In vivo MR spectroscopy of human breast tissue: quantification of fatty acid composition at a clinical field strength (3 T)

Coum, Amandine; Ouldamer, Lobna; Noury, Fanny; Barantin, Laurent; Saint-Hilaire, Aymeric; Vildé, A.; Bougnoux, Philippe; Gambarota, Giulio

doi:10.1007/s10334-015-0506-3

Cited by 16 publications

(16 citation statements)

References 12 publications

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“…Lipid MRS is a simple and fast tool to analyze metabolic modification when quantifying fatty acid: it could be advantageous in the follow‐up of the lipid composition modification in adipose tissues in weight gain or weight loss phases, in the evaluation of fat surrounding a tumor or in inflammatory tissue . However, the fatty acid composition modifications could be very small in comparison with the measurement uncertainties related to the current methods.…”

Section: Discussionmentioning

confidence: 99%

“…LCModel (Version 6.3‐0 L, Stephen Provencher, Oakville, ON, Canada), with the control parameter SPTYPE set to Lipid‐8 (as described in the LCModel user's manual), was also used on experimental data (described below) only. For lipid signals, this quantification method fits a flexible combination of Gaussian and Lorentzian lineshapes to the lipid resonances, but the exact model function used and the implementation details are unknown. As a result, the analysis of the Monte Carlo studies in the light of the model function and implementation used, as performed for M peak and M TG_param approaches, was not allowed.…”

Section: Methodsmentioning

confidence: 99%

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Comparison of MRI‐derived vs. traditional estimations of fatty acid composition from MR spectroscopy signals

et al. 2018

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Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Comparison of MRI‐derived vs. traditional estimations of fatty acid composition from MR spectroscopy signals

et al. 2018

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“…Initial ex vivo and in vivo MRS studies demonstrated differences in fat and water between malignant, benign, and normal tissue, showing that cancerous tissue display higher water concentrations and lower methylene lipid peaks at 1.3 ppm. 21,[23][24][25][26][27] So far, although most of the research on lipid metabolites has focused on the detection of the 1.3 ppm lipid peaks from in vivo MRS, a whole spectrum of 9-10 lipid peaks with different chemical shifts can also be detected with MRS. 28 A few studies have looked at L21, L23, and L28 resonances in the adipose tissue in breast controls 29 and contralateral breast adipose tissue in breast cancer patients. 8 Thus, we hypothesized that through the noninvasive quantitative assessment of lipid metabolism with 1 H-MRS, insights into tumor biology are feasible that might be useful for breast cancer diagnosis, characterization, and prognosis.…”

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Quantitative in vivo proton MR spectroscopic assessment of lipid metabolism: Value for breast cancer diagnosis and prognosis

Thakur

Horvat

Hancu

et al. 2019

Magnetic Resonance Imaging

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Background Breast magnetic resonance spectroscopy (1H‐MRS) has been largely based on choline metabolites; however, other relevant metabolites can be detected and monitored. Purpose To investigate whether lipid metabolite concentrations detected with 1H‐MRS can be used for the noninvasive differentiation of benign and malignant breast tumors, differentiation among molecular breast cancer subtypes, and prediction of long‐term survival outcomes. Study Type Retrospective. Subjects In all, 168 women, aged ≥18 years. Field Strength/Sequence Dynamic contrast‐enhanced MRI at 1.5 T: sagittal 3D spoiled gradient recalled sequence with fat saturation, flip angle = 10°, repetition time / echo time (TR/TE) = 7.4/4.2 msec, slice thickness = 3.0 mm, field of view (FOV) = 20 cm, and matrix size = 256 × 192. 1H‐MRS: PRESS with TR/TE = 2000/135 msec, water suppression, and 128 scan averages, in addition to 16 reference scans without water suppression. Assessment MRS quantitative analysis of lipid resonances using the LCModel was performed. Histopathology was the reference standard. Statistical Tests Categorical data were described using absolute numbers and percentages. For metric data, means (plus 95% confidence interval [CI]) and standard deviations as well as median, minimum, and maximum were calculated. Due to skewed data, the latter were more adequate; unpaired Mann–Whitney U‐tests were performed to compare groups without and with Bonferroni correction. ROC analyses were also performed. Results There were 111 malignant and 57 benign lesions. Mean voxel size was 4.4 ± 4.6 cm3. Six lipid metabolite peaks were quantified: L09, L13 + L16, L21 + L23, L28, L41 + L43, and L52 + L53. Malignant lesions showed lower L09, L21 + L23, and L52 + L53 than benign lesions (P = 0.022, 0.027, and 0.0006). Similar results were observed for Luminal A or Luminal A/B vs. other molecular subtypes. At follow‐up, patients were split into two groups based on median values for the six peaks; recurrence‐free survival was significantly different between groups for L09, L21 + L23, and L28 (P = 0.0173, 0.0024, and 0.0045). Data Conclusion Quantitative in vivo 1H‐MRS assessment of lipid metabolism may provide an additional noninvasive imaging biomarker to guide therapeutic decisions in breast cancer. Level of Evidence: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;50:239–249.

