Magnetic Resonance Electrical Impedance Mammography (MREIM) is a new imaging technique under development by Wollin Ventures, Inc. in conjunction with the H. Lee Moffitt Cancer Center & Research Institute. MREIM addresses the problem of low specificity of magnetic resonance mammography and high false-positive rates, which lead to unnecessary biopsies. Because cancerous tissue has a higher electrical conductivity than benign tissue, it may serve as a biomarker for differentiation between malignant and benign lesions. The MREIM principle is based on measuring both magnetic resonance and electric properties of the breast by adding a quasi-steady-state electric field to the standard magnetic resonance breast image acquisition. This applied electric field produces a current density that creates an additional magnetic field that in turn alters the native magnetic resonance signal in areas of higher electrical conductivity, corresponding to cancerous tissue. This work comprises MREIM theory, computer simulations, and experimental developments. First, a general overview and background review of tissue modeling and electrical-impedance imaging techniques are presented. The experimental part of this work provides a description of the MREIM apparatus and the imaging results of a custom-made breast phantom. This phantom was designed and developed to mimic the magnetic resonance and electrical properties of the breast. The theoretical part of this work provides an extension to the initial MREIM theoretical developments to further understand the MREIM effects. MREIM computer simulations were developed for both idealized and realistic tumor models. A method of numerical calculation of electric potential and induced magnetic field distribution in objects with irregular boundaries and anisotropic conductivity was developed based on the Finite Difference Method. Experimental findings were replicated with simulations. MREIM effects were analyzed with contrast diagrams to show the theoretical perceptibility as a function of the acquisition parameters. An important goal was to reduce the applied current. A new protocol for an MREIM sequence is suggested. This protocol defines parameters for the applied current synchronized to a specific magnetic resonance imaging sequence. A simulation utilizing this protocol showed that the MREIM effect is detectable for a 3-mm-diameter tumor with a current density of 0.5 A/m², which is within acceptable limits.

This thesis aims to study the effects of endogenous and exogenous hormones and mammographic breast density (BD) on cellular markers in non-cancerous female breast tissue. Women on the waiting list for breast reduction plastic surgery were recruited (n = 79), and randomized to 2 months of hormone therapy or no therapy before surgery. The women had a mammogram and a needle biopsy 2 months before surgery and tissue samples were obtained at the operation. In premenopausal women, estrogen receptor (ER)α levels were associated with age (p = 0.0002), were similar in the follicular and luteal phases of the menstrual cycle and were higher in parous than in nulliparous women (p = 0.009). Current smokers had lower PR levels than non-smokers (p = 0.019). Women on oral contraception had lower ERα (p = 0.048) and PR (p = 0.007) levels than women in the follicular phase. The ERα levels did not differ significantly between postmenopausal estrogen and estrogen-progestogen users, but PR levels were lower among estrogen-progestogen users (p = 0.03). We found lower expression of the genes for decorin and syndecans 1 and 4 in the luteal phase than in the follicular phase, among parous women. Protein levels of the androgen receptor, syndecan-4 and decorin was lower in premenopausal women who were using oral contraceptives (OC) than in those in the follicular phase (p = 0.002 - 0.02), whereas no significant differences between OC use and the luteal phase were found. In premenopausal women, BD was negatively associated with age and body mass index but was similar for the menstrual phases. Breast density was associated with genetic expression of the androgen receptor and remained significant after adjustment for age (rs = 0.56; p = 0.04). After adjustement for age, breast density was also marginally associated with expression of the caspase 3 gene (0.55; 0.053). However, protein levels of caspase 3 was negatively associated (-0.61; 0.03).

