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HR-MAS MR spectroscopy of breast cancer tissue obtained with core needle biopsy: correlation with prognostic factors

Authors
 Ji Soo Choi ; Hyeon-Man Baek ; Ja Seung Koo ; Seung Il Kim ; Dong-hyun Kim ; Kyung Hwa Han ; Eun-Kyung Kim ; Hee Jung Moon ; Ji Hyun Youk ; Min Jung Kim ; Suhkmann Kim 
Citation
 PLoS One, Vol.7(12) : e51712, 2012 
Journal Title
 PLoS One 
ISSN
 1932-6203 
Issue Date
2012
Abstract
The purpose of this study was to examine the correlation between high-resolution magic angle spinning (HR-MAS) magnetic resonance (MR) spectroscopy using core needle biopsy (CNB) specimens and histologic prognostic factors currently used in breast cancer patients. After institutional review board approval and informed consent were obtained for this study, CNB specimens were collected from 36 malignant lesions in 34 patients. Concentrations and metabolic ratios of various choline metabolites were estimated by HR-MAS MR spectroscopy using CNB specimens. HR-MAS spectroscopic values were compared according to histopathologic variables [tumor size, lymph node metastasis, histologic grade, status of estrogens receptor (ER), progesterone receptor (PR), HER2 (a receptor for human epidermal growth factor), and Ki-67, and triple negativity]. Multivariate analysis was performed with Orthogonal Projections to Latent Structure-Discriminant Analysis (OPLS-DA). HR-MAS MR spectroscopy quantified and discriminated choline metabolites in all CNB specimens of the 36 breast cancers. Several metabolite markers [free choline (Cho), phosphocholine (PC), creatine (Cr), taurine, myo-inositol, scyllo-inositol, total choline (tCho), glycine, Cho/Cr, tCho/Cr, PC/Cr] on HR-MAS MR spectroscopy were found to correlate with histologic prognostic factors [ER, PR, HER2, histologic grade, triple negativity, Ki-67, poor prognosis]. OPLS-DA multivariate models were generally able to discriminate the status of histologic prognostic factors (ER, PR, HER2, Ki-67) and prognosis groups. Our study suggests that HR-MAS MR spectroscopy using CNB specimens can predict tumor aggressiveness prior to surgery in breast cancer patients. In addition, it may be helpful in the detection of reliable markers for breast cancer characterization.
URI
http://ir.ymlib.yonsei.ac.kr/handle/22282913/91728
DOI
10.1371/journal.pone.0051712
Appears in Collections:
1. 연구논문 > 1. College of Medicine > Yonsei Biomedical Research Center
1. 연구논문 > 1. College of Medicine > Dept. of Pathology
1. 연구논문 > 1. College of Medicine > Dept. of Radiology
1. 연구논문 > 1. College of Medicine > Dept. of Surgery
Yonsei Authors
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