Quantitative in vivo proton MR spectroscopic assessment of lipid metabolism: Value for breast cancer diagnosis and prognosis. Issue 1 (3rd January 2019)

• Record Type: Journal Article
• Authors: Thakur, Sunitha B.; Horvat, Joao V.; Hancu, Ileana; Sutton, Olivia M.; Bernard‐Davila, Blanca; Weber, Michael; Oh, Jung Hun; Marino, Maria Adele; Avendano, Daly; Leithner, Doris; Brennan, Sandra; Giri, Dilip; Manderski, Elizabeth; Morris, Elizabeth A.; Pinker, Katja
• Is Part Of: Journal of magnetic resonance imaging. Volume 50:Issue 1(2019)
• Page Start: 239
• Page End: 249
• Publication Date: 2019-01-03
• Subjects: breast cancer -- magnetic resonance spectroscopy -- lipid -- metabolism -- radiometabolomics; Magnetic resonance imaging -- Periodicals; 616
• DOI: 10.1002/jmri.26622
• Languages: English
• ISSNs: 1053-1807

Abstract

Abstract : 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.