Vibrational speckle tomography microscopy for fast intra-operative cancer tissue histopathology
The SpeckleCARS project aims to develop fast, label-free 3D histology imaging for real-time cancer diagnosis and treatment, eliminating the need for biopsies and improving accuracy and accessibility.
Projectdetails
Introduction
Histology is central to the diagnosis, staging, and treatment of cancers. It requires the removal of small regions of suspect tissues (biopsies) that are later sectioned and stained with haematoxylin and eosin (HE).
Challenges in Histology
However, histology suffers from major weaknesses:
- The standard HE protocol cannot work in vivo and requires ex vivo biopsies.
- HE is labour intensive and time-consuming, with final tissue section inspection possible only after 12 hours.
A faster but less accurate protocol, known as extemporaneous histology, can be performed in 40 minutes and is used in an intra-operative context to guide surgeries.
Project Overview
The SpeckleCARS project aims to develop, for the first time, fast label-free tomography microscopy with vibrational sensitivity. This will provide images with tridimensional improvement compared to extemporaneous histology and near-perfect concordance with conventional stained HE histology.
Innovative Approach
This pioneering approach overcomes all the previous challenges:
- Using a wide field reflection scheme and label-free contrast rules out all drawbacks due to tissue removal and external labelling.
- It provides instantaneous intraoperative 3D histological data, improving the accessibility and accuracy of tumour detection, diagnosis, and treatment.
Technological Advancements
Combining the latest advances in:
- 3D tomography reconstruction algorithms
- High power laser systems
- Key innovations in random speckle illumination and hyperspectral vibrational imaging
The SpeckleCARS project will provide, for the first time, volumetric histology imaging in real time over large (mm) fields of view without the need for tissue removal.
Validation and Applications
To demonstrate the power of the developed technologies, both ex vivo human and in vivo mouse cancer assessments will be conducted in collaboration with pathologists.
The SpeckleCARS approach is broadly applicable to all cancer types and to any tissue diagnostic requiring histological data, so the project breakthroughs will benefit many medical and biology applications.
Financiële details & Tijdlijn
Financiële details
Subsidiebedrag | € 2.726.936 |
Totale projectbegroting | € 2.726.936 |
Tijdlijn
Startdatum | 1-1-2023 |
Einddatum | 31-12-2027 |
Subsidiejaar | 2023 |
Partners & Locaties
Projectpartners
- CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE CNRSpenvoerder
Land(en)
Vergelijkbare projecten binnen European Research Council
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Advanced X-ray Energy-sensitive Microscopy for Virtual Histology
This project aims to develop a prototype phase-contrast micro-CT scanner for non-invasive 3D histology to enhance volumetric analysis of tissue samples, particularly lung lesions.
Backscattering coherent Stokes Raman scattering (sCiSsoRS) for real-time cancer diagnostics
This project aims to enhance real-time cancer diagnosis during surgery by developing backward Coherent Stokes Raman Scattering (CSRS) for rapid, HE-like imaging of thick tissue samples.
Development of a nanobody-based, slide-free approach for 3D-Histological analysis of the spatial tumor microenvironment using lightsheet imaging
This project aims to revolutionize cancer histology through a nanobody-based 3D-histopathology approach, enabling rapid, spatially accurate analysis of tumor microenvironments for improved diagnosis and patient stratification.
In vivo Immunofluorescence-Optical Coherence Tomography
Develop a high-resolution endoscopic imaging system combining Optical Coherence Tomography and fluorescent antibodies for improved diagnosis and treatment of esophageal cancer and lung disease.
Advanced analysis of multiparametric volumetric ultrafast ultrasound: a novel approach for non-invasive breast cancer diagnosis
This project aims to enhance non-invasive breast cancer diagnosis by integrating machine learning with advanced ultrasound techniques to create predictive models for tumor characteristics, reducing reliance on biopsies.
Vergelijkbare projecten uit andere regelingen
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Multimodal Hypersprectal Imaging and Raman Spectroscopy for Intraoperative Assessment of Breast Tumor Resection MarginsSpectra-BREAST aims to enhance tumor margin assessment in breast conserving surgery using a novel multimodal approach for real-time, accurate feedback, improving patient outcomes and reducing reoperation rates. | EIC Pathfinder | € 2.990.207 | 2024 | Details |
Hybrid endoscope for esophageal in vivo histology and histochemistryESOHISTO aims to revolutionize GI cancer diagnosis through innovative endoscopic technologies that enable real-time 3D imaging of diseased tissues, enhancing early detection and treatment. | EIC Pathfinder | € 3.046.127 | 2025 | Details |
ulTRafast hOlograPHic FTIR microscopYTROPHY combines advanced microscopy techniques to enable rapid, high-resolution imaging of tumor biopsies for precise diagnosis and tailored cancer therapies, enhancing patient outcomes. | EIC Pathfinder | € 1.904.544 | 2022 | Details |
Chemometric histopathology via coherent Raman imaging for precision medicineThe CHARM project aims to revolutionize cancer diagnosis with a novel AI-integrated, label-free tissue analysis system, achieving high accuracy in tumor identification and classification. | EIC Transition | € 2.441.979 | 2022 | Details |
Enabling the transition to 3D digital pathology
3DPATH aims to develop a clinically viable 3D tissue scanner using advanced light-sheet fluorescence microscopy to enhance histopathology accuracy and improve patient care globally.
Multimodal Hypersprectal Imaging and Raman Spectroscopy for Intraoperative Assessment of Breast Tumor Resection Margins
Spectra-BREAST aims to enhance tumor margin assessment in breast conserving surgery using a novel multimodal approach for real-time, accurate feedback, improving patient outcomes and reducing reoperation rates.
Hybrid endoscope for esophageal in vivo histology and histochemistry
ESOHISTO aims to revolutionize GI cancer diagnosis through innovative endoscopic technologies that enable real-time 3D imaging of diseased tissues, enhancing early detection and treatment.
ulTRafast hOlograPHic FTIR microscopY
TROPHY combines advanced microscopy techniques to enable rapid, high-resolution imaging of tumor biopsies for precise diagnosis and tailored cancer therapies, enhancing patient outcomes.
Chemometric histopathology via coherent Raman imaging for precision medicine
The CHARM project aims to revolutionize cancer diagnosis with a novel AI-integrated, label-free tissue analysis system, achieving high accuracy in tumor identification and classification.