Abstract
To demonstrate the feasibility of real-time phase contrast magnetic resonance (PCMR) assessment of continuous cardiac output with a heterogeneous (CPU/GPU) system for online image reconstruction.Twenty healthy volunteers underwent aortic flow examination during exercise using a real-time spiral PCMR sequence. Acquired data were reconstructed in online fashion using an iterative sensitivity encoding (SENSE) algorithm implemented on an external computer equipped with a GPU card. Importantly, data were sent back to the scanner console for viewing. A multithreaded CPU implementation of the real-time PCMR reconstruction was used as a reference point for the online GPU reconstruction assessment and validation. A semiautomated segmentation and registration algorithm was applied for flow data analysis.There was good agreement between the GPU and CPU reconstruction (-0.4 ± 0.8 mL). There was a significant speed-up compared to the CPU reconstruction (15×). This translated into the flow data being available on the scanner console ≈9 seconds after acquisition finished. This compares to an estimated time using the CPU implementation of 83 minutes.Our heterogeneous image reconstruction system provides a base for translation of complex MRI algorithms into clinical workflow. We demonstrated its feasibility using real-time PCMR assessment of continuous cardiac output as an example.
Highlights
Novel real-time phase contrast MR sequences allow assessment of flow during exercise
The batch reconstructed 7.7 times faster on the Graphical processing units (GPU) than CPU (15.2 if time required for data transmission is excluded)
Continuous assessment of flow during exercise could provide a novel way of assessing hemodynamic responses in patients
Summary
Novel real-time phase contrast MR sequences allow assessment of flow during exercise. Such sequences require a time-consuming reconstruction, which prevents continuous cardiac output monitoring during exercise. Graphical processing units (GPU) offer the possibility of performing fast reconstruction of real-time MR-data. Such reconstructions would make continuous assessment of cardiac output during exercise possible and uncover new areas in cardiovascular monitoring. The aim of this project is to validate a novel real-time flow sequence with online GPU-based reconstruction
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