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通过质子光谱法测量的脂肪成分:一种乳腺癌肿瘤标志物?

Fat Composition Measured by Proton Spectroscopy: A Breast Cancer Tumor Marker?

作者信息

Bitencourt Almir, Sevilimedu Varadan, Morris Elizabeth A, Pinker Katja, Thakur Sunitha B

机构信息

Memorial Sloan Kettering Cancer Center, New York, NY, 10065, USA.

A.C.Camargo Cancer Center, São Paulo 01509-010, Brazil.

出版信息

Diagnostics (Basel). 2021 Mar 21;11(3):564. doi: 10.3390/diagnostics11030564.

Abstract

Altered metabolism including lipids is an emerging hallmark of breast cancer. The purpose of this study was to investigate if breast cancers exhibit different magnetic resonance spectroscopy (MRS)-based lipid composition than normal fibroglandular tissue (FGT). MRS spectra, using the stimulated echo acquisition mode sequence, were collected with a 3T scanner from patients with suspicious lesions and contralateral normal tissue. Fat peaks at 1.3 + 1.6 ppm (L13 + L16), 2.1 + 2.3 ppm (L21 + L23), 2.8 ppm (L28), 4.1 + 4.3 ppm (L41 + L43), and 5.2 + 5.3 ppm (L52 + L53) were quantified using LCModel software. The saturation index (SI), number of double bods (NBD), mono and polyunsaturated fatty acids (MUFA and PUFA), and mean chain length (MCL) were also computed. Results showed that mean concentrations of all lipid metabolites and PUFA were significantly lower in tumors compared with that of normal FGT ( ≤ 0.002 and 0.04, respectively). The measure best separating normal and tumor tissues after adjusting with multivariable analysis was L21 + L23, which yielded an area under the curve of 0.87 (95% CI: 0.75-0.98). Similar results were obtained between HER2 positive versus HER2 negative tumors. Hence, MRS-based lipid measurements may serve as independent variables in a multivariate approach to increase the specificity of breast cancer characterization.

摘要

包括脂质在内的代谢改变是乳腺癌新出现的一个特征。本研究的目的是调查乳腺癌基于磁共振波谱(MRS)的脂质成分是否与正常纤维腺组织(FGT)不同。使用刺激回波采集模式序列,通过3T扫描仪从有可疑病变的患者及对侧正常组织采集MRS波谱。使用LCModel软件对1.3 + 1.6 ppm(L13 + L16)、2.1 + 2.3 ppm(L21 + L23)、2.8 ppm(L28)、4.1 + 4.3 ppm(L41 + L43)和5.2 + 5.3 ppm(L52 + L53)处的脂肪峰进行定量。还计算了饱和指数(SI)、双键数量(NBD)、单不饱和脂肪酸和多不饱和脂肪酸(MUFA和PUFA)以及平均链长(MCL)。结果显示,与正常FGT相比,肿瘤中所有脂质代谢物和PUFA的平均浓度均显著降低(分别≤0.002和0.04)。多变量分析调整后,最能区分正常组织和肿瘤组织的指标是L21 + L23,其曲线下面积为0.87(95%CI:0.75 - 0.98)。HER2阳性肿瘤与HER2阴性肿瘤之间也得到了类似结果。因此,基于MRS的脂质测量可能作为多变量方法中的自变量,以提高乳腺癌特征描述的特异性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f17f/8004005/64e95f97bfb8/diagnostics-11-00564-g001.jpg

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