WP2: Ultrasonography (echOpen)
WP2 Research Leaders
IRD: Institut de la recherche pour le développement (France & Peru)
ULB: Université Libre de Bruxelles (Belgium)
Developing a specific medical imaging protocol to help to characterize the liver function in the detection of HCC.
In Peru, we discovered an unusual pattern of early-onset liver cancer in patients attending INEN. These patients were much younger than previously observed elsewhere (on average 25 years old), with already advanced-stage HCC and large tumours exceeding 14cm in diameter. Work package 2 brings together expertise from different countries to develop new medical imaging techniques to help characterize the liver function in the detection of HCC in order to develop better diagnostic and treatment protocols for this new pattern of liver cancer.
First we will implement magnetic resonance imaging (MRI) acquisition sequences, developed at ULB specifically for the liver, at the radiology department in INEN. This protocol aims to study liver mechanical properties using real time cinematic sequences.
In order to exchange data between Lima and Brussels, we will set up the image server infrastructure to collect, anonymize and share Dicom data. This will be done using open source available PACS software (Orthanc). This infrastructure will enable practitioners at the INEN facility to easily exchange images with ULB. The anonymized transmitted images will be analysed using specific motion amplification software, results are then shared with the medical staff of INEN. Liver pathologies differ between patients in Brussels and Lima; in particular Peruvian patients exhibit more advanced tumours and a lower age, whereas Brussels patients present more fibrosis. After a first survey composed of both healthy volunteers and patient in INEN, the training and the research will be carried out in Brussels.
Secondly we will develop tissue level image analysis; previous work done by some members of the consortium identified some very specific patterns inside the pathological liver tissue. ULB expertise on pathological image analysis will be used in order to detect and automatically quantify these patterns directly from the digitized slices using both traditional methods and machine learning algorithms. This approach will be shared with INEN and CILM.
Finally, we plan to later implement the echOpen project [http://www.echopen.org], aiming to provide a low-cost first-line echography device. A comparative screening of echOpen vs. standard imaging equipment on selected patients will assess the accuracy of echOpen used by non-radiologist health professionals at INEN and CILM for identification of cirrhosis criteria in chronic viral hepatitis patients clinically diagnosed with cirrhosis. This approach will help in developing methods for the early detection of hepatic diseases using low-cost devices which could be available even in remote locations.