In a groundbreaking development, a new breast cancer test backed by artificial intelligence promises to deliver results in just 10 minutes, without the radiation exposure associated with conventional mammograms.

Traditional mammograms use low doses of radiation to obtain high-quality X-ray images of the breasts. However, a Polish tech company has designed an innovative test that eliminates this exposure. The Ailis test, currently in its clinical trial stage, measures thermal changes in breast tissue and its surroundings, offering a functional imaging method that could revolutionize breast cancer screening.

Ailis: A New Approach to Breast Cancer Screening

Developed by a team of innovators in Krakow, Ailis aims to provide a more comfortable and accessible screening experience. The test avoids the discomfort of breast compression and is delivered in a soothing environment, potentially encouraging more women to undergo regular screenings.

The Ailis system uses parametric imaging to examine the body's surface for thermal activity that could signal the presence of a tumor. Increased metabolic activity and blood flow in many breast cancers supply the tumor with nutrients, creating detectable thermal changes. AI-powered image analysis then automatically screens patients to identify those most at risk.

Michał Matuszewski, the system’s co-creator and CEO of Ailis, emphasized the user-centered design of the device. “Our priority was to create an innovative device in which women would want to undergo examinations,” he said. “We conducted numerous studies and interviews around the world to gather their expectations. Our vision is a world in which breast cancer is no longer a life-threatening disease. If detected at a very early stage, the chance of recovery is currently up to 99 percent.”

An Alternative to Traditional Imaging Techniques

Ailis's approach differs from standard anatomical imaging techniques like mammography or ultrasound, which rely on detecting structural changes in breast tissue. Instead, Ailis aims to detect functional, metabolic changes that often precede visible anatomical differences, potentially enabling earlier detection.

Women were actively involved in the design process to understand their preferences and address common complaints about traditional mammograms. Matuszewski highlighted the system’s non-invasive approach, which is more suitable for frequent examinations. “The possibility of frequent examinations without any negative consequences for health, performing them painlessly, comfortably and outside doctors' offices is a reality that is already coming,” he said.

AI in Breast Cancer Detection

A similar AI tool, called “Mia,” has been successfully implemented in the NHS in the UK. Mia correctly identified signs of breast cancer in 11 women missed by doctors who checked more than 10,000 mammograms. During pilot tests, Mia proved effective in detecting particularly small tumors around 6mm, which can be difficult to spot but are easy to treat with excellent outcomes.

Dr. Nyla Khan, a consultant diagnostic and interventional breast radiologist at Burjeel Medical City in Abu Dhabi, noted the potential of AI applications like Mia to supplement the work of doctors. “Health care is moving more towards how AI can help us,” she said. “It won't replace healthcare professionals, but it will definitely flag up and prioritize mammograms which need to be looked at more urgently.”

Global Breast Cancer Goals

Breast cancer is the most common malignancy and the second-leading cause of cancer death among women. The World Health Organization (WHO) predicts a 77 percent increase in cases by 2050. WHO goals call for 60 percent of breast cancers to be detected in early stages one and two, ensuring the best chance of recovery.

Screening in remote, rural areas remains a key challenge in developing nations, preventing many from meeting survival targets. Research published in The Lancet Global Health showed that in Africa, the mortality rate of women living 50km or further from treatment hospitals for screening is twice those living in urban areas of five sub-Saharan countries.

“Access to health care is a big factor,” said Dr. Khan. “In urban areas, you've got good facilities and access to a number of hospitals. But in those rural, less developed communities, you've got transportation barriers and a limitation on the number of screening centers available, often with long waiting times. Any new effective technology that’s portable would be very helpful.”

The Ailis system represents a significant step forward in breast cancer detection, offering a radiation-free, AI-powered alternative that could make regular screenings more accessible and comfortable for women worldwide.