Development of a CAD system for automatic classification of microcalcifications based on FPGA

This paper presents a Computer Aided Diagnosis (CAD) system that automatically classifies microcalcifications detected on digital mammograms into one of the five types proposed by Michele Le Gal, a classification scheme that allows radiologists to determine whether a breast tumor is malignant or not without the need for surgeries. The developed system uses a combination of wavelets and Artificial Neural Networks (ANN) and is executed on an Altera DE2-115 Development Kit, a kit containing a Field-Programmable Gate Array (FPGA) that allows the system to be smaller, cheaper and more energy efficient. Results have shown that the system was able to correctly classify 96.67% of test samples, which can be used as a second opinion by radiologists in breast cancer early diagnosis. (C) 2013 The Authors. Published by Elsevier B.V.

Optimum-Path Forest Applied for Breast Masses Classification

In Computer-Aided Diagnosis-based schemes in mammography analysis each module is interconnected, which directly affects the system operation as a whole. The identification of mammograms with and without masses is highly needed to reduce the false positive rates regarding the automatic selection of regions of interest for further image segmentation. This study aims to evaluate the performance of three techniques in classifying regions of interest as containing masses or without masses (without clinical findings), as well as the main contribution of this work is to introduce the Optimum-Path Forest (OPF) classifier in this context, which has never been done so far. Thus, we have compared OPF against with two sorts of neural networks in a private dataset composed by 120 images: Radial Basis Function and Multilayer Perceptron (MLP). Texture features have been used for such purpose, and the experiments have demonstrated that MLP networks have been slightly better than OPF, but the former is much faster, which can be a suitable tool for real-time recognition systems.

Desigualdade social no adoecimento e morte por câncer de boca e orofaríngeo no Município de São Paulo, Brasil: 1997 a 2008

A ocupação do espaço geográfico é determinada historicamente pelo modelo socioeconômico e pelo dinamismo de suas relações sociais, políticas e ideológicas. O objetivo deste trabalho é avaliar a distribuição espacial e o efeito de indicadores socioeconômicos no adoecimento e morte por câncer de boca e orofaríngeo no Município de São Paulo, Brasil, no período de 1997 a 2008. Os dados foram coletados no Registro de Câncer de Base Populacional e no Programa de Aprimoramento das Informações de Mortalidade - PRO-AIM e georreferenciados pelos softwares Terraview e GeoDa. O referencial teórico para avaliação dos resultados foi baseado na teoria de Milton Santos. As taxas de incidência apresentaram um índice de autocorrelação Global de Moran de 0,226 e as taxas de mortalidade de 0,337. A Incidência de câncer de boca e orofaríngeo não apresenta um padrão espacial bem definido no Município de São Paulo, mas é bastante desigual no que se refere à Mortalidade, concentrando as suas menores taxas na área central, mais rica e economicamente menos desigual.

Timely follow-up of abnormal diagnostic imaging test results in an outpatient setting: are electronic medical records achieving their potential?

