Ebner, M;
Patel, PA;
Atkinson, D;
Caselton, L;
Firmin, L;
Amin, Z;
Bainbridge, A;
... Vercauteren, T; + view all
(2019)
Super-resolution for upper abdominal MRI: Acquisition and post-processing protocol optimization using brain MRI control data and expert reader validation.
Magnetic Resonance in Medicine
, 82
(5)
pp. 1905-1919.
10.1002/mrm.27852.
Preview |
Text
Taylor_Super-resolution for upper abdominal MRI. Acquisition and post-processing protocol optimization using brain MRI control data and expert reader validation_AOP.pdf - Published Version Download (3MB) | Preview |
Abstract
Purpose Magnetic resonance (MR) cholangiopancreatography (MRCP) is an established specialist method for imaging the upper abdomen and biliary/pancreatic ducts. Due to limitations of either MR image contrast or low through‐plane resolution, patients may require further evaluation with contrast‐enhanced computed tomography (CT) images. However, CT fails to offer the high tissue‐ductal‐vessel contrast‐to‐noise ratio available on T2‐weighted MR imaging. Methods MR super‐resolution reconstruction (SRR) frameworks have the potential to provide high‐resolution visualizations from multiple low through‐plane resolution single‐shot T2‐weighted (SST2W) images as currently used during MRCP studies. Here, we (i) optimize the source image acquisition protocols by establishing the ideal number and orientation of SST2W series for MRCP SRR generation, (ii) optimize post‐processing protocols for two motion correction candidate frameworks for MRCP SRR, and (iii) perform an extensive validation of the overall potential of upper abdominal SRR, using four expert readers with subspeciality interest in hepato‐pancreatico‐biliary imaging. Results Obtained SRRs show demonstrable advantages over traditional SST2W MRCP data in terms of anatomical clarity and subjective radiologists’ preference scores for a range of anatomical regions that are especially critical for the management of cancer patients. Conclusions Our results underline the potential of using SRR alongside traditional MRCP data for improved clinical diagnosis.
Archive Staff Only
 |
View Item |
