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Quantitative neuropathology by high resolution magic angle spinning proton magnetic resonance spectroscopy.

Abstract:
We describe a method that directly relates tissue neuropathological analysis to medical imaging. Presently, only indirect and often tenuous relationships are made between imaging (such as MRI or x-ray computed tomography) and neuropathology. We present a biochemistry-based, quantitative neuropathological method that can help to precisely quantify information provided by in vivo proton magnetic resonance spectroscopy (1HMRS), an emerging medical imaging technique. This method, high resolution magic angle spinning (HRMAS) 1HMRS, is rapid and requires only small amounts of unprocessed samples. Unlike chemical extraction or other forms of tissue processing, this method analyzes tissue directly, thus minimizing artifacts. We demonstrate the utility of this method by assessing neuronal damage using multiple tissue samples from differently affected brain regions in a case of Pick disease, a human neurodegenerative disorder. Among different regions, we found an excellent correlation between neuronal loss shown by traditional neurohistopathology and decrease of the neuronal marker N-acetylaspartate measured by HRMAS 1HMRS. This result demonstrates for the first time, to our knowledge, a direct, quantitative link between a decrease in N-acetylaspartate and neuronal loss in a human neurodegenerative disease. As a quantitative method, HRMAS 1HMRS has potential applications in experimental and clinical neuropathologic investigations. It should also provide a rational basis for the interpretation of in vivo 1HMRS studies of human neurological disorders.
Publication status:
Published

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Publisher copy:
10.1073/pnas.94.12.6408

Authors


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Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Role:
Author


Journal:
Proceedings of the National Academy of Sciences of the United States of America More from this journal
Volume:
94
Issue:
12
Pages:
6408-6413
Publication date:
1997-06-01
DOI:
EISSN:
1091-6490
ISSN:
0027-8424


Language:
English
Keywords:
Pubs id:
pubs:376235
UUID:
uuid:ad3b1bfa-ce7d-4eff-b124-2ac30434d79f
Local pid:
pubs:376235
Source identifiers:
376235
Deposit date:
2013-11-16

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