  Objectives:To develop a framework for obtaining dynamic susceptibility
contrast magnetic resonance imaging (DSC-MRI) derived relative cerebral blood
volume (rCBV) maps without gadolinium-based contrast agent (GBCA) injection.
Methods:This retrospective study included 146 patients (124 IDH wildtype; 22
IDH mutation) diagnosed with glioma. The DSC-MRI-derived rCBV maps were
synthesized from intravoxel incoherent motion (IVIM) MRI data by the deep
neural network trained only with IDH wildtype data due to thedata imbalance.
Linear regression analysis, Pearson correlation coefficient, and Bland-Altman
analysis, were done to evaluate the consistency between real and synthetic rCBV
maps. The generalizability of the proposed framework was evaluated with IDH
mutation data. IDH mutation status identification ability of real and synthetic
rCBV maps was analyzed and compared using ROC analysis and the DeLong test.
Results:Linear regression analysis shows a linear relationship between real and
synthetic rCBV maps with a relatively high Pearson correlation coefficient (IDH
wildtype: Pearson P = 0.7536; IDH mutation: Pearson P = 0.8933). Bland-Altman
analysis between real and synthetic rCBV maps shows that almost all the data
distribute within the 95% limits of agreement (IDH wildtype: 19 of 20 [95%];
IDH mutation: 19 of 20 [95%]). ROC analysis and the DeLong test show that the
IDH mutation status identification abilities of real (AUC = 0.8375) and
synthetic rCBV (AUC = 0.8325) are comparable and show no significant difference
(P = 0.9075). Conclusions:It is feasible to obtain DSC-MRI-derived rCBV maps
without the injection of GBCA. The synthetic rCBV map shows high consistency
with real one.
