QQ‐NET – using deep learning to solve quantitative susceptibility mapping and quantitative blood oxygen level dependent magnitude (QSM+qBOLD or QQ) based oxygen extraction fraction (OEF) mapping

Author(s):  
Junghun Cho ◽  
Jinwei Zhang ◽  
Pascal Spincemaille ◽  
Hang Zhang ◽  
Simon Hubertus ◽  
...  
2015 ◽  
Vol 36 (8) ◽  
pp. 1424-1433 ◽  
Author(s):  
Kohsuke Kudo ◽  
Tian Liu ◽  
Toshiyuki Murakami ◽  
Jonathan Goodwin ◽  
Ikuko Uwano ◽  
...  

The purposes of this study are to establish oxygen extraction fraction (OEF) measurements using quantitative susceptibility mapping (QSM) of magnetic resonance imaging (MRI), and to compare QSM–OEF data with the gold standard 15O positron emission tomography (PET). Twenty-six patients with chronic unilateral internal carotid artery or middle cerebral artery stenosis or occlusion, and 15 normal subjects were included. MRI scans were conducted using a 3.0 Tesla scanner with a three-dimensional spoiled gradient recalled sequence. QSM images were created using the morphology-enabled dipole inversion method, and OEF maps were generated from QSM images using extraction of venous susceptibility induced by deoxygenated hemoglobin. Significant correlation of relative OEF ratio to contra-lateral hemisphere between QSM–OEF and PET–OEF was observed (r = 0.62, p < 0.001). The local (intra-section) correlation was also significant (r = 0.52, p < 0.001) in patients with increased PET–OEF. The sensitivity and specificity of OEF increase in QSM was 0.63 (5/8) and 0.89 (16/18), respectively, in comparison with PET. In conclusion, good correlation was achieved between QSM–OEF and PET–OEF in the identification of elevated OEF in affected hemispheres of patients with unilateral chronic steno-occlusive disease.


Sign in / Sign up

Export Citation Format

Share Document