An investigation of tumor 1H nuclear magnetic resonance spectra by the application of chemometric techniques
Research output: Contribution to journal › Article › peer-review
Colleges, School and Institutes
- CRC Biomedical Magnetic Resonance Research Group, Division of Biochemistry, St. George's Hospital Medical School, London, United Kingdom.
1H 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 1H spectra from perchloric acid extracts of three normal tissues (liver, kidney, and spleen) and five rat tumors (GH3 prolactinoma, Morris hepatomas 7777 and 9618a, LBDS1 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.
|Number of pages||23|
|Journal||Magnetic Resonance in Medicine|
|Publication status||Published - Dec 1992|
- Adenocarcinoma, Animals, Artificial Intelligence, Carcinoma, Hepatocellular, Carcinosarcoma, Classification, Cluster Analysis, Factor Analysis, Statistical, Female, Fibrosarcoma, Hydrogen, Kidney, Liver, Liver Neoplasms, Magnetic Resonance Spectroscopy, Male, Models, Chemical, Neoplasms, Experimental, Neural Networks (Computer), Prolactinoma, Rats, Rats, Inbred Strains, Rats, Inbred WF, Rats, Wistar, Signal Processing, Computer-Assisted, Spleen, Journal Article, Research Support, Non-U.S. Gov't