New Approaches to Classification and Diagnostic Prediction of Breast Cancers


Book Description

Despite many years of translational research in breast cancer, very few new biomarkers have been implemented for clinical use beyond estrogen receptor, progesterone receptor, and HER2. The main reason is that many promising biomarkers are clinically validated but lack analytical and clinical utility. One explanation is that proper validation of the predictive ability of the biomarker in independent datasets, and with a pre-planned statistical analysis, is not always performed. Thus, there is a need to identify new biomarkers or new ways to subclassify breast cancer patients that are reproducible and easy to implement in the clinical setting but, more importantly, that improve patient’s outcomes.




New Approaches for


Book Description

Biomarkers accepted for clinical use in breast cancer, such as CA 15-3 and CEA have low sensitivity and specificity, and are thus more useful for patients at an advanced stage of breast cancer rather than for early cancer diagnosis. So, there is a need for new biomarkers to help in diagnosis of primary breast cancer and this is one of the aims of the present study. Once a patient has been diagnosed with breast cancer, there are several factors shown to be associated with survival. These factors are referred to as prognostic factors such as axillary lymph node status, tumor size, histological grade and hormone receptor expression. All these factors require tissue samples which is not practical for a screening regimen. So, measurement of the parameters in the present study was on the serum. Angiogenesis is a key factor in cancer development. It is initiated when there is a predominance of angiogenic factors that favour new vessel growth such as VEGF. Besides VEGF, there are several growth factors and molecules included in angiogenesis such as HGF, IL-18 and nitric oxide.




Saving Women's Lives


Book Description

Building on the 2001 report, Mammongrapy and Beyond, this book not only examines ways to improve implementation and use of new and current breast cancer detection technologies, but also evaluates the need to develop tools that identify women who would benefit most from early detection screening. It encourages more research that integrates the development, validation, and analysis of the types of technologies in clinical practice that promote improved risk identification techniques.




Saving Women's Lives


Book Description

The outlook for women with breast cancer has improved in recent years. Due to the combination of improved treatments and the benefits of mammography screening, breast cancer mortality has decreased steadily since 1989. Yet breast cancer remains a major problem, second only to lung cancer as a leading cause of death from cancer for women. To date, no means to prevent breast cancer has been discovered and experience has shown that treatments are most effective when a cancer is detected early, before it has spread to other tissues. These two facts suggest that the most effective way to continue reducing the death toll from breast cancer is improved early detection and diagnosis. Building on the 2001 report Mammography and Beyond, this new book not only examines ways to improve implementation and use of new and current breast cancer detection technologies but also evaluates the need to develop tools that identify women who would benefit most from early detection screening. Saving Women's Lives: Strategies for Improving Breast Cancer Detection and Diagnosis encourages more research that integrates the development, validation, and analysis of the types of technologies in clinical practice that promote improved risk identification techniques. In this way, methods and technologies that improve detection and diagnosis can be more effectively developed and implemented.







Breast Cancer Classification Using Machine Learning. An Empirical Study


Book Description

Diploma Thesis from the year 2020 in the subject Medicine - Diagnostics, grade: 3.55, , course: Computer Science, language: English, abstract: The study will classify breast cancers into foremost problems: (Benign tumor and Malignant tumor). A benign tumor is a most cancers does now not invade its surrounding tissue or spread around the host. A malignant tumor is another kind of cancers which can invade its surrounding tissue or spread around the frame of the host. Benign cancers on uncommon event can also surely result in someone’s death, but as a fashionable rule they're no longer nearly as horrific because the malignant cancers. The malignant cancers at the contrary are like those killer bees. In this situation, you do not need to be doing something to them or maybe be everywhere near their hive, they will just spread out and attack you emass – they could even kill the individual if they are extreme enough. Manual manner of cancer category into benign and malignant may be very tedious, susceptible to human error and unnecessarily time consuming. The proposed system while constructed can robotically classify the sort of most cancers into the safe (benign) and also the risky (malignant). This machine plays this role through the usage of machine getting to know algorithm. The following is the extensive of this new system: Classification mistakes could be notably removed, early analysis of disorder, removal of possible human mistakes and the device does no longer die. However, the researcher seeks to detect and assess the class of breast using Machine learning.




Practical Breast Pathology


Book Description

All the information needed for successful diagnosis and management of breast carcinoma Focused on a modern, interdisciplinary approach to diagnosing and managing diseases of the breast, this concise book builds on the high standard set in the previous edition. It provides a complete foundation in the basic principles, radiologic appearance and underlying pathology of breast disease, without overwhelming non-pathologist members of the team with excessive detail. For effective communication at every level, Practical Breast Pathology, Second Edition provides the clear information, case examples and superb illustrations that make it an ideal clinical problem solver. Special features of the second edition: High-quality examples of modern multimodality radiology (digital mammography, ultrasound and magnetic resonance imaging) correlated with large-format 2D and 3D histologic slides New findings on such clinically important topics as the lobar nature of breast carcinoma, multifocality, diffuse carcinomas and extent of disease, concept of the sick lobe and more Introduction of the molecular classification of invasive breast cancer Discussion of prognostic and predictive factors in breast carcinoma, such as hormone receptors and HER2 status Updates on preoperative diagnosis, including intact biopsy and radiologic assessment of the extent and distribution of lesions Enriched with new information and stunning illustrations in every chapter, Practical Breast Pathology, Second Edition is a key link in the exchange between pathologists, radiologists, oncologists and breast surgeons, as well as residents and trainees. It provides an essential framework for understanding the mammographic-pathologic correlation, leading to increased cooperation among clinical team members and significantly improved outcomes for patients.







Breast Cancer, a Heterogeneous Disease Entity


Book Description

The volume raises attention to the need of a completely new approach to breast cancer based on the knowledge collected on early breast cancer in the past two decades. The chapters are contributed by experts of all the fields participating in the clinical research and care of breast cancer. The practical importance of such a book is underlined by the increasing number of breast cancer cases, and also the increasing proportion of early stage-cases. The ultimate goal of the book is to point to the heterogeneous nature of the disease which is more striking and has more importance in care at the very early stages than at the more advanced stages. The book recommends the utilization of all the information provided by multimodality imaging and special pathological methods, a new classification system and therapeutic guidelines since early breast cancers should not be treated based on experience obtained with palpable tumors. No similar book has been yet released to the market. The book is written for all the members of the team participating in the diagnosis and treatment of breast cancer (radiologists, pathologists, surgeons, clinical and radiation oncologists), but may be useful for medical students and residents too. The chapters are illustrated with didactic pictures, and special emphasis is given to provide a peep into the practice of the special procedures for the careful examination and individualized therapy of each case.




Translational Research in Breast Cancer


Book Description

This book offers a comprehensive introduction to translational efforts in breast cancer, addressing the latest approaches to precision medicine based on the current state of understanding of breast cancer. With the latest developments in breast cancer research, our understanding of the genomic changes and the oncogenic signaling cascade of breast cancer has made considerable strides. Further, the immuno-environment has been demonstrated as the barrier to clinical cancer. In addition, major advances in cancer biology, immunology, genomics and metabolism have broken new ground for designing therapeutic approaches and selecting appropriate treatments on the basis of more precise information on the individual patient. As a result of these two trends, a clearer picture of the molecular landscape of breast cancers has facilitated the development of diagnostic, prognostic and predictive biomarkers for clinical oncology. All these aspects are addressed in this volume, which offers a comprehensive resource for researchers, graduate students and oncologists in cancer research.