Discrimination of fresh frozen non-tumour and tumour brain tissue using spectrochemical analyses and a classification model.
Danielle BuryCamilo de Lelis Medeiros de MoraisFrancis Luke MartinKássio M G LimaKatherine M AshtonMatthew J BakerTimothy P DawsonPublished in: British journal of neurosurgery (2019)
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.
Keyphrases
- high resolution
- single molecule
- resting state
- white matter
- machine learning
- deep learning
- solid state
- squamous cell carcinoma
- functional connectivity
- magnetic resonance imaging
- cerebral ischemia
- dna damage response
- dna damage
- magnetic resonance
- multiple sclerosis
- computed tomography
- drug delivery
- oxidative stress
- climate change
- dna repair
- contrast enhanced