当前位置: X-MOL 学术NMR Biomed. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
A metabolomic data fusion approach to support gliomas grading.
NMR in Biomedicine ( IF 2.7 ) Pub Date : 2019-12-11 , DOI: 10.1002/nbm.4234
Valeria Righi 1 , Nicola Cavallini 2 , Antonella Valentini 3 , Giampietro Pinna 3, 4 , Giacomo Pavesi 3, 5 , Maria Cecilia Rossi 6 , Annette Puzzolante 3 , Adele Mucci 2 , Marina Cocchi 2
Affiliation  

Magnetic resonance imaging (MRI) is the current gold standard for the diagnosis of brain tumors. However, despite the development of MRI techniques, the differential diagnosis of central nervous system (CNS) primary pathologies, such as lymphoma and glioblastoma or tumor-like brain lesions and glioma, is often challenging. MRI can be supported by in vivo magnetic resonance spectroscopy (MRS) to enhance its diagnostic power and multiproject-multicenter evaluations of classification of brain tumors have shown that an accuracy around 90% can be achieved for most of the pairwise discrimination problems. However, the survival rate for patients affected by gliomas is still low. The High-Resolution Magic-Angle-Spinning Nuclear Magnetic Resonance (HR-MAS NMR) metabolomics studies may be helpful for the discrimination of gliomas grades and the development of new strategies for clinical intervention. Here, we propose to use T2 -filtered, diffusion-filtered and conventional water-presaturated spectra to try to extract as much information as possible, fusing the data gathered by these different NMR experiments and applying a chemometric approach based on Multivariate Curve Resolution (MCR). Biomarkers important for glioma's discrimination were found. In particular, we focused our attention on cystathionine (Cyst) that shows promise as a biomarker for the better prognosis of glioma tumors.

中文翻译:

一种代谢组学数据融合方法,可支持神经胶质瘤分级。

磁共振成像(MRI)是目前诊断脑肿瘤的金标准。然而,尽管MRI技术得到了发展,但对中枢神经系统(CNS)主要病理学(如淋巴瘤和成胶质细胞瘤或肿瘤样脑病变和神经胶质瘤)的鉴别诊断通常具有挑战性。MRI可以通过体内磁共振波谱(MRS)来增强其诊断能力,并且对脑肿瘤分类的多项目-多中心评估显示,对于大多数成对的辨别问题,可以达到90%左右的准确度。但是,受神经胶质瘤影响的患者的存活率仍然很低。高分辨率魔角旋转核磁共振(HR-MAS NMR)代谢组学研究可能有助于区分神经胶质瘤等级和开发新的临床干预策略。在这里,我们建议使用经过T2过滤,扩散过滤和常规的水预饱和光谱来尝试提取尽可能多的信息,将这些不同的NMR实验收集的数据融合在一起,并应用基于多元曲线分辨率(MCR)的化学计量方法)。发现了对神经胶质瘤的鉴别重要的生物标志物。特别是,我们将注意力集中在半胱氨酸(胱氨酸)上,胱氨酸具有作为有望更好地预后神经胶质瘤肿瘤的生物标志物的潜力。扩散过滤和常规的水预饱和光谱,以尝试提取尽可能多的信息,将这些不同的NMR实验收集的数据融合在一起,并应用基于多变量曲线分辨率(MCR)的化学计量方法。发现了对神经胶质瘤的鉴别重要的生物标志物。特别是,我们将注意力集中在半胱氨酸(胱氨酸)上,胱氨酸具有作为有望更好地预后神经胶质瘤肿瘤的生物标志物的潜力。扩散过滤和常规的水预饱和光谱,以尝试提取尽可能多的信息,将这些不同的NMR实验收集的数据融合在一起,并应用基于多变量曲线分辨率(MCR)的化学计量方法。发现了对神经胶质瘤的鉴别重要的生物标志物。特别是,我们将注意力集中在半胱氨酸(胱氨酸)上,胱氨酸具有作为有望更好地预后神经胶质瘤肿瘤的生物标志物的潜力。
更新日期:2020-02-04
down
wechat
bug