ArticleSensors (Basel, Switzerland)2018
An Intraoperative Visualization System Using Hyperspectral Imaging to Aid in Brain Tumor Delineation.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07036783 (Multimodal Data Collection for the Development and Validation of the STRATUM Tool to Assist Surgery in Patients Affected by Brain Tumours), which is not on this map. Cited by 48 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Multimodal Data Collection for the Development and Validation of the STRATUM Tool to Assist Surgery in Patients Affected by Brain Tumours: Observational Study
Who cites it
48 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Medical hyperspectral imaging: an updated review of technology advancements and biomedical applications.Journal of biomedical optics · 2026Pooled it
- Hyperspectral imaging for tumor resection guidance in surgery: a systematic review of preclinical and clinical studies.Journal of biomedical optics · 2025Pooled it
- High-to-Low Spectral Mapping for Cross-System Feature Adaptation in Medical Hyperspectral Imaging.Bioengineering (Basel, Switzerland) · 2026Article
- Precise delineation of glioma margins in hyperspectral images using cross-channel spectral feature fusion.Biomedical optics express · 2026Article
- Article
- Artificial Intelligence in the Diagnosis and Treatment of Brain Gliomas.Biomedicines · 2025Review
- SLIMBRAIN database: A multimodal image database of in vivo human brains for tumour detection.Scientific data · 2025Article
- Hyperspectral imaging in neurosurgery: a review of systems, computational methods, and clinical applications.Journal of biomedical optics · 2025Review
- Advancements in real-time oncology diagnosis: harnessing AI and image fusion techniques.Frontiers in oncology · 2025Review
- Spectral analysis comparison of pushbroom and snapshot hyperspectral cameras forJournal of biomedical optics · 2024Article
- The LMIT: Light-mediated minimally-invasive theranostics in oncology.Theranostics · 2024Review
- A Review of Recent Advances in Computer-Aided Detection Methods Using Hyperspectral Imaging Engineering to Detect Skin Cancer.Cancers · 2023Review
- Hyperspectral imaging benchmark based on machine learning for intraoperative brain tumour detection.NPJ precision oncology · 2023Article
- Letter concerning "Novel intra-operative strategies for enhancing tumour control: Future directions".Neuro-oncology · 2023Article
- Impact of Pre- and Post-Processing Steps for Supervised Classification of Colorectal Cancer in Hyperspectral Images.Cancers · 2023Article
- Circulating Biomarkers for the Early Diagnosis and Management of Hepatocellular Carcinoma with Potential Application in Resource-Limited Settings.Diagnostics (Basel, Switzerland) · 2023Review
- Effects of dimension reduction of hyperspectral images in skin gross pathology.Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) · 2023Article
- Lightfield hyperspectral imaging in neuro-oncology surgery: an IDEAL 0 and 1 study.Frontiers in neuroscience · 2023Article
- Evaluation of Preprocessing Methods on Independent Medical Hyperspectral Databases to Improve Analysis.Sensors (Basel, Switzerland) · 2022Article
- The diagnostic accuracy of intraoperative differentiation and delineation techniques in brain tumours.Discover oncology · 2022Review
Corrections and comments
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Authors and funding
23 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hyperspectral imaging (HSI) allows for the acquisition of large numbers of spectral bands throughout the electromagnetic spectrum (within and beyond the visual range) with respect to the surface of scenes captured by sensors. Using this information and a set of complex classification algorithms, it is possible to determine which material or substance is located in each pixel. The work presented in this paper aims to exploit the characteristics of HSI to develop a demonstrator capable of delineating tumor tissue from brain tissue during neurosurgical operations. Improved delineation of tumor boundaries is expected to improve the results of surgery. The developed demonstrator is composed of two hyperspectral cameras covering a spectral range of 400-1700 nm. Furthermore, a hardware accelerator connected to a control unit is used to speed up the hyperspectral brain cancer detection algorithm to achieve processing during the time of surgery. A labeled dataset comprised of more than 300,000 spectral signatures is used as the training dataset for the supervised stage of the classification algorithm. In this preliminary study, thematic maps obtained from a validation database of seven hyperspectral images of in vivo brain tissue captured and processed during neurosurgical operations demonstrate that the system is able to discriminate between normal and tumor tissue in the brain. The results can be provided during the surgical procedure (~1 min), making it a practical system for neurosurgeons to use in the near future to improve excision and potentially improve patient outcomes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.