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

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

Identification of molecular subtypes and gene expression patterns of breast cancer analysing RNA-seq data

Breast cancer is the most common diagnosed cancer and the leading cause of cancer death among females worldwide. It is considered a highly heterogeneous disease and it must be classified into more homogeneous groups. Hence, the purpose of this study was to classify breast tumors based on variations in gene expression patterns derived from RNA sequencing by using different class discovery methods. 42 breast tumors paired-samples were sequenced by Illumine Genome Analyzer and the data was analyzed and prepared by TopHat2 and htseq-count. As reported previously, breast cancer could be grouped into five main groups known as basal epithelial-like group, HER2 group, normal breast-like group and two Luminal groups with a distinctive expression profile. Classifying breast tumor samples by using PAM50 method, the most common subtype was Luminal B and was significantly associated with ESR1 and ERBB2 high expression. Luminal A subtype had ESR1 and SLC39A6 significant high expression, whereas HER2 subtype had a high expression of ERBB2 and CNNE1 genes and low luminal epithelial gene expression. Basal-like and normal-like subtypes were associated with low expression of ESR1, PgR and HER2, and had significant high expression of cytokeratins 5 and 17. Our results were similar compared with TGCA breast cancer data results and with known studies related with breast cancer classification. Classifying breast tumors could add significant prognostic and predictive information to standard parameters, and moreover, identify marker genes for each subtype to find a better therapy for patients with breast cancer.

Core communication components along the cancer care process: the perspective of breast cancer patients

This study sought to assess the impact of health care professional (HCP) communication on breast cancer patients across the acute care process as perceived by patients. Methodological approach was based on eight focus groups conducted with a sample of patients (n ¼ 37) drawn from 15 Spanish Regions; thematic analysis was undertaken using the National Cancer Institute (NCI) framework of HCP communication as the theoretical basis. Relevant results of this study were the identification of four main communication components: (1) reassurance in coping with uncertainty after symptom detection and prompt access until confirmed diagnosis; (2) fostering involvement before delivering treatments, by anticipating information on practical and emotional illness-related issues; (3) guidance on the different therapeutic options, through use of clinical scenarios; and, (4) eliciting the feeling of emotional exhaustion after ending treatments and addressing the management of potential treatment-related effects. These communication-related components highlighted the need for a comprehensive approach in this area of cancer care

Estimation of age- and stage-specific Catalan breast cancer survival functions using US and Catalan survival data

During the last part of the 1990s the chance of surviving breast cancer increased. Changes in survival functions reflect a mixture of effects. Both, the introduction of adjuvant treatments and early screening with mammography played a role in the decline in mortality. Evaluating the contribution of these interventions using mathematical models requires survival functions before and after their introduction. Furthermore, required survival functions may be different by age groups and are related to disease stage at diagnosis. Sometimes detailed information is not available, as was the case for the region of Catalonia (Spain). Then one may derive the functions using information from other geographical areas. This work presents the methodology used to estimate age- and stage-specific Catalan breast cancer survival functions from scarce Catalan survival data by adapting the age- and stage-specific US functions. Methods: Cubic splines were used to smooth data and obtain continuous hazard rate functions. After, we fitted a Poisson model to derive hazard ratios. The model included time as a covariate. Then the hazard ratios were applied to US survival functions detailed by age and stage to obtain Catalan estimations. Results: We started estimating the hazard ratios for Catalonia versus the USA before and after the introduction of screening. The hazard ratios were then multiplied by the age- and stage-specific breast cancer hazard rates from the USA to obtain the Catalan hazard rates. We also compared breast cancer survival in Catalonia and the USA in two time periods, before cancer control interventions (USA 1975–79, Catalonia 1980–89) and after (USA and Catalonia 1990–2001). Survival in Catalonia in the 1980–89 period was worse than in the USA during 1975–79, but the differences disappeared in 1990–2001. Conclusion: Our results suggest that access to better treatments and quality of care contributed to large improvements in survival in Catalonia. On the other hand, we obtained detailed breast cancer survival functions that will be used for modeling the effect of screening and adjuvant treatments in Catalonia

Rapid increase in incidence of breast ductal cancer in situ in Girona, Spain 1983-2007

Introduction: The aim of this study was to describe breast ductal cancer in situ (DCIS) incidence trends in women in the Girona province during a period of 25 years. The influence of age, use of mammography and implementation of the breast cancer screening programs was explored. Incidence of subsequent invasive breast cancers (IBC) and DCIS treatment was also considered. Materials and Methods: Cases diagnosed with primary pure DCIS (n=416) during 1983-2007 were extracted from the population-based Girona Cancer Registry. The estimated annual percent change was estimated using joinpoint analysis. Results: DCIS incidence showed a sharp rise until 1998, followed by a less marked upward trend. Among women aged 50-69 the increase was particularly important between 1992 and in 1996, reflecting the spread in mammography use. Conclusion: The upward trend of DCIS was mainly related to an increase in mammography use either opportunistic or as a result of screening implementation

Reliability of intraoperative ultrasound in margin status assessment in women undergoing breast conserving surgery

Background: Effective treatment for breast cancer requires accurate preoperative planning, developing and implementing a consistent definition of margin clearance, and using tools that provide detailed real-time intraoperative information on margin status. Intraoperative ultrasound (IOUS) may fulfil these requirements and may offer few advantages that other preoperative localization and intraoperative margin assessment techniques may notPurpose: The goal of the present work is to determine how accurate the intraoperative ultrasound should be to acquire complete surgical excision with negative histological margins in patients undergoing Breast Conservative SurgeryDesign: A diagnostic test study with a cross-sectional design carried out in a tertiary referral hospital in Girona within a Breast Pathology UnitParticipants: Women diagnosed with breast cancer undergoing a Breast Conservative Surgery in the Breast Pathology Unit at Hospital Universitari de Girona Dr. Josep Trueta

Patson Approach versus the Standard Approach for increasing breast reconstruction rates in women undergoing mastectomy. A randomized, controlled, open-label clinical trial

Breast cancer is the most prevalent neoplasm among women in the majority of countries worldwide. Breast cancer treatment include mastectomy which is associated to strong impact in women. Breast reconstruction is an option for many women to re-establish their body image and also to decrease psychological impact. However, breast reconstruction rates are low and many factors are involved in not undergoing breast reconstruction. Patient involvement in the decision-making process increases breast reconstruction rates and is associated to higher satisfaction and less anxiety and depression symptoms. More physician-patient relation and more education in terms of breast reconstruction are needed to achieve our objective. A new approach of medical care, called Patson Approach, is created in order to meet our goal with more patient involvement, as well as, physician and psychological counsellingObjective: to increase breast reconstruction rates in women who are candidates for breast reconstruction after mastectomy and are included in the Patson Approach compared to women included in the Standard ApproachMethods: the study design will be a randomized, controlled, open-label clinical trial. 62 patients will be recruited during two years and randomly divided in two groups, 31 will be included in the Standard Approach and 31 will be included in the Patson Approach. Preoperative and postoperative appointments are established in order to do a follow-up of the patients and collect all the data