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The present study aims to investigate the potential application of multispectral analysis, hyperspectral imaging, and fluorescence during neuro-oncological procedures, specifically during brain tumour debulking / resection. These optics techniques are entirely non-invasive and consist in camera with a filter to be linked to the standard microsurgical and endoscopic instruments used in theatre. The research procedure consists of images acquisition and data processing, with virtually no additional invasive procedures to be performed on patients.
Surgical resection of brain tumours remains a challenge. While the center of a tumour is easily resectable, its margins are often fading into normal brain, and therefore quite difficult to identify. Moreover, there is now extensive literature proving that tumour cells extend way beyond visible margins of a tumour, following white matter tracts in the brain. As opposite to different organs (such as liver or kidney), resection of brain tumours beyond the visible margins is limited by the presence of eloquent/functional areas. Damages or resection of these areas will inevitably cause a permanent disability, which can be incredibly serious and impact on further treatment: a paralyzed or unconscious patient is not capable of tolerating chemotherapy or radiotherapy after surgery, both crucial complementary forms of treatment to contain the disease, in combination with surgery.
Because of these premises, the concept of "functional margins of resection" is now established in the neurosurgical community: a tumour is resected and the resection is pushed up to 1-2 cms beyond the margins or only up to the point where a functional/eloquent area is found. If the latter is the case, the functional area is obviously preserved and tumour resection is stopped. Identifying these areas is the main challenge in brain tumour surgery.
The aim of this study and its scientific justification is to refine a new, potentially more practical and quick technique to identify functional brain areas in real time. This study can serve as a benchmark study to both improve surgery of brain tumours and increase our knowledge about brain tumours and eloquent brain vascular supply. This technique can also potentially be implemented to obtain a novel technology to assess brain perfusion during neurosurgical procedures. Maintaining blood supply to healthy brain tissue is a key component of successful neuro-oncological surgery. Multispectral/hyperspectral analysis can be evaluated as a complementary tool to assess brain perfusion in real-time and prevent post-operative devastating neurological complications, such as strokes, or significantly reduce the secondary damage would these complications occurr.
The present project consists of a pilot observational study on patients diagnosed with brain tumours candidate for a neurosurgical operation.
From a practical point of view, participation in the study will only imply that some images will be acquired during surgery and processed at a later stage. The study won't impact on patients' care at any stage, nor will produce results that will be relevant for future medical records of patients enrolled. Patients will be approached about this study at the time of their first neuro-oncology clinic consultation. A member of the research team will be present at the time of the consultation and will explain in details what are the purposes and the methods of the present study.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Patients with brain tumours candidate for neurosurgery | Experimental | Patients will be recruited following the inclusion criteria: any patient with a diagnosis of brain tumour, age ranging from 18 with no upper limit, who will agree to the operation and to take part of the present study, will be enrolled. During surgery, multispectral and/or hyper spectral acquisition of images from the surgical field will be performed. Each patient will have an average acquisition of 6 datasets. As each dataset will correspond to an image, this will be divided into many reading regions (from 10 to 20) for a total of approximatively 60 measurements per patient. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Intra-operative multispectral / hyperspectral analysis | Device | During surgery, the operating surgeon will be using standard NHS neurosurgical equipment such as an endoscope and/or a microscope. This equipment is operated in exactly the same way as with any other procedure, but either the microscope or the endoscope in use will be connected to the system of camera and filters for multispectral/hyperspectral analysis. During each surgical intervention, tissue-specific spectral data will be collected at specific stages - mostly once the brain surface is exposed and at the end of the resection on the surgical cavity. The operation will be visually recorded in order to sync visual data with the spectral data obtained at the same moment in time. The video recording will not be patient identifiable and will be viewed only by members of the research team working on this project (see below). The use of video recording equipment will be included in the patient information sheet given to all patients prior to gaining consent |
