Breast cancer screening in a resource poor country: Ultrasound versus mammography

Omidiji, Olubukola; Campbell, P C; Irurhe, N.K.; Atalabi, Omolola Mojisola; Toyobo, Oluyemisi O

doi:10.4314/gmj.v51i1.2

Cited by 29 publications

(20 citation statements)

References 11 publications

(21 reference statements)

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“…As main complementary examination to mammography, US was much superior to mammography due to its attractive advantages including, but not limited to, high sensitivity especially in dense breasts, are unexposed to X-rays and are safe for young, pregnant, lactating population (28,29).…”

Section: Discussionmentioning

confidence: 99%

Study on automatic detection and classification of breast nodule using deep convolutional neural network system

Wang¹,

Liu²,

Yuan³

et al. 2020

J Thorac Dis

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Backgrounds: Conventional ultrasound manual scanning and artificial diagnosis approaches in breast are considered to be operator-dependence, slight slow and error-prone. In this study, we used Automated Breast Ultrasound (ABUS) machine for the scanning, and deep convolutional neural network (CNN) technology, a kind of Deep Learning (DL) algorithm, for the detection and classification of breast nodules, aiming to achieve the automatic and accurate diagnosis of breast nodules. Methods: Two hundred and ninety-three lesions from 194 patients with definite pathological diagnosis results (117 benign and 176 malignancy) were recruited as case group. Another 70 patients without breast diseases were enrolled as control group. All the breast scans were carried out by an ABUS machine and then randomly divided into training set, verification set and test set, with a proportion of 7:1:2. In the training set, we constructed a detection model by a three-dimensionally U-shaped convolutional neural network (3D U-Net) architecture for the purpose of segment the nodules from background breast images. Processes such as residual block, attention connections, and hard mining were used to optimize the model while strategies of random cropping, flipping and rotation for data augmentation. In the test phase, the current model was compared with those in previously reported studies. In the verification set, the detection effectiveness of detection model was evaluated. In the classification phase, multiple convolutional layers and fully-connected layers were applied to set up a classification model, aiming to identify whether the nodule was malignancy.Results: Our detection model yielded a sensitivity of 91% and 1.92 false positive subjects per automatically scanned imaging. The classification model achieved a sensitivity of 87.0%, a specificity of 88.0% and an accuracy of 87.5%.Conclusions: Deep CNN combined with ABUS maybe a promising tool for easy detection and accurate diagnosis of breast nodule.

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Section: Discussionmentioning

confidence: 99%

Study on automatic detection and classification of breast nodule using deep convolutional neural network system

Wang¹,

Liu²,

Yuan³

et al. 2020

J Thorac Dis

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“…In cases where mammography is not available; ultrasound could be an alternative for young patients and patients with dense breasts. Some studies report an improved sensitivity of ultrasound compared to mammogram as the first-line screening in this population [40]. However, ultrasound has little to offer in mass screening because of its inability to detect microcalcifications and a high rate of false positive findings, so cannot replace the mammogram [20].…”

Section: High Burden Of Locally Advanced/advanced Bcmentioning

confidence: 99%

Barriers in Latin America for the management of locally advanced breast cancer

Pinto

Pinillos

Villarreal‐Garza

et al. 2019

ecancer

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Breast cancer (BC) is a highly prevalent malignancy in Latin American women, most cases being diagnosed at locally advanced or metastatic stages when options for cancer care are limited. Despite its label as a public health problem in the region, Latin American BC patients face several barriers in accessing standard of care treatment when compared with patients from developed countries. In this review, we analyse the landscape of the four main identified barriers in the region: i) high burden of locally advanced/advanced BC; ii) inadequate access to medical resources; iii) deficient access to specialised cancer care and iv) insufficient BC research in Latin America. Unfortunately, these barriers represent the main factors associated with the BC poor outcomes seen in the region. Targeted actions should be conducted independently by each country and as a region to overcome these limitations and create an enhanced model of BC care.

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“…This figure is comparable to other low-income countries that have inadequate screening coverage. A similar study in Nigeria reported a figure of 2% of histopathology proven malignancy among the screening mammography cases [ 23 ].…”

Section: Discussionmentioning

confidence: 99%

Strengthening Breast Cancer Screening Mammography Services in Pakistan Using Islamabad Capital Territory as a Pilot Public Health Intervention

2022

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Late diagnosis of treatable breast cancer is the reason for higher breast cancer mortality. Until now, no public breast cancer facility has been established in the Islamabad Capital Territory. First, a Federal Breast Screening Center (FBSC) was established. Afterward, awareness campaigns about breast cancer were organized among the public. Subsequently, women above 40 years of age were provided with mammography screenings. Data were analyzed in SPSS version 22.0. An intervention was performed using a six tier approach to strengthening the health system. Utilizing the offices of the FBSC and the national breast cancer screening campaign, breast cancer awareness has become a national cause and is being advocated by the highest offices of the country. The number of females undergoing mammography has increased each year, starting from 39 in 2015 to 1403 in 2019. Most of the cases were BI-RAD I (n = 2201, 50.74%) followed by BI-RAD II (n = 864, 19.92%), BI-RAD III (n = 516, 11.89%), BI-RAD IV (n = 384, 8.85%), BI-RAD V (n = 161, 3.71%), and BI-RVAD VI (n = 60, 1.38%). The current study has theoretical and practical implications for the contemplation of policymakers. The FBSC can serve as a model center for the establishment of centers in other parts of the country, thereby promoting nationwide screening coverage.

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Breast cancer screening in a resource poor country: Ultrasound versus mammography

Cited by 29 publications

References 11 publications

Study on automatic detection and classification of breast nodule using deep convolutional neural network system

Study on automatic detection and classification of breast nodule using deep convolutional neural network system

Barriers in Latin America for the management of locally advanced breast cancer

Strengthening Breast Cancer Screening Mammography Services in Pakistan Using Islamabad Capital Territory as a Pilot Public Health Intervention

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