Utility of multiparametric 3-T MRI for glioma characterization.
Utility of multiparametric 3-T MRI for glioma characterization.
复制标题
多参数3-T MRI用于神经胶质瘤表征的效用。
DOI：
10.1007/s00234-013-1145-x
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发表时间：
2013-05
期刊：
影响因子：
2.8
通讯作者：
Alger, Jeffry R.
中科院分区：
文献类型：
--
作者：
Roy, Bhaswati;Gupta, Rakesh K.;Maudsley, Andrew A.;Awasthi, Rishi;Sheriff, Sulaiman;Gu, Meng;Husain, Nuzhat;Mohakud, Sudipta;Behari, Sanjay;Pandey, Chandra M.;Rathore, Ram K. S.;Spielman, Daniel M.;Alger, Jeffry R.
关键词：
Accurate grading of cerebral glioma using conventional structural imaging techniques remains challenging due to the relatively poor sensitivity and specificity of these methods. The purpose of this study was to evaluate the relative sensitivity and specificity of structural MRI and MR measurements of perfusion, diffusion, and spectroscopic parameters for glioma grading. A secondary objective was to evaluate a whole-brain MR spectroscopic imaging method for evaluation of brain tumors. Fifty six patients with radiologically suspected untreated glioma were studied with T1- and T2-weighted MR imaging, DCE-MR imaging, DTI, and volumetric whole-brain MR spectroscopic imaging. ROC analysis was performed using the relative CBV, ADC, FA, and multiple spectroscopic parameters to determine optimum thresholds for tumor grading and to obtain the sensitivity, specificity, PPV, and NPV for identifying high-grade gliomas. Logistic regression was performed to analyze all the parameters together. The relative CBV individually classified glioma as low and high grade with a sensitivity and specificity of 100% and 88% respectively based on a threshold value of 3.34. On combining all parameters under consideration, the classification was achieved with 2% error and sensitivity and specificity of 100% and 96% respectively. Individually, CBV measurement provides the greatest diagnostic performance for predicting glioma grade; however, the most accurate classification can be achieved by combining all of the imaging parameters. The whole-brain MR spectroscopic imaging method provided data from of a large fraction of the tumor volumes.
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影响因子：
2.8
作者：
Server, Andres;Orheim, Tone E. Doli;Nakstad, Per H.
通讯作者：
Nakstad, Per H.
影响因子：
3.9
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Arvinda, H. R.;Kesavadas, C.;Nair, S.
通讯作者：
Nair, S.
影响因子：
2.8
作者：
Server, Andres;Graff, Bjorn A.;Nakstad, Per H.
通讯作者：
Nakstad, Per H.
影响因子：
2.8
作者：
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通讯作者：
Crisi, Girolamo
影响因子：
4.4
作者：
Singh, Anup;Haris, Mohammad;Gupta, Rakesh K.
通讯作者：
Gupta, Rakesh K.