Low Grade Glioma of BrainHSI-LGG-2019NCT04859725
HyperSpectral Imaging in Low Grade Glioma
A study testing Hyperspectral Imaging with Snapscan camera in people with Low Grade Glioma of Brain, run by Universitaire Ziekenhuizen KU Leuven at 1 site in Belgium.
Trial summary
Low grade glioma (LGG) is a slowly evolving, highly invasive intrinsic brain tumor displaying only subtle tissue differences with the normal surrounding brain, hampering the attempts to visually discriminate tumor from normal brain, especially at the border interface. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Low Grade Glioma of Brain
- What is being tested?
- Hyperspectral Imaging with Snapscan camera
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 10 participants
- Where
- 1 siteBelgium
- Study dates
- 31 May 2021to 30 Jun 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Age ≥ 18 years
- Radiologically suspected low grade glioma (newly diagnosed or recurrent)
- Scheduled for tumor resection at UZ Leuven
- Signed informed consent document prior to resection
Who cannot join
- Children with age < 18 years
- If final pathology reveals other pathological diagnosis than low grade glioma, datacubes will not be included in the final analysis
Trial locations and contacts
1 site in 1 country.
About this study
Official title: Validation of Label-free, Wide-field, Real-time Intra-operative Tissue Discrimination and Tumor Detection of Low Grade Glioma Using a Hyperspectral Imaging (HSI) Sensor/Camera Integrated in the Operative Microscope
Low grade glioma (LGG) is a slowly evolving, highly invasive intrinsic brain tumor displaying only subtle tissue differences with the normal surrounding brain, hampering the attempts to visually discriminate tumor from normal brain, especially at the border interface. This makes anatomical borders hard to define during early maximal resection, which is the initial treatment strategy. Therefore, innovative, robust and easy-to-use real-time strategies for intra-operative detection and discrimination of (residual) LGG tumor tissue would strongly influence on-site, surgical decision making, enabling a maximal extent of resection.
To validate this approach hyperspectral imaging (HSI) - using a SnapScan HSI-Camera (IMEC), stably mounted on an OPMI Pentero 900 microscope (Zeiss) - will be used to generate spectral imaging data patterns that discriminate in vivo low grade glioma tissue from normal brain both on the cortical and subcortical level.
Read the detailed description
Included patients will undergo a resection of the low grade glioma as standard-of-care. Before, during and after the resection, HSI data ('datacubes') will be acquired by the SnapScan HSI camera on the microscope of all relevant areas of the exposed cortical surface and subcortical cavity walls. The exact points of which the datacubes will be acquired are defined by unequivocal single points on the neuronavigational system (Brainlab). From the points from which the datacubes have been obtained a corresponding tissue sample will be obtained (labeled biopsy) if tumor tissue is to be expected in that particular point, based on the current standard of care assessments intraoperatively using white light illumination on the microscope, intraoperative navigation and intraoperative ultrasound. As such, normally looking brain in the resection cavity wall, will only be biopsied if tumor free margins should be proven as part of the standard-of-care operative procedure (non-critically eloquent brain regions). The objective of this all is to get an initial high quality in vivo dataset to start exploring the potential of the technology.
The project will follow a 'stop and go' design: during the first 9 months, the initially collected spectrally corrected datacubes will be analyzed using machine learning on coded data sets. After this initial phase, an interim analysis will be made from the full list of analyzed datacubes. If a reliable and robust discriminative signal can be detected in low grade glioma tissue, segregating these signals from those in normal tissue (as defined pathologically and/or radiologically), efficacy is demonstrated (proof of concept) and the trial will go on for further collecting of samples in the following 26 months. Within the expanded dataset, the different spectral data patterns will be translated into user's friendly pattern codes for rapid real-time, on-site detection and interpretation through development of dedicated software. If no reliable signal can be retrieved from low grade glioma tissue in vivo during the surgery, further recruitment of patients will be stopped. At that time, the investigators and partners will decide on whether or not relevant amendments to the study will be proposed or not.
