Summary
Detection of bowel cancer is currently performed by visual inspection of the colonic mucosa during endoscopy, which is less reliable for small-sized lesions that are not easily visualised. If they are not detected and removed at an early stage, there is a chance that they may become cancerous. This project seeks to develop a new mathematical tool for analysing the sensing capability of micro-robots to aid the detection of hard-to-visualise bowel lesions. Micro-robots experiencing vibrations, frictions, and impacts, known as non-smooth dynamical systems, exhibit a rich variety of different long-term behaviours co-existing for a given set of parameters, which is referred to as multi-stability or co-existing attractors. When the robot moves in the colon and encounters a lesion, some particular attractor may dominate its dynamics, while the other co-existing attractors could fade away due to the tissue’s mechanical properties associated with different stages of malignant transformation. This significant change in multi-stability can be utilised to distinguish between healthy and abnormal tissues. The fellow proposes to use for the first time robot’s multi-stability through the development of state-of-the-art numerical techniques to analyse such robot-lesion correlation, and produce a suite of computational analysis and advanced control methods for cancer detection and staging. In the long term, this work will initiate a new modality for bowel cancer screening, delivering an efficient minimally invasive procedure for patients. The unique research approach of this fellowship, a joint effort of numerical and experimental studies, will be hosted by Dr Yang Liu from the University of Exeter with the secondment supervisor, Prof. Bradley Nelson from ETH Zurich, and the consulting gastroenterologist, Dr Shyam Prasad, from the Royal Devon and Exeter NHS Foundation Trust.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101018793 |
| Start date: | 01-10-2021 |
| End date: | 30-09-2023 |
| Total budget - Public funding: | 212 933,76 Euro - 212 933,00 Euro |
Cordis data
Original description
Detection of bowel cancer is currently performed by visual inspection of the colonic mucosa during endoscopy, which is less reliable for small-sized lesions that are not easily visualised. If they are not detected and removed at an early stage, there is a chance that they may become cancerous. This project seeks to develop a new mathematical tool for analysing the sensing capability of micro-robots to aid the detection of hard-to-visualise bowel lesions. Micro-robots experiencing vibrations, frictions, and impacts, known as non-smooth dynamical systems, exhibit a rich variety of different long-term behaviours co-existing for a given set of parameters, which is referred to as multi-stability or co-existing attractors. When the robot moves in the colon and encounters a lesion, some particular attractor may dominate its dynamics, while the other co-existing attractors could fade away due to the tissue’s mechanical properties associated with different stages of malignant transformation. This significant change in multi-stability can be utilised to distinguish between healthy and abnormal tissues. The fellow proposes to use for the first time robot’s multi-stability through the development of state-of-the-art numerical techniques to analyse such robot-lesion correlation, and produce a suite of computational analysis and advanced control methods for cancer detection and staging. In the long term, this work will initiate a new modality for bowel cancer screening, delivering an efficient minimally invasive procedure for patients. The unique research approach of this fellowship, a joint effort of numerical and experimental studies, will be hosted by Dr Yang Liu from the University of Exeter with the secondment supervisor, Prof. Bradley Nelson from ETH Zurich, and the consulting gastroenterologist, Dr Shyam Prasad, from the Royal Devon and Exeter NHS Foundation Trust.Status
CLOSEDCall topic
MSCA-IF-2020Update Date
28-04-2024
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