Personalized management of Oral Cavity Cancer: models and point-of-care diagnostic to help treatment decisions
Tuesday September 27, 2016
|16:30-16:35||T. Poli and E. Martinelli||VPH and prognostic modelling for cancer|
|16:35-16:45||Tito Poli||The challenge of Oral Cancer patients stratification|
|16:45-17:00||Steven Mes and D. Te Beest||Prognostic modelling and treatment decision making: the case of Oral Cancer|
|17:00-17:15||Florian Jung||New techniques for diagnostic image analysis and automatic features extraction|
|K. Schneckenbach, E. Jazzani, and F. Jung||demo slideshow|
|17:15-17:30||Marco Cereda||Point of care personalized genomic analysis: the Q3 qRT-PCR in vitro diagnostic|
|17:30-17:45||OneToNet and VCI||OraMod platform: Virtual Representation and Virtual Tumor Board for decision support: presentation and demo slideshow|
|17:45-18:00||Chair: Ruud Brakenhoff||Round table and open discussion|
Oral Squamous Cell Carcinoma (OSCC) is one of the deadliest cancers of the head and neck region: around 50% of diagnosed patients die within five years from diagnosis, 90% of which within two years after treatment. It is a particularly challenging disease due to its variability and unpredictability and due to the impacts of treatment and post-treatment morbidity. Surgical treatment can be devastating, associated with disfigurement, impairments in speech and swallowing (dysphagia) and an overall compromise in quality of life. At present treatment decisions are taken based on few prognostic factors, the so called TNM staging and grading system, with a “one fits all” approach which does not take into consideration all the multiscale complexity of the disease. Therefore it might occur that patients considered at high risk do not develop reoccurrences and have a high survival rate, while patients considered at low risk relapse very fast and have very poor survival. Computational models and prognostic signatures have been proposed in the past for all head and neck cancers. However these models do not consider the particularity of oral cavity cancer and the specific biomolecular characteristics of the disease in each individual.
The goal of OraMod is to address the challenge of personalized treatment for Oral Cavity Cancer and support treatment decision-making. The prognostic models realized and validated by the project allow patients stratification and prediction of disease progression. Integrated into a simulation and collaborative decision support environment, supported by a layered virtual patient representation and knowledge sharing through a Virtual Tumor Board, they support collaborative decision making. The project also provides image analysis tools for automatic features extraction, thus reducing intra-operator variability and the time required for diagnostic image referral and a portable qRT-PCR device for personalized genomic data extraction at point-of care-
The scope of the satellite event is to propose a new ground for treatment decision-making and new concepts and ideas for the building of more precise clinical guidelines for Oral Cavity Cancer, founded on multiscale computational models and innovative diagnostic tools. The workshop will give the opportunity to present and discuss the latest scientific and technological results of OraMod and to confront concerning the real applicability and effectiveness of computational prognostic modelling in clinical practice.