammographie. Enfin, nous avons proposé un scénario pour la réalisation d’un examen de stéréotaxie avec injection d’un agent de contraste iodé et étudié la faisabilité de recombinaison d’image de haute et de basse énergie acquises à des temps différents de l’injection.Résultats et conclusion : Les optima des paramètres d’exposition trouvés par simulation avec les valeurs de SDNRpixel et SDNR2pixel /Dosetotale qui en résultent, ont été confirmés expérimentalement. Les valeurs de SDNR par pixel dans les images recombinées sont augmentées pour toutes les indications cliniques en comparaison à celle obtenues avec SenoBright ® (produit commercial de référence). L'impact sur la qualité de l’image de BE, évalué par des expérimentations sur fantôme CDMAM, a montré que les paramètres optimisés fournissent une détection similaire ou acceptable par rapport à la mammographie standard, à l’exception de l'indication de dépistage lorsque l’on considère les objets de très petits diamètres.L’étude de lecture humaine d’images simulées d’un fantôme anthropomorphique du sein incluant le rehaussement glandulaire physiologique et différents modèle tumoraux n’a pas montré d’augmentation significative de sensibilité de détection des acquisition 3D d’angiotomosynthèse comparativement aux acquisitions 2D d’angiomammographie. Les deux paramètres qui influençaient le plus la sensibilité était la concentration en iode des tumeurs et la densité du sein. L’angiomammographie était par ailleurs significativement plus spécifique que l’angiotomosynthèse. Une perspective d’amélioration pour l’angiotomosynthèse pourrait donc être l’utilisation d’algorithmes de reconstruction 3D spécifiques de cette modalité qui minimiseraient le bruit de reconstruction. Le scénario proposé pour la réalisation de biopsies sous guidage de l’angiomammographie, a mis en évidence deux contraintes techniques que sont l’échauffement du tube à rayons X et le surcroit de dose dû à la répétition des paires d’acquisitions en haute et basse énergies. Une des solutions envisagées a été de limiter le nombre d’acquisitions de BE. Notre étude a montré que la recombinaison d’une image HE avec une image BE acquise antérieurement modifiait le SDNR des lésions simulées comparativement à une recombinaison appariée d’images BE et HE acquises au même temps de l’injection. Ces modifications dépendaient du temps du pic de rehaussement maximal et du washout de la lésion. / Objectives: The purpose was to optimize the exposure parameters of CESM examinations, to assess the feasibility of contrast-enhanced DBT (CE-DBT) for the detection and the characterization of breast tumors, and to assess CESM-guided stereotactic biopsies. Methods: At first, we optimized the CESM exposure parameters in four different clinical applications for which different levels of average glandular dose and different low energy image quality are required. The optimization of exposure parameters (anode/filter, kVp, mAs) for low energy (LE) and high energy (HE) images at different levels of average glandular dose and different ratios between LE and total doses has been conducted using a simulator of the x-ray mammographic image chain. An experimental validation was then performed through phantom experiments. Secondly, we assessed the potential of CE-DBT based on a dual-energy approach. A new mesh-based anthropomorphic breast phantom was improved and used to evaluate the performance of CESM and then to compare CESM and CE-DBT. Finally, we evaluated the technical feasibility of CESM-guided biopsy. After identifying some technical constraints, we assessed the performance of the recombination of LE and HE images acquired at different times after injection, using simulated images of a geometric phantom with uniform texture, and simulated images of an anthropomorphic textured phantom with and without motion artifacts.Results and conclusion : For the four different clinical indications, optima found by simulation, with resulting SDNRpixel and SDNR2pixel/Dosetotal, were confirmed through real acquisition of images on phantoms. Our results indicate that the SDNR per pixel in recombined CESM images increased in all of the four clinical indications compared to recombined images obtained using SenoBright ® (commercial product used as reference). This result suggests the possibility to detect more subtle contrast enhancements and to decrease the number of false negatives found in clinical CESM examinations. The impact of a new dose allocation between LE and HE exposures was also evaluated on LE image quality. Results from CDMAM phantom experiments indicate that optimized parameters provide similar or acceptable detection compared to standard mammography, except for screening indication when considering the very small diameter objects.The human observer study on anthropomorphic phantom images, taking into account tumor and breast parenchyma enhancement, revealed that detection and characterization sensitivity of iodine-enhanced lesions are not statistically different between 2D CESM and 3D CE-DBT. The most influencing parameters for the detectability and the lesion size assessment were the lesion iodine concentration and the breast density. CESM was significantly more specific than CE-DBT. One of the assumptions to explain this result is the presence of higher noise in CE-DBT than in CESM images. A future improvement for CE-DBT could therefore be the design of a specific reconstruction algorithm minimizing reconstructed noise.With respect to CESM-guided biopsy the proposed scenario pointed out two major constraints, one related to the thermal load of the x-ray tube, the second related to the increased dose due to the repetition of LE and HE images. One proposed solution was to limit the number of LE exposures, requiring the possibility to recombined LE and HE images acquired at different injection time points. Our study showed that the recombination of a HE image with a LE image acquired earlier leads to SDNR changes compared to paired recombination. These changes are function of the enhancement time to peak and the washout of the lesion, and had a limited impact on the lesion detectability.