Dada a dificuldade de avaliação das imagens mamográficas no rastreamento do câncer de mama e a necessidade de precisão diagnóstica, tornou-se estimulante a luta pelo desenvolvimento de ferramentas computacionais que auxiliam esse processo, denominadas de esquemas de Computer-aided detection/diagnosis (CADe/CADx). Apresenta-se como um desafio para a comunidade científica a padronização dos critérios de avaliação destes esquemas a partir de bancos de imagens amplos e diversificados que representem casos tanto de benignidade quanto os de malignidade. Considerando este aspecto, o presente trabalho consiste no desenvolvimento de um objeto simulador (phantom) de mama capaz de gerar diversos padrões de imagens obtidos pela variação aleatória de tamanho, forma, contraste e distribuição de lesões. Para garantir imagens mais realistas, o phantom foi confeccionado em camadas compostas por filme de PVC submerso em parafina gel em uma distribuição não uniforme. Essa distribuição permite simular regiões heterogeneamente densas, de acordo com a concentração do material. A estimativa da densidade percentual da mama simulada foi obtida com a ajuda do software LIBRA®, para gerar imagens nas quatro categorias de classificação de densidades BI-RADS®. Os nódulos foram simulados usando dois modelos tridimensionais impressos em 3D, um para lesões circunscritas e outro para espiculadas. Para as microcalcificações, foi utilizada a hidroxiapatita granulada distribuída em quatro clusters que representam casos comumente encontrados em mamas reais. Alternativamente, uma ferramenta computacional foi desenvolvida para a inserção das lesões nas imagens, de acordo com a localização e intensidade escolhidas. As características do phantom foram estudadas comparando os coeficientes de atenuação dos materiais utilizados e dos tecidos mamários. Também textura e ruído das imagens do phantom foram comparados em relação aos das imagens clínicas. A partir da base de imagens formada, um protótipo de esquema CADx foi avaliado. Os resultados foram analisados estatisticamente a partir de curvas ROC e comparados com os obtidos nos testes realizados com imagens clínicas. Concluiu-se que o phantom desenvolvido neste trabalho permitiu gerar um padrão de imagem próximo ao obtido em mamografias reais e apropriado ao suprimento da base de imagens para validação dos sistemas CADx. / The need for diagnostic accuracy in breast cancer screening has motivated the use of computational schemes known as computer-aided detection/diagnosis (CAD/CADx). However, standardization of the evaluation criteria regarding these schemes is still a challenge, since they depend on the access to large and diversified image databases representing both benign and malignant cases. With this feature in view, this work aimed at the development of a structured breast phantom able to generate many images patterns achieved not only by the variation of size, shape, contrast but also by mainly the distribution of simulated lesions. To guarantee the realism of the images, the phantom was made in layers composed by PVC film submerged in paraffin gel with a non-uniform distribution. Such distribution allowed simulating more or less dense regions, according to the material concentration. The percent density estimative of the simulated breast was determined with the LIBRA® software, resulting in the four categories of BIRADS® density classification. Nodules were simulated using two 3D printed models, one for circumscribed and another for spiculated lesions. For simulating microcalcifications, granulated hydroxyapatite was used distributed in four clusters. Alternatively, a computational tool was developed for the insertion of lesions into the images, according to the location and intensity chosen. Phantom characteristics were studied comparing attenuation coefficients of the materials used and breast tissues. The texture and noise of the phantom images were also compared in relation to the clinical ones. From the image database created, a CADx system was evaluated considering its modules of nodule classification and detection of microcalcifications. The results were analyzed statistically from ROC curves and compared with those usually obtained in clinical imaging tests. We concluded that the phantom developed in this work allowed to generate an image pattern similar to that obtained in real mammograms and suitable for supplying an image database to be used as a ground truth for CAD and CADx schemes validation/evaluation.

