title: A fractional motion diffusion model for grading pediatric brain tumors.
abstract: To demonstrate the feasibility of a novel fractional motion (FM) diffusion model for distinguishing low- versus high-grade pediatric brain tumors; and to investigate its possible advantage over apparent diffusion coefficient (ADC) and/or a previously reported continuous-time random-walk (CTRW) diffusion model.
  
  
  
  With approval from the institutional review board and written informed consents from the legal guardians of all participating patients, this study involved 70 children with histopathologically-proven brain tumors (30 low-grade and 40 high-grade). Multi-b-value diffusion images were acquired and analyzed using the FM, CTRW, and mono-exponential diffusion models. The FM parameters,Dfm,φ,ψ(non-Gaussian diffusion statistical measures), and the CTRW parameters,Dm,α,β(non-Gaussian temporal and spatial diffusion heterogeneity measures) were compared between the low- and high-grade tumor groups by using a Mann-Whitney-WilcoxonUtest. The performance of the FM model for differentiating between low- and high-grade tumors was evaluated and compared with that of the CTRW and the mono-exponential models using a receiver operating characteristic (ROC) analysis.
  
  
  
  The FM parameters were significantly lower (p< 0.0001) in the high-grade (Dfm: 0.81 ± 0.26,φ: 1.40 ± 0.10,ψ: 0.42 ± 0.11) than in the low-grade (Dfm: 1.52 ± 0.52,φ: 1.64 ± 0.13,ψ: 0.67 ± 0.13) tumor groups. The ROC analysis showed that the FM parameters offered better specificity (88% versus 73%), sensitivity (90% versus 82%), accuracy (88% versus 78%), and area under the curve (AUC, 93% versus 80%) in discriminating tumor malignancy compared to the conventional ADC. The performance of the FM model was similar to that of the CTRW model.
  
  
  
  Similar to the CTRW model, the FM model can improve differentiation between low- and high-grade pediatric brain tumors over ADC.
authors.affiliation: Center for MR Research, University of Illinois at Chicago, Chicago, IL, USA.
authors.forename: M Muge
authors.initials: MM
authors.lastname: Karaman
authors.affiliation: Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
authors.forename: He
authors.initials: H
authors.lastname: Wang
authors.affiliation: Center for MR Research, University of Illinois at Chicago, Chicago, IL, USA; Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA.
authors.forename: Yi
authors.initials: Y
authors.lastname: Sui
authors.affiliation: Department of Neurosurgery, University of Illinois at Chicago, Chicago, IL, USA.
authors.forename: Herbert H
authors.initials: HH
authors.lastname: Engelhard
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, IL, USA; Department of Radiology, University of Illinois at Chicago, Chicago, IL, USA; Department of Neurosurgery, University of Illinois at Chicago, Chicago, IL, USA; Department of Bioengineering, University of Illinois at Chicago, Chicago, IL, USA.
authors.forename: Xiaohong Joe
authors.initials: XJ
authors.lastname: Zhou
mesh_terms: D001932:Brain Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology*; D002648:Child; D002675:Child, Preschool; D003198:Computer Simulation; D004058:Diffusion; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D007223:Infant; D008279:Magnetic Resonance Imaging; D008297:Male; D060787:Neoplasm Grading; D012372:ROC Curve
keywords: Anomalous diffusion; Continuous-time random-walk; Fractional motion; Non-Gaussian diffusion models; Pediatric brain tumor; Tumor grading