title: Differentiating low- and high-grade pediatric brain tumors using a continuous-time random-walk diffusion model at high b-values.
abstract: To demonstrate that a continuous-time random-walk (CTRW) diffusion model can improve diagnostic accuracy of differentiating low- and high-grade pediatric brain tumors.
  
  
  
  Fifty-four children with histopathologically confirmed brain tumors underwent diffusion MRI scans at 3Twith 12 b-values (0-4000 s/mm(2) ). The diffusion imageswere fit to a simplified CTRW model to extract anomalous diffusion coefficient, Dm , and temporal and spatial heterogeneity parameters, α and β, respectively. Using histopathology results as reference, a k-means clustering algorithm and a receiver operating characteristic (ROC) analysis were employed to determine the sensitivity, specificity, and diagnostic accuracy of the CTRW parameters in differentiating tumor grades.
  
  
  
  Significant differences between the low- and high-grade tumors were observed in the CTRW parameters (p-values<0.001). The k-means analysis showed that the combination of three CTRW parameters produced higher diagnostic accuracy (85% vs. 75%) and specificity (83% vs. 54%) than the apparent diffusion coefficient (ADC) from a mono-exponential model. The ROC analysis revealed that any combination of the CTRW parameters gave a larger area under the curve (0.90-0.96) than using ADC (0.80).
  
  
  
  With its sensitivity to intravoxel heterogeneity, the simplified CTRW model is useful for non-invasive grading of pediatric brain tumors, particularly when surgical biopsy is not feasible. Magn Reson Med 76:1149-1157, 2016. © 2015 Wiley Periodicals, Inc.
authors.affiliation: Center for MR Research, University of Illinois at Chicago, Chicago, Illinois, USA.
authors.forename: M Muge
authors.initials: MM
authors.lastname: Karaman
authors.affiliation: Center for MR Research, University of Illinois at Chicago, Chicago, Illinois, USA.|Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, USA.
authors.forename: Yi
authors.initials: Y
authors.lastname: Sui
authors.affiliation: Philips Research China, Shanghai, China.
authors.forename: He
authors.initials: H
authors.lastname: Wang
authors.affiliation: Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, USA.
authors.forename: Richard L
authors.initials: RL
authors.lastname: Magin
authors.affiliation: Xinhua Hospital, Shanghai, China.
authors.forename: Yuhua
authors.initials: Y
authors.lastname: Li
authors.affiliation: Center for MR Research, University of Illinois at Chicago, Chicago, Illinois, USA. xjzhou@uic.edu.|Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois, USA. xjzhou@uic.edu.|Department of Radiology, University of Illinois at Chicago, Chicago, Illinois, USA. xjzhou@uic.edu.|Department of Neurosurgery, University of Illinois at Chicago, Chicago, Illinois, USA. xjzhou@uic.edu.
authors.forename: Xiaohong Joe
authors.initials: XJ
authors.lastname: Zhou
mesh_terms: D000293:Adolescent; D000465:Algorithms; D001932:Brain Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology*; D002648:Child; D002675:Child, Preschool; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007223:Infant; D008297:Male; D015233:Models, Statistical; D060787:Neoplasm Grading; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: continuous-time-random-walk; high b-value diffusion imaging; non-Gaussian diffusion; pediatric brain tumor; tumor grading