<p>Breast cancer is the most commonly diagnosed cancer type worldwide. Given high survivorship, increased focus has been placed on long-term treatment outcomes and patient quality of life. While breast-conserving surgery (BCS) is the preferred treatment strategy for early-stage breast cancer, anticipated healing and breast deformation (cosmetic) outcomes weigh heavily on surgeon and patient selection between BCS and more aggressive mastectomy procedures. Unfortunately, surgical outcomes following BCS are difficult to predict, owing to the complexity of the tissue repair process and significant patient-to-patient variability. To overcome this challenge, we developed a predictive computational mechanobiological model that simulates breast healing and deformation following BCS. The coupled biochemical-biomechanical model incorporates multi-scale cell and tissue mechanics, including collagen deposition and remodeling, collagen-dependent cell migration and contractility, and tissue plastic deformation. Available human clinical data evaluating cavity contraction and histopathological data from an experimental porcine lumpectomy study were used for model calibration. The computational model was successfully fit to data by optimizing biochemical and mechanobiological parameters through the Gaussian Process. The calibrated model was then applied to define key mechanobiological parameters and relationships influencing healing and breast deformation outcomes. Variability in patient characteristics including cavity-to-breast volume percentage and breast composition were further evaluated to determine effects on cavity contraction and breast cosmetic outcomes, with simulation outcomes aligning well with previously reported human studies. The proposed model has the potential to assist surgeons and their patients in developing and discussing individualized treatment plans that lead to more satisfying post-surgical outcomes and improved quality of life.</p>

Breast cancer is one of the most common types of cancer affecting women in the world today. To better understand breast cancer initiation and progression modeling biological tissue under physiological conditions is essential. Indeed, breast cancer involves complex interactions between mammary epithelial cells and the stroma, both extracellular matrix (ECM) and cells including adipocytes (fat tissue) and fibroblasts (connective tissue). Therefore, the engineering of in vitro three-dimensional (3D) systems of breast tissues allows a deeper understanding of the complex cell-cell and cell-ECM interactions involved during breast tissue development and cancer initiation and progression. Furthermore, such 3D systems may provide a viable alternative to investigate new drug or drug regimen and to model and monitor concurrent cellular processes during tumor growth and invasion. The development of suitable 3D in vitro models relies on the ability to mimic the microenvironment, the structure, and the functions of the breast tissue. Different approaches to develop a novel 3D breast model have been investigated. Most models use gel scaffolds, including Matrigel® and collagen to generate breast tissue-like structures. However, the physicochemical, mechanical, and geometrical properties of these scaffolds only partially meet the mechanical, physical, and chemical parameters of the breast tissue matrix. In the present studies, we investigated the overall hypothesis that electrospun SF-derived scaffolds promote mammary cell growth and the formation of mammary-like structures depending on the composition and/or coating of the scaffolds with ECM proteins. Through an extensive literature search (1) the importance of 3D modeling of tissues and organs in vivo, (2) 3D modeling of the mammary tissue and currently available models, (3) the properties and applications of SF in tissue modeling and regeneration were reviewed (Chapter 1). Our studies provide evidence of the effects of various concentrations (Chapter 2) of SF along with different electrospinning techniques (Chapter 3) on the structure of electrospun scaffolds and whether those scaffolds provide suitable microenvironments for mammary epithelial cells as determined by MCF10A cell attachment, viability, and structure formation. Further, we investigated the effects of the key ECM proteins collagen I (Chapter 4) and laminin (Chapter 5) used to blend or coat, respectively, SF scaffolds on the attachment, viability and structure formation of mammary epithelial cells. Our studies first highlight the mechanical and physical properties of the different SF-derived scaffolds through various SF concentrations and electrospinning techniques. Second, the biocompatibility of these SF electrospun scaffolds was defined based on MCF10A cell survival and adhesion. Third, our data indicate that scaffolds derived from blended and/or coated SF with collagen I also promoted human mammary cell survival and adhesion. Lastly, our observations suggest that on laminin-coated SF scaffolds MCF10A mammary cells, in the presence of lactogenic hormones, differentiated forming acinus-like structures. Overall, these studies provide evidence that SF electrospun scaffolds closely mimic the structure of the ECM fibers and allow many advantages such as; physical and chemical modification of the microenvironment by varying electrospinning parameters and addition of various proteins, hormones, and growth factors, respectively. Further, coating these SF scaffolds with essential ECM proteins, in particular laminin, promote cell-ECM interactions necessary for cell differentiation and formation of growth-arrested structures, through providing cell integrin binding sites and appropriate chemical cues.

