Active Microwave Imaging for Breast Cancer Detection

Active microwave imaging is explored as an imaging modality for early detection of breast cancer. When exposed to microwaves, breast tumor exhibits electrical properties that are significantly different from that of healthy breast tissues. The two approaches of active microwave imaging — confocal microwave technique with measured reflected signals and microwave tomographic imaging with measured scattered signals are addressed here. Normal and malignant breast tissue samples of same person are subjected to study within 30 minutes of mastectomy. Corn syrup is used as coupling medium, as its dielectric parameters show good match with that of the normal breast tissue samples. As bandwidth of the transmitter is an important aspect in the time domain confocal microwave imaging approach, wideband bowtie antenna having 2:1 VSWR bandwidth of 46% is designed for the transmission and reception of microwave signals. Same antenna is used for microwave tomographic imaging too at the frequency of 3000 MHz. Experimentally obtained time domain results are substantiated by finite difference time domain (FDTD) analysis. 2-D tomographic images are reconstructed with the collected scattered data using distorted Born iterative method. Variations of dielectric permittivity in breast samples are distinguishable from the obtained permittivity profiles.

Dielectric Studies of Corn Syrup for Applications in Microwave Breast Imaging

Permittivity and conductivity studies of corn syrup in various concentrations are performed using coaxial cavity perturbation technique over a frequency range of 250 MHz–3000 MHz. The results are utilized to estimate relaxation time and dipole moments of the samples. The stability of the material over the variations of time is studied. The measured specific absorption rate of the material complies with the microwave power absorption rate of biological tissues. This suggests the feasibility of using corn syrup as a suitable, cost effective coupling medium for microwave breast imaging. The material can also be used as an efficient breast phantom in microwave breast imaging studies.

Two-dimensional Microwave Tomographic Imaging of Breast Tissues

Despite its recognized value in detecting and characterizing breast disease, X-ray mammography has important limitations that motivate the quest for alternatives to augment the diagnostic tools that are currently available to the radiologist. The rationale for pursuing electromagnetic methods are based on the significant dielectric contrast between normal and cancerous breast tissues, when exposed to microwaves. The present study analyzes two-dimensional microwave tomographic imaging on normal and malignant breast tissue samples extracted by mastectomy, to assess the suitability of the technique for early detection ofbreast cancer. The tissue samples are immersed in matching coupling medium and are illuminated by 3 GHz signal. 2-D tomographic images ofthe breast tissue samples are reconstructed from the collected scattered data using distorted Born iterative method. Variations of dielectric permittivity in breast samples are distinguishable from the obtained permittivity profiles, which is a clear indication of the presence of malignancy. Hence microwave tomographic imaging is proposed as an alternate imaging modality for early detection ofbreast cancer.

An update of the mechanisms of resistance to EGFR-tyrosine kinase inhibitors in breast cancer: gefitinib (Iressatrade mark)-induced changes in the expression and nucleo-cytoplasmic trafficking of HER-ligands (Review)

Intrinsic resistance to the epidermal growth factor receptor (EGFR; HER1) tyrosine kinase inhibitor (TKI) gefitinib, and more generally to EGFR TKIs, is a common phenomenon in breast cancer. The availability of molecular criteria for predicting sensitivity to EGFR-TKIs is, therefore, the most relevant issue for their correct use and for planning future research. Though it appears that in non-small-cell lung cancer (NSCLC) response to gefitinib is directly related to the occurrence of specific mutations in the EGFR TK domain, breast cancer patients cannot be selected for treatment with gefitinib on the same basis as such EGFR mutations have been reported neither in primary breast carcinomas nor in several breast cancer cell lines. Alternatively, there is a general agreement on the hypothesis that the occurrence of molecular alterations that activate transduction pathways downstream of EGFR (i.e., MEK1/MEK2 - ERK1/2 MAPK and PI-3'K - AKT growth/survival signaling cascades) significantly affect the response to EGFR TKIs in breast carcinomas. However, there are no studies so far addressing a role of EGF-related ligands as intrinsic breast cancer cell modulators of EGFR TKI efficacy. We recently monitored gene expression profiles and sub-cellular localization of HER-1/-2/-3/-4 related ligands (i.e., EGF, amphiregulin, transforming growth factor-α, ß-cellulin, epiregulin and neuregulins) prior to and after gefitinib treatment in a panel of human breast cancer cell lines. First, gefitinibinduced changes in the endogenous levels of EGF-related ligands correlated with the natural degree of breast cancer cell sensitivity to gefitinib. While breast cancer cells intrinsically resistant to gefitinib (IC50 ≥15 μM) markedly up-regulated (up to 600 times) the expression of genes codifying for HERspecific ligands, a significant down-regulation (up to 106 times) of HER ligand gene transcription was found in breast cancer cells intrinsically sensitive to gefitinib (IC50 ≤1 μM). Second, loss of HER1 function differentially regulated the nuclear trafficking of HER-related ligands. While gefitinib treatment induced an active import and nuclear accumulation of the HER ligand NRG in intrinsically gefitinib-resistant breast cancer cells, an active export and nuclear loss of NRG was observed in intrinsically gefitinib-sensitive breast cancer cells. In summary, through in vitro and pharmacodynamic studies we have learned that, besides mutations in the HER1 gene, oncogenic changes downstream of HER1 are the key players regulating gefitinib efficacy in breast cancer cells. It now appears that pharmacological inhibition of HER1 function also leads to striking changes in both the gene expression and the nucleo-cytoplasmic trafficking of HER-specific ligands, and that this response correlates with the intrinsic degree of breast cancer sensitivity to the EGFR TKI gefitinib. The relevance of this previously unrecognized intracrine feedback to gefitinib warrants further studies as cancer cells could bypass the antiproliferative effects of HER1-targeted therapeutics without a need for the overexpression and/or activation of other HER family members and/or the activation of HER-driven downstream signaling cascades

