Machine Learning-Assisted Classification of Paraffin-Embedded Brain Tumors with Raman Spectroscopy
Abstract
1. Introduction
2. Materials and Methods
2.1. Patient Data
2.2. Sample Preparation
2.3. Data Acquisition and Raman Spectroscopy
2.4. Machine Learning
3. Results
3.1. Multi-Class Classification for Discrimination of Tumor Origin
3.2. A Practical Approach: Carcinoma Metastases and Glioma Classifier
3.3. A Practical Approach: Classification of Tumor Necrosis
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Tumor Group/ Tumor Type | Number of Cases n = 82 | Number of Measurements n = 679 |
---|---|---|
Astrocytoma of grades 2,3, IDH mutant | 9 | 74 |
Oligodendroglioma of grades 2,3, 1p19q co-deleted | 7 | 60 |
Ependymoma | 5 | 44 |
Glioblastoma, IDH wildtype | 27 | 179 |
Meningothelial meningioma | 4 | 36 |
Transitional meningioma | 6 | 56 |
Breast carcinoma metastases | 8 | 53 |
Colorectal carcinoma metastases | 6 | 65 |
Non-small cell lung carcinoma (NSCLC) metastases | 10 | 112 |
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Klamminger, G.G.; Mombaerts, L.; Kemp, F.; Jelke, F.; Klein, K.; Slimani, R.; Mirizzi, G.; Husch, A.; Hertel, F.; Mittelbronn, M.; et al. Machine Learning-Assisted Classification of Paraffin-Embedded Brain Tumors with Raman Spectroscopy. Brain Sci. 2024, 14, 301. https://doi.org/10.3390/brainsci14040301
Klamminger GG, Mombaerts L, Kemp F, Jelke F, Klein K, Slimani R, Mirizzi G, Husch A, Hertel F, Mittelbronn M, et al. Machine Learning-Assisted Classification of Paraffin-Embedded Brain Tumors with Raman Spectroscopy. Brain Sciences. 2024; 14(4):301. https://doi.org/10.3390/brainsci14040301
Chicago/Turabian StyleKlamminger, Gilbert Georg, Laurent Mombaerts, Françoise Kemp, Finn Jelke, Karoline Klein, Rédouane Slimani, Giulia Mirizzi, Andreas Husch, Frank Hertel, Michel Mittelbronn, and et al. 2024. "Machine Learning-Assisted Classification of Paraffin-Embedded Brain Tumors with Raman Spectroscopy" Brain Sciences 14, no. 4: 301. https://doi.org/10.3390/brainsci14040301
APA StyleKlamminger, G. G., Mombaerts, L., Kemp, F., Jelke, F., Klein, K., Slimani, R., Mirizzi, G., Husch, A., Hertel, F., Mittelbronn, M., & Kleine Borgmann, F. B. (2024). Machine Learning-Assisted Classification of Paraffin-Embedded Brain Tumors with Raman Spectroscopy. Brain Sciences, 14(4), 301. https://doi.org/10.3390/brainsci14040301