Esse trabalho apresenta uma nova metodologia para a correção do espectro de potência do ruído no processo de simulação de aquisições de imagens de tomossíntese digital mamária (Digital Breast Tomosynthesis - DBT) com doses reduzidas de radiação. A simulação é realizada por meio da inserção de ruído quântico dependente do sinal em imagens previamente adquiridas com a dose padrão de radiação. A DBT utiliza a mesma tecnologia de raios X que a mamografia digital, porém com a capacidade de prover ao médico exames do volume tridimensional da mama, minimizando o problema de superposição de tecidos. Apesar de ser o sucessor da mamografia, estudos têm mostrado que a otimização da relação entre a dose de radiação e a qualidade da imagem adquirida ainda não está bem estabelecida na DBT. Devido à impossibilidade de realizar diversas exposições de radiação a uma mesma paciente para os estudos de otimização da dose de radiação, é desejável que exista um método capaz de simular com exatidão diversas exposições tendo como base uma imagem clínica de referência. Embora existam diversos métodos para a simulação da redução de dose em exames mamográficos, o mesmo não pode ser dito quanto a imagens de DBT. O método desenvolvido para simulação da redução da dose de radiação em imagens de DBT se baseia em uma abordagem de inserção de ruído por meio de uma transformada de estabilização de variância, que já foi utilizada para simulação da redução de dose em exames de mamografia digital. Porém, esse trabalho propõe a inclusão da correção do espectro de potência do ruído para otimizar o desempenho do método de inserção de ruído para exames de DBT. Os resultados obtidos mostraram que, quando comparando a imagens de referência, a as imagens simuladas apresentaram erro menores que 1% para a análise do valor médio e desvio padrão e erro próximo de 5% para a análise do espectro de potência, apresentado resultados até 64% melhores que métodos não otimizados para DBT. / This work presents a new methodology for noise power spectrum correction in the simulation of digital breast tomosynthesis (DBT) images with reduced dose of radiation. The simulation is performed by inserting a signal-dependent quantum noise into previously acquired images with the standard dose of radiation. Using the same X-ray technology as a standard mammography, the DBT is capable of reconstructing the inner tissues of the patients\' breasts as a three-dimensional volume, providing more resources for cancer detection than its bi-dimensional counterpart and minimizing tissue overlapping. Despite being the successor to mammography, studies have shown that the optimization of the relationship between radiation dose and image quality is not well established in DBT yet. Due to the impossibility of exposing the same patient to multiple exams with different doses each, a simulation method able to mimic clinical images with high reliability is desirable. Despite the number of methods proposed for dose reduction simulation in mammography, scarcely any may be used in DBT. The method developed for simulation of radiation dose reduction in DBT images is based on a noise insertion approach using a variance-stabilizing transformation, which has already been used to simulate dose reduction in digital mammography exams. However, this work proposes the inclusion of the noise power spectrum correction to optimize the performance of the noise insertion method for DBT exams. The results showed that, when compared with reference images, the simulated images achieved less than 1% error for mean and standard deviation values and close to 5% error for power spectrum analysis, improving in up to 64% when compared with non-optimized for DBT simulation methods.

In x-ray imaging, the x-ray radiation must be the minimum necessary to achieve the required diagnostic objective, to ensure the patients safety. However, low-dose acquisitions yield images with low quality, which affect the radiologists image interpretation. Therefore, there is a compromise between image quality and radiation dose. This work proposes an image restoration framework capable of restoring low-dose acquisitions to achieve the quality of full-dose acquisitions. The contribution of the new method includes the capability of restoring images with quantum and electronic noise, pixel offset and variable detector gain. To validate the image processing chain, a simulation algorithm was proposed. The simulation generates low-dose DBT projections, starting from fulldose images. To investigate the feasibility of reducing the radiation dose in breast cancer screening programs, a simulated pre-clinical trial was conducted using the simulation and the image processing pipeline proposed in this work. Digital breast tomosynthesis (DBT) images from 72 patients were selected, and 5 human observers were invited for the experiment. The results suggested that a reduction of up to 30% in radiation dose could not be perceived by the human reader after the proposed image processing pipeline was applied. Thus, the image processing algorithm has the potential to decrease radiation levels in DBT, also decreasing the cancer induction risks associated with the exam. / Em programas de rastreamento de câncer de mama, a dose de radiação deve ser mantida o mínimo necessário para se alcançar o diagnóstico, para garantir a segurança dos pacientes. Entretanto, imagens adquiridas com dose de radiação reduzida possuem qualidade inferior. Assim, existe um equilíbrio entre a dose de radiação e a qualidade da imagem. Este trabalho propõe um algoritmo de restauração de imagens capaz de recuperar a qualidade das imagens de tomossíntese digital mamária, adquiridas com doses reduzidas de radiação, para alcançar a qualidade de imagens adquiridas com a dose de referência. As contribuições do trabalho incluem a melhoria do modelo de ruído, e a inclusão das características do detector, como o ganho variável do ruído quântico. Para a validação a cadeia de processamento, um método de simulação de redução de dose de radiação foi proposto. Para investigar a possibilidade de redução de dose de radiação utilizada na tomossíntese, um estudo pré-clínico foi conduzido utilizando o método de simulação proposto e a cadeia de processamento. Imagens clínicas de tomossíntese mamária de 72 pacientes foram selecionadas e cinco observadores foram convidados para participar do estudo. Os resultados sugeriram que, após a utilização do processamento proposto, uma redução de 30% de dose de radiação pôde ser alcançada sem que os observadores percebessem diferença nos níveis de ruído e borramento. Assim, o algoritmo de processamento tem o potencial de reduzir os níveis de radiação na tomossíntese mamária, reduzindo também os riscos de indução do câncer de mama.