A terapia hormonal na menopausa tem sido objeto de muita contradição nos últimos anos, pois trabalhos mostram resultados contraditórios quanto a benefícios e riscos para as usuárias. Ficou demonstrada, em alguns trabalhos, a maior incidência de carcinoma de mama em usuárias de terapia hormonal clássica e, portanto, existe uma constante busca no que diz respeito ao refinamento de métodos diagnósticos e avaliação dos efeitos das novas drogas na mama. Dentre as drogas mais modernas, a tibolona vem se destacando por apresentar poucos efeitos colaterais, principalmente relacionados à mama. Esta droga apresenta três metabólitos com ação tecidual específica. Assim, efeitos androgênicos, estrogênicos ou progesterônicos podem ser observados na dependência do órgão alvo estudado. Os objetivos de nosso estudo foram avaliar um método de análise computadorizada da densidade mamográfica e, ao mesmo tempo, avaliar os efeitos da tibolona na densidade dessas mamografias. Em nosso estudo, foram avaliadas 26 pacientes na pós menopausa e que tinham indicação do uso de terapia hormonal oral, de acordo com o protocolo vigente no Setor de Endocrinologia Ginecológica do Centro de Saúde Escola da Faculdade de Medicina de Ribeirão Preto-USP. Essas pacientes receberam tibolona na dose de 2,5 mg/dia por 24 semanas. Todas foram submetidas à mamografia antes a após o uso da droga sendo, durante a realização do exame, colocado sobre a plataforma de compressão da mama (Buck) um objeto de referência (escala em acrílico confeccionada para essa finalidade) na intenção de normalizar os exames pré e pós-tratamento. Além disto, as mamografias foram submetidas à avaliação de dois examinadores com o intuito de verificar variações da densidade mamográfica. Essas mesmas mamografias, após normalização pelo objeto de referência, também foram submetidas à análise computadorizada da densidade. Foram realizadas comparações entre os resultados da avaliação da densidade da mama antes e após o uso da tibolona tanto nos laudos dos examinadores, quanto nas imagens digitalizadas. Foi feito também comparação inter-examinadores. As análises comparativas das densidades das grafias antes a após o uso da tibolona não mostraram variações significativas tanto na análise dos examinadores quanto na análise computadorizada. A análise comparativa inter-examinadores mostrou uma tendência à variação entre as classificações da densidade mamográfica, apesar de não ser estatisticamente significante. Podemos concluir que a tibolona, se administrada a pacientes na pós menopausa, na dose de 2,5 mg/dia por 24 semanas não causa variação da densidade mamográfica. Desta forma, a avaliação computadorizada da densidade mamográfica pode ser usada como método auxiliar aos radiologistas, em casos de mamas mais densas permitindo uma melhor avaliação desses casos. / Over the last few years, hormonal therapy has been subject of much controversy since various studies have shown contradictory results regarding the risks and benefits for users. A higher incidence of breast carcinoma among users of classical hormonal therapy has been demonstrated in some studies and therefore there is a constant search regarding the refinement of diagnostic methods and the evaluation of the effects of new drugs on the breast. Among the more modern drugs, tibolone is particularly outstanding because it has few side effects, especially related to the breast. This drug has three metabolites with specific tissue action. Therefore, androgenic, estrogenic or progestogenic effects can be achieved, depending on the organ evaluated. The objectives of the present study were to assess a computerized method for the analysis of mammographic density. The author evaluated 26 menopausal women with an indication for oral hormonal therapy according to the protocol of the sector of gynecologic endocrinology of the Faculty of Medicine of Ribeirão Preto, USP. Tibolone at the dose of 2.5 mg/day was administered to these patients for 24 weeks. The patients were submitted to mammography before and after the use of the drug. During the exam, a reference object (an acrylic scale prepared for this purpose) was placed on the platform for breast compression (Buck) in order to normalize the pre- and post-treatment exams. In addition, two examiners evaluated the mammographies in order to determine variations in mammographic density. After normalization according to the reference object, these same mammographies were submitted to computerized density analysis. The mamographic density results obtained before and after the use of tibolone are compared in the digitalized images and in the examiners evaluation. In the same way, an inter-examiners analysis was done. The comparative analyses of the mammographic densities before and after the use of tibolone did not show significant variations in the analyses of the examiners or in the computerized analysis. Inter-examiner analysis showed a tendency to variation in the classification of mammographic density, although the difference was not statistically significant. The author concluded that tibolone, when administered to menopausal women at the dose of 2.5 mg/day for 24 weeks, did not cause a variation in mammographic density. Computerized evaluation of mammographic density can be used as an auxiliary method to radiologists, in cases of high density breast mammography, allowing a more confident evaluation of these cases.

