Highly accelerated real-time T2-weighted imaging with through-time radial GRAPPA and low-latency GPU reconstruction

Di Xu,Haris Saybasili,Shuo Han,Daniel A Herzka,Menekhem Zviman,Aravindan Kolandaivelu,Nicole Seiberlich,Henry Halperin,Mark A Griswold

doi:10.1186/1532-429x-16-s1-w33

Abstract

Background T2-weighted cardiac images are commonly used for edema detection [1-4]. However, neither black-blood TSE nor cine images can offer real-time edema monitoring, and are therefore not suitable for the guidance of cardiac ablation procedures. We proposed a radial T2weighted interrupted balanced SSFP (rT2W-iSSFP), a real-time high temporal resolution sequence targeted at monitoring edema.

Highlights

T2-weighted cardiac images are commonly used for edema detection [1,2,3,4]
TE-effective for the radial sequence is defined as the time from the beginning of the train to the median imaging echo. rT2W-iSSFP incorporates through-time radial GRAPPA to achieve high temporal resolution with high degrees of acceleration (R = 8) [5], (Figure 1) which was implemented on a 48-core hybrid system with a GPU (Tesla C1060, NVIDIA), achieving 10-20 fps image acquisition with 20 ms latency reconstruction and image display [6]
Simulations Bloch equation simulations were performed to evaluate the T2-weighting and the image quality of rT2W-iSSFP using a variant of the Shepp-Logan phantom containing 3 ellipsoids with different T1s and T2s to represent cerebrospinal fluid (CSF), liver, and myocardium (Figure 2a) [7,8]

Summary

Introduction

T2-weighted cardiac images are commonly used for edema detection [1,2,3,4]. neither black-blood TSE nor cine images can offer real-time edema monitoring, and are not suitable for the guidance of cardiac ablation procedures. Sequence rT2W-iSSFP generates T2-weighting with a series of 180° RF pulses. TE-effective for the radial sequence is defined as the time from the beginning of the train to the median imaging echo. RT2W-iSSFP incorporates through-time radial GRAPPA to achieve high temporal resolution with high degrees of acceleration (R = 8) [5], (Figure 1) which was implemented on a 48-core hybrid system with a GPU (Tesla C1060, NVIDIA), achieving 10-20 fps image acquisition with 20 ms latency reconstruction and image display [6].

Results

Conclusion