Peritumoral Fat Content Identified Using Iterative Decomposition of Water and Fat with Echo Asymmetry and Least-squares Estimation (IDEAL) Correlates with Breast Cancer Prognosis

利用回声不对称性和最小二乘估计的迭代水脂分解法(IDEAL)识别的肿瘤周围脂肪含量与乳腺癌预后相关

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Abstract

PURPOSE: Adipocytes around aggressive breast cancer (BC) are less lipid different from naive adipocytes (cancer-associated adipocytes, CAAs), and peritumoral edema caused by the release of cytokines from CAAs can conduce to decrease the peritumoral fat proportion. The purpose of this study was to correlate peritumoral fat content identified by using iterative decomposition of water and fat with echo asymmetry and least-squares estimation (IDEAL) with lymph node metastasis (LNM) and recurrence-free survival (RFS) in BC patients and to compare with T2-weighted (T2WI) and diffusion-weighted images (DWI) analyses. METHODS: This retrospective study consisted of 85 patients who were diagnosed with invasive carcinoma of breast and underwent breast MRI, including IDEAL before surgery. The scan time of fat fraction (FF) map imaging using IDEAL was 33s. Four regions of interest (ROIs), which are 5 mm from the tumor edge, and one ROI in the mammary fat of the healthy side were set on the FF map. Then average peritumoral FF values (TFF), average FF values on the healthy side (HFF), and peritumoral fat ratio (PTFR, which is defined as TFF/HFF) were calculated. Tumor apparent diffusion coefficient (ADC) values were measured on ADC map obtained by DWI. Peritumoral edema was classified into three grades based on the degree of signal intensity around the tumor on T2WI (T2 edema). RESULTS: The results of stepwise logistic regression analysis for four variables (TFF, PTFR, T2 edema, and ADC value) indicated that TFF and T2 edema were significant factors of LNM (P < 0.01). RFS was significantly associated with TFF (P = 0.016), and 47 of 49 (95.9%) patients with TFF more than 85.5% were alive without recurrence. CONCLUSION: Peritumoral fat content identified by using IDEAL is associated with LNM and RFS and may therefore be a useful prognostic biomarker for BC.

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