CSF quantification study is typically useful in pediatric and elderly population for normal pressure hydrocephalus (NPH). In these population, scan time reduction is particularly useful for patient cooperation and comfort. The potential for CS to accelerate MRI acquisition without hampering image quality will increase patient comfort and compliance in CSF quantification. The purpose of this study is to quantitatively evaluate the impact of Compressed-SENSE (CS), the latest image acceleration technique that combines compressed sensing with parallel imaging (or SENSE), on acquisition time and image quality in MR imaging of the Cerebrospinal fluid quantification study.
Standard in-practice CSF quantification study includes a 2D-gradient echo sequence for flow visualization and 2D-gradient echo T1 weighted phase-contrast sequence for flow quantification. Both these sequences were pulse gated using PPU triggering, planned perpendicular to the mid-aqueduct. Both these sequences were modified to obtain higher acceleration with CS (Table 1). Ten volunteers were scanned both, with and without CS, on a 3.0 T wide-bore MRI (Ingenia, Philips Health Systems). The study was approved by the IRB. The flow quantification was done using IntelliSpace Portal, version 9, Q-Flow analysis package (Philips Health Systems). Absolute stroke volume, mean velocity and regurgitant fraction were calculated for flow-quantification sequence with and without CS. Correlation between these three parameters for CS protocol and non-CS protocol were statistically evaluated using Spearman’s rank correlation test.
There is no significant difference in image quality between the current standard of care and CS-based accelerated CSF quantification MRI scans. Compressed-SENSE in this segment can reliably replace the existing scan protocol of higher acquisition time without loss in image quality, quantifications and at the same time with a significant reduction in scan time. The compressed-SENSE technique was originally designed for scan time acceleration of qualitative MRI . In this work, CS proves to have the potential of being extended to quantitative MRI without any significant information loss and 44% scan time reduction.
The EPOS can be viewed here: http://dx.doi.org/10.26044/ecr2020/C-05874
