Raman spectral cytopathology for cancer diagnostic applications.
Damien TraynorIsha BehlDeclan O'DeaFranck BonnierSiobhan NicholsonFinbar O'ConnellAoife MaguireStephen FlintSheila GalvinClaire M HealyCara M MartinJohn J O'LearyAlison MalkinHugh J ByrneFiona M LyngPublished in: Nature protocols (2021)
Raman spectroscopy can provide a rapid, label-free, nondestructive measurement of the chemical fingerprint of a sample and has shown potential for cancer screening and diagnosis. Here we report a protocol for Raman microspectroscopic analysis of different exfoliative cytology samples (cervical, oral and lung), covering sample preparation, spectral acquisition, preprocessing and data analysis. The protocol takes 2 h 20 min for sample preparation, measurement and data preprocessing and up to 8 h for a complete analysis. A key feature of the protocol is that it uses the same sample preparation procedure as commonly used in diagnostic cytology laboratories (i.e., liquid-based cytology on glass slides), ensuring compatibility with clinical workflows. Our protocol also covers methods to correct for the spectral contribution of glass and sample pretreatment methods to remove contaminants (such as blood and mucus) that can obscure spectral features in the exfoliated cells and lead to variability. The protocol establishes a standardized clinical routine allowing the collection of highly reproducible data for Raman spectral cytopathology for cancer diagnostic applications for cervical and lung cancer and for monitoring suspicious lesions for oral cancer.
Keyphrases
- fine needle aspiration
- raman spectroscopy
- optical coherence tomography
- label free
- data analysis
- papillary thyroid
- randomized controlled trial
- squamous cell
- ultrasound guided
- high grade
- dual energy
- machine learning
- molecularly imprinted
- electronic health record
- magnetic resonance
- lymph node metastasis
- cell proliferation
- climate change
- mass spectrometry
- cell death
- risk assessment
- signaling pathway
- cell cycle arrest
- deep learning