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“…These changes correlated with the follicular, ovulatory and luteal phases of the menstrual cycle, thus providing valuable information on the lipid metabolism, which is associated with breast disease. Use of high‐field MR scanners facilitates visualization of the various fatty acid compositions of breast adipose tissues at 3 T and at 7 T using 1 H MRS …”

Section: In Vivo Mrs Methods In the Study Of Breast Cancer Metabolismmentioning

confidence: 99%

Application of in vivo MR methods in the study of breast cancer metabolism

Jagannathan

2018

NMR in Biomedicine

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In the last two decades, various in vivo MR methodologies have been evaluated for their potential in the study of cancer metabolism. During malignant transformation, metabolic alterations occur, leading to morphological and functional changes. Among various MR methods, in vivo MRS has been extensively used in breast cancer to study the metabolism of cells, tissues or whole organs. It provides biochemical information at the metabolite level. Altered choline, phospholipid and energy metabolism has been documented using proton ( 1 H), phosphorus ( 31 P) and carbon ( 13 C) isotopes. Increased levels of choline-containing compounds, phosphomonoesters and phosphodiesters in breast cancer, which are indicative of altered choline and phospholipid metabolism, have been reported using in vivo, in vitro and ex vivo NMR studies. These changes are reversed on successful therapy, which depends on the treatment regimen given.Monitoring the various tumor intermediary metabolic pathways using nuclear spin hyperpolarization of 13 C-labeled substrates by dynamic nuclear polarization has also been recently reported. Furthermore, the utility of various methods such as diffusion, dynamic contrast and perfusion MRI have also been evaluated to study breast tumor metabolism. Parameters such as tumor volume, apparent diffusion coefficient, volume transfer coefficient and extracellular volume ratio are estimated. These parameters provide information on the changes in tumor microstructure, microenvironment, abnormal vasculature, permeability and grade of the tumor. Such changes seen during cancer progression are due to alterations in the tumor metabolism, leading to changes in cell architecture. Due to architectural changes, the tissue mechanical properties are altered; this can be studied using magnetic resonance elastography, which measures the elastic properties of tissues. Moreover, these structural MRI methods can be used to investigate the effect of therapy-induced changes in tumor characteristics. This review discusses the potential of various in vivo MR methodologies in the study of breast cancer metabolism.

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In vivo MR spectroscopy of human breast tissue: quantification of fatty acid composition at a clinical field strength (3 T)

Abstract: The results of the current study show that it is possible to quantify the fatty acid composition of breast tissue in vivo in a clinical setting (3 T).

Cited by 16 publications

References 12 publications

Comparison of MRI‐derived vs. traditional estimations of fatty acid composition from MR spectroscopy signals

Comparison of MRI‐derived vs. traditional estimations of fatty acid composition from MR spectroscopy signals

Quantitative in vivo proton MR spectroscopic assessment of lipid metabolism: Value for breast cancer diagnosis and prognosis

Application of in vivo MR methods in the study of breast cancer metabolism

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