BACKGROUND: Given the fragmentation of outpatient care, timely follow-up of abnormal diagnostic imaging results remains a challenge. We hypothesized that an electronic medical record (EMR) that facilitates the transmission and availability of critical imaging results through either automated notification (alerting) or direct access to the primary report would eliminate this problem. METHODS: We studied critical imaging alert notifications in the outpatient setting of a tertiary care Department of Veterans Affairs facility from November 2007 to June 2008. Tracking software determined whether the alert was acknowledged (ie, health care practitioner/provider [HCP] opened the message for viewing) within 2 weeks of transmission; acknowledged alerts were considered read. We reviewed medical records and contacted HCPs to determine timely follow-up actions (eg, ordering a follow-up test or consultation) within 4 weeks of transmission. Multivariable logistic regression models accounting for clustering effect by HCPs analyzed predictors for 2 outcomes: lack of acknowledgment and lack of timely follow-up. RESULTS: Of 123 638 studies (including radiographs, computed tomographic scans, ultrasonograms, magnetic resonance images, and mammograms), 1196 images (0.97%) generated alerts; 217 (18.1%) of these were unacknowledged. Alerts had a higher risk of being unacknowledged when the ordering HCPs were trainees (odds ratio [OR], 5.58; 95% confidence interval [CI], 2.86-10.89) and when dual-alert (>1 HCP alerted) as opposed to single-alert communication was used (OR, 2.02; 95% CI, 1.22-3.36). Timely follow-up was lacking in 92 (7.7% of all alerts) and was similar for acknowledged and unacknowledged alerts (7.3% vs 9.7%; P = .22). Risk for lack of timely follow-up was higher with dual-alert communication (OR, 1.99; 95% CI, 1.06-3.48) but lower when additional verbal communication was used by the radiologist (OR, 0.12; 95% CI, 0.04-0.38). Nearly all abnormal results lacking timely follow-up at 4 weeks were eventually found to have measurable clinical impact in terms of further diagnostic testing or treatment. CONCLUSIONS: Critical imaging results may not receive timely follow-up actions even when HCPs receive and read results in an advanced, integrated electronic medical record system. A multidisciplinary approach is needed to improve patient safety in this area.

An analysis of two methods for the classification of stage of readiness to obtain repeat mammography screening

Background and purpose: Breast cancer continues to be a health problem for women, representing 28 percent of all female cancers and remaining one of the leading causes of death for women. Breast cancer incidence rates become substantial before the age of 50. After menopause, breast cancer incidence rates continue to increase with age creating a long-lasting source of concern (Harris et al., 1992). Mammography, a technique for the detection of breast tumors in their nonpalpable stage when they are most curable, has taken on considerable importance as a public health measure. The lifetime risk of breast cancer is approximately 1 in 9 and occurs over many decades. Recommendations are that screening be periodic in order to detect cancer at early stages. These recommendations, largely, are not followed. Not only are most women not getting regular mammograms, but this circumstance is particularly the case among older women where regular mammography has been proven to reduce mortality by approximately 30 percent. The purpose of this project was to increase our understanding of factors that are associated with stage of readiness to obtain subsequent mammograms. A secondary purpose of this research was to suggest further conceptual considerations toward the extension of the Transtheoretical Model (TTM) of behavior change to repeat screening mammography. ^ Methods. A sample (n = 1,222) of women 50 years and older in a large multi-specialty clinic in Houston, Texas was surveyed by mail questionnaire regarding their previous screening experience and stage of readiness to obtain repeat screening. A computerized database, maintained on all women who undergo mammography at the clinic, was used to identify women who are eligible for the project. The major statistical technique employed to select the significant variables and to examine the man and interaction effects of independent variables on dependent variables was polychotomous stepwise, logistic regression. A prediction model for each stage of readiness definition was estimated. The expected probabilities for stage of readiness were calculated to assess the magnitude and direction of significant predictors. ^ Results. Analysis showed that both ways of defining stage of readiness for obtaining a screening mammogram were associated with specific constructs, including decisional balance and processes of the change. ^ Conclusions. The results of the present study demonstrate that the TTM appears to translate to repeat mammography screening. Findings in the current study also support finding of previous studies that suggest that stage of readiness is associated with respondent decisional balance and the processes of change. ^

Factors associated with mammography utilization in Sao Paulo and Mexico city elderly females

