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An Investigation of Tumor 1 H Nuclear Magnetic Resonance Spectra by the Application of Chemometric Techniques
Author(s) -
Howells S. L.,
Maxwell R. J.,
Peet A. C.,
Griffiths J.R.
Publication year - 1992
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.1910280205
Subject(s) - nuclear magnetic resonance , principal component analysis , chemistry , nmr spectra database , nuclear magnetic resonance spectroscopy , spectral line , artificial intelligence , computer science , physics , astronomy
1 H nuclear magnetic resonance (NMR) spectra of tumors and normal tissue include signals from all hydrogen‐containing metabolites and can therefore be considered multicomponent multivariate mixtures. We have obtained 1 H spectra from perchloric acid extracts of three normal tissues (liver, kidney, and spleen) and five rat tumors (GH3 prolactinoma, Morris hepatomas 7777 and 9618a, LBDS 1 fibrosarcoma, and Walker 256 carcinosarcoma). We have applied several different chemometric methods to analyze the data. First, we used principal component analysis, cluster analysis, and an optimized artificial neural network to develop a classification rule from a training set of samples of known origin or class. The classification rule was then assessed using a set of unknown samples. We were able to successfully determine the class of each unknown sample. Second, we used the chemometric techniques of factor analysis followed by target testing to investigate the underlying biochemical differences that are detected between the classes of samples.© 1992 Academic Press,Inc.