This work describes the development of an optical probe for measuring movement of tissue particles deep inside which are loaded by an ultrasound remote palpation device. The principle of the method is that ultrasound force which can be applied inside the tissue makes the tissue particles vibrate and this vibration phase-modulates the light intercepting the insoniified region which results in a modulated speckle intensity on detection outside the object. This speckle intensity modulation detected through the measured intensity autocorrelation is a measure of the vibration amplitude. Since the vibration amplitude is related to the local elastic properties of the medium, the measured modulation depth in intensity autocorrelation can be used to map the elastic property in the insonified region. In this work, first the ultrasound induced force is calculated for both plane and focused ultrasound beams, and converted to amplitude of vibration and refractive index modulation, solving the forward elastography equation. Light propagation inside an insonified object is modelled using Monte Carlo simulation and the amplitude and intensity correlations are computed. The modulation depth on the autocorrelation is estimated and shown that it is inversely correlated to the local elastic modulus and optical absorption coefficient. It is further shown that whereas the variation in modulation depth is linear with respect to absorption coefficient, the same variation with elastic property is nonlinear. These results are verified experimentally in a tissue mimicking phantom. The phantom was constructed out of poly vinyl alcohol(PVA) whose optical, mechanical and acoustic properties are independently controlled. It is also shown that for loading with focused ultrasound beam the displacement is almost along the ultrasound transducer axis and therefore the contribution from refractive index modulation alone can be ascertained by probing the insonified perpendicular to the transducer axis. This helps one to find the contribution to the modulation depth from the ultrasound-induced vibration, which can be used to compute a quantitative estimate of the elastic modulus from the modulation depth.

Made available in DSpace on 2016-08-17T14:53:17Z (GMT). No. of bitstreams: 1 Ulysses Santos Sousa.pdf: 1410915 bytes, checksum: 88235f7f4a3bc07a4da1b27c23dc71ca (MD5) Previous issue date: 2011-05-13 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Cancer is one of the biggest health problems worldwide, and the breast cancer is the one that causes more deaths among women. Also it is the second most frequent type in the world. The chances of survival for a patient with breast cancer increases the sooner this disease is discovered. Several Computer Aided Detection/Diagnosis Systems has been used to assist health professionals. This work presents a methodology to discriminate and classify mammographic tissues regions in mass and non-mass. For this purpose the Shannon-Wiener‟s Diversity Index, which is applied to measure the biodiversity in ecosystem, is used to describe pattern of breast image region with four approaches: global, in circles, in rings and directional. After, a Support Vector Machine is used to classify the regions in mass and non-mass. The methodology presents promising results for classification of mammographic tissues regions in mass and non-mass, achieving 99.85% maximum accuracy. / O câncer é um dos maiores problemas de saúde mundial, sendo o câncer de mama o que mais causa óbito entre as mulheres e o segundo tipo mais freqüente no mundo. As chances de uma paciente sobreviver ao câncer de mama aumentam à medida que a doença é descoberta mais cedo. Diversos Sistemas de Detecção e Diagnóstico auxiliados por computador (Computer Aided Detection/Diagnosis) têm sido utilizados para auxiliar profissionais de saúde. Este trabalho apresenta uma metodologia de discriminação e classificação de regiões de tecidos de mamografias em massa e não massa. Para este propósito utiliza-se o Índice de Diversidade de Shannon-Wiener, comumente aplicado para medir a biodiversidade em um ecossistema, para descrever padrões de regiões de imagens de mama com quatro abordagens: global, em círculos, em anéis e direcional. Em seguida, utiliza-se o classificador Support Vector Machine para classificar estas regiões em massa e não massa. A metodologia apresenta resultados promissores para a classificação de regiões de tecidos de mamografia em massa e não massa, obtendo uma acurácia máxima de 99,85%.

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