In vivo brain tumor classification using fiber endoscopy

J. Dremel; T. Wang; S. Richter; O. Uckermann; W. Polanski; I. Eyüpoglu; J. Czarske; R. Kuschmierz

doi:10.1117/12.3003265

12 March 2024 In vivo brain tumor classification using fiber endoscopy

J. Dremel, T. Wang, S. Richter, O. Uckermann, W. Polanski, I. Eyüpoglu, J. Czarske, R. Kuschmierz

Proceedings Volume 12831, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XXII; 1283102 (2024) https://doi.org/10.1117/12.3003265
Event: SPIE BiOS, 2024, San Francisco, California, United States

Abstract

The classification of brain tissue plays a key role in brain tumor diagnosis and treatment. It revolves around post-surgical histochemical staining, which is often time consuming and delays follow up treatment. Identifying tumor boarders during tumor resection is essential for an efficient therapy minimizing removed healthy tissue and maximizing removed tumor tissue. The different approaches in use are either expensive and time consuming or limited to certain tumor types. We propose a real-time in vivo label free classification approach, applicable for both demands. Based on autofluorescence properties, a label-free differentiation between tissue types is possible. Therefore, a multicore fiber (MCF) based endoscope is designed to fit into biopsy needles used during diagnosis and to be used as a handheld probe during tumor resection. It allows illuminating and imaging through the same MCF, minimizing the endoscope to a submillimeter diameter. Currently, autofluorescence images are not used in pathology. Thus, medical doctors cannot interpret them. We use a neural network for diagnosis, bridging this gap. One problem with neural networks in medical applications is data availability for training. Different techniques are investigated to maximize the classification performance with a limited training dataset. Cascaded neural networks in combination with digital twins improve the results while lowering the needed training dataset size. The preliminary data indicates that our technology might lead to a paradigm shift in brain tumor diagnosis and therapy due to the accurate result, the versatile design, and being low-cost.

Conference Presentation

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

J. Dremel, T. Wang, S. Richter, O. Uckermann, W. Polanski, I. Eyüpoglu, J. Czarske, and R. Kuschmierz "In vivo brain tumor classification using fiber endoscopy", Proc. SPIE 12831, Advanced Biomedical and Clinical Diagnostic and Surgical Guidance Systems XXII, 1283102 (12 March 2024); https://doi.org/10.1117/12.3003265

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