ArticleFrontiers in oncology2021
Deep Neural Network for Differentiation of Brain Tumor Tissue Displayed by Confocal Laser Endomicroscopy.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Fluorescein-stained confocal laser endomicroscopy versus conventional frozen section for intraoperative histopathological assessment of intracranial tumors.Neuro-oncology · 2024Trial
- AI Augmented Confocal Laser Endomicroscopy for Rapid Intraoperative Diagnosis of Brain Tumors.NPJ digital medicine · 2026Article
- Real-time intraoperative confocal laser endomicroscopy with on-site neuropathologist consultation for glioma margin assessment: illustrative case.Journal of neurosurgery. Case lessons · 2026Article
- Envisioning the Future of the Neurosurgical Operating Room with the Concept of the Medical Metaverse.Journal of Korean Neurosurgical Society · 2025Article
- Artificial intelligence prediction of nonenhancing brain tumor malignancy based onFrontiers in surgery · 2025Article
- Clinical application of confocal laser endomicroscopy in neurosurgery: a scoping review.Frontiers in surgery · 2025Review
- Advancement of fluorescent aminopeptidase probes for rapid cancer detection-current uses and neurosurgical applications.Frontiers in surgery · 2024Review
- Machine learning in neuro-oncology: toward novel development fields.Journal of neuro-oncology · 2022Review
- Seasonal variations of serotonin in the visual system of an ant revealed by immunofluorescence and a machine learning approach.Royal Society open science · 2022Article
- Neuroinflammation and immunoregulation in glioblastoma and brain metastases: Recent developments in imaging approaches.Clinical and experimental immunology · 2021Review
- Socio-Organizational Impact of Confocal Laser Endomicroscopy in Neurosurgery and Neuropathology: Results from a Process Analysis and Expert Survey.Diagnostics (Basel, Switzerland) · 2021Article
- Use of neuroendoscopy in metastatic brain tumours: A systematic review.Medicine internationalArticle
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Authors and funding
7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundReliable on site classification of resected tumor specimens remains a challenge. Implementation of high-resolution confocal laser endoscopic techniques (CLEs) during fluorescence-guided brain tumor surgery is a new tool for intraoperative tumor tissue visualization. To overcome observer dependent errors, we aimed to predict tumor type by applying a deep learning model to image data obtained by CLE.
methodsHuman brain tumor specimens from 25 patients with brain metastasis, glioblastoma, and meningioma were evaluated within this study. In addition to routine histopathological analysis, tissue samples were stained with fluorescein
resultsMultiple CLE images were obtained from each specimen with a total number of 13,972 fluorescein based images. Test accuracy of 90.9% was achieved after applying a two-class prediction for glioblastomas and brain metastases with an area under the curve (AUC) value of 0.92. For three class predictions, our model achieved a ratio of correct predicted label of 85.8% in the test set, which was confirmed with five-fold cross validation, without definition of confidence. Applying a confidence rate of 0.999 increased the prediction accuracy to 98.6% when images with substantial artifacts were excluded before the analysis. 36.3% of total images met the output criteria.
conclusionsWe trained a residual network model that allows automated, on site analysis of resected tumor specimens based on CLE image datasets. Further
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