Triple Assessment of Breast – Gold Standard in Mass Screening for Breast Cancer 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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Comparative Study by Analytical Multidisciplinary Methods and Oxidative Stress in Breast Cancer Diagnosis

Revista de Chimie ◽

10.37358/rc.18.8.6511 ◽

2018 ◽

Vol 69 (8) ◽

pp. 2254-2259

Author(s):

Irina Jari ◽

Alexandru Naum ◽

Liliana Gheorghe Moisii ◽

Cipriana Stefanescu ◽

Dragos Negru ◽

...

Keyword(s):

Breast Cancer ◽

Oxidative Stress ◽

Cancer Diagnosis ◽

Gold Standard ◽

Breast Imaging ◽

Diagnostic Performance ◽

Area Under The Curve ◽

Breast Mri ◽

Breast Cancer Diagnosis ◽

And Oxidative Stress

To evaluate the diagnostic performance of mammography, elastography and breast magnetic resonance imaging (MRI), as tools for breast cancer diagnosis, against pathological diagnosis as the gold standard. Other risk factors such as obesity and oxidative stress are also disccused. In this comparison study, a total of 169 female patients (mean age 51 years, range 35-77 years) were enrolled between January 2016 and June 2017. After the physical examination of the breasts, patients were further randomized into three groups to mammography, elastography, or breast MRI. Only women with detected lesions classified into breast imaging and reporting data system (BI-RADS) category or Tsukuba elasticity score from 2 to 5 were included. Histopathology was used as the gold standard for diagnosis. The diagnostic performance of each modality was calculated. Of a total of 50 pathologically confirmed cancers, 25 were detected by mammography, 11 by elastography, and 14 by breast MRI, which resulted in sensitivities of 84% (PPV = 78%), 75% (PPV = 64%) and 86% (PPV = 75%), respectively. Mammography, elastography, and breast MRI led to 6, 5, and 4 false positive findings, which resulted in specificities of 86% (NPV = 90%), 87% (NPV = 92%) and 89% (NPV = 94%), respectively. The area under the curve (AUC) values for the mammography, elastography and breast MRI were 0.849 (95% CI, 0.758-0.939), 0.809 (95% CI, 0.670-0.948) and 0.876 (95% CI, 0.769-0.983). The DOR values were 32 (95% CI, 8-125), 20 (95% CI, 4-99) and 51 (95% CI, 8-315). The breast MRI proved a slight advantage over mammography as a diagnostic tool in breast cancer diagnosis.

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