Skip to main content

Real Organ Generation

Periodic Reporting for period 1 - ROG (Real Organ Generation)

Berichtszeitraum: 2019-12-01 bis 2020-05-31

Globally, there are millions of people every year who need urgent medical attention and early diagnosis because affected by heart dangerous diseases. Innovative tools, capable of speeding up the diagnostic process, making it economically more efficient and medically more effective, will help patients suffering from serious diseases and doctors committed to treating them. The intervention simulation activities available today have as their main tool the use of corpses that are increasingly difficult to find and expensive to maintain. Furthermore, culturally many populations find it difficult to be able to leave their bodies to science. ROG is developing a system that will allow surgeons to practice 3D organs identical to the originals, also recreating the context of the operation, with the pulsating organ and sprayed with blood vessels, as currently it is not possible to recreate. The objectives of the project are reaching a diagnosis’s accuracy improvement, a surgical mistake decreasing, surgical and medical training facilitation. During phase 2 of the EIC Accelerator project, our ambition is to reach a production and marketing capacity for our solutions on the European target markets.
During the SME phase I we carried out the feasibility study which was divided in 4 complementary assessments linked to well-defined activities designed to reach the overall goal of gaining reliable in-depth insight as to the general feasibility of our product in order to take a final go decision on implementation. The feasibility study led us to develop a deep knowledge of our Project and to improve technical innovative solutions. In particular, ROG has managed to developed a complex software able to generate 3D models with a very deep and specialized detail. Our original and registered integrated modelling platform is now able to supports the definition of mockup and immediately adapt models for use in virtual reality and 3D printing by applying one or more multiparametric models through our algorithm and in-house-developed mathematical modelling tools. Concerning the dissemination strategy we will implement, into the web site, a dedicate section to the product and its technical and scientific presentation (by creating several institutional video), we will expand our already solid partner network to other hospital, university and research institutes and we will establish a physical commercial network to consolidate the service awareness channel.
3 Progress beyond the state of the art, expected results until the end of the project and potential impacts (including the socio-economic impact and the wider societal implications of the project so far)
Expected results:
Create a European web platform that creates synergies between hospitals, research centers and Fab labs across Europe by providing tools for the analysis of high resolution diagnostic images in order to improve the training processes of doctors and surgeons and allow a more effective preparation for stimulating surgeryPotential impacts:
The process will be completed thanks to the use of high resolution 3D printing tools that allow dynamic mock ups to be used to improve the training of medical personnel. These mock ups will be made with an innovative and patented material in combination with original printing technologies developed during the project. The socio-economic impact at European level will mainly derive from the reduction of intervention times and the corresponding decrease in costs necessary to carry out these activities. It will also be possible to train new doctors and surgeons interactively and dynamically also thanks to virtual or augmented reality tools for the simulation of interventions. The use of the ROG platform will thus allow a better sharing of medical knowledge by expanding the skill set of specialized personnel, ensuring a better and more standardized process of sharing information and medical and surgical best practices
mtm-rog.jpg