OraMod is an EC-FP7-ICT project that starts from the need of researchers and clinicians in the field of oncology to improve the representation of biological processes related to onset, growth, dissemination and relapse of human cancer. The project specifically addresses the challenge of early prediction of relapses of Oral Squamous Cell Carcinoma (OSCC), a disease with impressive effects on patients due to its invasiveness in face characteristics as well as speaking and eating ability.
OraMod is a follow-up project of the NeoMark project, focusing on a more intuitive user experience, thereby bringing it closer to clinical application.
After treatment, oral cancer leads to remission, however it might still be present. Several factors correlate with the disease reoccurrence (e.g. age, sex, HPV infection, site and stage of primary tumour) but they have not been studied all together. So the current method for prediction reoccurrence risk in OSCC patients is still not enough.
OSCC patients' data (clinical, biomedical, genomic, histological, from digital imaging, from surgery evidence) is used to generate a reoccurrence risk model. This model can then be used to predict the reoccurrence risk for an individual patient by analyzing the OSCC data.
Fraunhofer IGD's Contribution
In OraMod, Fraunhofer IGD is developing technologies for extracting imaging features from CT and MRI data sets in order to enhance the OraMod oral cancer prediction engine. This includes automatic segmentation and registration methods applied to the head and neck region as well as lymph node analysis. Hereby, the novel “Articulated Atlas” developed at Fraunhofer IGD will play an essential role.
OraMod Image Processing Tool
The purpose of the OraMod Image Processing Tool is to enable the radiologist to automatically and semi-automatically extract geometry and texture based features of tumors and lymph nodes from CT and MR head & neck images. The use of state of the art and beyond the art image processing and image analysis algorithms ensures great accuracy and robustness of the numerical features, ensuring the ability to integrate the imaging data with the genomic and clinical data by the OraMod data analysis tool.