scholarly journals Thermography as an Economical Alternative Modality to Mammography for Early Detection of Breast Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Asim Ali Khan ◽  
Ajat Shatru Arora
Keyword(s):  
Breast Cancer ◽  
Early Detection ◽  
Rural Areas ◽  
Classification Accuracy ◽  
Early Detection Of Cancer ◽  
Developing Economies ◽  
Medical Professionals ◽  
Human Errors ◽  
Double Reading ◽  
Alternative Modality

Breast cancer has become a menacing form of cancer among women accounting for 11.6% of total deaths of 9.6 million due to all types of cancer every year all over the world. Early detection increases chances of survival and reduces the cost of treatment as well. Screening modalities such as mammography or thermography are used to detect cancer early; thus, several lives can be saved with timely treatment. But, there are interpretational failures on the part of the radiologists to read the mammograms or thermograms and also there are interobservational and intraobservational differences between them. So, the degree of variations among the different radiologists in the interpretation of results is very high resulting in false positives and false negatives. The double reading can reduce the human errors involved in the interpretation of mammograms. But, the limited number of medical professionals in developing or underdeveloped countries puts a limitation on this remedial way. So, a computer-aided system (CAD) is proposed to detect the benign cases from the abnormal cases that can result in automatic detection of breast cancer or can provide a double reading in the case of nonavailability of the trained medical professionals in developing economies. The generally accepted screening modality is mammography for the early detection of cancer. But thermography has been tried for early detection of breast cancer in recent times. The high metabolic activity of the cancer cells results in an early change in the temperature profile of the region. This shows asymmetry between normal and cancerous breast which can be detected using different techniques. Thus, this work is focussed on the use of thermography in the early detection of breast cancer. An experimental study is conducted to find the results of classification accuracy to compare the efficacy of thermography and mammography in classifying the normal from abnormal ones and further abnormal ones into benign and malignant cases. Thermography is found to have classification accuracy almost at par with mammography for classifying the cancerous breasts from healthy ones with classification accuracies of thermography and mammography being 96.57% and 98.11%, respectively. Thermography is found to have much better accuracy in identifying benign cases from the malignant ones with the classification accuracy of 92.70% as compared to 82.05% with mammography. This will result in the early detection of cancer. The advantage of being portable and inexpensive makes thermography an attractive modality to be used in economically backward rural areas where mammography is not practically possible.

scholarly journals Breast Cancer: A Review of Mammography and Clinical Breast Examination for Early Detection of Cancer

OALib ◽  
2020 ◽  
Vol 07 (10) ◽  
pp. 1-19
Author(s):  
Gadafi Iddrisu Balali ◽  
Denis Dekugmen Yar ◽  
Vera Gobe Afua Dela ◽  
Emmanuel Effah-Yeboah ◽  
Philip Asumang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Early Detection ◽  
Early Detection Of Cancer ◽  
Clinical Breast Examination ◽  
Breast Examination ◽  
Clinical Breast

Pre-Trained Convolutional Neural Networks for Breast Cancer Detection Using Ultrasound Images

2021 ◽  
Vol 21 (4) ◽  
pp. 1-17
Author(s):  
Mehedi Masud ◽  
M. Shamim Hossain ◽  
Hesham Alhumyani ◽  
Sultan S. Alshamrani ◽  
Omar Cheikhrouhou ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Neural Network ◽  
Early Detection ◽  
Convolutional Neural Network ◽  
Cancer Detection ◽  
Early Detection Of Cancer ◽  
Fine Tuning ◽  
Volunteer Computing ◽  
Ultrasound Images ◽  
Key Features

Volunteer computing based data processing is a new trend in healthcare applications. Researchers are now leveraging volunteer computing power to train deep learning networks consisting of billions of parameters. Breast cancer is the second most common cause of death in women among cancers. The early detection of cancer may diminish the death risk of patients. Since the diagnosis of breast cancer manually takes lengthy time and there is a scarcity of detection systems, development of an automatic diagnosis system is needed for early detection of cancer. Machine learning models are now widely used for cancer detection and prediction research for improving the successive therapy of patients. Considering this need, this study implements pre-trained convolutional neural network based models for detecting breast cancer using ultrasound images. In particular, we tuned the pre-trained models for extracting key features from ultrasound images and included a classifier on the top layer. We measured accuracy of seven popular state-of-the-art pre-trained models using different optimizers and hyper-parameters through fivefold cross validation. Moreover, we consider Grad-CAM and occlusion mapping techniques to examine how well the models extract key features from the ultrasound images to detect cancers. We observe that after fine tuning, DenseNet201 and ResNet50 show 100% accuracy with Adam and RMSprop optimizers. VGG16 shows 100% accuracy using the Stochastic Gradient Descent optimizer. We also develop a custom convolutional neural network model with a smaller number of layers compared to large layers in the pre-trained models. The model also shows 100% accuracy using the Adam optimizer in classifying healthy and breast cancer patients. It is our belief that the model will assist healthcare experts with improved and faster patient screening and pave a way to further breast cancer research.