- Conditions
- Low Grade Glioma of Brain
- Being tested
- Hyperspectral Imaging with Snapscan camera
- Keywords
- Hyperspectral imaging, Low grade glioma, Tissue discrimination
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Hyperspectral Imaging with Snapscan cameraDevice
Before, during and after the resection, HSI data ('datacubes') will be acquired by the SnapScan camera of all relevant areas of the exposed cortical surface and subcortical cavity walls. The exact points of which the datacubes will be acquired are defined by unequivocal single points on the routinely used neuronavigational system. From the points from which the datacubes have been obtained a corresponding tissue sample will be obtained (labeled biopsy) if tumor tissue is to be expected in that particular point, based on the current standard of care assessments intraoperatively using white light illumination on the microscope, intraoperative navigation and intraoperative ultrasound. As such, normally looking brain in the resection cavity wall, will only be biopsied if tumor free margins should be proven as part of the standard-of-care operative procedure (non-critically eloquent brain regions).
| Study group | Role | What they receive |
|---|---|---|
| Hyperspectral Imaging with Snapscan camera | Experimental | Included patients will undergo a resection of the low grade glioma as standard-of-care. Hyperspectral imaging data will be acquired by the SnapScan HSI camera mounted on the (standard) surgical microscope.
As such, the surgical procedure does not deviate from the common, standard-of-care surgical procedures, apart from the acquisition of intraoperative scanning images using the SnapScan HSI camera on the microscope. The objective of this all is to get an initial high quality in vivo dataset to start exploring the potential of the technology. Receives: Device: Hyperspectral Imaging with Snapscan camera |
What is being measured
The primary outcome is the main question the study is designed to answer.
Comparison of hyperspectral image patterns of superficial and deep tumor tissue with patterns of normal brain
Assessment of discriminate power of HSI data between 468 and 780 nm between tumor and normal brain tissue by comparison of data acquired on imec VNIR HSI Snapscan camera and gold standard image segmentation of brain tissue.
Image segmentation of white light images acquired on the Pentero 900 surgical microscope will be performed based on the assessment of the surgeon and on histopathological assessment of biopsies taken within the standard of care procedure. A co-registration of the segmented images and will be transferred to subsequently acquired HSI data and used to statistical assess whether HSI data can be used to discriminate the spectral signatures of healthy and tumorous tissue in vivo.
Measured: During the surgical procedure
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted26 Apr 2021
- Study start31 May 2021
- Primary completion31 May 2026 (estimated)
- Study completion30 Jun 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Low Grade Glioma of BrainStudies of the same condition, open and under way.
- More trials run by Universitaire Ziekenhuizen KU LeuvenThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Device feasibility
- Allocation
- Not applicable
- Intervention model
- Single group
- Model description
- During the first 9 months, the initially collected spectrally corrected datacubes will be analyzed using machine learning. After 9 months, an interim analysis will be made on the datacubes from this primary set with an estimated 10 participants. If a reliable and robust discriminative signal can be detected in low grade glioma tissue, segregating these signals from those in normal tissue, the trial will go on collecting samples for the following 26 months with an inclusion of 10 to 15 participant per year. Within the expanded dataset, the different spectral data patterns will be translated into user's friendly pattern codes for rapid real-time, on-site detection and interpretation through development of dedicated software. If no reliable signal can be retrieved from low grade glioma tissue in vivo during the surgery, further recruitment of patients will be stopped. At that time, a decision will be taken on whether or not relevant amendments to the study will be proposed.
