Discrimination of fresh frozen non-tumour and tumour brain tissue using spectrochemical analyses and a classification model

Danielle Bury, Camilo L.M. Morais, Francis L. Martin, Kássio M. G. Lima, Katherine M. Ashton, Matthew J. Baker, Timothy P. Dawson

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)
1 Downloads (Pure)


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 languageEnglish
JournalBritish Journal of Neurosurgery
Early online date23 Oct 2019
Publication statusE-pub ahead of print - 23 Oct 2019


  • brain tumours
  • classification model
  • intraoperative diagnosis
  • neurosurgery
  • spectrochemical analyses

Cite this