This New Robot Can Carry Out More Accurate Clinical Breast Exams Than Ever Before

Researchers at the University of Bristol in the UK have unveiled a groundbreaking prototype robot designed to perform clinical breast examinations (CBEs) for early breast cancer detection. This development, presented at the RO-MAN 2023 conference, represents a significant step toward enhancing the accuracy and accessibility of breast cancer screening.

Breast cancer, a leading cause of cancer-related deaths in women worldwide, emphasizes the importance of early detection for successful treatment and recovery. While self-examination plays a vital role, CBEs conducted by medical experts can uncover suspicious areas warranting further investigation. George Jenkinson, the lead author of the study, emphasizes the value of well-performed CBEs as a low-risk diagnostic technique.

The University of Bristol’s research team has introduced a 3D-printed robotic manipulator, aptly named IRIS (Robotic Radial Palpation Mechanism for Breast Examination), aimed at revolutionizing breast examinations. IRIS demonstrates the potential to replicate human medical professionals’ dexterity and precision in palpating breast tissue.

Through extensive simulations and laboratory experiments, the researchers rigorously tested IRIS’s capabilities. They conducted thousands of palpations and explored various scenarios, comparing the effectiveness of two, three, or four tactile sensors. In the lab, they employed a silicone breast model to verify the accuracy of their simulations and assess the forces applied by IRIS during palpation.

One of IRIS’s remarkable features is its ability to apply specific forces akin to those used by human professionals. Additionally, it incorporates advanced sensor technology capable of detecting breast lumps, including those located deep within breast tissue.

While IRIS is currently in the prototype stage, the researchers have ambitious goals for its future development. They intend to enhance its ability to detect lumps more accurately and at greater depths by incorporating CBE techniques used by medical experts to train artificial intelligence systems.

George Jenkinson expresses hope that this research will complement existing breast cancer diagnostic methods and contribute valuable data for identifying significant trends in early breast cancer diagnosis. Their vision includes placing IRIS in easily accessible locations like pharmacies and health centers, offering women a safe and accurate alternative for CBEs. Furthermore, IRIS could be integrated with diagnostic tools such as ultrasound to enhance early detection capabilities.

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