English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Objectives:To develop a framework for obtaining dynamic susceptibilitycontrast magnetic resonance imaging (DSC-MRI) derived relative cerebral bloodvolume (rCBV) maps without gadolinium-based contrast agent (GBCA) injection.Methods:This retrospective study included 146 patients (124 IDH wildtype; 22IDH mutation) diagnosed with glioma. The DSC-MRI-derived rCBV maps weresynthesized from intravoxel incoherent motion (IVIM) MRI data by the deepneural network trained only with IDH wildtype data due to thedata imbalance.Linear regression analysis, Pearson correlation coefficient, and Bland-Altmananalysis, were done to evaluate the consistency between real and synthetic rCBVmaps. The generalizability of the proposed framework was evaluated with IDHmutation data. IDH mutation status identification ability of real and syntheticrCBV maps was analyzed and compared using ROC analysis and the DeLong test.Results:Linear regression analysis shows a linear relationship between real andsynthetic rCBV maps with a relatively high Pearson correlation coefficient (IDHwildtype: Pearson P = 0.7536; IDH mutation: Pearson P = 0.8933). Bland-Altmananalysis between real and synthetic rCBV maps shows that almost all the datadistribute 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 theIDH mutation status identification abilities of real (AUC = 0.8375) andsynthetic rCBV (AUC = 0.8325) are comparable and show no significant difference(P = 0.9075). Conclusions:It is feasible to obtain DSC-MRI-derived rCBV mapswithout the injection of GBCA. The synthetic rCBV map shows high consistencywith real one.

DSC-MRI derived relative CBV maps synthesized from IVIM-MRI data:Application in glioma IDH mutation status identification