Esta tese apresenta uma metodologia para classificação automática de achados mamográficos em mamas densas através de uma abordagem híbrida de classificadores e extração de atributos, como parte de um esquema computadorizado de auxílio ao diagnóstico (CAD) para mamografia. Foram implementadas duas redes Backpropagation. Uma responde pela classificação de clusters de microcalcificações, através de atributos descritores geométricos, em duas classes - suspeito e não suspeito. A outra rede classifica nódulos utilizando descritores geométricos e uma entrada com informação extraída de atributos de intensidade, produzindo na saída dois tipos de informação: presença ou não do nódulo, e constatada a presença do nódulo, classificação da região de interesse (RI) entre as categorias BI-RADS. As respostas de um \"clusterizador\" de RIs através de atributos de intensidade serviram de entrada para essa rede fornecendo uma informação de grau de densidade da RI. Uma interface foi desenvolvida para a apresentação dos resultados a fim de fornecer informações mais detalhadas da classificação e do caso analisado. Os resultados do classificador foram analisados através de análise estatística de sensibilidade e especificidade, e também por curvas ROC. Os resultados obtidos ficaram próximos a 89% de acerto total (verdadeiros-positivos mais verdadeiros-negativos) para nódulos produzindo valor de Az superior a 0,92 e ultrapassaram 75% de acerto da classificação entre as classes BI-RADS. Na classificação dos clusters os acertos totais do classificador ficaram próximos de 90%, com Az superior a 0,94. Para ambos tipos de lesões, as taxas de respostas falsas-negativas ficaram abaixo de 0,1, o que significa baixo erro em relação à não detecção da doença quando o sinal está presente. O classificador apresentado nesse trabalho é a conclusão de uma etapa importante do esquema CAD que vem sendo desenvolvido pelo grupo, além de possibilitar a disponibilização de mais uma ferramenta automática de auxílio ao diagnóstico do câncer de mama aos serviços de mamografia. / This thesis presents a methodology for automatic classification of mamographic findings in image of dense breast through hybrid approach of classifiers and features extraction techniques, as part of a computer-aided diagnostic (CAD) scheme for mammography. Two Backpropagation neural networks were implemented. One for microcalcifications clustered classification, through geometric descriptors, in two classes - suspect and non-suspect. The other neural network classifies nodules using geometric descriptors and additional information from intensity features extracted, producing in the output two kinds of information: presence or not of the nodule, and if nodule is present in the image, classification among BI-RADS categories. The result of clustering technique by using intensity features is presented as a new input to neural network, supplying density degree of image. An interface was developed for results presentation in order to supply more detailed information from the classifier outputs and of the analyzed case. The results of the classifier were analyzed through sensibility and specificity statistical analysis, and also for ROC curves. The results were close to 89% of total accuracy (positive-true plus negative-true) for nodules producing value of Az more than 0,92 and 75% of accuracy to classification among BI-RADS categories. In the cluster classification the total accuracy is about 90%, and Az greater than 0,94. In both kinds of lesions, negative-false result rates were below 0,1, which means low error related to the fail to detect the disease when the signal is present. The classifier presented in this work is the conclusion of an important stage of the CAD scheme that has been developed by the group, besides making possible the availability of one more automatic tool of aid to the breast cancer diagnosis to be used in mammography centers.

