Periodic Reporting for period 2 - HyperProbe (Transforming brain surgery by advancing functional-guided neuronavigational imaging)
Reporting period: 2023-10-01 to 2025-01-31
The HyperProbe project aims to revolutionize neuronavigation in brain surgery by introducing a hyperspectral imaging approach for real-time quantitative assessment of cerebral tissue. This technology is designed to assist neurosurgeons in both optimizing the delineation of pathological areas compared to healthy tissue and identifying the functional borders around a specific lesion. In neurosurgery - particularly in the resection of gliomas and glioblastomas - it is crucial to distinguish between tumor and healthy brain tissue while preserving essential cerebral functions. Current neuronavigation approaches rely on brain mapping techniques, which involve brain stimulation to localize, identify, and assess cortical and subcortical functions. Various paradigms are employed intraoperatively, depending on the targeted brain regions. These include cognitive tasks in awake patients (e.g. for speech and visual functions) and electro-stimulation (e.g. for sensory and motor functions). Electrical stimulation can be performed through direct transcortical and/or subcortical stimulation with probes, as well as indirect stimulation via electrodes to monitor muscular responses. However, all these approaches have limitations, including varying degrees of invasiveness, lack of real-time quantitative data, and limited specificity and sensitivity.
Current imaging techniques used in neurosurgery also present several constraints. Some rely on static, preoperative assessments (e.g. MRI, PET-CT), while intraoperative modalities, such as fluorescence imaging, are primarily used for tumor visualization rather than functional assessment. In particular, fluorescence molecules help to identify the tumor by selectively accumulating a fluorescent molecule in tumor cells, which emit fluorescence under specific illumination. While this technique enhances tumor visualization with high specificity, it lacks sensitivity for detecting tumor infiltration and is not effective for low-grade gliomas. Therefore, it is inaccurate to state that fluorescence imaging has low specificity for cerebral functions, as it does not assess brain function at all.
Addressing these limitations requires advancements in clinical practice toward a functionally guided neuronavigation approach that provides neurosurgeons with real-time, quantitative, and accurate intraoperative information. The HyperProbe project will design, develop, and clinically validate a novel, all-optical, multifunctional imaging device capable of providing comprehensive characterization of cerebral tissue during surgery. This device will offer neurosurgeons unprecedented structural, pathological, and functional insights to enhance patient outcomes in neurosurgical procedures.
The project has the following objectives, all contributing to the goal of a novel device to transform neuronavigation during brain surgery and cortical activity stimulation:
1) Development of the hyperspectral imaging system - the HyperProbe (HP) - to map, monitor, and quantify biochemical compounds in brain tissue during neurosurgery and cortical activity stimulation.
2) Upgrading HP to a portable, cost-effective prototype suitable for use in operating rooms.
3) Characterization and validation of HP on optically-realistic brain tissue phantoms.
4) Development of artificial intelligence-based algorithms to identify biomarkers of brain activity for in vivo imaging with HP during brain surgery and cortical activity stimulation.
5) Clinically validating HP against existing surgical imaging techniques like fMRI.
6) Conduction of feasibility studies on the performances of the HP on patients during glioma surgery and multiple paradigms of stimulation of brain activity, as part of observational, proof-of-concept analysis.
The scientific objectives of the project are: (i) multi-disciplinary, merging engineering, physics, computer science, neurology, and neurosurgery; (ii) translational, transforming laboratory-based devices and technology into clinical instrumentation that can be used during brain surgery and in vivo cortical activity stimulation, and (iii) ground-breaking, with aiming to improve patient and surgical outcomes.
Current imaging techniques used in neurosurgery also present several constraints. Some rely on static, preoperative assessments (e.g. MRI, PET-CT), while intraoperative modalities, such as fluorescence imaging, are primarily used for tumor visualization rather than functional assessment. In particular, fluorescence molecules help to identify the tumor by selectively accumulating a fluorescent molecule in tumor cells, which emit fluorescence under specific illumination. While this technique enhances tumor visualization with high specificity, it lacks sensitivity for detecting tumor infiltration and is not effective for low-grade gliomas. Therefore, it is inaccurate to state that fluorescence imaging has low specificity for cerebral functions, as it does not assess brain function at all.
Addressing these limitations requires advancements in clinical practice toward a functionally guided neuronavigation approach that provides neurosurgeons with real-time, quantitative, and accurate intraoperative information. The HyperProbe project will design, develop, and clinically validate a novel, all-optical, multifunctional imaging device capable of providing comprehensive characterization of cerebral tissue during surgery. This device will offer neurosurgeons unprecedented structural, pathological, and functional insights to enhance patient outcomes in neurosurgical procedures.
The project has the following objectives, all contributing to the goal of a novel device to transform neuronavigation during brain surgery and cortical activity stimulation:
1) Development of the hyperspectral imaging system - the HyperProbe (HP) - to map, monitor, and quantify biochemical compounds in brain tissue during neurosurgery and cortical activity stimulation.
2) Upgrading HP to a portable, cost-effective prototype suitable for use in operating rooms.
3) Characterization and validation of HP on optically-realistic brain tissue phantoms.
