Yi Sui MS, Presenter: Nothing to Disclose

Ying Xiong, Abstract Co-Author: Nothing to Disclose

Karen Xie DO, Abstract Co-Author: Nothing to Disclose

Frederick C. Damen PhD, Abstract Co-Author: Nothing to Disclose

Xiaohong Joe Zhou PhD, Abstract Co-Author: Nothing to Disclose

Wenzhen Zhu MD, PhD, Abstract Co-Author: Nothing to Disclose

To investigate the feasibility of using a set of novel parameters from a non-Gaussian diffusion imaging model to differentiate low-grade from high-grade gliomas.

The study was performed on 27 patients with diagnosed gliomas, including 13 WHO low grade (I or II) and 14 WHO high grade (III or IV) tumors. MRI scans were conducted at 3Tesla using an 8-channel head coil. In addition to T1, T2, FLAIR and T1+C images, diffusion images with 17 b-values (0-4000 sec/mm2) were acquired in order to apply a new non-Gaussian diffusion model, known as fractional order calculus (FROC) model in which tissue microstructural information can be directly obtained. A set of FROC parametric maps (ADC, intra-voxel tissue heterogeneity index β, and mean free diffusion length µ) was calculated. The tumor ROIs were drawn on the diffusion images by an experienced neuro-radiologist, guided by anatomic images. Areas of necrosis, cyst, hemorrhage and edema were avoided. The parameter values averaged from the entire ROI of each tumor were used to differentiate low grade from high grade gliomas. ADC, β and µ were also combined using a binary logistic regression method for tumor differentiation. The difference in those parameters between the two tumor groups was analyzed using a Mann-Whitney U-test. The performance of tumor differentiation was further evaluated by an ROC analysis on each individual parameter and the combination of all parameters.

Significant differences between the low and high grade glioma groups were found in ADC (1.7 ± 0.5 µm2/ms vs 1.1 ± 0.4 µm2/ms, p = 0.005) and β (0.84 ± 0.06 vs 0.77 ± 0.04, p = 0.001), but not in µ (8.7 ± 0.6 µm vs 8.1 ± 0.7 µm, p = 0.06). The AUC values for ADC, β and µ were 0.817, 0.876 and 0.722, respectively, suggesting that individually β was the best indicator. The AUC value was further increased to 0.953 when combining all three parameters of the FROC diffusion model. 

The use of high b-value diffusion MRI together with a non-Gaussian diffusion model – the FROC model - can effectively differentiate high-grade from low-grade gliomas. 

High b-value diffusion imaging and non-Gaussian diffusion analysis have great potential for differential diagnosis of gliomas, and thereby providing valuable information for glioma patient management.

Sui, Y, Xiong, Y, Xie, K, Damen, F, Zhou, X, Zhu, W, Differentiation of Low Grade and High Grade Gliomas Using A Non-Gaussian Diffusion Imaging Model.  Radiological Society of North America 2014 Scientific Assembly and Annual Meeting, - ,Chicago IL. http://archive.rsna.org/2014/14019047.html