Evaluation of the Reconfiguration of the Data Acquisition System for 3D USCT

As today's standard screening methods often fail to diagnose breast cancer before metastases have developed, an earlier breast cancer diagnosis is still a major challenge. To improve this situation, we are currently developing a fully three-dimensional ultrasound computer tomography (3D USCT) system, promising high-quality volume images of the breast. For obtaining these images, a time-consuming reconstruction has to be performed. As this is currently done on a PC, parallel processing in reconfigurable hardware could accelerate both signal and image processing. In this work, we investigated the suitability of an existing data acquisition (DAQ) system for further computation tasks. The reconfiguration features of the embedded FPGAs have been exploited to enhance the systems functionality. We have adapted the DAQ system to allow for bidirectional communication and to provide an overall process control. Our results show that the studied system can be applied for data processing.

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Breast Cancer Diagnosis With Mammography

Biomedical Computing for Breast Cancer Detection and Diagnosis - Advances in Bioinformatics and Biomedical Engineering ◽

10.4018/978-1-7998-3456-4.ch006 ◽

2021 ◽

pp. 107-127

Author(s):

Abir Baâzaoui ◽

Walid Barhoumi

Keyword(s):

Breast Cancer ◽

Cancer Diagnosis ◽

Gold Standard ◽

Breast Cancer Diagnosis ◽

Black Box ◽

Diagnose Breast Cancer ◽

Cad Systems ◽

Helpful Tool ◽

Cancerous Lesion ◽

Aided Diagnosis

Breast cancer, which is the second-most common and leading cause of cancer death among women, has witnessed growing interest in the two last decades. Fortunately, its early detection is the most effective way to detect and diagnose breast cancer. Although mammography is the gold standard for screening, its difficult interpretation leads to an increase in missed cancers and misinterpreted non-cancerous lesion rates. Therefore, computer-aided diagnosis (CAD) systems can be a great helpful tool for assisting radiologists in mammogram interpretation. Nonetheless, these systems are limited by their black-box outputs, which decreases the radiologists' confidence. To circumvent this limit, content-based mammogram retrieval (CBMR) is used as an alternative to traditional CAD systems. Herein, authors systematically review the state-of-the-art on mammography-based breast cancer CAD methods, while focusing on recent advances in CBMR methods. In order to have a complete review, mammography imaging principles and its correlation with breast anatomy are also discussed.

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CytoPAN—Portable cellular analyses for rapid point-of-care cancer diagnosis

Science Translational Medicine ◽

10.1126/scitranslmed.aaz9746 ◽

2020 ◽

Vol 12 (555) ◽

pp. eaaz9746

Author(s):

Jouha Min ◽

Lip Ket Chin ◽

Juhyun Oh ◽

Christian Landeros ◽

Claudio Vinegoni ◽

...

Keyword(s):

Breast Cancer ◽

Cancer Diagnosis ◽

Point Of Care ◽

Growth Factor Receptor ◽

Image Cytometry ◽

Breast Cancer Diagnosis ◽

Needle Aspiration ◽

Current Standard ◽

Diagnose Breast Cancer ◽

Palpable Mass

Rapid, automated, point-of-care cellular diagnosis of cancer remains difficult in remote settings due to lack of specialists and medical infrastructure. To address the need for same-day diagnosis, we developed an automated image cytometry system (CytoPAN) that allows rapid breast cancer diagnosis of scant cellular specimens obtained by fine needle aspiration (FNA) of palpable mass lesions. The system is devoid of moving parts for stable operations, harnesses optimized antibody kits for multiplexed analysis, and offers a user-friendly interface with automated analysis for rapid diagnoses. Through extensive optimization and validation using cell lines and mouse models, we established breast cancer diagnosis and receptor subtyping in 1 hour using as few as 50 harvested cells. In a prospective patient cohort study (n = 68), we showed that the diagnostic accuracy was 100% for cancer detection and the receptor subtyping accuracy was 96% for human epidermal growth factor receptor 2 and 93% for hormonal receptors (ER/PR), two key biomarkers associated with breast cancer. A combination of FNA and CytoPAN offers faster, less invasive cancer diagnoses than the current standard (core biopsy and histopathology). This approach should enable the ability to more rapidly diagnose breast cancer in global and remote settings.

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