Modeling and Classifying Breast Tissue Density in Mammograms

We present a new approach to model and classify breast parenchymal tissue. Given a mammogram, first, we will discover the distribution of the different tissue densities in an unsupervised manner, and second, we will use this tissue distribution to perform the classification. We achieve this using a classifier based on local descriptors and probabilistic Latent Semantic Analysis (pLSA), a generative model from the statistical text literature. We studied the influence of different descriptors like texture and SIFT features at the classification stage showing that textons outperform SIFT in all cases. Moreover we demonstrate that pLSA automatically extracts meaningful latent aspects generating a compact tissue representation based on their densities, useful for discriminating on mammogram classification. We show the results of tissue classification over the MIAS and DDSM datasets. We compare our method with approaches that classified these same datasets showing a better performance of our proposal

A Novel Breast Tissue Density Classification Methodology

It has been shown that the accuracy of mammographic abnormality detection methods is strongly dependent on the breast tissue characteristics, where a dense breast drastically reduces detection sensitivity. In addition, breast tissue density is widely accepted to be an important risk indicator for the development of breast cancer. Here, we describe the development of an automatic breast tissue classification methodology, which can be summarized in a number of distinct steps: 1) the segmentation of the breast area into fatty versus dense mammographic tissue; 2) the extraction of morphological and texture features from the segmented breast areas; and 3) the use of a Bayesian combination of a number of classifiers. The evaluation, based on a large number of cases from two different mammographic data sets, shows a strong correlation ( and 0.67 for the two data sets) between automatic and expert-based Breast Imaging Reporting and Data System mammographic density assessment

Automatic classification of breast density

A recent trend in digital mammography is computer-aided diagnosis systems, which are computerised tools designed to assist radiologists. Most of these systems are used for the automatic detection of abnormalities. However, recent studies have shown that their sensitivity is significantly decreased as the density of the breast increases. This dependence is method specific. In this paper we propose a new approach to the classification of mammographic images according to their breast parenchymal density. Our classification uses information extracted from segmentation results and is based on the underlying breast tissue texture. Classification performance was based on a large set of digitised mammograms. Evaluation involves different classifiers and uses a leave-one-out methodology. Results demonstrate the feasibility of estimating breast density using image processing and analysis techniques

A new approach to the classification of mammographic masses and normal breast tissue

A new approach to mammographic mass detection is presented in this paper. Although different algorithms have been proposed for such a task, most of them are application dependent. In contrast, our approach makes use of a kindred topic in computer vision adapted to our particular problem. In this sense, we translate the eigenfaces approach for face detection/classification problems to a mass detection. Two different databases were used to show the robustness of the approach. The first one consisted on a set of 160 regions of interest (RoIs) extracted from the MIAS database, being 40 of them with confirmed masses and the rest normal tissue. The second set of RoIs was extracted from the DDSM database, and contained 196 RoIs containing masses and 392 with normal, but suspicious regions. Initial results demonstrate the feasibility of using such approach with performances comparable to other algorithms, with the advantage of being a more general, simple and cost-effective approach