Introduction. Breast cancer has the highest incidence and mortality rates of all cancers in Sao Paulo and Mexico City women with rates expected to rise due to increasing elderly populations. While mammograms could reduce the breast cancer burden, little information exists about screening behavior factors in these areas. The primary objective of this study is testing the association of socio-demographic, geographic, and health access/health status variables on mammogram screenings in elderly females in both cities. Studying the regions' healthcare systems and their screening impact is the ancillary objective. ^ Methods. Accounting for the complex sample design (weights, stratification, and clusters) of the 1999-2000 SABE study, analysis of mammogram utilization in the past two years was performed. The sample consisted of 1239 women from Sao Paulo and 1349 women from Mexico City. ^ Results. Having private insurance in Sao Paulo (OR = 5.86) and Mexico City (OR = 4.09) increased the chance of having a mammogram in the targeted women. In both cities, women with higher levels of education had higher likelihoods of screening (Sao Paulo OR = 4.56 and Mexico City OR = 3.04). Age, regular medical care, and health status were significant in Sao Paulo; however, the factors showed no significance in Mexico City. ^ Discussion. Mammogram utilization can reduce mortality from breast cancer, and understanding screening factors is crucial to screening adherence. Addressing key variables may lead to increased screening and decreased breast cancer mortality in elderly women in Sao Paulo, Mexico City, and similar regions. ^

Information sources influencing urban Mexican-American women's cancer screening participation

Breast and cervical cancer, though less common in Mexican-American than in Anglo women, are more likely to go undetected in Mexican-American women, leaving them more vulnerable to advanced disease and death. Although highly effective screening tests--the Pap smear and the mammogram--can detect these cancers early, many Mexican-American women do not regularly undergo these preventive screening tests.^ To explore the differential influence of encouraging sources of health information, this investigation examined the relationship between encouragement from a "peer"--husband or partner, child or children, other family members, or close friends--and a "health professional"--a doctor, a nurse, or another health professional--on Mexican-American women's cancer screening intentions and behaviors. Furthermore, this research explored whether the sources' influence on cancer screening intentions and behaviors differed depending on level of acculturation.^ One thousand seven hundred eleven surveys of Mexican-American women were analyzed to identify the source that most effectively encourages these women to participate in cancer screening. The data provided evidence that health professionals strongly influenced this population's cancer screening intentions and behaviors. Evidence for peer influence was also found; however, it was usually weaker, and, in some cases, negligible. Peer encouragement was related to Pap test behaviors and mammogram intentions, but not to Pap test intentions or mammogram behaviors. Consistently, women reported greater intentions and screening behaviors when encouraged from a health professional than from a peer. Acculturation was not found to be a modifying variable related to the relationship between sources of information and Pap test or mammogram intentions and behaviors.^ Because health professionals were identified as strongly influencing both intentions and behaviors for Pap tests and mammograms, further efforts should be undertaken to urge them to encourage their clients to obtain cancer screening. Failure to provide this encouragement leads to missed opportunities. Enlisting support from peers also may help to increase cancer screening participation in urban Mexican-American women; however, the consistently greater intentions and behaviors related to a health professional's encouragement indicated the greater power of the latter. ^

Impact of racial differences in medical care on breast cancer survival: Findings from a large nationwide and retrospective cohort study

Background: No studies have attempted to determine whether nodal surgery utilization, time to initiation and completion of chemotherapy or surveillance mammography impact breast cancer survival. ^ Objectives and Methods: To determine whether receipt of nodal surgery, initiation and completion of chemotherapy, and surveillance mammography impact of racial disparities in survival among breast cancer patients in SEER areas, 1992-2005. ^ Results: Adjusting for nodal surgery did not reduce racial disparities in survival. Patients who initiated chemotherapy more than three months after surgery were 1.8 times more likely to die of breast cancer (95% CI 1.3-2.5) compared to those who initiated chemotherapy less than a month after surgery, even after controlling for known confounders or controlling for race. Despite correcting for chemotherapy initiation and completion and known predictors of outcome, African American women still had worse disease specific survival than their Caucasian counterparts. We found that non-whites underwent surveillance mammography less frequently compared with whites and mammography use during a one- or two-year time interval was associated with a small reduced risk of breast-cancer-specific and all-cause mortality. Women who received a mammogram during a two-year interval could expect the same disease-specific survival benefit or overall survival benefit as women who received a mammogram during a one-year interval. We found that while adjustment for surveillance mammography receipt and physician visits reduced differences in mortality between blacks and whites, these survival disparities were eliminated after adjusting for the number of surveillance mammograms received. ^ Conclusions: The disparities in survival among African American and Hispanic women with breast cancer are not explained by nodal surgery utilization or chemotherapy initiation and chemotherapy completion. Surveillance mammograms, physician visits and number of mammograms received may play a major role in achieving equal outcomes for breast cancer-specific mortality for women diagnosed with primary breast cancer. Racial disparities in all-cause mortality were explained by racial differences in surveillance mammograms to certain degree, but were no longer significant after controlling for differences in comorbidity. Focusing on access to quality care and post treatment surveillance might help achieve national goals to eliminate racial disparities in healthcare and outcomes. ^

