## 4 Discussion
\begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Author** & **Grade** & **\(p\) Value** & **Cutoff** & **Sensitivity (\%)** & **Specificity (\%)** & **AUC** \\
**[Reference No.]** & **(Mean \(\pm\) SD)** & & **\(p\) Value** & **Cutoff** & **Sensitivity (\%)** & **Specificity (\%)** & **AUC** \\ \hline [PERSON] [26] & Low-grade & High-grade & & & & & \\ [PERSON] [16] & 1.40 \(\pm\) 0.26 & & 1.08 \(\pm\) 0.27 & \(<\)0.001 & NA & 73.0 & 76.2 & 0.804 \\ [PERSON] [16] & 1.55 \(\pm\) 0.28 & & 0.92 \(\pm\) 0.24 & 0.023 & 1.03 & 76.5 & 100.0 & 0.902 \\ [PERSON] [18] & 1.58 \(\pm\) 0.21 & & 1.20 \(\pm\) 0.27 & \(<\)0.001 & NA & NA & NA & NA \\ [PERSON] [17] & 1.23 (1.15-1.32) \({}^{\star}\) & & 0.79 (0.69-0.88)\({}^{\star}\) & \(<\)0.001 & 0.92 & 75.0 & 95.8 & 0.906 \\  & Grade 1 & Grade 2 & Grade 3 & & & & \\ [PERSON] [20] & 1.41 (0.68–2.00) \(\dagger\) & 1.15 (1.06–2.10) \(\dagger\) & 0.74 (0.17–2.18) \(\dagger\) & \(<\)0.001 & NA & NA & NA & NA \\ [PERSON] [14] & 1.00 (0.92–11.14) \(\dagger\) & 0.83 (0.75–0.92) \(\dagger\) & 0.74 (0.62–0.85) \(\dagger\) & \(<\)0.001 & NA & NA & NA & NA \\ \hline \hline \end{tabular}  
* mean (95%CI), \(\dagger\) median (IQR). AUC, area under curve; SD, standard deviation.  
\end{table} 
Table 3: Diagnostic performance of ADC value to differentiate high-grade disease from low-grade disease. Although the ADC is reportedly associated with the prognosis of patients with several malignancies such as breast cancer and gastric cancer [32; 33], the prognostic role of the ADC has not yet been fully evaluated. Recent studies on bladder cancer have also reported the prognostic significance of ADC values in terms of disease-specific survival [34; 35]. Another study showed that ADC values could predict sensitivity to chemoradiotherapy in patients with MIBC [36]. These findings suggest that the measurement of ADC values is helpful for counseling patients on prognosis and for considering a chemoradiation-based bladder-sparing strategy in MIBC patients. However, due to the exploratory findings derived from studies consisting of a relatively small number of patients, further studies are needed to validate and confirm the prognostic role of the ADC in bladder cancer patients. Although the mono-exponential model is generally used to measure ADC values, blood flow in capillaries in a voxel of an MR image moves much faster than water molecule diffusion. As the b-value increases, the deviation from the mono-exponential decay becomes non-negligible. To overcome the intrinsic limitation of ADC values, non-mono-exponential models, such as the intravoxel incoherent motion (IVIM) [37] and FROC [38] models, have been developed to resolve the variability of ADC values. IVIM can distinguish the incoherent motion of water molecules within capillaries from molecular diffusion in the extravascular space [39]. IVIM-derived parameters (D, D\({}^{\prime}\), and f) were generated using a biexponential model. [PERSON] et al. [40] reported that IVIM-derived parameters could predict the aggressiveness of bladder cancer according to pathologic phenotypes: low aggressiveness, Ta of any grade and T1 with low-grade; intermediate aggressiveness, T1 with high-grade; and high aggressiveness, T2-T4 with any grade. In their study, ADC values showed slightly better diagnostic abilities than the IVIM-derived parameters to predict aggressiveness of bladder cancer. [PERSON] et al. [26] reported that FROC parameters, which describe anomalous diffusion processes in complex biological tissues [38], were useful in distinguishing MIBC from NMIBC and in predicting histological grade in bladder cancer, and they outperformed ADC values in predicting histological grade. The combination of these novel parameters with ADC values is expected to improve the accuracy of preoperative diagnosis. The VI-RADS has recently been shown to be useful in differentiating MIBC from NMIBC [9].