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Improvements in Alzheimer’s Disease Diagnosis using Principal Component Analysis (PCA) in Combination with Raman Spectroscopy

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Abstract

The significant achievements of medical science over the last century are evident in the increasing age of the global population, however this now brings new problems, the most prominent being the growth in the number of people suffering from dementia. Over half the people with dementia in the UK are sufferers of Alzheimer’s disease1, a condition in which intraneuronal neurofibrillary tangles and extraneuronal senile tangles take over neurons prompting their death. A definitive diagnosis is still only currently available post-mortem, whilst current symptom based processes of elimination are far from perfect, especially when the only treatments available are symptom inhibiting drugs. Principal component analysis (PCA) of the Raman spectra taken from brain tissue has proved to be a potential tool in the diagnosis. However, this work now has to be refined in order to progress to tissue less associated with the symptoms of Alzheimer’s disease. The first step of this has already been taken in progressing from frontal tissue to occipital tissue point spectra taken at random positions from bulk tissue. Now we present initial work into acquiring Raman spectral maps from across a tissue area, in pursuit of identifying unique plaque and tangle spectra. These spectra are presented alongside synthetic β-Amyloid spectra, in a study of the role that the peptide plays in the biomarker spectra, and how this information can aid the PCA of bulk tissue, and point towards a Raman spectroscopic test on less sensitive tissue, such as blood.

© 2007 SPIE

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