The Murab project is developing technology that will make it possible to take...
The Murab project is developing technology that will make it possible to take more accurate biopsies and diagnose cancer and other illnesses faster.

MURAB: Roboter-assisted diagnostic of breast cancer

The Murab project is developing technology that will make it possible to take more accurate biopsies and diagnose cancer and other illnesses faster.

Breast cancer is the most common cancer among females in the EU. Important for the diagnosis are imaging examinations, such as mammography, ultrasound or magnetic resonance tomography (MRI). But, at the end of the day, biopsy is the only true detection of cancer. However, it is undisputed that biopsy risks and can harm the patient’s procedure. The MURAB (MRI and Ultrasound Robotic Assisted Biopsy) project is developing technology that will make it possible to take more precise and effective biopsies (tissue samples) and diagnose cancer and other illnesses faster. It is creating a robot that will scan a patient’s body using a combination of MRI and ultrasound technology, and select the right location for a biopsy.

Photo
The project is creating a robot that will scan a patient’s body using a combination of MRI and ultrasound technology, and select the right location for a biopsy.
Source: MURAB

This will be quicker and more comfortable for patients, and will have the potential to identify early-stage signs of cancer that conventional ultrasounds may not pick up as well as reduce the likelihood of false negative results. Current screening techniques result in 10-20% of patients being wrongly informed that they do not have breast cancer. With this new technology scans will take 15-20 minutes (instead of 45-60 minutes for a standard MRI scan). It will also allow patients to benefit from MRI scanning technology, which is highly accurate and very safe, without its high costs.

Currently MURAB is focusing on the diagnosis of breast cancer and also muscle diseases, although it should ultimately help with any diagnosis for which a small section of tissue needs to be removed from the body. A robotically-steered device will take an image using MRI and overlay it with images taken by ultrasound and pressure sensors: the sharper MRI image will be able to locate signs of potential disease in the less clear ultrasound.

A biopsy robot will then take a tissue sample for analysis. This process has some advantages for the patients. First, the roboters have a calmer hand and do not get tired. Second, you can convert the doctor’s movement so that the robotic arm moves only by millimeters. That means they can make the smallest cuts with the utmost precision, thus hurting less tissue, causing less pain and making the procedure more bearable.

The process will use an innovative technique called Tissue Active Slam (TAS) which combines elements of different diagnostic procedures, including elastography (measuring whether tissue is hard or soft). The project is cross-disciplinary, combining elements of medical imaging and robotics, and involves collaboration between hospitals, universities and manufacturers of medical equipment. Project participants are also working on an MRI-compatible robot, which could be used to carry out some procedures inside a scanner.

The research project

Project partners include the company KUKA Medical Robotics, Siemens Nederland N.V., the University of Verona (UNIVR), the Medical University of Vienna and the Radboud University Medical Center (RUMD) in the Netherlands. The EU is supporting the project with around 4 million euros.

The official launch of the project was part of the annual European Robotics Summit 2016 in the Netherlands and is expected to be completed by the end of 2019. At the Medica 2018, the prototype was presented and gave hope for a new future in breast cancer diagnostics.

Subscribe to our newsletter

Related articles

Combination of AI and radiologists accurately identified breast cancer

Combination of AI and radiologists accurately identified breast cancer

An AI tool identified breast cancer with approximately 90 percent accuracy when combined with analysis by radiologists.

AI improves biomedical imaging

AI improves biomedical imaging

Researchers use artificial intelligence to improve quality of images recorded by a relatively new biomedical imaging method.

Technology pinpoints biopsies to detect prostate cancer

Technology pinpoints biopsies to detect prostate cancer

Medical software that overlays tumour information from MRI scans onto ultrasound images can help guide surgeons conducting biopsies and improve prostate cancer detection.

Using robotics technology to fight breast cancer

Using robotics technology to fight breast cancer

Various prototypes of 3D-printed biopsy robots could alleviate the suffering of patients and make breast cancer testing more accurate and efficient.

AI & MRI look into the genome of brain tumors

AI & MRI look into the genome of brain tumors

Researcher have developed a computer method that uses MRI and machine learning to rapidly forecast genetic mutations in glioma tumors,

Google-powered AI spots breast cancer

Google-powered AI spots breast cancer

A computer algorithm has been shown to be as effective as human radiologists in spotting breast cancer from x-ray images.

Robotic system for endovascular instrument guidance

Robotic system for endovascular instrument guidance

Researchers have developed a new method to guide endovascular instruments into complex vascular structures that were inaccessible to endovascular surgeons until now.

Using AI to predict risk of thyroid cancer on ultrasound

Using AI to predict risk of thyroid cancer on ultrasound

Researchers from Thomas Jefferson University use machine learning on ultrasound images of thyroid nodules to predict risk of malignancy.

‘Uncanny Valley’: Brain network evaluates robot likeability

‘Uncanny Valley’: Brain network evaluates robot likeability

Scientists have identified mechanisms in the human brain that could help explain the the unsettling feeling we get from robots and virtual agents that are too human-like.

Popular articles