A fractional motion diffusion model for grading pediatric brain tumors.

M Muge Karaman,Xiaohong Joe Zhou,Herbert H Engelhard,Yuhua Li,He Wang,Yi Sui

doi:10.1016/j.nicl.2016.10.003

Abstract

ObjectivesTo 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.Materials and methodsWith 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-Wilcoxon U test. 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.ResultsThe 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.ConclusionsSimilar to the CTRW model, the FM model can improve differentiation between low- and high-grade pediatric brain tumors over ADC.

Highlights

IntroductionDiffusion-weighted imaging (DWI) has been investigated for brain tumor grading based on the apparent diffusion coefficient (ADC) (Kono et al, 2001; Tien et al, 1994; Provenzale et al, 2006; Cha, 2006; Maier et al, 2010)
The present study aims at investigating whether the diffusion statistical properties revealed by the fractional motion (FM) model can be applied to differentiating low- from high-grade pediatric brain tumors, and whether the FM model offers an advantage over the mono-exponential and the continuous-time random-walk (CTRW) models
We have demonstrated that a novel diffusion model, the FM model, can provide a set of parameters (Dfm, φ, ψ) that improved

Summary

Introduction

Diffusion-weighted imaging (DWI) has been investigated for brain tumor grading based on the apparent diffusion coefficient (ADC) (Kono et al, 2001; Tien et al, 1994; Provenzale et al, 2006; Cha, 2006; Maier et al, 2010) This parameter, which is computed using a mono-exponential model (i.e., the Gaussian model), has been found to be sensitive to tissue cellularity changes associated with the neoplastic as well as other pathologic processes (Stadnik et al, 2001; Schaefer et al, 2000; Rowley et al, 1999; Moffat et al, 2005). The mismatch between the mono-exponential model and the actual diffusion process is believed to be responsible, as least partially, for the substantial overlap in ADC values between low- and high-grade brain tumors (Kono et al, 2001; Maier et al, 2010; Yamasaki et al, 2005; Poretti et al, 2012)

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