Improvement for detection of microcalcifications through clustering algorithms and artificial neural networks

A new method for detecting microcalcifications in regions of interest (ROIs) extracted from digitized mammograms is proposed. The top-hat transform is a technique based on mathematical morphology operations and, in this paper, is used to perform contrast enhancement of the mi-crocalcifications. To improve microcalcification detection, a novel image sub-segmentation approach based on the possibilistic fuzzy c-means algorithm is used. From the original ROIs, window-based features, such as the mean and standard deviation, were extracted; these features were used as an input vector in a classifier. The classifier is based on an artificial neural network to identify patterns belonging to microcalcifications and healthy tissue. Our results show that the proposed method is a good alternative for automatically detecting microcalcifications, because this stage is an important part of early breast cancer detection

Image Segmentation Using Ant System-based Clustering Algorithm

Industrial applications of computer vision sometimes require detection of atypical objects that occur as small groups of pixels in digital images. These objects are difficult to single out because they are small and randomly distributed. In this work we propose an image segmentation method using the novel Ant System-based Clustering Algorithm (ASCA). ASCA models the foraging behaviour of ants, which move through the data space searching for high data-density regions, and leave pheromone trails on their path. The pheromone map is used to identify the exact number of clusters, and assign the pixels to these clusters using the pheromone gradient. We applied ASCA to detection of microcalcifications in digital mammograms and compared its performance with state-of-the-art clustering algorithms such as 1D Self-Organizing Map, k-Means, Fuzzy c-Means and Possibilistic Fuzzy c-Means. The main advantage of ASCA is that the number of clusters needs not to be known a priori. The experimental results show that ASCA is more efficient than the other algorithms in detecting small clusters of atypical data.

Microcalcifications Detection using PFCM and ANN

This work presents a method to detect Microcalcifications in Regions of Interest from digitized mammograms. The method is based mainly on the combination of Image Processing, Pattern Recognition and Artificial Intelligence. The Top-Hat transform is a technique based on mathematical morphology operations that, in this work is used to perform contrast enhancement of microcalcifications in the region of interest. In order to find more or less homogeneous regions in the image, we apply a novel image sub-segmentation technique based on Possibilistic Fuzzy c-Means clustering algorithm. From the original region of interest we extract two window-based features, Mean and Deviation Standard, which will be used in a classifier based on a Artificial Neural Network in order to identify microcalcifications. Our results show that the proposed method is a good alternative in the stage of microcalcifications detection, because this stage is an important part of the early Breast Cancer detection

Aplicación de técnicas de inteligencia artificial para contribuir en la detección de microcalcificaciones en mamografía digitalizada

