Parallel imaging compressed sensing for accelerated imaging and improved signal-to-noise ratio in MRI-based postimplant dosimetry of prostate brachytherapy

Purpose: To investigate the feasibility of using parallel imaging compressed sensing (PICS) to reduce scan time and improve signal-to-noise ratio (SNR) in MRI-based postimplant dosimetry of prostate brachytherapy. Methods and Materials: Ten patients underwent low-dose-rate prostate brachytherapy with radioactive seeds stranded with positive magnetic resonance-signal seed markers and were scanned on a Siemens 1.5T Aera. MRI comprised a fully balanced steady-state free precession sequence with two 18-channel external pelvic array coils with and without a rigid two-channel endorectal coil. The fully sampled data sets were retrospectively subsampled with increasing acceleration factors and reconstructed with parallel imaging and compressed sensing algorithms. The images were assessed in a blinded reader study by board-certified care providers. Rating scores were compared for statistically significant differences between reconstruction types. Results: Images reconstructed from subsampling up to an acceleration factor of 4 with PICS demonstrated consistently sufficient quality for dosimetry with no apparent loss of SNR, anatomy depiction, or seed/marker conspicuity when compared to the fully sampled images. Images obtained with acceleration factors of 5 or 6 revealed reduced spatial resolution and seed marker contrast. Nevertheless, the reader study revealed that images obtained with an acceleration factor of up to 5 and reconstructed with PICS were adequate-to-good for postimplant dosimetry. Conclusions: Combined parallel imaging and compressed sensing can substantially reduce scan time in fully balanced steady-state free precession imaging of the prostate while maintaining adequate-to-good image quality for postimplant dosimetry. The saved scan time can be used for multiple signal averages and improved SNR, potentially obviating the need for an endorectal coil in MRI-based postimplant dosimetry.