4) Development of artificial intelligence-based algorithms to identify biomarkers of brain activity for in vivo imaging with HP during brain surgery and cortical activity stimulation.
5) Clinically validating HP against existing surgical imaging techniques like fMRI.
6) Conduction of feasibility studies on the performances of the HP on patients during glioma surgery and multiple paradigms of stimulation of brain activity, as part of observational, proof-of-concept analysis.
The scientific objectives of the project are: (i) multi-disciplinary, merging engineering, physics, computer science, neurology, and neurosurgery; (ii) translational, transforming laboratory-based devices and technology into clinical instrumentation that can be used during brain surgery and in vivo cortical activity stimulation, and (iii) ground-breaking, with aiming to improve patient and surgical outcomes.
During the last two years, the HP consortium developed its second prototype, HyperProbe1.1 (HP1.1) optimizing key parameters for the final clinical device. A comprehensive characterization of HP1 and HP1.1 was conducted, evaluating and comparing signal-to-noise ratios (SNR), emitted power, resolution, sensitivity, and reproducibility of both systems. Compared to its predecessor, HP1.1 features an extended spectral range (385–1015 nm), improved SNR, a larger field of view (~1 cm), customizable parameters and enhanced stability. Initial validation of HP1.1 was performed on plastic phantoms with varying absorption and scattering properties, followed by successful tests on fresh surgical biopsies. These experiments yielded promising results in identifying novel biomarkers for differentiating high- and low-grade gliomas as well as meningiomas.
The insights gained from HP1.1 testing allowed the HP consortium to define key requirements for the next-generation device, designed for functional imaging and tumor grading in clinics. This prototype will incorporate a high-speed, multi-wavelength LED-based system (visible-NIR) coupled with a high-resolution cMOS camera and custom achromatic lenses to minimize distortions. The system will ensure real-time multi-spectral image acquisition and processing while adhering to medical device standards, featuring robotic-assisted positioning and full sterilization compatibility for surgical use.
Furthermore, a digital phantom for simulating the optical properties of brain tissue and the implementation of hyperspectral imaging in silico has been successfully created and tested. This provides an important metrological tool for the validation and optimization of the technology. Ongoing work includes developing AI tools to process the hyperspectral data and validation pipelines to compare HP performances against gold standards in routine neuronavigation.
The insights gained from HP1.1 testing allowed the HP consortium to define key requirements for the next-generation device, designed for functional imaging and tumor grading in clinics. This prototype will incorporate a high-speed, multi-wavelength LED-based system (visible-NIR) coupled with a high-resolution cMOS camera and custom achromatic lenses to minimize distortions. The system will ensure real-time multi-spectral image acquisition and processing while adhering to medical device standards, featuring robotic-assisted positioning and full sterilization compatibility for surgical use.
Furthermore, a digital phantom for simulating the optical properties of brain tissue and the implementation of hyperspectral imaging in silico has been successfully created and tested. This provides an important metrological tool for the validation and optimization of the technology. Ongoing work includes developing AI tools to process the hyperspectral data and validation pipelines to compare HP performances against gold standards in routine neuronavigation.
The technological capacity developed will impact the neurosurgical field by transforming neuronavigation approaches towards functional imaging-based decision-making.This will be achieved by overcoming current limitations, particularly thanks to:
◾ Minimal invasiveness of HP by employing an all-optical, contactless, neuroimaging approach based on the illumination with non-ionizing light of the exposed brain and the measurement of the reflected and fluorescent signals from the cerebral tissues, intraoperatively;
◾ The capacity of HP to provide real-time, intraoperative information that is quantitative and highly specific to brain tissue activity and structure, via multiple biomarkers related to morpho-chemical features (such as cerebral haemodynamics, metabolism, tumour boundaries, and others);
◾ High-resolution imaging for detailed structural, physiological, and pathological insights.
◾ The cost-effectiveness, compactness, and integration capacity of HyperProbe with current neuronavigation tools in the surgical room, also designed to be transportable and easy-to-use for clinicians
◾The application of AI algorithms for image reconstruction, image segmentation and for the recognition of morpho-chemical features of interest in the targeted cerebral tissue to be delivered in augmented-reality to the clinicians, intraoperatively.
◾ Minimal invasiveness of HP by employing an all-optical, contactless, neuroimaging approach based on the illumination with non-ionizing light of the exposed brain and the measurement of the reflected and fluorescent signals from the cerebral tissues, intraoperatively;
◾ The capacity of HP to provide real-time, intraoperative information that is quantitative and highly specific to brain tissue activity and structure, via multiple biomarkers related to morpho-chemical features (such as cerebral haemodynamics, metabolism, tumour boundaries, and others);
◾ High-resolution imaging for detailed structural, physiological, and pathological insights.
◾ The cost-effectiveness, compactness, and integration capacity of HyperProbe with current neuronavigation tools in the surgical room, also designed to be transportable and easy-to-use for clinicians
◾The application of AI algorithms for image reconstruction, image segmentation and for the recognition of morpho-chemical features of interest in the targeted cerebral tissue to be delivered in augmented-reality to the clinicians, intraoperatively.