"Genome-Wide Linkage in a Highly Consanguineous Pedigree Reveals Two Novel Loci on Chromosome 7 for Non-Syndromic Familial Premature Ovarian Failure"

Background: The human condition known as Premature Ovarian Failure (POF) is characterized by loss of ovarian function before the age of 40. A majority of POF cases are sporadic, but 10–15% are familial, suggesting a genetic origin of the disease. Although several causal mutations have been identified, the etiology of POF is still unknown for about 90% of the patients. Methodology/Principal Findings: We report a genome-wide linkage and homozygosity analysis in one large consanguineous Middle-Eastern POF-affected family presenting an autosomal recessive pattern of inheritance. We identified two regions with a LODmax of 3.26 on chromosome 7p21.1-15.3 and 7q21.3-22.2, which are supported as candidate regions by homozygosity mapping. Sequencing of the coding exons and known regulatory sequences of three candidate genes (DLX5, DLX6 and DSS1) included within the largest region did not reveal any causal mutations. Conclusions/Significance: We detect two novel POF-associated loci on human chromosome 7, opening the way to the identification of new genes involved in the control of ovarian development and function.

The Autoimmune Tautology: From Polyautoimmunity and Familial Autoimmunity to the Autoimmune Genes

Autoimmune diseases (ADs) are chronic conditions initiated by the loss of immunological tolerance to self-antigens and represent a heterogeneous group of disorders that afflict specific target organs ormultiple organ systems [1]. The chronic nature of these diseases places a significant burden on the utilization of medical care, direct and indirect economic costs, and quality of life. The fact that ADs share several clinical signs and symptoms (i.e., subphenotypes), physiopathological mechanisms, and genetic factors has been called autoimmune tautology and indicates that they have common mechanisms

Effects of 17β-estradiol and tamoxifen on the induction of chromosomal abnormalities and on the expression of her2 gene in breast cancer cell lines

This study covers an area of great importance in the research of breast cancer, related to the study of the effects of both estrogens (E2) and anti-estrogens (Tamoxifen) on chromosomes and of modulation of gene expression. Considering that breast cancer is a very heterogeneous disease and that patients respond differently to treatment, the identification of chromosomal abnormalities as well as genes responsive to 17β-estradiol (E2) and Tamoxifen (TAM) could provide the necessary framework to understand the complex effects of this hormone in target cells and could explain, at least in part, the development of cellular resistance to TAM treatment and the subsequent best therapeutic option. In this order of ideas, we determined the effects of E2 and TAM on the chromosomes and on the modulation of gene expression in four breast cancer cell lines, which represent three of the five subtypes of breast cancer known at present. The results are presented in six chapters - each one has a group of the results achieved around the cytogenetic characteristics and gene expression profiles of four cell lines and the effects of E2 and TAM incubation on those. The first chapter describes the main features of breast cancer, furthering the use and effects of E2 and TAM treatment.

Factores asociados a recaída en pacientes con cáncer de mama de una institución de Bogotá

Introducción: El cáncer de seno es la primera causa de cáncer entre las mujeres, además es la primera causa de muerte por cáncer entre las hispanas y la segunda entre otras razas, sin contar con el gran impacto social y económico que conlleva esta patología. Esto motiva la realización de estudios propios, que permitan ampliar nuestro conocimiento y aportar a la literatura colombiana, una publicación que refleje los factores asociados a la recaída en el cáncer de mama. Métodos: Estudio observacional analítico retrospectivo de casos y controles en el que se tomaron 267 historias clínicas de pacientes con diagnóstico de cáncer de seno, clasificadas según estadio clínico y expresión molecular del tumor, se analizaron los factores más fuertemente asociados a la recaída. Resultados: La población total consistió en 267 mujeres de las cuales 58 presentaron recaída, con un relación caso – control, 1:3. Al evaluar los grupos se evidencia homogeneidad en cuanto a edad, tipo de neoplasia, paridad e histología con lo que concluimos que estos grupos son comparables. Se presentó una tasa de mortalidad de 13,8 % en las pacientes que presentaron recaída tumoral vs un 0% de mortalidad en aquellas pacientes sin recaída. Adicionalmente se evidencia una relación entre la presencia del receptor HER 2 y recaída tumoral, que aunque no es estadísticamente significativa (p = 0.112) es importante tener en cuenta por su significancia clínica. Por su parte la presencia de receptor de estrógenos y progestágenos no es un predictor de recaída. La realización de cirugía se muestra como un factor de protección (OAR: 0.046 p = 0.008). Finalmente se encontró una asociación estadísticamente significativa como variables de asociación a recaída tumoral: la edad (p=0.009), el estadio clínico en el momento del diagnóstico (p= <0.001) y la clasificación molecular del tumor (p= 0.016). Conclusiones: Se identificaron como factores asociados a recaída tumoral en pacientes con cáncer de mama de una institución de Bogotá, Colombia a: la edad, el estadio clínico en el momento del diagnóstico y la clasificación molecular del tumor, confirmando la agresividad de los tumores triple negativos. Todos los hallazgos son compatibles a lo descrito en la literatura mundial. Esto permite definir la necesidad de generar en nuestro país estrategias de salud pública, que permitan la educación a todos los grupos etarios para el tamizaje en población joven que está siendo afectada, la detección en estadios tempranos del cáncer de mama, asociados a priorización del manejo y mejoras en la ruta de atención de las pacientes que permitan impactar positivamente en el desenlace y calidad de vida de las mujeres con esta patología. Adicionalmente estos resultados impulsan a la continua investigación de nuevas tecnologías y medicamentos que permitan combatir los tumores más agresivos molecularmente hablando.