A nivel mundial, el cáncer de mama es el tipo de cáncer más frecuente además de una de las principales causas de muerte entre la población femenina. Actualmente, el método más eficaz para detectar lesiones mamarias en una etapa temprana es la mamografía. Ésta contribuye decisivamente al diagnóstico precoz de esta enfermedad que, si se detecta a tiempo, tiene una probabilidad de curación muy alta. Uno de los principales y más frecuentes hallazgos en una mamografía, son las microcalcificaciones, las cuales son consideradas como un indicador importante de cáncer de mama. En el momento de analizar las mamografías, factores como la capacidad de visualización, la fatiga o la experiencia profesional del especialista radiólogo hacen que el riesgo de omitir ciertas lesiones presentes se vea incrementado. Para disminuir dicho riesgo es importante contar con diferentes alternativas como por ejemplo, una segunda opinión por otro especialista o un doble análisis por el mismo. En la primera opción se eleva el coste y en ambas se prolonga el tiempo del diagnóstico. Esto supone una gran motivación para el desarrollo de sistemas de apoyo o asistencia en la toma de decisiones. En este trabajo de tesis se propone, se desarrolla y se justifica un sistema capaz de detectar microcalcificaciones en regiones de interés extraídas de mamografías digitalizadas, para contribuir a la detección temprana del cáncer demama. Dicho sistema estará basado en técnicas de procesamiento de imagen digital, de reconocimiento de patrones y de inteligencia artificial. Para su desarrollo, se tienen en cuenta las siguientes consideraciones: 1. Con el objetivo de entrenar y probar el sistema propuesto, se creará una base de datos de imágenes, las cuales pertenecen a regiones de interés extraídas de mamografías digitalizadas. 2. Se propone la aplicación de la transformada Top-Hat, una técnica de procesamiento digital de imagen basada en operaciones de morfología matemática. La finalidad de aplicar esta técnica es la de mejorar el contraste entre las microcalcificaciones y el tejido presente en la imagen. 3. Se propone un algoritmo novel llamado sub-segmentación, el cual está basado en técnicas de reconocimiento de patrones aplicando un algoritmo de agrupamiento no supervisado, el PFCM (Possibilistic Fuzzy c-Means). El objetivo es encontrar las regiones correspondientes a las microcalcificaciones y diferenciarlas del tejido sano. Además, con la finalidad de mostrar las ventajas y desventajas del algoritmo propuesto, éste es comparado con dos algoritmos del mismo tipo: el k-means y el FCM (Fuzzy c-Means). Por otro lado, es importante destacar que en este trabajo por primera vez la sub-segmentación es utilizada para detectar regiones pertenecientes a microcalcificaciones en imágenes de mamografía. 4. Finalmente, se propone el uso de un clasificador basado en una red neuronal artificial, específicamente un MLP (Multi-layer Perceptron). El propósito del clasificador es discriminar de manera binaria los patrones creados a partir de la intensidad de niveles de gris de la imagen original. Dicha clasificación distingue entre microcalcificación y tejido sano. ABSTRACT Breast cancer is one of the leading causes of women mortality in the world and its early detection continues being a key piece to improve the prognosis and survival. Currently, the most reliable and practical method for early detection of breast cancer is mammography.The presence of microcalcifications has been considered as a very important indicator ofmalignant types of breast cancer and its detection and classification are important to prevent and treat the disease. However, the detection and classification of microcalcifications continue being a hard work due to that, in mammograms there is a poor contrast between microcalcifications and the tissue around them. Factors such as visualization, tiredness or insufficient experience of the specialist increase the risk of omit some present lesions. To reduce this risk, is important to have alternatives such as a second opinion or a double analysis for the same specialist. In the first option, the cost increases and diagnosis time also increases for both of them. This is the reason why there is a great motivation for development of help systems or assistance in the decision making process. This work presents, develops and justifies a system for the detection of microcalcifications in regions of interest extracted fromdigitizedmammographies to contribute to the early detection of breast cancer. This systemis based on image processing techniques, pattern recognition and artificial intelligence. For system development the following features are considered: With the aim of training and testing the system, an images database is created, belonging to a region of interest extracted from digitized mammograms. The application of the top-hat transformis proposed. This image processing technique is based on mathematical morphology operations. The aim of this technique is to improve the contrast betweenmicrocalcifications and tissue present in the image. A novel algorithm called sub-segmentation is proposed. The sub-segmentation is based on pattern recognition techniques applying a non-supervised clustering algorithm known as Possibilistic Fuzzy c-Means (PFCM). The aim is to find regions corresponding to the microcalcifications and distinguish them from the healthy tissue. Furthermore,with the aim of showing themain advantages and disadvantages this is compared with two algorithms of same type: the k-means and the fuzzy c-means (FCM). On the other hand, it is important to highlight in this work for the first time the sub-segmentation is used for microcalcifications detection. Finally, a classifier based on an artificial neural network such as Multi-layer Perceptron is used. The purpose of this classifier is to discriminate froma binary perspective the patterns built from gray level intensity of the original image. This classification distinguishes between microcalcifications and healthy tissue.

