Accelerating anatomical 2D turbo spin echo imaging of the ankle using compressed sensing

Abstract

Introduction: To assess the feasibility and diagnostic value of compressed sensing for accelerating two-dimensional turbo spin echo imaging of the ankle.

Materials and methods: Ankles of 20 volunteers were scanned (mean age 30.2 ± 7.3 years, 13 men) at 3 T MRI. Coronal and sagittal intermediate-weighted (IM) sequences with fat saturation as well as axial T2- and coronal T1-weighted sequences were acquired using parallel imaging based on sensitivity encoding (SENSE) only as well as with a combination of compressed sensing (CS) and SENSE. Compressed sensing is a technique that acquires less data through k-space random undersampling and enables a reduction in total acquisition time by 20%. All images were reviewed by two radiologists, image quality was graded using a 5-point Likert scale and signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of different anatomical structures of the ankle were assessed and compared between sequences with SENSE only and with the combination of CS and SENSE using Wilcoxon signed-rank tests and Cohen's kappa.

Results: There was a substantial to perfect agreement for the rating between the images acquired with SENSE only and with the combination of CS and SENSE when assessing cartilage, subchondral bone and ligaments (κ = 0.75 - 0.89). SNR was slightly higher for the combination of CS and SENSE sequences compared to the sequences acquired with SENSE only, yet this finding was not significant (P = 0.18-0.62). Moreover, CNR of cartilage/fluid, subchondral bone/cartilage, ligaments/fluid and ligaments/fat did not show significant differences between the sequences acquired with SENSE only and the combination of CS and SENSE (P > 0.05). The interreader agreement was substantial to excellent for both techniques (κ=0.75 - 0.89).

Conclusions: Compressed sensing reduced the acquisition time of conventional MR imaging of the ankle by 20% without decreasing diagnostic image quality, SNR and CNR.

Keywords: Accelerated data acquisition; Diagnostic imaging; Magnetic resonance imaging; Musculoskeletal system; Sparse sampling.