scholarly journals Model for Early Detection of Breast Cancer in Low-Resource Areas: The Experience in Peru

2018 ◽  
pp. 1-7 ◽  
Author(s):  
Carolyn Bain ◽  
Tara Hayes Constant ◽  
Ines Contreras ◽  
Ana Maria Burga Vega ◽  
Jose Jeronimo ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Early Detection ◽  
Cancer Detection ◽  
Rural Areas ◽  
Community Outreach ◽  
Northern Region ◽  
Screening Mammography ◽  
Breast Cancer Detection ◽  
Local Health ◽  
Low Resource

Purpose Late-stage breast cancer detection should be something of the past; however, it is still all too common in low-resource areas, including Peru, where 57% of women diagnosed with cancer are diagnosed at stage III or IV disease. Early detection of breast cancer is feasible in low-resource semirural and rural areas where mammography is rarely accessible. Methods PATH collaborated with Peruvian health institutions at local, regional, and national levels to design and implement a model of care for the early detection of breast cancer in Peru. The model includes training health promoters for community outreach, professional midwives in clinical breast exam, doctors to perform fine-needle aspiration biopsy sampling with ultrasound to triage, and patient navigators to ensure patients follow through with treatment. Results In a northern region of Peru, 400 individuals, including health promoters, midwives, doctors, and volunteers, received early-detection training in two phases. In Peru, local health professionals continue to refine and improve methods and materials using locally available resources, and the Peruvian health information system now includes specific breast cancer detection categories. Despite challenges and limited resources, the model is effective, and partnership with government health administrations improves health systems and benefits the population. Conclusion Given the absence of screening mammography, the public health challenge is to bring breast cancer early detection and diagnostic services closer to women’s homes and to ensure appropriate follow-up and care. The model is eminently transferable with appropriate adaptation and should now be tested in other settings within and outside of Peru.

Unexpected Breast Cancer Detection after Outpatient Biopsy for Benign Lesion

1981 ◽  
Vol 67 (5) ◽  
pp. 437-441 ◽  
Author(s):  
Sergio Di Pietro ◽  
Alberto Azzarelli ◽  
Mirella Merson
Keyword(s):  
Breast Cancer ◽  
Early Detection ◽  
Cancer Detection ◽  
Early Detection Of Cancer ◽  
Breast Biopsy ◽  
Benign Lesion ◽  
Nipple Discharge ◽  
Waiting Lists ◽  
Breast Cancer Detection ◽  
Unexpected Findings

At the Istituto Nazionale Tumori of Milan, in its Outpatient Department, 1302 breast surgical biopsies were carried out in 1978. Fibroadenomas occurred in 44.2% and benign dysplasias in 39.3%. Sixty-two cancers (4.8%) and 23 atypical hyperplasias (1.8%) were unexpected findings, with an increasing incidence in women over 50. Seventy-nine duct resections were performed for significant nipple discharge and revealed 5 unexpected carcinomas and 28 papillomas or papillomatosis. In our opinion and experience, this procedure of performing breast biopsy in the presence of a solid lump in women over 30 without hospitalization improves early detection of cancer, lowers costs, cuts down admission waiting lists and increases the number of women who better accept a surgical diagnosis and treatment.

scholarly journals Breast Cancer Knowledge, Behaviors, and Preferences in Malawi: Implications for Early Detection Interventions From a Discrete Choice Experiment

2017 ◽  
Vol 3 (5) ◽  
pp. 480-489 ◽  
Author(s):  
Racquel E. Kohler ◽  
Satish Gopal ◽  
Clara N. Lee ◽  
Bryan J. Weiner ◽  
Bryce B. Reeve ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Early Detection ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Rural Areas ◽  
Choice Experiment ◽  
Multivariable Analysis ◽  
Breast Health ◽  
Cancer Knowledge ◽  
Breast Cancer Knowledge

