Accelerated T1ρ acquisition for knee cartilage quantification using compressed sensing and data‐driven parallel imaging: A feasibility study

Abstract

Purpose Quantitative T1ρ imaging is beneficial for early detection for osteoarthritis, but has seen limited clinical use due to long scan times. This work evaluates the feasibility of accelerated T1ρ mapping for knee cartilage quantification using a combination of compressed sensing (CS) and data-driven parallel imaging (ARC). Methods A sequential combination of ARC and CS, both during data acquisition and reconstruction, was used to accelerate the acquisition of T1ρ maps. Phantom, ex vivo (porcine knee) and in vivo (human knee) imaging was carried out on a GE 3T MR750 scanner. T1ρ quantification post CS-accelerated acquisition was compared with non CS-accelerated acquisition for various cartilage compartments. Results Accelerating image acquisition using CS did not introduce major deviations in quantification. The coefficient of variation for the root mean squared error (CV(RMSE)) increased with increasing acceleration, but for in vivo measurements, it stayed under 5% for net acceleration factor up to 2, where the acquisition was 25% faster than the reference (only ARC). Conclusion To the best of our knowledge this is the first implementation of CS for in vivo T1ρ quantification. These early results show that this technique holds great promise in making quantitative imaging techniques more accessible for clinical applications.

Sparse Reconstruction Techniques in Magnetic Resonance Imaging

“…It has been shown that sparse reconstructions can be used for faster and yet accurate quantitative sodium imaging of knee cartilage at 7T, opening the door for sodium imaging-based quantitative assessment of osteoarthritis 170 . Quantification of T 1ρ similarly holds promise for characterization of osteoarthritis, and acceleration of T 1ρ mapping in the knee has been demonstrated in early feasibility studies 171,172 . Accelerated dynamic functional metabolic imaging of phosphocreatine kinetics after calf muscle exercise has also been shown for 3D 31 P spectroscopic imaging at 7T 173 .…”

Rapid compositional mapping of knee cartilage with compressed sensing MRI

“…The reconstruction problem can be formulated as: where x is a vector that represents the reconstructed set of relaxation‐weighted images, with its original size of , y is a vector that represents the captured k ‐space data for all relaxation‐weighted images, its original size is k y × k z × c × p , where c is the number of receive coils, and the matrix E represents the encoding matrix mapping x to y , containing coil sensitivities (when parallel imaging and CS is jointly used, Fourier transforms, and sampling pattern . Many CS methods for knee cartilage use the joint parallel imaging and CS approach to achieve higher undersampling rates, as shown previously . The use of squared l 2 ‐norm, or Euclidean norm, , is quite common either because it is related to the usual assumption of Gaussian noise, or because it leads to a more tractable mathematical problem.…”

“…Pandit et al combined CS with autocalibrating reconstruction for Cartesian sampling (ARC) . They reported acceleration factors of 3 compared to the fully sampled acquisition, but the resulting acquisition time of 3 minutes is what is typically observed in other CS studies.…”

Accelerated whole brain intracranial vessel wall imaging using black blood fast spin echo with compressed sensing (CS-SPACE)

“…CS has been used to accelerate black blood extracranial T1 weighted carotid plaque imaging using 3D gradient echo sequences [16, 17], and also for the T2 mapping of the carotid plaque using a 3D fast-spin-echo (CUBE) technique [18]. The combination of CS and PI has also been used in different clinical applications, including the breast [19], carotid plaque [20], abdomen [21] and musculoskeletal disorders [22, 23]. …”