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Investigation of breast cancer using two‐dimensional MRS
Author(s) -
Thomas M. Albert,
Lipnick Scott,
Velan S. Sendhil,
Liu Xiaoyu,
Banakar Shida,
Binesh Nader,
Ramadan Saadallah,
Ambrosio Art,
Raylman Raymond R.,
Sayre James,
DeBruhl Nanette,
Bassett Lawrence
Publication year - 2009
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.1310
Subject(s) - phosphocholine , in vivo , breast cancer , choline , ex vivo , magic angle spinning , cancer , nuclear magnetic resonance , pathology , in vitro , chemistry , medicine , biology , biochemistry , nuclear magnetic resonance spectroscopy , phospholipid , physics , phosphatidylcholine , microbiology and biotechnology , membrane
Proton ( 1 H) MRS enables non‐invasive biochemical assay with the potential to characterize malignant, benign and healthy breast tissues. In vitro studies using perchloric acid extracts and ex vivo magic angle spinning spectroscopy of intact biopsy tissues have been used to identify detectable metabolic alterations in breast cancer. The challenges of 1 H MRS in vivo include low sensitivity and significant overlap of resonances due to limited chemical shift dispersion and significant inhomogeneous broadening at most clinical magnetic field strengths. Improvement in spectral resolution can be achieved in vivo and in vitro by recording the MR spectra spread over more than one dimension, thus facilitating unambiguous assignment of metabolite and lipid resonances in breast cancer. This article reviews the recent progress with two‐dimensional MRS of breast cancer in vitro , ex vivo and in vivo . The discussion includes unambiguous detection of saturated and unsaturated fatty acids, as well as choline‐containing groups such as free choline, phosphocholine, glycerophosphocholine and ethanolamines using two‐dimensional MRS. In addition, characterization of invasive ductal carcinomas and healthy fatty/glandular breast tissues non‐invasively using the classification and regression tree (CART) analysis of two‐dimensional MRS data is reviewed. Copyright © 2008 John Wiley & Sons, Ltd.