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>With 7 000 new cases in Sweden each year, breast cancer represents 30 percent of all female malignancies and is therefore the most commonly diagnosed cancer among women. There are limitations as to what can be done to prevent the disease but with the use of mammography screening the chances of finding and treating the disease at an early stage are increasing. Unfortunately, mammography screening is associated with radiation, which is an established risk factor for developing breast cancer. However, the newest screening technologies come with a reduced dose which decreases the risk of developing breast cancer due to the radiation.</p><p> </p><p>The effects of this lower dose compared to that of traditional technologies have not yet been studied and the purpose of this paper is therefore to assess the cost-effectiveness of the use of this new technology, with a focus on the number of radiation-induced cancers. A cost-utility analysis was performed where three different mammography technologies (one analogue and two digital) were compared. The total costs and QALYs of breast cancer generated by the use of these three technologies were calculated with the use of a Markov decision-analytic model, where a cohort of hypothetical 40 year-old women was followed throughout life.</p><p> </p><p>The results of the analysis showed that with the new digital technology (the PC-DR), one in 14 100 screened women develops breast cancer due to radiation while with the traditional mammography systems (SFM and the CR) this number is one in 3 500 and 4 300 screened women, respectively. Consequently, the number of induced cancers is decreased with up to 75 percent with the use of the PC-DR. Assuming that only the radiation dose differs between the three units, the analysis resulted in an incremental effect of 0.000269 QALYs over a life-time for the PC-DR when compared to SFM(0.000210 QALYs compared to the CR). The PC-DR was also associated with a 33 SEK (26 SEK) lower cost. Thus, if the only difference can be found in radiation dose, the PC-DR is the dominating technology to use since it is both more effective and costs less. However, it is possible that the PC-DR is more expensive per screening occasion than the other technologies and if so, the PC-DR would no longer be less costly. The study found that the scope for the possibility of excessive pricing is very small and under these circumstances, the willingness to pay for a QALY has to be considered when deciding what technology to invest in.</p>

<p>The first part of this thesis is concerned with trend modelling of breast cancer mortality rates. By using an age-period-cohort model, the relative contributions of period and cohort effects are evaluated once the unquestionable existence of the age effect is controlled for. The result of such a modelling gives indications in the search for explanatory factors. While this type of modelling is usually performed with 5-year period intervals, the use of 1-year period data, as in Paper I, may be more appropriate.</p><p>The main theme of the thesis is the evaluation of the ability to detect signals in x-ray images of breasts. Early detection is the most important tool to achieve a reduction in breast cancer mortality rates, and computer-aided detection systems can be an aid for the radiologist in the diagnosing process.</p><p>The evaluation of computer-aided detection systems includes the estimation of distributions. One way of obtaining estimates of distributions when no assumptions are at hand is kernel density estimation, or the adaptive version thereof that smoothes to a greater extent in the tails of the distribution, thereby reducing spurious effects caused by outliers. The technique is described in the context of econometrics in Paper II and then applied together with the bootstrap in the breast cancer research area in Papers III-V.</p><p>Here, estimates of the sampling distributions of different parameters are used in a new model for free-response receiver operating characteristic (FROC) curve analysis. Compared to earlier work in the field, this model benefits from the advantage of not assuming independence of detections in the images, and in particular, from the incorporation of the sampling distribution of the system's operating point.</p><p>Confidence intervals obtained from the proposed model with different approaches with respect to the estimation of the distributions and the confidence interval extraction methods are compared in terms of coverage and length of the intervals by simulations of lifelike data.</p>

Contrast-enhanced mammography (CEM) relies on visualizing the growth of new blood vessels (i.e. tumor angiogenesis) to provide sufficient materials for cell proliferation during the development of cancer. Since cancers will accumulate an injected contrast agent more than other tissues, it is possible to use one of several methods to enhance the area of lesions in the x-ray image and remove the contrast of normal tissue. Large area flat panel detectors may be used for CEM wherein the subtraction of two acquired images is used to create the resulting enhanced image. There exist several methods to acquire the images to be subtracted, which include temporal subtraction (pre- and post-contrast images) and dual-energy subtraction (low- and high-energy images), however these methods suffer from artifacts due to patient motion between image acquisitions. In this research the use of a multilayer flat panel detector is examined for CEM that is designed to acquire both (low- and high-energy) images simultaneously, thus avoiding motion artifacts in the resulting subtracted image. For comparison, a dual-energy technique prone to motion artifacts that uses a single-layer detector is also investigated. Both detectors are evaluated and optimized using amorphous selenium as the x-ray to charge conversion material, however the theoretical analysis could be extended to other conversion materials. Experimental results of single pixel prototypes of both multilayer and single-layer detectors are also discussed and compared to theoretical results. For a more comprehensive analysis, the motion artifacts present in dual-exposure techniques are modeled and the performance degradation due to motion artifacts is estimated. The effects of noise reduction techniques are also evaluated to determine potential image quality improvements in CEM images.

