EU Funded Clinical Workstation Will Help Accurately Detect Breast Cancer

HAMAMEach year 350,000 new cases of breast cancer are detected in the European Union, but a lack of effective technology to assist in cases that are difficult to diagnose means some cases go undetected or are incorrectly diagnosed. The EU is investing €3.1 million to develop better and quicker breast cancer diagnostics through the HAMAM project. This project is developing a prototype workstation to help diagnose breast cancer by integrating multi-modal images resulting from mammography, magnetic resonance imaging and other technologies as well as patient information. Doctors will be able to compare those multi-modal images side by side while viewing the patient's history and medical analyses. The workstation will be tested in selected hospitals in Germany, the UK and the Netherlands.

Commission Vice-President for the Digital Agenda Neelie Kroes said: "Breast cancer is a condition that touches millions of lives. In Europe about 130,000 women die of breast cancer every year. If more cancers could be detected on time, we could save many thousands of them. So I am very excited by the potential of the HAMAM project's digital technology to help save lives."

Around 350,000 new breast cancer cases are detected in Europe every year, which accounts for 26% of all new cancer cases among women. 17% of women dying from cancer each year die from breast cancer. Currently, the fight against breast cancer is focused on its early detection.

Despite advances in modern imaging technology, early detection and accurate diagnosis of breast cancer are still unresolved challenges. Unnecessary biopsies are taken and tumours frequently go undetected until a stage where a successful therapy is much more difficult or even impossible. The HAMAM project is tackling this by integrating multi-modal images and patient information on a single clinical workstation. Imaging modalities which can be compared include X-ray mammography, tomosynthesis, magnetic resonance imaging, 2D/3D ultrasound and positron emission mammography. The three-year project started in 2008 and received €3.1 million from the EU. It ensures that scientists, clinicians, and IT experts work together to collect all the existing patient data in a common database. More specifically, the project is developing clinical software tools that integrate imaging and quantitative data and combine it with personalised risk profiles for developing breast cancer, based on genetic information and family history.

The project's clinical advisory board involves leading experts in breast cancer diagnosis from six EU member states (Belgium, Germany, Italy, The Netherlands, Sweden and the UK) as well as from the US. Clinical tests will be undertaken in hospitals in Berlin (Germany), Dundee (the UK) and Nijmegen (The Netherlands). The tests will be supported by IT experts from several universities in Europe.

HAMAM is a successor of two other EU-funded projects: SCREEN and SCREEN-TRIAL. These projects brought major advances in European breast cancer diagnosis, meaning that today Europe is the world leader in diagnostic systems for digital mammography. With HAMAM, Europe will strengthen its leadership in the area of image-based breast cancer diagnoses.

For further information, please visit:
http://www.hamam-project.eu

Related articles:

Most Popular Now

Philips and Medtronic Advocacy Partnersh…

Royal Philips (NYSE: PHG, AEX: PHIA), a global leader in health technology, and Medtronic Neurovascular, a leading innovator in neurovascular therapies, today announced a strategic advocacy partnership. Delivering timely stroke...

New AI Tool Predicts Protein-Protein Int…

Scientists from Cleveland Clinic and Cornell University have designed a publicly-available software and web database to break down barriers to identifying key protein-protein interactions to treat with medication. The computational tool...

AI for Real-Rime, Patient-Focused Insigh…

A picture may be worth a thousand words, but still... they both have a lot of work to do to catch up to BiomedGPT. Covered recently in the prestigious journal Nature...

New Research Shows Promise and Limitatio…

Published in JAMA Network Open, a collaborative team of researchers from the University of Minnesota Medical School, Stanford University, Beth Israel Deaconess Medical Center and the University of Virginia studied...

G-Cloud 14 Makes it Easier for NHS to Bu…

NHS organisations will be able to save valuable time and resource in the procurement of technologies that can make a significant difference to patient experience, in the latest iteration of...

Start-Ups will Once Again Have a Starrin…

11 - 14 November 2024, Düsseldorf, Germany. The finalists in the 16th Healthcare Innovation World Cup and the 13th MEDICA START-UP COMPETITION have advanced from around 550 candidates based in 62...

Hampshire Emergency Departments Digitise…

Emergency departments in three hospitals across Hampshire Hospitals NHS Foundation Trust have deployed Alcidion's Miya Emergency, digitising paper processes, saving clinical teams time, automating tasks, and providing trust-wide visibility of...

MEDICA HEALTH IT FORUM: Success in Maste…

11 - 14 November 2024, Düsseldorf, Germany. How can innovations help to master the great challenges and demands with which healthcare is confronted across international borders? This central question will be...

A "Chemical ChatGPT" for New M…

Researchers from the University of Bonn have trained an AI process to predict potential active ingredients with special properties. Therefore, they derived a chemical language model - a kind of...

Siemens Healthineers co-leads EU Project…

Siemens Healthineers is joining forces with more than 20 industry and public partners, including seven leading stroke hospitals, to improve stroke management for patients all over Europe. With a total...

MEDICA and COMPAMED 2024: Shining a Ligh…

11 - 14 November 2024, Düsseldorf, Germany. Christian Grosser, Director Health & Medical Technologies, is looking forward to events getting under way: "From next Monday to Thursday, we will once again...

In 10 Seconds, an AI Model Detects Cance…

Researchers have developed an AI powered model that - in 10 seconds - can determine during surgery if any part of a cancerous brain tumor that could be removed remains...