Factores perinatales para riesgo de sobrepeso y obesidad en niños de 4 a 5 años en Colombia 2010.

Introducción: La OMS revela que en 2010 alrededor de 43 millones de niños menores de 5 años presentan sobrepeso. En Colombia según la Encuesta Nacional de Situación Nutricional en Colombia en su versión 2005, mostraba una prevalencia general de sobrepeso de 3.1% niños de 0 a 4 años. Es una condición de salud de origen multifactorial en la que interviene factores genéticos, ambientales, maternos y perinatales. Objetivo: Establecer la asociación de riesgo entre el bajo peso al nacer y el desarrollo de sobrepeso y obesidad en niños de 4 a 5 años. Metodología: Se realizó un estudio observacional descriptivo retrospectivo de corte transversal con los datos nutricionales, maternos y perinatales de la Encuesta Nacional de Demografía en Salud del año 2010 en Colombia. Se analizó la asociación entre la variable independiente bajo peso al nacer con el desenlace sobrepeso y obesidad en menores de 4 a 5 años, usando como medida el IMC según la edad. Se realizaron análisis univariados, bivariados y de regresión logística con un modelo de riesgo según las variables que inciden en el desenlace y la variable independiente. Resultados: La muestra obtenida para el estudio fue de 2166 niños de 4 a 5 años de edad quienes cumplían los criterios de inclusión. La prevalencia de sobrepeso u obesidad en la primera infancia fue de 21.8% (472) y el bajo peso al nacer. Los resultados sugieren la asociación de bajo peso y sobrepeso u obesidad es de ORajustado= 0.560 (0.356 – 0.881). Conclusiones: Los resultados sugieren que existe una asociación como factor protector entre el bajo peso y el sobrepeso u obesidad en la primera infancia. Sin embargo, debido al comportamiento de las variables consideradas en la muestra no hay suficiente información para rechazar completamente la hipótesis nula.

Breast cancer incidence and overdiagnosis in Catalonia (Spain)

Early detection of breast cancer (BC) with mammography may cause overdiagnosis and overtreatment, detecting tumors which would remain undiagnosed during a lifetime. The aims of this study were: first, to model invasive BC incidence trends in Catalonia (Spain) taking into account reproductive and screening data; and second, to quantify the extent of BC overdiagnosis. We modeled the incidence of invasive BC using a Poisson regression model. Explanatory variables were: age at diagnosis and cohort characteristics (completed fertility rate, percentage of women that use mammography at age 50, and year of birth). This model also was used to estimate the background incidence in the absence of screening. We used a probabilistic model to estimate the expected BC incidence if women in the population used mammography as reported in health surveys. The difference between the observed and expected cumulative incidences provided an estimate of overdiagnosis.Incidence of invasive BC increased, especially in cohorts born from 1940 to 1955. The biggest increase was observed in these cohorts between the ages of 50 to 65 years, where the final BC incidence rates more than doubled the initial ones. Dissemination of mammography was significantly associated with BC incidence and overdiagnosis. Our estimates of overdiagnosis ranged from 0.4% to 46.6%, for women born around 1935 and 1950, respectively.Our results support the existence of overdiagnosis in Catalonia attributed to mammography usage, and the limited malignant potential of some tumors may play an important role. Women should be better informed about this risk. Research should be oriented towards personalized screening and risk assessment tools