Junqi Xu^{1}, He Wang^{1,2}, Xueying Zhao^{1}, Hui Zhang^{1}, Xiaoyuan Feng^{3}, and Ren Yan^{3}

^{1}Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China, ^{2}Human Phenome Institute, Fudan University, Shanghai, China, ^{3}Radiology, Huashan Hospital, Fudan University, Shanghai, China

To offer a potential multiparameter-mapping platform for clinical pathological diagnosis using multi-diffusion models including mono-exponentional model, IVIM, SEM, FROC, CTRW, SM and DKI. The U-test and ROC analysis show the superiority of FROC, CTRW and DKI models in diagnostic accuracy for grading brain tumors (at 0.770, 0.780 and 0.817 respectively).

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Fig. 1 All models of diffusion MR imaging. This image
shows one patient with high-grade brain tumor, where the first image is DWI at b = 1500s/mm^{2}and from image
a) to p) represents "ADCmap", "Dmap", "D_{f} map", "Dsmap" of IVIM ,"DDCmap","$$$\alpha$$$map" of SEM,"Dmap","$$$\mu$$$map","$$$\beta_f$$$map" of FROC,"Dcmap","$$$\alpha_c$$$map","$$$\beta_c$$$map" of CTRW, "D_{k }map","Kmap"of DKI and "ADC_{S}map ” of SM respectively.

Tabel.1
16 parameters ROC analysis with AUC (accuracy), sensitivity, specificity and P
values from U-tes

Fig.
2
Jointly parameters in each models and this picture shows ROC analysis of 7
models.