Abstract
Introduction: In order for brain tumours to be successfully treated, maximal resection is beneficial. A method to detect infiltrative tumour edges intraoperatively, improving on current methods would be clinically useful. Vibrational spectroscopy offers the potential to provide a handheld, reagent-free method for tumour detection. Purpose: This study was designed to determine the ability of both Raman and Fourier-transform infrared (FTIR) spectroscopy towards differentiating between normal brain tissue, glioma or meningioma. Method: Unfixed brain tissue, which had previously only been frozen, comprising normal, glioma or meningioma tissue was placed onto calcium fluoride slides for analysis using Raman and attenuated total reflection (ATR)-FTIR spectroscopy. Matched haematoxylin and eosin slides were used to confirm tumour areas. Analyses were then conducted to generate a classification model. Results: This study demonstrates the ability of both Raman and ATR-FTIR spectroscopy to discriminate tumour from non-tumour fresh frozen brain tissue with 94% and 97.2% of cases correctly classified, with sensitivities of 98.8% and 100%, respectively. This decreases when spectroscopy is used to determine tumour type. Conclusion: The study demonstrates the ability of both Raman and ATR-FTIR spectroscopy to detect tumour tissue from non-tumour brain tissue with a high degree of accuracy. This demonstrates the ability of spectroscopy when targeted for a cancer diagnosis. However, further improvement would be required for a classification model to determine tumour type using this technology, in order to make this tool clinically viable.
Original language | English |
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Journal | British Journal of Neurosurgery |
Early online date | 23 Oct 2019 |
DOIs | |
Publication status | E-pub ahead of print - 23 Oct 2019 |
Keywords
- brain tumours
- classification model
- intraoperative diagnosis
- neurosurgery
- spectrochemical analyses
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Data for: "Discrimination of fresh frozen non-tumour and tumour brain tissue using spectrochemical analyses and a classification model"
Bury, D. (Creator), Morais, C. L. M. (Creator), Martin, F. L. (Creator), Lima, K. M. G. (Contributor), Ashton, K. M. (Creator), Baker, M. J. (Creator) & Dawson, T. P. (Creator), figshare, 16 Mar 2023
DOI: 10.6084/m9.figshare.10028438.v1
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