- Masking
- None (open label)
- Enrolment
- 10 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Universitaire Ziekenhuizen KU Leuven
- Sponsor type
- University, hospital or other
- Collaborators
- Imec, Carl Zeiss Meditec AG
- Responsible party
- Principal investigator, Prof. Dr. Steven De Vleeschouwer, Universitaire Ziekenhuizen KU Leuven
- Investigators
- Steven De Vleeschouwer, MD, PhD, Principal investigator, UZ Leuven
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT04859725
- Sponsor's protocol ID
- S63174
- Acronym
- HSI-LGG-2019
- Status last verified
- May 2026
- First submitted
- 2 Apr 2021
- Last updated
- 15 May 2026
- Results posted
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 15 May 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Validation of Label-free, Wide-field, Real-time Intra-operative Tissue Discrimination and Tumor Detection of Low Grade Glioma Using a Hyperspectral Imaging (HSI) Sensor/Camera Integrated in the Operative Microscope
- ClinicalTrials.gov ID
- NCT04859725
- Acronym / sponsor ID
- HSI-LGG-2019 / S63174
- Conditions
- Low Grade Glioma of Brain
- Keywords
- Hyperspectral imaging, Low grade glioma, Tissue discrimination
- Study type
- Interventional
- Recruitment status
- Active, not recruiting
- Enrolment
- 10 participants (estimated)
- Lead sponsor
- Universitaire Ziekenhuizen KU LeuvenUniversity, hospital or other
- Collaborators
- Imec, Carl Zeiss Meditec AG
- Study start
- 31 May 2021 (actual)
- Primary completion
- 31 May 2026 (estimated)
- Study completion
- 30 Jun 2026 (estimated)
- First posted
- 26 Apr 2021 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
Low grade glioma (LGG) is a slowly evolving, highly invasive intrinsic brain tumor displaying only subtle tissue differences with the normal surrounding brain, hampering the attempts to visually discriminate tumor from normal brain, especially at the border interface. This makes anatomical borders hard to define during early maximal resection, which is the initial treatment strategy. Therefore, innovative, robust and easy-to-use real-time strategies for intra-operative detection and discrimination of (residual) LGG tumor tissue would strongly influence on-site, surgical decision making, enabling a maximal extent of resection.
To validate this approach hyperspectral imaging (HSI) - using a SnapScan HSI-Camera (IMEC), stably mounted on an OPMI Pentero 900 microscope (Zeiss) - will be used to generate spectral imaging data patterns that discriminate in vivo low grade glioma tissue from normal brain both on the cortical and subcortical level.
Detailed description
Included patients will undergo a resection of the low grade glioma as standard-of-care. Before, during and after the resection, HSI data ('datacubes') will be acquired by the SnapScan HSI camera on the microscope of all relevant areas of the exposed cortical surface and subcortical cavity walls. The exact points of which the datacubes will be acquired are defined by unequivocal single points on the neuronavigational system (Brainlab). From the points from which the datacubes have been obtained a corresponding tissue sample will be obtained (labeled biopsy) if tumor tissue is to be expected in that particular point, based on the current standard of care assessments intraoperatively using white light illumination on the microscope, intraoperative navigation and intraoperative ultrasound. As such, normally looking brain in the resection cavity wall, will only be biopsied if tumor free margins should be proven as part of the standard-of-care operative procedure (non-critically eloquent brain regions). The objective of this all is to get an initial high quality in vivo dataset to start exploring the potential of the technology.
The project will follow a 'stop and go' design: during the first 9 months, the initially collected spectrally corrected datacubes will be analyzed using machine learning on coded data sets. After this initial phase, an interim analysis will be made from the full list of analyzed datacubes. If a reliable and robust discriminative signal can be detected in low grade glioma tissue, segregating these signals from those in normal tissue (as defined pathologically and/or radiologically), efficacy is demonstrated (proof of concept) and the trial will go on for further collecting of samples in the following 26 months. Within the expanded dataset, the different spectral data patterns will be translated into user's friendly pattern codes for rapid real-time, on-site detection and interpretation through development of dedicated software. If no reliable signal can be retrieved from low grade glioma tissue in vivo during the surgery, further recruitment of patients will be stopped. At that time, the investigators and partners will decide on whether or not relevant amendments to the study will be proposed or not.