Purpose Breast cancer is the most common female cancer in Africa and leading cause of death resulting from cancer; however, many countries lack early detection services. In Malawi, women are frequently diagnosed with large tumors after long symptomatic periods. Little is known about local cancer knowledge. Methods We administered a cross-sectional survey with a discrete choice experiment to a random sample in urban and rural areas of Lilongwe district. Bivariable and multivariable analyses determined factors associated with knowledge. Preference utilities for early detection interventions were estimated using a hierarchical Bayesian model in Sawtooth software. Results Of 213 women recruited, fewer than half were aware of breast cancer. In multivariable analysis, electricity at home and knowing someone with cancer increased the odds of awareness. Women were more knowledgeable about symptoms than treatment or risk factors; more than 60% erroneously believed local misconceptions. Seventeen percent were aware of breast self-examination, and 20% were aware of clinical breast examination (CBE); few reported either behavior. Common barriers included not knowing where to access CBE and transportation difficulties. Discrete choice experiment results indicated the detection strategy (breast health awareness, CBE, or both) was the most important attribute of an intervention, followed by the encounter setting and travel time. Conclusion Addressing misconceptions in health messages and engaging survivors to promote early detection may help improve breast cancer knowledge in Malawi. Program designs accounting for women’s preferences should provide breast health education and CBEs in convenient settings to address transportation barriers, particularly for women with low socioeconomic position.

scholarly journals Advocacy Campaign: Breast Care International Approach

2018 ◽  
Vol 4 (Supplement 2) ◽  
pp. 237s-237s ◽  
Author(s):  
H.E. Wiafe ◽  
B. Wiafe Addai
Keyword(s):  
Breast Cancer ◽  
Early Detection ◽  
Cancer Patients ◽  
Rural Areas ◽  
Late Stage ◽  
Service Providers ◽  
Noncommunicable Diseases ◽  
Screening Programs ◽  
Awareness Campaigns ◽  
Breast Care

Background and context: Breast cancer is the leading cause of cancer deaths among Ghanaian women, but it has been identified as 1 of the neglected noncommunicable diseases (NCDs). In 2012, GLOBOCAN reported that ∼2260 people were diagnosed with breast cancer in Ghana with a high age standardized mortality rate of 11.7 per 100,000. Although, it is acknowledged that early detection and prompt action reduces mortality, 80% of newly diagnosed breast cancer patients delay presentation. It is a well-known fact that cancers are now killing more people in Africa than HIV/AIDS, tuberculosis and malaria combined. Due to lack of awareness about cancers and late reporting of the cases, a lot of cancer patients get very little intervention and support and that explains why most cancer deaths occur in Africa, especially women in rural areas. Breast Care International (BCI), a nongovernmental organization in Ghana, established in 2002, is a leading breast cancer advocacy organization in Africa providing an enabling environment to enhance early detection and reduce the late-stage presentation of breast cancer. Aim: To maximize personal and community wellness through community participation, excellence in public health education, empowering people to save lives and to end late-stage presentation of breast cancer in Ghana. Strategy/Tactics: To enhance early detection and reduce late-stage presentation of breast cancer in Ghana by disintegrating the myths and misconception about breast cancer. Program/Policy process: BCI has been conducting outreach awareness programs in Ghana to women groups, educational institutions, churches and social groups, especially those in deprived communities, educating them on breast self-examination (BSE) and then clinically screening the women. The involvement of breast cancer survivors to share their testimonies on various platforms to demystify breast cancer as an incurable disease and the misconceptions of it being from ancestral curses. Community-based nurses trained in basic oncology are to be deployed to the district level to create awareness about breast health and other NCDs at the grass root level with the aim of detecting breast cancer early for a prompt referral to health facilities for further management. Outcomes: BCI’s demand-driven outreach awareness campaigns and screening programs have been empowering women to perform their BSE and as a result most patients report to the hospital with lumps and abnormalities that were detected during their BSE. What was learned: Although, BCI has been intensively involved in breast cancer advocacy programs in Ghana, a concerted effort is required from opinion leaders, political figures, health service providers, organized groups and business organizations to assist to control the incidence of breast cancer in Ghana.

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