Project description
An endoscope for predicting head and neck cancer progression
Head and neck cancers are a group of malignancies that develop in the mucosal linings of the mouth, throat, nose, salivary glands and larynx. As with most cancers, early diagnosis is central for therapy. However, existing endoscopic techniques cannot reliably predict which precancerous lesions will progress to cancer, making intervention challenging. To address this, the ERC-funded EPIC project aims to develop a miniaturised fibre-optic probe that simultaneously captures molecular, structural and vascular information from tissue in real time. The platform integrates a deep learning model for predicting progression of precancerous lesions to cancer. The technology will be validated first in animal models and then in a longitudinal human study.
Objective
Head and neck cancers (HNC), which include malignancies of the oral cavity, tonsils, nasopharynx, and larynx, are life-threatening, particularly when diagnosed in advanced stages. Effective management requires early detection and continuous monitoring to enable earliest possible intervention of high-risk precancerous lesions. Unfortunately, current endoscopic techniques are limited in their ability to provide accurate predictions of disease trajectories.
The overarching goal of EPIC is to develop a new endoscopic technology to predict HNC tissue state trajectory with the fidelity needed to intervene in the present – an “endoscopic tissue time machine”. We will create a miniaturized 2.0 mm forward-viewing fibre-optic probe compatible with head and neck (H&N) endoscopes that integrates Raman spectroscopy (for molecular state), optical coherence tomography (for morphological state), and real-time optical vascular imaging (for microvascular state). This ground-breaking label-free platform technology will facilitate a synergistic integration of clinically relevant multi-modal endoscopic data, bridging different scales and modalities while putting endoscopic data in a clinical and biological context. We will develop an explainable deep learning model (an endoscopic time machine) to predict transition points in the progression from normal tissue to dysplasia and ultimately to cancer in an animal model. To address the unmet clinical need, we will conduct a longitudinal human observational study utilizing the endoscopic tissue time machine for real-time in vivo prediction of progression risk from dysplasia to cancer.
This project will integrate scientific and technological advances to offer new insights into the microenvironment of H&N carcinogenesis, enhance understanding of clinical diversity, and identify novel transition biomarkers for improved prognostics and timely interventions.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
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Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
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Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
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Call for proposal
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Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2025-COG
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
WC2R 2LS London
United Kingdom
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