Knee imaging: Rapid three-dimensional fast spin-echo using compressed sensing

To investigate the feasibility of using compressed sensing (CS) to accelerate three-dimensional fast spin-echo (3D-FSE) imaging of the knee.

A 3D-FSE sequence was performed at 3T with CS (CUBE-CS with 3:16-minute scan time) and without CS (CUBE with 4:44-minute scan time) twice on the knees of 10 healthy volunteers to assess signal-to-noise ratio (SNR) using the addition-subtraction method and once on the knees of 50 symptomatic patients to assess diagnostic performance. SNR of cartilage, muscle, synovial fluid, and bone marrow on CUBE and CUBE-CS images were measured in the 10 healthy volunteers. The CUBE and CUBE-CS sequences of all 50 symptomatic patients were independently reviewed twice by two musculoskeletal radiologists. The radiologists used CUBE and CUBE-CS during each individual review to determine the presence or absence of knee joint pathology. Student's t-tests were used to compare SNR values between sequences, while the kappa statistic was used to determine agreement between sequences for detecting knee joint pathology. Sensitivity and specificity of CUBE and CUBE-CS for detecting knee joint pathology was also calculated in the 18 symptomatic patients who underwent subsequent arthroscopic knee surgery.

CUBE and CUBE-CS had similar SNR (P = 0.15-0.67) of cartilage, muscle, synovial fluid, and bone marrow. There was near-perfect to perfect agreement between CUBE and CUBE-CS for both radiologists for detecting cartilage and bone marrow edema lesions, medial and lateral meniscus tears, anterior cruciate ligament tears, effusions, and intra-articular bodies. CUBE and CUBE-CS had similar sensitivity (75.0-100%) and specificity (87.5-100%) for detecting 60 cartilage lesions, 20 meniscus tears, four anterior cruciate ligament tears, and four intra-articular bodies confirmed at surgery.

CS provided a 30% reduction in scan time for 3D-FSE imaging of the knee without a corresponding decrease in SNR or diagnostic performance.

1 J. MAGN. RESON. IMAGING 2017;45:1712-1722.