title: Accelerated T1ρ acquisition for knee cartilage quantification using compressed sensing and data-driven parallel imaging: A feasibility study.
abstract: OBJECTIVE
  Quantitative T1ρ imaging is beneficial for early detection for osteoarthritis but has seen limited clinical use due to long scan times. In this study, we evaluated the feasibility of accelerated T1ρ mapping for knee cartilage quantification using a combination of compressed sensing (CS) and data-driven parallel imaging (ARC-Autocalibrating Reconstruction for Cartesian sampling).
  
  
  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 performed on a GE 3T MR750 scanner. T1ρ quantification after 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 increased with increasing acceleration, but for in vivo measurements, it stayed under 5% for a net acceleration factor up to 2, where the acquisition was 25% faster than the reference (only ARC).
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA.
authors.forename: Prachi
authors.initials: P
authors.lastname: Pandit
authors.affiliation: Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA.
authors.forename: Julien
authors.initials: J
authors.lastname: Rivoire
authors.affiliation: GE Healthcare, Waukesha, Wisconsin, USA.
authors.forename: Kevin
authors.initials: K
authors.lastname: King
authors.affiliation: Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA.
authors.forename: Xiaojuan
authors.initials: X
authors.lastname: Li
mesh_terms: D000465:Algorithms; D000818:Animals; D002358:Cartilage, Articular / Q000000981:diagnostic imaging*; D003198:Computer Simulation; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D019047:Phantoms, Imaging; D013264:Stifle / Q000000981:diagnostic imaging*; D013552:Swine
keywords: ARC; MRI; T1ρ; cartilage; compressed sensing