New Robot could Help Diagnose Breast Cancer Early

A device has been created that could carry out Clinical Breast Examinations (CBE).

The manipulator, designed by a team at the University of Bristol and based at the Bristol Robotics Laboratory, is able to apply very specific forces over a range similar to forces used by human examiners and can detect lumps using sensor technology at larger depths than before.

This could revolutionise how women monitor their breast health by giving them access to safe electronic CBEs, located in easily accessible places, such as pharmacies and health centres, which provide accurate results.

Precision, repeatability and accuracy are of paramount importance in these tactile medical examinations to ensure favourable patient outcomes. A range of automatic and semi-automatic devices have been proposed to aid with optimising this task, particularly for difficult to detect and hard to reach situations such as during minimally invasive surgery.

The research team included a mix of postgraduate and undergraduate researchers, supervised by Dr Antonia Tzemanaki from Bristol Robotics Laboratory. Lead author George Jenkinson explained: "There are conflicting ideas about how useful carrying out Clinical Breast Examinations (CBE) are for the health outcomes of the population.

"It's generally agreed upon that if it is well performed, then it can be a very useful and low risk diagnostic technique.

"There have been a few attempts in the past to use technology to improve the standard to which healthcare professionals can perform a CBE by having a robot or electronic device physically palpate breast tissue. But the last decade or so of technological advances in manipulation and sensor technology mean that we are now in a better position to do this.

"The first question that we want to answer as part of this is whether a specialised manipulator can be demonstrated to have the dexterity necessary to palpate a realistic breast size and shape."

The team created their manipulator using 3D printing and other Computerised Numerical Control techniques and employed a combination of laboratory experiments and simulated experiments on a fake (silicone) breast and its digital twin, both modelled on a volunteer at the Simulation and Modelling in Medicine and Surgery research group at Imperial College London.

The simulations allowed the team to perform thousands of palpations and test lots of hypothetical scenarios such as calculating the difference in efficiency when using two, three, or four sensors at the same time. In the lab, they were able to carry out the experiments on the silicone breast to demonstrate the simulations were accurate and to experimentally discover the forces for the real equipment.

George added: "We hope that the research can contribute to and complement the arsenal of techniques used to diagnose breast cancer, and to generate a large amount of data associated with it that may be useful in trying to identify large scale trends that could help diagnose breast cancer early.

"One advantage that some doctors have mentioned anecdotally is that this could provide a low-risk way to objectively record health data. This could be used, for example, to compare successive examinations more easily, or as part of the information packet sent to a specialist if a patient is referred for further examination."

As a next step, the team will combine CBE techniques learned from professionals with AI, and fully equip the manipulator with sensors to determine the effectiveness of the whole system at identifying potential cancer risks.

The ultimate goal is that the device and sensors will have the capability to detect lumps more accurately and deeper than it is possible only from applying human touch. It could also be combined with other existing techniques, such as ultrasound examination.

"So far we have laid all of the groundwork," said George. "We have shown that our robotic system has the dexterity necessary to carry out a clinical breast examination - we hope that in the future this could be a real help in diagnosing cancers early."

This research was a part of project ARTEMIS, funded by Cancer Research UK and supported by EPSRC.

'A robotIc Radial palpatIon mechaniSm for breast examination (IRIS)’ by George Jenkinson et al which was presented at the RO-MAN conference.

Most Popular Now

ChatGPT can Produce Medical Record Notes…

The AI model ChatGPT can write administrative medical notes up to ten times faster than doctors without compromising quality. This is according to a new study conducted by researchers at...

Can Language Models Read the Genome? Thi…

The same class of artificial intelligence that made headlines coding software and passing the bar exam has learned to read a different kind of text - the genetic code. That code...

Study Shows Human Medical Professionals …

When looking for medical information, people can use web search engines or large language models (LLMs) like ChatGPT-4 or Google Bard. However, these artificial intelligence (AI) tools have their limitations...

Bayer and Google Cloud to Accelerate Dev…

Bayer and Google Cloud announced a collaboration on the development of artificial intelligence (AI) solutions to support radiologists and ultimately better serve patients. As part of the collaboration, Bayer will...

Advancing Drug Discovery with AI: Introd…

A transformative study published in Health Data Science, a Science Partner Journal, introduces a groundbreaking end-to-end deep learning framework, known as Knowledge-Empowered Drug Discovery (KEDD), aimed at revolutionizing the field...

Shared Digital NHS Prescribing Record co…

Implementing a single shared digital prescribing record across the NHS in England could avoid nearly 1 million drug errors every year, stopping up to 16,000 fewer patients from being harmed...

Ask Chat GPT about Your Radiation Oncolo…

Cancer patients about to undergo radiation oncology treatment have lots of questions. Could ChatGPT be the best way to get answers? A new Northwestern Medicine study tested a specially designed ChatGPT...

North West Anglia Works with Clinisys to…

North West Anglia NHS Foundation Trust has replaced two, legacy laboratory information systems with a single instance of Clinisys WinPath. The trust, which serves a catchment of 800,000 patients in North...

Can AI Techniques Help Clinicians Assess…

Investigators have applied artificial intelligence (AI) techniques to gait analyses and medical records data to provide insights about individuals with leg fractures and aspects of their recovery. The study, published in...

AI Makes Retinal Imaging 100 Times Faste…

Researchers at the National Institutes of Health applied artificial intelligence (AI) to a technique that produces high-resolution images of cells in the eye. They report that with AI, imaging is...

Standing Up for Health Tech and SMEs: Sh…

AS the new chair of the health and social care council at techUK, Shane Tickell talked to Highland Marketing about his determination to support small and innovative companies, by having...

GPT-4 Matches Radiologists in Detecting …

Large language model GPT-4 matched the performance of radiologists in detecting errors in radiology reports, according to research published in Radiology, a journal of the Radiological Society of North America...