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Metabolomics of Breast Cancer Using High-Resolution Magic Angle Spinning Magnetic Resonance Spectroscopy: Correlations with 18F-FDG Positron Emission Tomography-Computed Tomography, Dynamic Contrast-Enhanced and Diffusion-Weighted Imaging MRI

Authors
 Haesung Yoon  ;  Dahye Yoon  ;  Mijin Yun  ;  Ji Soo Choi  ;  Vivian Youngjean Park  ;  Eun-Kyung Kim  ;  Joon Jeong  ;  Ja Seung Koo  ;  Jung Hyun Yoon  ;  Hee Jung Moon  ;  Suhkmann Kim  ;  Min Jung Kim 
Citation
 PLoS One, Vol.11(7) : e0159949, 2016 
Journal Title
 PLoS One 
Issue Date
2016
MeSH
Adult ; Aged ; Breast Neoplasms/diagnostic imaging ; Breast Neoplasms/metabolism* ; Diffusion Magnetic Resonance Imaging ; Female ; Fluorodeoxyglucose F18 ; Humans ; Magnetic Resonance Spectroscopy ; Metabolome* ; Middle Aged ; Positron-Emission Tomography ; Radiopharmaceuticals
Abstract
PURPOSE: Our goal in this study was to find correlations between breast cancer metabolites and conventional quantitative imaging parameters using high-resolution magic angle spinning (HR-MAS) magnetic resonance spectroscopy (MRS) and to find breast cancer subgroups that show high correlations between metabolites and imaging parameters. MATERIALS AND METHODS: Between August 2010 and December 2013, we included 53 female patients (mean age 49.6 years; age range 32-75 years) with a total of 53 breast lesions assessed by the Breast Imaging Reporting and Data System. They were enrolled under the following criteria: breast lesions larger than 1 cm in diameter which 1) were suspicious for malignancy on mammography or ultrasound (US), 2) were pathologically confirmed to be breast cancer with US-guided core-needle biopsy (CNB) 3) underwent 3 Tesla MRI with dynamic contrast-enhanced (DCE) and diffusion-weighted imaging (DWI) and positron emission tomography-computed tomography (PET-CT), and 4) had an attainable immunohistochemistry profile from CNB. We acquired spectral data by HR-MAS MRS with CNB specimens and expressed the data as relative metabolite concentrations. We compared the metabolites with the signal enhancement ratio (SER), maximum standardized FDG uptake value (SUV max), apparent diffusion coefficient (ADC), and histopathologic prognostic factors for correlation. We calculated Spearman correlations and performed a partial least squares-discriminant analysis (PLS-DA) to further classify patient groups into subgroups to find correlation differences between HR-MAS spectroscopic values and conventional imaging parameters. RESULTS: In a multivariate analysis, the PLS-DA models built with HR-MAS MRS metabolic profiles showed visible discrimination between high and low SER, SUV, and ADC. In luminal subtype breast cancer, compared to all cases, high SER, ADV, and SUV were more closely clustered by visual assessment. Multiple metabolites were correlated with SER and SUV in all cases. Multiple metabolites showed correlations with SER and SUV in the ER positive, HER2 negative, and Ki-67 negative groups. CONCLUSION: High levels of PC, choline, and glycine acquired from HR-MAS MRS using CNB specimens were noted in the high SER group via DCE MRI and the high SUV group via PET-CT, with significant correlations between choline and SER and between PC and SUV. Further studies should investigate whether HR-MAS MRS using CNB specimens can provide similar or more prognostic information than conventional quantitative imaging parameters.
DOI
10.1371/journal.pone.0159949
Appears in Collections:
1. College of Medicine (의과대학) > Dept. of Pathology (병리학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Radiology (영상의학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Nuclear Medicine (핵의학교실) > 1. Journal Papers
1. College of Medicine (의과대학) > Dept. of Surgery (외과학교실) > 1. Journal Papers
Yonsei Authors
구자승(Koo, Ja Seung) ORCID logo https://orcid.org/0000-0003-4546-4709
김민정(Kim, Min Jung) ORCID logo https://orcid.org/0000-0003-4949-1237
김은경(Kim, Eun-Kyung) ORCID logo https://orcid.org/0000-0002-3368-5013
문희정(Moon, Hee Jung) ORCID logo https://orcid.org/0000-0002-5643-5885
박영진(Park, Vivian Youngjean) ORCID logo https://orcid.org/0000-0002-5135-4058
윤미진(Yun, Mi Jin) ORCID logo https://orcid.org/0000-0002-1712-163X
윤정현(Yoon, Jung Hyun) ORCID logo https://orcid.org/0000-0002-2100-3513
윤혜성(Yoon, Haesung) ORCID logo https://orcid.org/0000-0003-0581-8656
정준(Jeong, Joon) ORCID logo https://orcid.org/0000-0003-0397-0005
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URI
https://ir.ymlib.yonsei.ac.kr/handle/22282913/151736
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