Abstract:
Raman
Spectroscopy for the identification and classification of malignancy in the
oesophagus has been demonstrated in this thesis. The potential of Raman spectroscopy
in this field is twofold; as a adjunct for the pathologist and as a biopsy targeting tool at
endoscopy. This study has demonstrated the feasibility of these potential applications in
vitro.
Spectral diagnostic models have been developed by correlating spectral
information with
histopathology. This is the current 'gold standard' diagnostic method
for the identification of
dysplasia, the established risk factor for the development of
oesophageal cancer. Histopathology is a subjective assessment and widely
acknowledged to have limitations. A more rigorous gold standard was therefore
developed, as part of this study, using the consensus opinion of three independent
expert pathologists to train the diagnostic models.
Raman
spectra have been measured from oesophageal tissue covering the full spectrum
of
malignant disease in the oesophagus, using a near infrared Raman spectrometer
customised for tissue
spectral measurements. Two spectral datasets were measured with
different volumes of tissue
probed using twenty and eighty times magnification ultra
long working distance objectives. Multivariate statistical analysis has been used to
extract the
required spectral information with the greatest discriminative power.
Principal component fed linear discriminant spectral models have been tested with leave
one out cross validation
procedures. Three pathology group models have correctly
classified
up to 91% of spectra, and eight group models have correctly classified up to
82% of spectra. Optimisation of the spectral models by selection of significant principal
components, filtering the data and using staggered models was investigated. Effort has
been made to understand the
findings in their clinical context, with review of patient
history and clinical progress, long term follow up is required. Preliminary work
projecting independent data on to the models has been encouraging with 76% of the
spectra in the three group model correctly classified, approaching classification levels of
the
training dataset. Formalin fixed tissue models were demonstrated to
perform well,
with 80% of the
spectra were correctly classified in the seven group model. This further
demonstrates the
potential of Raman spectroscopy as a pathology tool. If Raman
spectroscopy is to be implemented in a clinical setting it must be transferable between
different measurement systems. This has been evaluated with oesophageal tissue spectra
measured on two
systems using three objectives. Simple calibration has demonstrated
the use of
multiple systems and measurement parameters in the development and
application of spectral classification models. Testing of a new design of fibre probe has
provided encouraging preliminary results. There is potential for the application of
Raman spectroscopy in vivo, however the technology remains immature.
Spectral maps of samples taken from across the spectrum of disease have shown clear
delineation of the
morphological features seen on the H&E images. Furthermore the
biochemical information elicited has been
analysed. Initial measurements of
oesophageal tissue using multiphoton imaging have demonstrated the potential of
collagen autofuorescence in the diagnosis of malignant change.