Study design
- Primary purpose
- Device feasibility
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
- Model description
- During the first 9 months, the initially collected spectrally corrected datacubes will be analyzed using machine learning. After 9 months, an interim analysis will be made on the datacubes from this primary set with an estimated 10 participants. If a reliable and robust discriminative signal can be detected in low grade glioma tissue, segregating these signals from those in normal tissue, the trial will go on collecting samples for the following 26 months with an inclusion of 10 to 15 participant per year. Within the expanded dataset, the different spectral data patterns will be translated into user's friendly pattern codes for rapid real-time, on-site detection and interpretation through development of dedicated software. If no reliable signal can be retrieved from low grade glioma tissue in vivo during the surgery, further recruitment of patients will be stopped. At that time, a decision will be taken on whether or not relevant amendments to the study will be proposed.
| Arm | Type | Receives |
|---|---|---|
| Hyperspectral Imaging with Snapscan camera | Experimental | Device: Hyperspectral Imaging with Snapscan cameraIncluded patients will undergo a resection of the low grade glioma as standard-of-care. Hyperspectral imaging data will be acquired by the SnapScan HSI camera mounted on the (standard) surgical microscope. As such, the surgical procedure does not deviate from the common, standard-of-care surgical procedures, apart from the acquisition of intraoperative scanning images using the SnapScan HSI camera on the microscope. The objective of this all is to get an initial high quality in vivo dataset to start exploring the potential of the technology. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (4 listed)
- Age ≥ 18 years
- Radiologically suspected low grade glioma (newly diagnosed or recurrent)
- Scheduled for tumor resection at UZ Leuven
- Signed informed consent document prior to resection
Key exclusion criteria (2 listed)
- Children with age < 18 years
- If final pathology reveals other pathological diagnosis than low grade glioma, datacubes will not be included in the final analysis
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Hyperspectral Imaging with Snapscan cameraBefore, during and after the resection, HSI data ('datacubes') will be acquired by the SnapScan camera of all relevant areas of the exposed cortical surface and subcortical cavity walls. The exact points of which the datacubes will be acquired are defined by unequivocal single points on the routinely used neuronavigational system. From the points from which the datacubes have been obtained a corresponding tissue sample will be obtained (labeled biopsy) if tumor tissue is to be expected in that particular point, based on the current standard of care assessments intraoperatively using white light illumination on the microscope, intraoperative navigation and intraoperative ultrasound. As such, normally looking brain in the resection cavity wall, will only be biopsied if tumor free margins should be proven as part of the standard-of-care operative procedure (non-critically eloquent brain regions). | Device | Hyperspectral Imaging with Snapscan camera |
Primary outcome
Comparison of hyperspectral image patterns of superficial and deep tumor tissue with patterns of normal brain
Time frame: During the surgical procedure
Assessment of discriminate power of HSI data between 468 and 780 nm between tumor and normal brain tissue by comparison of data acquired on imec VNIR HSI Snapscan camera and gold standard image segmentation of brain tissue. Image segmentation of white light images acquired on the Pentero 900 surgical microscope will be performed based on the assessment of the surgeon and on histopathological assessment of biopsies taken within the standard of care procedure. A co-registration of the segmented images and will be transferred to subsequently acquired HSI data and used to statistical assess whether HSI data can be used to discriminate the spectral signatures of healthy and tumorous tissue in vivo.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 15 May 2026.
- Individual participant dataSharing planned: No
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Low-grade Glioma
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Steven De Vleeschouwer, MD, PhD principal investigator
UZ Leuven
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Hyperspectral Imaging with Snapscan camera in people with Low Grade Glioma of Brain, run by Universitaire Ziekenhuizen KU Leuven at 1 site in Belgium.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: under way, not looking for participants, as of the sponsor's last update on 15 May 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Belgium. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Comparison of hyperspectral image patterns of superficial and deep tumor tissue with patterns of normal brain (time frame: During the surgical procedure). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 15 May 2026.