Acesso ao tratamento oncológico no município de São Paulo: o câncer de mama como condição traçadora

Acompanhando a tendência mundial, o Brasil apresenta um processo de envelhecimento de sua população, caracterizado pelo aumento das condições crônicas, inclusive do câncer. O quadro convoca mudanças profundas nos sistemas de saúde, demandando a implantação de Redes de Atenção, a fim de garantir acesso a todos os níveis de atenção, superando a fragmentação do cuidado. Com o intuito de conhecer os avanços no que se refere à atenção oncológica em rede, analisou-se o acesso ao tratamento do câncer em São Paulo, especialmente a partir do surgimento da Lei dos sessenta dias. Foram considerados os sistemas de monitoramento da atenção oncológica no município, além de analisados os itinerários assistenciais de usuárias, utilizando o câncer de mama como condição traçadora. Não foi possível identificar uma redução do tempo de espera para iniciar o tratamento, a partir do banco do Registro Hospitalar de Câncer de são Paulo, considerando que não há completude na base a partir de 2013, sendo observado que o tempo indicado na lei foi ultrapassado nos dois anos anteriores. Da mesma forma, notou-se um aumento da proporção de estádios avançados nesse período. Ainda com relação à variável tempo, as informações no SIGA demonstraram que, em 2013, o tempo médio para uma consulta em Onco-mastologia nos serviços de gestão municipal que estão sob regulação foi de apenas 4 dias. Por meio dos Sistemas de Informação Ambulatorial e Hospitalar, observou-se um aumento estatisticamente significativo na produção de radioterapia e de cirurgias oncológicas entre os anos 2011 e 2014, e uma tendência de redução dos procedimentos quimioterápicos. O Sistema de Informação sobre Câncer de Mama demonstrou aumento no percentual de mamografias alteradas, aspecto que, ao ser analisado em conjunto com o aumento da proporção de estadiamentos avançados, pode ser indicativo de maior dificuldade no acesso ao diagnóstico precoce do câncer de mama. Observou-se que a judicialização esteve muito relacionada a acesso a medicamentos quimioterápicos, de prescrição após a entrada nos serviços especializados, o que confirma que o acesso ao tratamento de câncer de mama no município não apresenta grandes barreiras. Um importante efeito visualizado com o surgimento da Lei foi a padronização dos protocolos de acesso aos serviços de gestão municipal e estadual. Entretanto, a rede de oncologia em São Paulo continua fragmentada dentre seus componentes estruturais, as ações permanecem no plano da construção de fluxos de encaminhamento, ficando restrita à atenção especializada. A atenção oncológica na cidade é atravessada pelo setor privado, o que deixa na dependência dos prestadores a disponibilização de vagas para acesso e o fluxo interno de cada serviço. O poder ainda continua com os grandes prestadores, não sendo bem conhecidos os caminhos para o acesso a algumas instituições, nem publicizadas as informações sobre fila e tempo de espera. A legislação sozinha não é indutora de melhoria de acesso, nem muito menos de garantia de integralidade. Um importante desafio para o SUS é a integração dos serviços e a construção de redes de atenção com centralidade na APS, garantindo, acima de tudo, o diagnóstico em tempo oportuno e a efetiva gestão sobre os serviços privados contratados de média e alta complexidade.

