Breast Cancer Detection Techniques: Issues and Challenges

Jaglan, Poonam; Dass, Rajeshwar; Duhan, Manoj

doi:10.1007/s40031-019-00391-2

Cited by 58 publications

(27 citation statements)

References 26 publications

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“…Other scanning methods include electrical impedance scanning and thermal imaging. The issues and challenges associated with these techniques, as well as some emerging experimental tests, have been reviewed [123]. The best way to improve the prognosis of breast cancer is early detection; therefore, convenient and inexpensive detection through liquid biopsy has attracted major research and commercial interest to facilitate frequent screenings for breast cancer [124].…”

Section: Detection Techniques Of Breast Cancermentioning

confidence: 99%

Application of Microfluidic Systems for Breast Cancer Research

et al. 2022

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Cancer is a disease in which cells in the body grow out of control; breast cancer is the most common cancer in women in the United States. Due to early screening and advancements in therapeutic interventions, deaths from breast cancer have declined over time, although breast cancer remains the second leading cause of cancer death among women. Most deaths are due to metastasis, as cancer cells from the primary tumor in the breast form secondary tumors in remote sites in distant organs. Over many years, the basic biological mechanisms of breast cancer initiation and progression, as well as the subsequent metastatic cascade, have been studied using cell cultures and animal models. These models, although extremely useful for delineating cellular mechanisms, are poor predictors of physiological responses, primarily due to lack of proper microenvironments. In the last decade, microfluidics has emerged as a technology that could lead to a paradigm shift in breast cancer research. With the introduction of the organ-on-a-chip concept, microfluidic-based systems have been developed to reconstitute the dominant functions of several organs. These systems enable the construction of 3D cellular co-cultures mimicking in vivo tissue-level microenvironments, including that of breast cancer. Several reviews have been presented focusing on breast cancer formation, growth and metastasis, including invasion, intravasation, and extravasation. In this review, realizing that breast cancer can recur decades following post-treatment disease-free survival, we expand the discussion to account for microfluidic applications in the important areas of breast cancer detection, dormancy, and therapeutic development. It appears that, in the future, the role of microfluidics will only increase in the effort to eradicate breast cancer.

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Section: Detection Techniques Of Breast Cancermentioning

confidence: 99%

Application of Microfluidic Systems for Breast Cancer Research

et al. 2022

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“…B REAST cancer is one of the commonest types of cancer which affects the women and its early detection is of vital importance for successful treatments [1], [2]. Among the commonest clinical imaging and diagnostic modalities employed for this aim it is worth to mention X-ray mammography, magnetic resonance imaging (MRI), ultrasound scanning and nuclear medicine [3].…”

Section: A Motivationmentioning

confidence: 99%

Microwave Breast Imaging via Neural Networks for Almost Real-time Applications

Ambrosanio¹,

Franceschini²,

Pascazio³

et al. 2021

Preprint

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Conventional breast cancer imaging techniques are nowadays based on the use of ionising radiations or ultrasound waves for the inspection of breast areas. Nevertheless, these conventional techniques present some drawbacks related to patient's safety, processing time and resolution issues. In this framework, microwave imaging can represent a valid alternative or a complementary technique compared to other conventional medical imaging modalities since it is safe (using non-ionising radiations), relatively cheap and more comfortable from patient's point of view. Unfortunately, it is slow and computationally expensive, which strongly limit its use in clinical scenarios. In this paper, an artificial neural network for effective and almost real-time breast imaging is proposed. First, a realistic breast-like phantom generator was developed for training the network. Subsequently, numerical analyses have been conducted for the optimisation and the performance evaluation of the approach. The results seem very promising in terms of recovery performance as well as for the computation burden.

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“…Another studies have shown that breast ultrasonography and breast Magnetic Resonance Imaging (MRI) are the best alternatives for mammography and may improve the breast cancer prognosis [16]. Breast ultrasonography screening have frequently focused on populations with mammographic density since dense breast tissue is a risk factor for breast cancer and reduces the sensitivity of mammography.…”

Section: Challenges For Breast Cancer Organized Screeningmentioning

confidence: 99%

Process Modelling (BPM) in Healthcare – Breast Cancer Screening

Marqués

Santos

2020

Lecture Notes in Computer Science

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Breast cancer is a malignant epithelial neoplasm and it is a public health problem that has high incidence and mortality in women. Focusing the clinical performance on processes is proving to be the way to improve morbidity and mortality statistics. Business process management (BPM) is a management field that improves and analyzes business processes according to organizations' strategies. The early diagnosis of breast cancer is of great importance since it will enable more conservative treatments and a longer disease-free survival. Organized oncology screenings programs, with all elements properly prepared, revealed to be more efficient than the opportunistic screenings. BPM usage will enable optimize and manage all processes from the screening until the diagnosis and treatment. The aim of this study is identification and modelling of BPM processes for the healthcare sector, namely, for Portuguese organized breast cancer screening. To achieve this goal, it was required the identification of the main processes by an interview to the employees and the development of "As-Is" diagrams. Some of the problems in a macroscopic way were detected and improvement suggestions were made.

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Breast Cancer Detection Techniques: Issues and Challenges

Cited by 58 publications

References 26 publications

Application of Microfluidic Systems for Breast Cancer Research

Application of Microfluidic Systems for Breast Cancer Research

Microwave Breast Imaging via Neural Networks for Almost Real-time Applications

Process Modelling (BPM) in Healthcare – Breast Cancer Screening

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