Revealing liver micrometastases in vivo using ultra-high definition MRI
MicroMetSCAN aims to revolutionize MRI techniques for early detection of liver micrometastases, enhancing cancer diagnosis and treatment through improved imaging sensitivity and biological insights.
Projectdetails
Introduction
Over 90% of cancer-related deaths are caused by metastases. A major obstacle for accurate patient stratification, development of new treatments against metastases, and thorough biological understanding is our inability to detect early-stage micrometastases (µMets). The liver is one of the first and most common sites for metastases, particularly in gastrointestinal tract tumours. Thus, early detection of liver metastases is an urgent need in cancer diagnosis for many patients.
Current Limitations
Present image-based diagnostic methods, including state-of-the-art Magnetic Resonance Imaging (MRI), cannot detect µMets due to major limitations in current image contrast and resolution, as well as a lack of understanding of liver tissue changes during the metastatic process.
Proposed Solution
MicroMetSCAN proposes a paradigm-shifting MRI approach based on highly promising preliminary results that leverage recent progress in MRI acquisition, denoising, and contrast generation. This approach aims to achieve the breakthrough of exquisite sensitivity and specificity required to detect and characterise μMets in the liver and provide new insights about metastases-related tissue microenvironment dynamics.
Objectives
To achieve its overarching goal, my proposal consists of four objectives:
- Developing new ultra-high resolution MRI methods targeting robust µMets detection.
- Tailoring the specificity of contrasts towards μMet environments.
- Unravelling the transformations from µMets to full metastases in animal models, yielding critical insights into tumour growth patterns.
- Translating the new MRI approach to the clinic in a prospective clinical study.
Impact
MicroMetSCAN will significantly advance the state-of-the-art in cancer imaging, enabling precision diagnosis and treatment planning, with wide-reaching applicability, especially benefitting small lesion detection. Furthermore, it will unveil important biological insights on the progression of metastasis, guiding future therapeutic strategies for better prognosis and outcomes.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 1.998.456 |
Totale projectbegroting | € 1.998.456 |
Tijdlijn
Startdatum | 1-4-2025 |
Einddatum | 31-3-2030 |
Subsidiejaar | 2025 |
Partners & Locaties
Projectpartners
- KING'S COLLEGE LONDONpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
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Treating Liver Metastasis
This project aims to enhance immunotherapy for colorectal liver metastases by targeting innate immune responses, utilizing advanced models to identify key cellular interactions and functions.
AI to predict Cancer metastasis using Ultra-Echo-Sono imaging
AI CUrES aims to enhance early diagnosis and pre-emptive therapies for cancer metastasis by utilizing nanosized-contrast agents and AI-driven bioimaging of extracellular vesicles from colorectal tumors.
Transformative Pediatric Brain Cancer Imaging using Integrated Biophysics-AI Molecular MRI
Develop a novel AI-driven molecular MRI technology for rapid, noninvasive monitoring of pediatric brain cancer treatment response, enhancing precision medicine and understanding of tumor dynamics.
Deuterium labeling of GLUCOse improves magnetic resonance imaging Sensitivity to CANcer metabolism
GLUCO-SCAN aims to develop and clinically evaluate a novel whole-body deuterium metabolic imaging (DMI) method for cancer assessment, overcoming PET's limitations and enabling widespread screening.
Capturing tumoral drug metabolism by Cells In the Tissue Environment using spatial pharmacometabolomics
The CITE project aims to develop innovative analytical technologies to study intratumoral drug metabolism in pancreatic cancer, enhancing understanding of treatment resistance mechanisms.
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