Is Ultrasound an Accurate Alternative for Mammography in Breast Cancer Screening in an Asian Population? A Meta-Analysis

Wang, Jing; Zheng, Senshuang; Ding, Lanjun; Liu, Xuan; Yuan, Wu; Greuter, Marcel J W; Bock, Geertruida H. de; Lu, Wenli

doi:10.3390/diagnostics10110985

Cited by 23 publications

(23 citation statements)

References 43 publications

(61 reference statements)

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“…Ultrasound can be used both in the screening and diagnosis of breast cancer, having superior performance in young women, due to the fact that they have more glandular tissue (dense breasts) than older women [ 27 ]. It can assess the orientation, structure, margins, and morphology of the lesions [ 15 ].…”

Section: Resultsmentioning

confidence: 99%

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Breast Cancer—How Can Imaging Help?

et al. 2022

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Breast cancer is the most common malignant disease among women, causing death and suffering worldwide. It is known that, for the improvement of the survival rate and the psychological impact it has on patients, early detection is crucial. For this to happen, the imaging techniques should be used at their full potential. We selected and examined 44 articles that had as subject the use of a specific imaging method in breast cancer management (mammography, ultrasound, MRI, ultrasound-guided biopsy, PET-CT). After analyzing their data, we summarized and concluded which are the best ways to use each one of the mentioned techniques for a good outcome. We created a simplified algorithm with easy steps that can be followed by radiologists when facing this type of neoplasia.

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Section: Resultsmentioning

confidence: 99%

“…Both in screening and diagnosis [27]; helpful in dense breast tissue; non-irradiating [27]; repetitive [27]; preoperative examination of the axilla [30].…”

Section: Breast Ultrasoundmentioning

confidence: 99%

Breast Cancer—How Can Imaging Help?

et al. 2022

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“…One meta-analysis results suggest the addition of US to mammography of women with dense breasts improves the sensitivity of detecting breast cancer, despite a slightly decreased specificity. Follow-up US also had good diagnostic sensitivity and specificity [59].…”

Section: Ultrasound (Us)mentioning

confidence: 94%

Breast Cancer Screening

Mutar¹,

Hameed²,

Goyani³

et al. 2021

Breast Cancer - Evolving Challenges and Next Frontiers

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Breast cancer is a common malignancy worldwide. It is considered top cancer in women and about 13% of women in the general population will develop breast cancer sometimes during their lives, with a gradual increase in incidence as survival increases. Primary prevention of breast cancer is directed toward promoting a healthy lifestyle and reversing modifiable risk factors; these factors include smoking cessation, physical activity, alcohol, and dietary modification. Imaging plays an important role in the diagnosis and management of breast cancer, it is also considered the most valuable tool in screening breast cancer. Mammogram is the most widely used method; it is recommended by many societies and committees as a useful method for early detection of breast cancer. False-positive and over-diagnosis constitute a problem in using screening mammogram. The implementation of a screening program faces many issues that may adversely affect its success such as personal factors, social factors, and accessibility issues. These issues should be identified as the initial step in program implementation. The role of Magnetic Resonance Imaging and Ultrasound is mainly in high-risk patients. The introduction of Artificial Intelligence in Mammogram may add beneficial effects in time and efforts improving its efforts.

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“…10 In addition, ultrasound can potentially detect malignant foci obscured by thick glands as a supplement of mammography. 11 However, present popularity of breast cancer screening with ultrasonography is insu cient. One primary reason is the shortage of experienced ultrasound specialists.…”

Section: Introductionmentioning

confidence: 99%

Go beyond image-based benign-malignant classification: AI can identify responsible frames better than physicians in breast ultrasound screening videos

Jiang

Liu

et al. 2022

Preprint

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Breast Cancer is the most common cancer in the world and the single leading cause of cancer mortality in women. Heavy workload and shortage of ultrasound specialists impede the penetration of breast cancer screening. To reduce the burden of sonographers and empower junior physicians, we propose a novel framework FEBrNet by integrating deep learning architecture with the idea of entropy from Information theory. FEBrNet is capable of auto-selecting responsible frames from ultrasound screening videos based on entropy reduce method and classifying breast nodules using Artificial Intelligence (AI). A combination of 13702 images and 1066 videos from breast ultrasound exams are used to train and test the robustness of the proposed framework. Reader studies show that FEBrNet has equivalent or even superior diagnostic performance to that of ultrasound specialists and that overall physician’s performance improves when using FEBrNet's recommended frames and corresponding prediction. Therefore, merging FEBrNet into clinical ultrasound screening workflow might bring actual benefit by helping address the scarcity of sonographers, so as to increase the use of ultrasound screening in cancer prevention.

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Is Ultrasound an Accurate Alternative for Mammography in Breast Cancer Screening in an Asian Population? A Meta-Analysis

Cited by 23 publications

References 43 publications

Breast Cancer—How Can Imaging Help?

Breast Cancer—How Can Imaging Help?

Breast Cancer Screening

Go beyond image-based benign-malignant classification: AI can identify responsible frames better than physicians in breast ultrasound screening videos

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