title: Glioma: application of whole-tumor texture analysis of diffusion-weighted imaging for the evaluation of tumor heterogeneity.
abstract: OBJECTIVE
  To apply a texture analysis of apparent diffusion coefficient (ADC) maps to evaluate glioma heterogeneity, which was correlated with tumor grade.
  
  
  METHODS
  Forty patients with glioma (WHO grade II (n = 8), grade III (n = 10) and grade IV (n = 22)) underwent diffusion-weighted imaging (DWI), and the corresponding ADC maps were obtained. Regions of interest containing the lesions were drawn on every section of the ADC map containing the tumor, and volume-based data of the entire tumor were constructed. Texture and first order features including entropy, skewness and kurtosis were derived from the ADC map using in-house software. A histogram analysis of the ADC map was also performed. The texture and histogram parameters were compared between low-grade and high-grade gliomas using an unpaired student's t-test. Additionally, a one-way analysis of variance analysis with a post-hoc test was performed to compare the parameters of each grade.
  
  
  RESULTS
  Entropy was observed to be significantly higher in high-grade gliomas than low-grade tumors (6.861±0.539 vs. 6.261±0.412, P  = 0.006). The fifth percentiles of the ADC cumulative histogram also showed a significant difference between high and low grade gliomas (836±235 vs. 1030±185, P = 0.037). Only entropy proved to be significantly different between grades III and IV (6.295±0.4963 vs. 7.119±0.3165, P<0.001). The diagnostic accuracy of ADC entropy was significantly higher than that of the fifth percentile of the ADC histogram (P = 0.0034) in distinguishing high- from low-grade glioma.
  
  
  CONCLUSIONS
  A texture analysis of the ADC map based on the entire tumor volume can be useful for evaluating glioma grade, which provides tumor heterogeneity.
authors.affiliation: Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.
authors.forename: Young Jin
authors.initials: YJ
authors.lastname: Ryu
authors.affiliation: Department of Radiology, Seoul National University College of Medicine, Seoul, Korea; Center for Nanoparticle Research, Institute for Basic Science, and School of Chemical and Biological Engineering, Seoul National University, Seoul, Korea.
authors.forename: Seung Hong
authors.initials: SH
authors.lastname: Choi
authors.affiliation: Department of Radiology, Seoul National University College of Medicine, Seoul, Korea; Biomedical Research Institute, Seoul National University Hospital, Seoul, Korea; Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul, Korea.
authors.forename: Sang Joon
authors.initials: SJ
authors.lastname: Park
authors.affiliation: Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.
authors.forename: Tae Jin
authors.initials: TJ
authors.lastname: Yun
authors.affiliation: Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.
authors.forename: Ji-Hoon
authors.initials: JH
authors.lastname: Kim
authors.affiliation: Department of Radiology, Seoul National University College of Medicine, Seoul, Korea.
authors.forename: Chul-Ho
authors.initials: CH
authors.lastname: Sohn
mesh_terms: D000328:Adult; D001932:Brain Neoplasms / Q000175:diagnosis* / Q000235:genetics / Q000473:pathology; D038524:Diffusion Magnetic Resonance Imaging / Q000706:statistics & numerical data*; D019277:Entropy; D015870:Gene Expression; D005910:Glioma / Q000175:diagnosis* / Q000235:genetics / Q000473:pathology; D006801:Humans; D007089:Image Enhancement; D007090:Image Interpretation, Computer-Assisted; D019394:Ki-67 Antigen / Q000235:genetics; D008297:Male; D008875:Middle Aged; D060787:Neoplasm Grading; D012680:Sensitivity and Specificity; D047368:Tumor Burden
chemical_list: D019394:Ki-67 Antigen