Compressed Sensing–Sensitivity Encoding (CS-SENSE) Accelerated Brain Imaging: Reduced Scan Time without Reduced Image Quality

Abstract

BACKGROUND AND PURPOSE:Compressed sensing-sensitivity encoding is a promising MR imaging acceleration technique. This study compares the image quality of compressed sensing-sensitivity encoding accelerated imaging with conventional MR imaging sequences. MATERIALS AND METHODS:Patients with known, treated, or suspected brain tumors underwent compressed sensing-sensitivity encoding accelerated 3D T1-echo-spoiled gradient echo or 3D T2-FLAIR sequences in addition to the corresponding conventional acquisition as part of their clinical brain MR imaging. Two neuroradiologists blinded to sequence and patient information independently evaluated both the accelerated and corresponding conventional acquisitions. The sequences were evaluated on 4-or 5-point Likert scales for overall image quality, SNR, extent/severity of artifacts, and gray-white junction and lesion boundary sharpness. SNR and contrast-to-noise ratio values were compared. RESULTS:Sixty-six patients were included in the study. For T1-echo-spoiled gradient echo, image quality in all 5 metrics was slightly better for compressed sensing-sensitivity encoding than conventional images on average, though it was not statistically significant, and the lower bounds of the 95% confidence intervals indicated that compressed sensing-sensitivity encoding image quality was within 10% of conventional imaging. For T2-FLAIR, image quality of the compressed sensing-sensitivity encoding images was within 10% of the conventional images on average for 3 of 5 metrics. The compressed sensing-sensitivity encoding images had somewhat more artifacts (P ϭ .068) and less gray-white matter sharpness (P ϭ .36) than the conventional images, though neither difference was significant. There was no significant difference in the SNR and contrast-to-noise ratio. There was 25% and 35% scan-time reduction with compressed sensing-sensitivity encoding for FLAIR and echo-spoiled gradient echo sequences, respectively. CONCLUSIONS:Compressed sensing-sensitivity encoding accelerated 3D T1-echo-spoiled gradient echo and T2-FLAIR sequences of the brain show image quality similar to that of standard acquisitions with reduced scan time. Compressed sensing-sensitivity encoding may reduce scan time without sacrificing image quality. ABBREVIATIONS:CNR ϭ contrast-to-noise ratio; CS ϭ compressed sensing; SENSE ϭ sensitivity encoding; SPGR ϭ echo-spoiled gradient echo

Reduction of procedure times in routine clinical practice with Compressed SENSE magnetic resonance imaging technique

“…Analysis was limited to six body regions and to examinations performed on 1.5T MR scanner. Apart from our initial image quality assessments described in this study, other studies confirm the unchanged image quality if sequences are scanned with Compressed Sensing techniques [11–14]. Especially in a neuroradiological and musculoskeletal setting the image impression and quality was described as comparable in comparison to images acquired without Compressed SENSE if denoising level and Compressed Sense factor were chosen accordingly [11–14].…”

Analysis of Magnetic Resonance Signals from Diffusion Weighted Imaging using Compressed Sensitivity Encoding Technique

“…However, the overall SNR of the TSE-DWI using CS was higher than that using SENSE. This may be supported by the iterative reconstruction from variable-density random under-sampling of k-space data, which may contribute to improvements in the SNR [12].…”

“…A study by Yoshida et al evaluated the relationship between the image quality of TSE-DWI and various sensitivity encoding (SENSE) acceleration factors (AFs) [11], and recent advances in combining compressed sensing and SENSE-based parallel imaging (PI) techniques, so called compressed SENSE (CS), can reduce scan times further than conventional PI techniques, while maintaining image quality [12,13]. However, there is currently no report directly comparing CS and conventional SENSE TSE-DWI sequences.…”

“…The CS acquisition involves a combination of compressed sensing and SENSE to obtain a balanced incoherent under-sampled acquisition of variable density, and then iterative reconstruction to remove the aliasing artifact, thereby resulting in a clean image without artifact [12,13,15]. The main difference between SENSE and CS is that the CS image is transformed into the wavelet domain, where information in the image is represented at different spatial scales and can be relatively sparse.…”

Application of Image Fusion in Diagnosis and Treatment of Liver Cancer

“…As a result, one research challenge and focus is to further improve the single modalities. These may include the reduction of the rising cost of these medical images, decreasing the patient's exposure time to radiation, while maintaining the image quality [185,186]. In addition, current clinical application of image fusion is still limited to merge the medical images from two independent medical devices.…”