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Quantitative in vivo proton MR spectroscopic assessment of lipid metabolism: Value for breast cancer diagnosis and prognosis
Author(s) -
Thakur Sunitha B.,
Horvat Joao V.,
Hancu Ileana,
Sutton Olivia M.,
BernardDavila Blanca,
Weber Michael,
Oh Jung Hun,
Marino Maria Adele,
Avendano Daly,
Leithner Doris,
Brennan Sandra,
Giri Dilip,
Manderski Elizabeth,
Morris Elizabeth A.,
Pinker Katja
Publication year - 2019
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.26622
Subject(s) - breast cancer , nuclear medicine , flip angle , metabolite , magnetic resonance imaging , confidence interval , nuclear magnetic resonance , medicine , choline , cancer , radiology , physics
Background Breast magnetic resonance spectroscopy ( 1 H‐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 1 H‐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. 1 H‐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 cm 3 . 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 1 H‐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.