Introduction

Breast cancer is a major societal challenge, and the deregulation of lipid composition in the breast has been suggested as a risk factor^1,2. Studies in BRCA1/2 genetic mutation carriers using correlation spectroscopy (COSY) has shown abnormal lipid metabolism in precancer state³. COSY, although providing accurate quantification of lipid composition, is limited to a single spatial location (single voxel) with a lengthy acquisition to collect signals from a full range of correlation times. Recent development in gradient-echo (GRE) based chemical shift-encoded imaging allows lipid composition mapping, utilising the known resonant frequencies of lipids with a theoretical triglyceride molecule structure^4-6. We therefore conducted a cross-sectional study to examine the relationship between peri-tumoural lipid composition and tumour tubule formation, an indicator for differentiation from normal breast ducts and lobules, in freshly excised breast tumour.

Methods

Twenty patients (9 Score 2 and 11 Score 3 in tubule formation) with invasive breast carcinoma participated in the study. Patients undergoing breast conservation surgery, with a tumour size larger than 10 mm in diameter on mammography, with no previous malignancies, chemotherapy or radiotherapy prior to surgery were eligible. The study was approved by the North West – Greater Manchester East Research Ethics Committee (REC Reference: 16/NW/0221), and signed written informed consents were obtained from all the participants prior to the study (Figure 1).

Specimen Preparation

Upon tumour excision, the tissue specimen was immediately transported from operating theatre to Aberdeen Biomedical Imaging Centre in a sealed container. The container was filled with 10 % formalin to prevent tissue degradation and the specimen was immobilised by a custom-built holding harness to prevent displacement during scans.

MRI Acquisition

The MRI data for all 20 excised breast tissue specimens were acquired at room temperature on a 3 T whole body clinical MRI scanner (Achieva TX, Philips Healthcare, Best, Netherlands) using a 32-channel receiver coil for high sensitivity detection and a body coil for uniform transmission. Anatomical images were acquired using standard T₁-weighted 3D sequence⁷ with repetition time (TR) of 5.7 ms, echo time (TE) of 2.9 ms, field of view (FOV) of 141 × 141 mm², matrix size of 256 × 256, 28 slices, slice thickness of 1.1 mm, parallel acquisition acceleration factor of 1.5. 3D multi-echo GRE data was acquired with a resolution of 2.2 mm isotropic, first TE of 1.14 ms, echo spacing of 1.14 ms, 16 echoes, TR of 20 ms, flip angle of 6° and 9 signal averages.

Data Processing

Regions of interests (ROI) were drawn on GRE images to define the adipose tissue boundary. A theoretical model⁴ was used to map the number of double bonds in triglyceride molecules from the magnitude GRE data on a pixel-by-pixel basis, from which the fatty acid components, including mean PUFA, MUFA and SFA^4,5, were subsequently derived. Fat fraction, defined as the ratio between fat and the sum of fat and water images, was also computed. Statistical analysis was conducted on fat fraction and fatty acid components using the aforementioned ROI together with the following inclusion criteria: (1) fat fraction must be greater than or equal to 60 % and (2) PUFA/MUFA/SFA must not exceed beyond the range between 0 % and 100 %, thus non-adipose tissue and voxels with low SNR did not contribute to the outliers of the analysis.

Statistical Analysis

All statistical analysis was performed in the SPSS software (Release 23.0, SPSS Inc., Chicago, IL, USA). Shapiro-Wilk test for normality was performed on all the collected data. Student’s t-tests were performed on normally distributed data to assess difference in fatty acid components between Score 2 and 3 tubule formation. The correspondence between fatty acid components against tumour size was examined using Pearson’s correlation. A p value < 0.05 was considered statistically significant.

Results

The patient demographics are summarised in Table 1. A significant lower mean fat fraction (p = 0.0200, Table 2, Figure 2a) was found for Score 3 (mean ± SD: 0.84 ± 0.04) compared to Score 2 (0.87 ± 0.02). A significant lower MUFA (p = 0.0119, Table 2, Figure 2b) was found for Score 3 (0.38 ± 0.02) compared to Score 2 (0.40 ± 0.01). A significantly higher SFA (p = 0.0329, Table 2, Figure 2c) was found for Score 3 (0.51 ± 0.04) compared to Score 2 (0.48 ± 0.02). There was no significant difference in PUFA (p = 0.0986, Table 2, Figure 2d) between Score 2 and Score 3.

There were no significant correlations between mean fat fraction (p = 0.1537, Table 2, Figure 3a), MUFA (p = 0.0560, Table 2, Figure 3b), SFA (p = 0.0676, Table 2, Figure 3c) and PUFA (p = 0.0968, Table 2, Figure 3d) against tumour size.

Discussion

There was a change in the lipid composition in peri-tumoural zone associated with tumour development. The neoplastic tubule formation, indicating the deviation from normal breast tissue, is associated with structural changes in the tumour and may affect the lipid composition because of the consumption of specific types of lipids for membrane synthesis.

Conclusion

Fat mapping in whole breast tumours provides a novel imaging tool to assess tumour development and metabolism in breast cancer.