Textural features of dynamic contrast‐enhanced MRI derived model‐free and model‐based parameter maps in glioma grading

2017 ◽  
Vol 47 (4) ◽  
pp. 1099-1111 ◽  
Author(s):  
Tian Xie ◽  
Xiao Chen ◽  
Jingqin Fang ◽  
Houyi Kang ◽  
Wei Xue ◽  
...  
2009 ◽  
Author(s):  
Ben K. Felsted ◽  
Ross T. Whitaker ◽  
Matthias Schabel ◽  
Edward V. R. DiBella

2006 ◽  
Vol 24 (3) ◽  
pp. 586-594 ◽  
Author(s):  
John A. Jesberger ◽  
Niusha Rafie ◽  
Jeffrey L. Duerk ◽  
Jeffrey L. Sunshine ◽  
Matthew Mendez ◽  
...  

2018 ◽  
Vol 60 (6) ◽  
pp. 777-787 ◽  
Author(s):  
Chun-Qiu Su ◽  
Shan-Shan Lu ◽  
Qiu-Yue Han ◽  
Mao-Dong Zhou ◽  
Xun-Ning Hong

Background The application of conventional magnetic resonance imaging (MRI) in glioma grading is limited and non-specific. Purpose To investigate the application values of MRI, texture analysis (TA) of dynamic contrast-enhanced MRI (DCE-MRI) and intratumoral susceptibility signal (ITSS) on susceptibility weighted imaging (SWI), alone and in combination, for glioma grading. Material and Methods Fifty-two patients with pathologically confirmed gliomas who underwent DCE-MRI and SWI were enrolled in this retrospective study. Conventional MRIs were evaluated by the VASARI scoring system. TA of DCE-MRI-derived parameters and the degree of ITSS were compared between low-grade gliomas (LGGs) and high-grade gliomas (HGGs). The diagnostic ability of each parameter and their combination for glioma grading were analyzed. Results Significant statistical differences in VASARI features were observed between LGGs and HGGs ( P < 0.05), of which the enhancement quality had the highest area under the curve (AUC) (0.873) with 93.3% sensitivity and 80% specificity. The TA of DCE-MRI derived parameters were significantly different between LGGs and HGGs ( P < 0.05), of which the uniformity of Ktrans had the highest AUC (0.917) with 93.3% sensitivity and 90% specificity. The degree of ITSS was significantly different between LGGs and HGGs ( P < 0.001). The AUC of the ITSS was 0.925 with 93.3% sensitivity and 90% specificity. The best discriminative power was obtained from a combination of enhancement quality, Ktrans- uniformity, and ITSS, resulting in 96.7% sensitivity, 100.0% specificity, and AUC of 0.993. Conclusion Combining conventional MRI, TA of DCE-MRI, and ITSS on SWI may help to improve the differentiation between LGGs and HGGs.


2009 ◽  
Vol 61 (5) ◽  
pp. 1173-1184 ◽  
Author(s):  
Deirdre M. McGrath ◽  
Daniel P. Bradley ◽  
Jean L. Tessier ◽  
Tony Lacey ◽  
Chris J. Taylor ◽  
...  

2011 ◽  
Vol 54 (3) ◽  
pp. 205-213 ◽  
Author(s):  
Rishi Awasthi ◽  
Ram K. S. Rathore ◽  
Priyanka Soni ◽  
Prativa Sahoo ◽  
Ashish Awasthi ◽  
...  

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