Use of structural equation modeling to examine the association between breast cancer risk perception and repeat screening mammography among United States women

Breast cancer is the second leading cause of cancer death in United States women, estimated to be diagnosed in 1 out of 8 women in their lifetime. Screening mammography detects breast cancer in its pre-clinical stages when treatment strategies have the greatest chance of success, and is currently the only population-wide prevention method proven to reduce the morbidity and mortality associated with breast cancer. Research has shown that the majority of women are not screened annually, with estimates ranging front 6% - 30% of eligible women receiving all available annual mammograms over a 5-year or greater time frame. Health behavior theorists believe that perception of risk/susceptibility to a disease influences preventive health behavior, in this case, screening mammography The purpose of this dissertation is to examine the association between breast cancer risk perception and repeat screening mammography using a structural equation modeling (SEM) framework. A series of SEM multivariate regressions were conducted using self-reported, nationally representative data from the 2005 National Health Interview Survey. Interaction contrasts were tested to measure the potential moderating effects of variables which have been shown to be predictive of mammography use (physician recommendation, economic barriers, structural barriers, race/ethnicity) on the association between breast cancer risk perception and repeat mammography, while controlling for the covariates of age, income, region, nativity, and educational level. Of the variables tested for moderation, results of the SEM analyses identify physician recommendation as the only moderator of the relationship between risk perception and repeat mammography, thus the potentially most effective point of intervention to increase mammography screening, and decrease the morbidity and mortality associated with breast cancer. These findings expand the role of the physician from recommendation to one of attenuating the effect of risk perception and increasing repeat screening. The long range application of the research is the use of the SEM methodology to identify specific points of intervention most likely to increase preventive behavior in population-wide research, allowing for the most effective use of intervention funds.^

Insulin-Like Growth Factor-I (IGF-1), IGF-Binding Protein-3 (IGFBP-3) and mammographic features

Introduction. The IGF system has recently been shown to play an important role in the regulation of breast tumor cell proliferation. However, also breast density is currently considered as the strongest breast cancer risk factor. It is not yet clear whether these factors are interrelated and if and how they are influenced by menopausal status. The purpose of this study was to examine the possible effects of IGF-1 and IGFBP-3 and IGF-1/IGFBP-3 molar ratio on mammographic density stratified by menopausal status. Patients and methods. A group of 341 Italian women were interviewed to collect the following data: family history of breast cancer, reproductive and menstrual factors, breast biopsies, previous administration of hormonal contraceptive therapy, hormone replacement therapy (HRT) in menopause and lifestyle information. A blood sample was drawn for determination of IGF-1, IGFBP-3 levels. IGF-1/ IGFBP-3 molar ratio was then calculated. On the basis of recent mammograms the women were divided into two groups: dense breast (DB) and non-dense breast (NDB). Student’s t-test was employed to assess the association between breast density and plasma level of IGF-1, IGFBP-3 and molar ratio. To assess if this relationship was similar in subgroups of pre- and postmenopausal women, the study population was stratified by menopausal status and Student’s t-test was performed. Finally, multivariate analysis was employed to evaluate if there were confounding factors that might influence the relationship between growth factors and breast density. Results. The analysis of the relationship between mammographic density and plasma level of IGF-1, IGFBP-3 and IGF-1/ IGFBP-3 molar ratio showed that IGF-1 levels and molar ratio varied in the two groups resulting in higher mean values in the DB group (IGF-1: 109.6 versus 96.6 ng/ml; p= 0.001 and molar ratio 29.4 versus 25.5 ng/ml; p= 0.001) whereas IGFBP-3 showed similar values in both groups (DB and NDB). Analysis of plasma level of IGF-1, IGFBP-3 and IGF-1/IGFBP-3 molar ratio compared to breast density after stratification of the study population by menopausal status (premenopausal and postmenopausal) showed that there was no association between the plasma of growth factors and breast density, neither in premenopausal nor in postmenopausal patients. Multivariate analysis showed that only nulliparity, premenopausal status and body mass index (BMI) are determinants of breast density. Conclusions. Our study provides a strong evidence of a crude association between breast density and plasma levels of IGF-1 and molar ratio. On the basis of our results, it is reasonable to assume that the role of IGF-1 and molar ratio in the pathogenesis of breast cancer might be mediated through mammographic density. IGF-1 and molar ratio might thus increase the risk of cancer by increasing mammographic density.