With 7 000 new cases in Sweden each year, breast cancer represents 30 percent of all female malignancies and is therefore the most commonly diagnosed cancer among women. There are limitations as to what can be done to prevent the disease but with the use of mammography screening the chances of finding and treating the disease at an early stage are increasing. Unfortunately, mammography screening is associated with radiation, which is an established risk factor for developing breast cancer. However, the newest screening technologies come with a reduced dose which decreases the risk of developing breast cancer due to the radiation.   The effects of this lower dose compared to that of traditional technologies have not yet been studied and the purpose of this paper is therefore to assess the cost-effectiveness of the use of this new technology, with a focus on the number of radiation-induced cancers. A cost-utility analysis was performed where three different mammography technologies (one analogue and two digital) were compared. The total costs and QALYs of breast cancer generated by the use of these three technologies were calculated with the use of a Markov decision-analytic model, where a cohort of hypothetical 40 year-old women was followed throughout life.   The results of the analysis showed that with the new digital technology (the PC-DR), one in 14 100 screened women develops breast cancer due to radiation while with the traditional mammography systems (SFM and the CR) this number is one in 3 500 and 4 300 screened women, respectively. Consequently, the number of induced cancers is decreased with up to 75 percent with the use of the PC-DR. Assuming that only the radiation dose differs between the three units, the analysis resulted in an incremental effect of 0.000269 QALYs over a life-time for the PC-DR when compared to SFM(0.000210 QALYs compared to the CR). The PC-DR was also associated with a 33 SEK (26 SEK) lower cost. Thus, if the only difference can be found in radiation dose, the PC-DR is the dominating technology to use since it is both more effective and costs less. However, it is possible that the PC-DR is more expensive per screening occasion than the other technologies and if so, the PC-DR would no longer be less costly. The study found that the scope for the possibility of excessive pricing is very small and under these circumstances, the willingness to pay for a QALY has to be considered when deciding what technology to invest in.

<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

Στα πλαίσια της συγκεκριμενης διδακτορικής διατριβής, δύο μοντέλα προσομοίωσης Monte Carlo επεκτάθηκαν ώστε να συμπεριλάβουν γεωμετρίες μεγέθυνσης και διάφορες περιεκτικότητες μαστού σε μαζικό αδένα, και χρησιμοποιήθηκαν με σκοπό τη βελτιστοποίηση των μεγεθυντικών λήψεων στη μαστογραφία. Με τα μοντέλα αυτά έγιναν δοσιμετρικές μελέτες, καθώς επίσης και μελέτες για την ποιότητα εικόνας. Πιο συγκεκριμένα, η δοση στο μαζικό αδένα του μαστού, η οποία συνδέεται άμεσα με την πιθανότητα καρκινογέννεσης κατά τη διάρκεια της μαστογραφίας, βρέθηκε να αυξάνει με το βαθμό μεγέθυνσης κυρίως λόγω του νόμου αντιστρόφου τετραγώνου της απόστασης. Ο λόγος αντίθεσης προς το θόρυβο επίσης αυξάνει με το βαθμό μεγέθυνσης. Ωστόσο, ο ρυθμός αύξησης είναι μεγαλύτερος για μεγέθυνση μέχρι 1.4. Με την εισαγωγή ενός δείκτη απόδοσης ο οποίος είναι συνάρτηση του επιθυμητού κέρδους (εκφραζόμενο από το CNRν) και του κόστους (εκφραζόμενο από τη δόση) διάφορες παράμετροι έκθεσης (βαθμός