Abstract
Background: Response guided treatment in breast cancer is highly desirable, but the effectiveness is only established based on residual cellularity from histopathological analysis after surgery. Tubule formation, a key component of grading score, is directly associated with cellularity, with significant implications on prognosis. Peri-tumoural lipid composition, a potential marker, can be rapidly mapped across the entire breast using novel method of chemical shift-encoded imaging, enabling the quantification of spatial distribution. We hypothesise that peri-tumoural spatial distribution of lipid composition is sensitive to tumour cellular differentiation and proliferative activity.Methods: Twenty whole tumour specimens freshly excised from patients with invasive ductal carcinoma (9 Score 2 and 11 Score 3 in tubule formation) were scanned on a 3 T clinical scanner (Achieva TX, Philips Healthcare). Quantitative lipid composition maps were acquired for polyunsaturated, monounsaturated, and saturated fatty acids (PUFA, MUFA, SFA). The peri-tumoural spatial distribution (mean, skewness, entropy and kurtosis) of each lipid constituent were then computed. The proliferative activity marker Ki-67 and tumour-infiltrating lymphocytes (TILs) were assessed histologically.Results: For MUFA, there were significant differences between groups in mean (p = 0.0119), skewness (p = 0.0116), entropy (p = 0.0223), kurtosis (p = 0.0381), and correlations against Ki-67 in mean (ρ = -0.5414), skewness (ρ = 0.6045) and entropy (ρ = 0.6677), and TILs in mean (ρ = -0.4621). For SFA, there were significant differences between groups in mean (p = 0.0329) and skewness (p = 0.0111), and correlation against Ki-67 in mean (ρ = 0.5910). For PUFA, there was no significant difference in mean, skewness, entropy or kurtosis between the groups.Conclusions: There was an association between peri-tumoural spatial distribution of lipid composition with tumour cellular differentiation and proliferation. Peri-tumoural lipid composition imaging might have potential in non-invasive quantitative assessment of patients with breast cancer for treatment planning and monitoring. [ABSTRACT FROM AUTHOR]