| Measure | Description | Time Frame |
|---|---|---|
| Analysis of spectroscopic signal reading between brain tissue and brain tumour | Brain tissue and tumour tissue, the signals collected will be correlated both to the visual signal seen on normal operative field, a pre-set of brain images, and the signal seen on the peri-operative imaging (MRI scan). | 3 years |
| Analysis of spectroscopic signal reading between functional brain areas and non functional brain areas | The signal collected will be correlated with the neuro-physiological intra-operative findings, in every case there is an indication to do so, and with the expected location of the eloquent areas on the peri-operative images. | 3 years |
| Measure | Description | Time Frame |
|---|---|---|
| Analysis of spectroscopic signal reading of surgical field as seen at its baseline and under fluorescence-specific light | Comparison will be made between multispectral / hyper spectral acquired images, and the same images acquired with the addition of fluorescence light | 3 years |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Giulio Anichini, MD, FEBNS | Contact | 00447460946298 | g.anichini@imperial.ac.uk |
| Name | Affiliation | Role |
|---|---|---|
| Kevin O'Neill, MD, FRCS | Imperial College of London, Charing Cross Hospital | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Imperial College NHS Trust, Charing Cross Hospital | Recruiting | London | England | W68RF | United Kingdom |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 28957220 | Background | Behrooz A, Waterman P, Vasquez KO, Meganck J, Peterson JD, Faqir I, Kempner J. Multispectral open-air intraoperative fluorescence imaging. Opt Lett. 2017 Aug 1;42(15):2964-2967. doi: 10.1364/OL.42.002964. | |
| 28063974 | Background | Lu HD, Chen G, Cai J, Roe AW. Intrinsic signal optical imaging of visual brain activity: Tracking of fast cortical dynamics. Neuroimage. 2017 Mar 1;148:160-168. doi: 10.1016/j.neuroimage.2017.01.006. Epub 2017 Jan 4. |
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| Type | Date | Date Unknown |
|---|---|---|
| Release | Nov 15, 2024 | |
| Reset | Jan 8, 2025 |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP | Yes | Yes | No | Study Protocol and Statistical Analysis Plan | Dec 30, 2019 | Jan 13, 2021 | Prot_SAP_000.pdf |
| ICF | No | No | Yes | Informed Consent Form | Dec 30, 2019 | Jan 13, 2021 | ICF_001.pdf |
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| Release Date | Unrelease Date | Unrelease Date Unknown | Reset Date | MCP Release Number |
|---|---|---|---|---|
| Nov 15, 2024 | Jan 8, 2025 |
| ID | Term |
|---|---|
| D001932 | Brain Neoplasms |
| D005910 | Glioma |
| D008579 | Meningioma |
| D009442 | Neurilemmoma |
| ID | Term |
|---|---|
| D016543 | Central Nervous System Neoplasms |
| D009423 | Nervous System Neoplasms |
| D009371 | Neoplasms by Site |
| D009369 | Neoplasms |
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| ID | Term |
|---|---|
| D000081862 | Hyperspectral Imaging |
| ID | Term |
|---|---|
| D013057 | Spectrum Analysis |
| D002623 | Chemistry Techniques, Analytical |
| D008919 | Investigative Techniques |
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|
| 26309761 | Background | Fawzy Y, Lam S, Zeng H. Rapid multispectral endoscopic imaging system for near real-time mapping of the mucosa blood supply in the lung. Biomed Opt Express. 2015 Jul 21;6(8):2980-90. doi: 10.1364/BOE.6.002980. eCollection 2015 Aug 1. |
| 28149926 | Background | Zhang Y, Wirkert SJ, Iszatt J, Kenngott H, Wagner M, Mayer B, Stock C, Clancy NT, Elson DS, Maier-Hein L. Tissue classification for laparoscopic image understanding based on multispectral texture analysis. J Med Imaging (Bellingham). 2017 Jan;4(1):015001. doi: 10.1117/1.JMI.4.1.015001. Epub 2017 Jan 25. |
| D001927 |
| Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
| D018302 | Neoplasms, Neuroepithelial |
| D017599 | Neuroectodermal Tumors |
| D009373 | Neoplasms, Germ Cell and Embryonal |
| D009370 | Neoplasms by Histologic Type |
| D009375 | Neoplasms, Glandular and Epithelial |
| D009380 | Neoplasms, Nerve Tissue |
| D009383 | Neoplasms, Vascular Tissue |
| D008577 | Meningeal Neoplasms |
| D018358 | Neuroendocrine Tumors |
| D009463 | Neuroma |
| D018317 | Nerve Sheath Neoplasms |