AI can make breast

Topic: AI can make breast cancer screening more accessible and affordable

High mortality rates for breast cancer patients are often due to late detection, particularly in rural areas where accessing reliable, affordable screening can be challenging.

In resource-constrained settings, innovative technology-assisted solutions for detecting cancer could be the way forward.

Analysing thermal images using AI-based algorithms, for example, provides a no-touch, no-radiation, low-cost way to accurately screen for breast cancer in such areas.

Breast cancer is the second most common cancer globally, and is the most commonly diagnosed cancer in Indian women. Of the 685,000 women who die around the world every year because of breast cancer, over 90,000 are in India, where cancer of the breast is the most common cause of cancer-related deaths in India. One of the major reasons for the high mortality rate in India is that most Indian patients present in the later stages of the disease.

Population-scale screening with early detection methods, and efforts to increase awareness of breast cancer, could help tackle the disease, improve survival rates and reduce treatment costs. Screening mammography is a widely used method, but its usage in low- and middle-income countries (LMICs) is limited due to equipment cost and the expert skill required for interpretation of mammograms.

Also, mammography has sensitivity of around 62% to 68% in women with dense breast tissue. Breast ultrasonography (USG) has demonstrated a greater sensitivity than mammography in younger women with dense breast tissue. However, USG is largely dependent on the skill and experience of the clinician. Additionally, due to India’s Pre-Conception and Pre-Natal Diagnostics Technique Act, which aims to prevent female feticide, a USG machine cannot be transported to be used as a community-based breast cancer screening tool.

As a result, the more affordable clinical breast examination (CBE) is the most common method for screening women in India because it does not require any equipment. It is more dependent on the healthcare worker performing the test, however. A shortage of more than 25,000 health workers means staff are already overloaded with maternal and child health, family planning and immunisation-related activities. In the absence of devoted, well-trained health workers and quality control, CBE can produce inconsistent results.

In a resource-constraint setting such as India, where the understaffed grass-root level health workers are overburdened and the radiologist to population ratio is as low as 1:100,000, innovative technology-assisted solutions could be the way forward.

Topic Discussed: AI can make breast cancer screening more accessible and affordable

Read Original Article