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• Glioma Papers •
The influence of texture retrieving method for support vector machine with DCE MR images to grade glioma
NAN Hai-yan  YANG Yang  YAN Lin-feng  ZHANG Xin  WANG Wen  CUI Guang-bin 

DOI:10.12015/issn.1674-8034.2018.10.004.


[Abstract] Objective: This study aimed to investigate the influence of texture retrieving model of dynamic contrast enhancement magnetic resonance imaging (DCE-MRI) for SVM-based glioma grading.Materials and Methods: One hundred and seventeen glioma patients (pathology confirmed grade II/III/IV) receiving MRI scans were retrospectively included. The tumor image texture attributes were retrieved using three common texture retrieving models, including GLCM, GLRLM, and GLSZM models. Model-derived features were input into linear SVM scheme and SVM-recursive feature elimination (SVM-RFE) feature selecting strategies to compare the model-dependent grading accuracies that were further tested with leave-one-out cross-validation (LOOCV). Classification results were further analyzed by Graphpad Prism 6.Results: Gray level had no significant influence on classification performance (P=0.1589). Texture model had obviously contracted (P=0.0001). GLCM performed best in combination with gray level 32 and 256 by using the top 22 and 17 attributes, respectively (accuracy=0.79).Conclusions: When using DCE-MRI image textures based SVM classification of gliomas, GLCM model in combination with feature selection performed best and should be recommended for preoperative glioma grading.
[Keywords] Texture model；Gray level；Support vector machine；Dynamic contrast enhancement；Magnetic resonance imaging；Glioma

NAN Hai-yan Department of Radiology, Tangdu Hospital, the Fourth Military Medical University, Xi’an 710038, China

YANG Yang Department of Radiology, Tangdu Hospital, the Fourth Military Medical University, Xi’an 710038, China

YAN Lin-feng Department of Radiology, Tangdu Hospital, the Fourth Military Medical University, Xi’an 710038, China

ZHANG Xin Department of Radiology, Tangdu Hospital, the Fourth Military Medical University, Xi’an 710038, China

WANG Wen Department of Radiology, Tangdu Hospital, the Fourth Military Medical University, Xi’an 710038, China

CUI Guang-bin* Department of Radiology, Tangdu Hospital, the Fourth Military Medical University, Xi’an 710038, China

*Correspondence to: Cui GB, E-mail:cgbtd@126.com

Conflicts of interest   None.

ACKNOWLEDGMENTS  This work was part of Social Development and Scientific Research Projects of Shaanxi Province No. 2014JZ2-007 Science and Innovation Development Fund of Tangdu Hospital of Air Force Military Medical University (the Fourth Military Medical University) No. 2016LCYJ001
Received  2018-03-18
DOI: 10.12015/issn.1674-8034.2018.10.004
DOI:10.12015/issn.1674-8034.2018.10.004.

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