Funding source: H2020-MSCA-IF-2017
Grant number: 798244
Funding period: 2018 – 2021
Advanced Laboratory Phantoms for Soft Tissues in Engineering and Medicine: ALPHA-STEM
Research has shown that the success rate in many types of surgeries is strictly related to the experience of the surgeon. However, early in their career, trainees are not given the opportunity to operate on a sufficient number of patients nor to perform an exhaustive mix of procedures. The scenario has been further worsened by the reduction of assisted training hours in Europe (since 2009) and US (since 2011). Training and technical tasks are usually practised on cadavers, animals or using virtual simulators. However, all these alternatives present difficulties: limited availability, expensive handling and preservation processes (cadaveric training), nonhuman anatomical structures (animal training), costly set-up, and doubtful skills transfer to the real operating theatre (virtual simulators). A potential solution is to promote the use of artificial synthetic models, also known as phantoms. Phantoms are reproduction of human parts and organs that allow the trainee to practice positioning of the anatomical structures as well as hand coordination. Unfortunately, they lack of reliable tactile feedback (e.g. palpation) and real tissue deformation patterns which critically reduce the fidelity of the surgical training.
The main objective of this project is to overcome the present limitations by developing phantoms capable of providing detailed anatomical structures along with an accurate tactile response when performing surgical tasks such as cutting, indention and suturing. The proposed investigation is aimed at designing, making and testing synthetic advanced materials tailored to reproduce the mechanical response of different human organs and tissues (lung, brain, liver, skin, cartilage, etc.). Direct comparisons with experimental data on organic tissues and feedback from a number of experienced surgeons will be used to validate the effectiveness of the proposed solutions during this research journey towards safer surgeries.
Funding source: MSCA-ITN-2018
Grant number: 813782
Funding period: 2019 – 2023
Abstract:ATLAS is a Marie Curie European Joint Doctorate school (813782) that targets the training of experts in a very specific branch of Robotic Surgery. ATLAS stands for “AuTonomous intraLuminAl Surgery”. Intraluminal navigation, a particularly challenging branch, reappears in many minimal invasive surgical (MIS) interventions that rely on steering flexible instruments through fragile lumens or vessels. The project, coordinated by the University of Leuven, is implemented by a consortium of seven Universities and many industrial partners.
The project will develop smart flexible robots that autonomously propel through complex deformable tubular structures. This calls for seamless integration of sensors, actuators, modelling and control. By engaging in this ambitious research topic, participants will be exposed to all aspects of robotics. While contributing to the state of the art, they will become proficient in building, modelling, testing, interfacing in short in integrating basic building blocks into systems that display sophisticated behavior.
Funding source: RIA H2020-ICT-2016
Grant number:H2020-ICT-2016- 732515
Funding period: 2017 – 2020
Funding period: 2016 – 2020
EDEN2020 will provide a step change in the modelling, planning and delivery of diagnostic sensors and therapies to the brain via flexible surgical access, with an initial focus on cancer therapy. It will engineer a family of steerable catheters for chronic disease management that can be robotically deployed and kept in situ for extended periods. The system will feature enhanced autonomy, surgeon cooperation, targeting proficiency and fault tolerance with a suite of technologies that are commensurate to the unique challenges of neurosurgery. Amongst these, the system will be able to sense and perceive intraoperative, continuously deforming, brain anatomy at unmatched accuracy, precision and update rates, and deploy a range of diagnostic optical sensors with the potential to revolutionise today’s approach to brain disease management. By modelling and predicting drug diffusion within the brain with unprecedented fidelity, EDEN2020 will contribute to the wider clinical challenge of extending and enhancing the quality of life of cancer patients–with the ability to plan therapies around delicate tissue structures and with unparalleled delivery accuracy.
EDEN2020 is strengthened by a significant industrial presence, which is embedded within the entire R&D process to enforce best practices and maximise translation and the exploitation of project outputs. As it aspires to impact the state of the art and consolidate the position of European industrial robotics, it will directly support the Europe 2020 Strategy.
For more information, please visit EDEN2020 website.