Wednesday, February 29 saw the official end of the ambitious HAMAM (Highly Accurate Breast Cancer Diagnosis through Integration of Biological Knowledge, Novel Imaging Modalities, and Modelling) project, which has culminated in the successful development of a prototype clinical workstation, combining the various technologies and information required to characterise and classify suspicious breast tissue.
The results of the project, including the workstation, were presented at a public session in the Austria Center Vienna on March 1, as a satellite event prior to the European Congress of Radiology (ECR 2012). A consortium of nine scientific and industrial partners from five European countries, plus the USA, contributed to the project, which was coordinated by the European Institute for Biomedical Imaging Research.
Early diagnosis is an essential part of the battle against breast cancer, and accurate differential diagnosis is vital for physicians to tailor treatment procedures to the individual patient. In a comprehensive and diagnostically robust breast imaging protocol, clinicians prefer a multi-modal approach, which can include techniques such as mammography, 2D ultrasound, MRI, digital breast tomosynthesis, positron emission mammography, and automated 3D breast ultrasound (ABUS).
The HAMAM project, which was partially funded by the EC’s 7th Framework Programme for Research, set out to develop a workstation that incorporates these diverse advanced image acquisition and corresponding image analysis methods, bringing together, in one user-friendly interface, the wide range of information needed for physicians to make accurate, early diagnosis of breast malignancy and therefore reliable treatment decisions.
Among the key outcomes of the project are a number of tools designed to automatically correlate and jointly interpret information from different sources. With conventional imaging workstations, extensive training is necessary before readers are able to reliably identify correspondences of suspicious structures in 2D projection images, like mammography, and 3D modalities, such as ABUS.
A major result of the HAMAM project was a set of new techniques to automatically map spatially corresponding anatomical structures in each modality. The images can then be presented such that sizes and positions match between modalities, thereby instantly orienting the human reader and facilitating more efficient and accurate combined assessment of findings.
Also, a novel system was developed to classify lesions as probably benign or malignant using image descriptors from mammography jointly with kinetic and morphological descriptors from MRI. Another computer-aided diagnosis (CAD) system assists radiologists in characterising suspicious lesions in ABUS; a promising technology for screening women with dense breasts. In a reader performance study this new CAD tool significantly improved the performance of radiology residents compared to conventional ABUS reading.
The majority of scientific results of the project became part of a patient-centric workstation that enables the reader to quickly access all available patient-related imaging studies plus non-imaging information and make fully informed, computer-assisted decisions about diagnosis and treatment, offering the potential to dramatically improve the efficiency of breast cancer care.
Video on Euronews: http://18.104.22.168/europa/futuris/10-breast-cancer-en.wmv
European Institute for Biomedical Imaging Research (EIBIR), Project Coordination
Neutorgasse 9, 1010 Vienna (AT)
Scientific Coordinator: Prof. Horst Hahn, Fraunhofer MEVIS, email@example.com
HAMAM Project Partners