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Classification of tumour 1 H NMR spectra by pattern recognition
Author(s) -
Howells S. L.,
Maxwell R. J.,
Griffiths J. R.
Publication year - 1992
Publication title -
nmr in biomedicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.278
H-Index - 114
eISSN - 1099-1492
pISSN - 0952-3480
DOI - 10.1002/nbm.1940050203
Subject(s) - fibrosarcoma , cancer , pathology , chemistry , kidney , nuclear magnetic resonance , biology , medicine , endocrinology , physics
Abstract 1 H spectra of tumours or normal tissues, which include signals from all hydrogen‐containing metabolites, are too complex for the human eye to interpret. We have studied 58 1 H spectra from perchloric acid extracts of three normal tissues (liver, kidney and spleen) and five rat tumours (GH3 pituitary, fibrosarcoma, Morris Hepatomas 7777 and 9618a and Walker carcinosarcoma). Instead of editing them or quantifying individual metabolites, we have used statistical pattern recognition techniques to classify them into groups. This automatic, objective method differentiated spectra from normal and malignant rat tissue biopsies, and from different types of cancer. It seems likely that this technique can be applied to human tissues and thus used for cancer diagnosis.