相关磁共振成像乳腺癌研究代谢物和脂质:加速和压缩传感重建。

BJR open Pub Date : 2022-01-01 DOI:10.1259/bjro.20220009
Ajin Joy, Andres Saucedo, Melissa Joines, Stephanie Lee-Felker, Sumit Kumar, Manoj K Sarma, James Sayre, Maggie DiNome, M Albert Thomas
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引用次数: 2

摘要

目的:这项工作的主要目的是通过使用加速5D EP-COSI技术在多个空间位置的二维上扩展MR光谱来检测乳腺癌中的新型生物标志物。方法:对5D EP-COSI数据进行非均匀欠采样,加速因子为8,采用基于群稀疏的压缩感知重构方法进行重构。然后对不同的代谢物和脂质比率进行量化并进行统计学分析。基于定量代谢物和脂质比率的线性判别模型被生成。定量代谢产物和脂质比率的光谱图像也被重建。结果:使用5D EP-COSI技术生成的二维COSY光谱显示健康、良性和恶性组织在代谢物和脂质比率的平均值方面存在差异,特别是基于不饱和脂肪酸、肌醇和甘氨酸的潜在新型生物标志物的比率。它进一步显示了胆碱和不饱和脂质比值图的潜力,由乳房多个位置的量化COSY信号产生,作为恶性肿瘤的补充标记,可以添加到多参数MR协议中。发现使用代谢物和脂质比率的判别模型在区分健康组织的良性和恶性肿瘤方面具有统计学意义。结论:加速5D EP-COSI技术显示出在乳腺癌中检测新的生物标志物如甘氨酸、肌醇和不饱和脂肪酸的潜力,以及通常报道的胆碱,并促进代谢物和脂质比率图,这在乳腺癌检测中有可能发挥重要作用。知识进展:本研究首次评估了一种多维磁共振光谱成像技术,该技术可用于检测基于甘氨酸、肌醇和不饱和脂肪酸的潜在新型生物标志物,以及通常报道的胆碱。胆碱和不饱和脂肪酸的比例相对于水在恶性和良性乳腺肿块的空间映射也显示。这些代谢特征可以作为提高乳腺癌诊断和治疗评价的额外生物标志物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Correlated MR spectroscopic imaging of breast cancer to investigate metabolites and lipids: acceleration and compressed sensing reconstruction.

Correlated MR spectroscopic imaging of breast cancer to investigate metabolites and lipids: acceleration and compressed sensing reconstruction.

Correlated MR spectroscopic imaging of breast cancer to investigate metabolites and lipids: acceleration and compressed sensing reconstruction.

Correlated MR spectroscopic imaging of breast cancer to investigate metabolites and lipids: acceleration and compressed sensing reconstruction.

Objectives: The main objective of this work was to detect novel biomarkers in breast cancer by spreading the MR spectra over two dimensions in multiple spatial locations using an accelerated 5D EP-COSI technology.

Methods: The 5D EP-COSI data were non-uniformly undersampled with an acceleration factor of 8 and reconstructed using group sparsity-based compressed sensing reconstruction. Different metabolite and lipid ratios were then quantified and statistically analyzed for significance. Linear discriminant models based on the quantified metabolite and lipid ratios were generated. Spectroscopic images of the quantified metabolite and lipid ratios were also reconstructed.

Results: The 2D COSY spectra generated using the 5D EP-COSI technique showed differences among healthy, benign, and malignant tissues in terms of their mean values of metabolite and lipid ratios, especially the ratios of potential novel biomarkers based on unsaturated fatty acids, myo-inositol, and glycine. It is further shown the potential of choline and unsaturated lipid ratio maps, generated from the quantified COSY signals across multiple locations in the breast, to serve as complementary markers of malignancy that can be added to the multiparametric MR protocol. Discriminant models using metabolite and lipid ratios were found to be statistically significant for classifying benign and malignant tumor from healthy tissues.

Conclusions: Accelerated 5D EP-COSI technique demonstrates the potential to detect novel biomarkers such as glycine, myo-inositol, and unsaturated fatty acids in addition to commonly reported choline in breast cancer, and facilitates metabolite and lipid ratio maps which have the potential to play a significant role in breast cancer detection.

Advances in knowledge: This study presents the first evaluation of a multidimensional MR spectroscopic imaging technique for the detection of potentially novel biomarkers based on glycine, myo-inositol, and unsaturated fatty acids, in addition to commonly reported choline. Spatial mapping of choline and unsaturated fatty acid ratios with respect to water in malignant and benign breast masses are also shown. These metabolic characteristics may serve as additional biomarkers for improving the diagnostic and therapeutic evaluation of breast cancer.

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