MIT researchers have designed a new bra-incorporated device that enables frequent monitoring for high-risk breast cancer patients.
Credits: Image: Canan Dagdeviren
When breast cancer is found early, survival rates near 100%, but drop to 25% in advanced stages. These figures highlight the crucial need for early detection and innovative diagnostic methods.
MIT researchers have created wearable ultrasound gear to improve breast cancer survival rates by detecting early tumours. Beneficial for high-risk individuals between mammogram screenings, the device consists of a flexible patch for a bra, enabling an ultrasound tracker to capture breast images from various angles. The team showed it can produce images with resolution comparable to traditional medical ultrasound probes.
A Portable Diagnostic Tool
The research team, skilled in creating wearable electronics that fit the body’s shape, aims to raise survival rates to potentially 98% through more frequent screening. They designed a compact ultrasound scanner using innovative piezoelectric material. A flexible, 3D-printed patch with a honeycomb structure allows the scanner to be attached to a bra with magnets, ensuring direct skin contact. Contained within a small tracker, the scanner can be moved to six positions, allowing full breast imaging, and its angle can be adjusted for different perspectives.
Early Detection
The research team tested their device on a 71-year-old woman with breast cysts, detecting cysts as small as 0.3 centimetres, like early-stage tumours. Linked to standard ultrasound machines, the device is being developed to resemble a smartphone. This reusable wearable ultrasound patch offers potential for home use, especially for high-risk individuals or those lacking regular screening access. The device, with resolution matching traditional ultrasound, allows tissue viewing up to 8 centimetres deep. It could transform early breast cancer detection, providing a more dependable and comfortable method. By removing the need to travel to imaging centres, it addresses a major obstacle in early detection.
The researchers are also exploring AI-driven assessment to analyse data over time for improved diagnostics, moving beyond the typical radiologist comparisons of images taken years apart. Additionally, they plan to investigate extending the ultrasound technology to scan other parts of the body.
