Literature DB >> 32611494

Staying abreast of imaging - Current status of breast cancer detection in high density breast.

D Ghieh1, C Saade2, E Najem3, R El Zeghondi4, M A Rawashdeh5, G Berjawi6.   

Abstract

OBJECTIVES: The aim of this paper is to illustrate the current status of imaging in high breast density as we enter a new decade of advancing medicine and technology to diagnose breast lesions. KEY
FINDINGS: Early detection of breast cancer has become the chief focus of research from governments to individuals. However, with varying breast densities across the globe, the explosion of breast density information related to imaging, phenotypes, diet, computer aided diagnosis and artificial intelligence has witnessed a dramatic shift in new screening recommendations in mammography, physical examination, screening younger women and women with comorbid conditions, screening women at high risk, and new screening technologies. Breast density is well known to be a risk factor in patients with suspected/known breast neoplasia. Extensive research in the field of qualitative and quantitative analysis on different tissue characteristics of the breast has rapidly become the chief focus of breast imaging. A summary of the available guidelines and modalities of breast imaging, as well as new emerging techniques under study that can potentially provide an augmentation or even a replacement of those currently available.
CONCLUSION: Despite all the advances in technology and all the research directed towards breast cancer, detection of breast cancer in dense breasts remains a dilemma. IMPLICATIONS FOR PRACTICE: It is of utmost importance to develop highly sensitive screening modalities for early detection of breast cancer.
Copyright © 2020 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Breast cancer; Breast cancer screening; Breast density; Mammography

Year:  2020        PMID: 32611494     DOI: 10.1016/j.radi.2020.06.003

Source DB:  PubMed          Journal:  Radiography (Lond)        ISSN: 1078-8174


  1 in total

1.  Estimation of Nuclear Medicine Exposure Measures Based on Intelligent Computer Processing.

Authors:  Junfeng Wang; Fangxiao Wang; Yue Liu; Yuanfan Xu; Jiangtao Liang; Ziming Su
Journal:  J Healthc Eng       Date:  2021-09-27       Impact factor: 2.682

  1 in total

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