Real-time flow with fast GPU reconstruction for continuous assessment of cardiac output

摘要

Purpose: 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. Materials and Methods: 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. Results: 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. Conclusion: 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.