μεγέθυνσης και φάσμα) αποτιμήθηκαν υπό συνθήκες μεγέθυνσης. Ο βαθμός μεγέθυνσης 1.3 βρέθηκε να έχει την καλύτερη απόδοσηγια όλους τους συνδυασμούς υλικών ανόδου/φίλτρου που μελετήθηκαν. Διάφοροι συνδυασμοί όπως οι W/0.050mmAl, Rh/0.51mmAl, W/0.030mmRh, Rh/0.029mmRh, Rh/0.030mmRu και Mo/0.029mmRh θα μπορούσαν να ανταγωνιστούν το Mo/0.030mmMo σε γεωμετρίες επαφής. Ωστόσο, όταν εφαρμόζεται η τεχνική της μεγέθυνσης και ειδικά βαθμός μεγαλύτερος από 1.3, το Mo/0.030mmMo έχει τη μεγαλύτερη συνολική απόδοση μεταξύ των συνδυασμών που μελετήθηκαν. Επιπλεον, μελετήθηκε η επίδραση του μεγέθους της εστίας και της κατανομής εκπεμπόμενης ακτινοβολίας ακτίων-χ στη χωρική διακριτική ικανότητα υπό συνθήκες μεγέθυνσης, χρησιμοποιώντας τη μέθοδο της αιχμής. Εστίες μεγαλύτερες από 0.12 mm θα έπρεπε να χρησιμοποιούνται μόνο για προληπτικές μαστογραφίες, ειδικά όταν συνδυάζονται με ομοιόμορφες ή κανονικές κατανομές διπλής κορυφής. Εστίες των 0.04 mm ή και ακόμα μικρότερες, συνδυασμένες με κανονικές κατανομές μονής κορυφής και μικρής τυπικής απόκλισης οδηγούν σε αποδεκτές τιμές διακριτικής ικανότητας με βάση τους διεθνείς κανονισμούς, ακόμα και σε μεγάλους βαθμούς μεγέθυνσης. Τέλος, βρέθηκε ότι η διακριτική ικανότητα υποβαθμίζεται με τη μεγέθυνση λόγω της γεωμετρικής ασάφειας. / In the framework of this doctorate thesis, two simulation models based on Monte Carlo were expanded in order to include magnification geometries and various breast compositions, and were utilized aiming to study and optimize the magnification views in mammography. With the use of these models, dosimetric as well as image quality characteristics were evaluated and combined in order to come into conclusions. More specifically, the dose in the glandular tissue of the breast, which is directly associated with the carcinogenic risk during mammography, was found to increase with the degree of magnification, mainly due to the inverse square law. Contrast to Noise Ratio also increases with magnification. However, the increase rate is higher for magnification up to 1.4. With the introduction of a Performance Index, which is a function of the desirable benefit (expressed by the (CNR)ν) and the cost (expressed by the dose), several exposure and design parameters (degree of magnification, spectrum) were evaluated under magnification conditions. Degree of magnification 1.3 was found to have the best overall performance for all the anode/filter combinations considered. Several combinations like W/0.050mmAl, Rh/0.51mmAl, W/0.030mmRh, Rh/0.029mmRh, Rh/0.030mmRu and Mo/0.029mmRh can compete with the Mo/0.030mmMo under contact geometry. However, when magnification is performed and especially degree higher than 1.3, Mo/0.030mmMo has the best overall performance between the anode/filter combinations considered. Moreover, the effect of focal spot size and x-ray intensity distribution on the spatial resolution was studied under magnification, using the edge method. Focal spots larger than 0.12 mm should be utilized only for screening mammography, especially when combined with uniform or double Gaussian intensity distributions. Small focal spots of 0.04 mm or less, combined with Gaussian distribution result in acceptable values of spatial resolution, according to the international regulations, even for high degrees of magnification. Finally, a degradation of the spatial resolution was found with the degree of magnification, which is mainly caused by the geometrical unsharpness.

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