title: Principal component analysis-T1ρvoxel based relaxometry of the articular cartilage: a comparison of biochemical patterns in osteoarthritis and anterior cruciate ligament subjects.
abstract: BACKGROUND
  Quantitative MR, including T1ρmapping, has been extensively used to probe early biochemical changes in knee articular cartilage of subjects with osteoarthritis (OA) and others at risk for cartilage degeneration, such as those with anterior cruciate ligament (ACL) injury and reconstruction. However, limited studies have been performed aimed to assess the spatial location and patterns of T1ρ. In this study we used a novel voxel-based relaxometry (VBR) technique coupled with principal component analysis (PCA) to extract relevant features so as to describe regional patterns and to investigate their similarities and differences in T1ρmaps in subjects with OA and subjects six months after ACL reconstruction (ACLR).
  
  
  METHODS
  T1ρquantitative MRI images were collected for 180 subjects from two separate cohorts. TheOA cohortincluded 93 osteoarthritic patients and 25 age-matched controls. TheACLR-6M cohortincluded 52 patients with unilateral ACL tears who were imaged 6 months after ACL reconstruction, and 10 age-matched controls. Non-rigid registration on a single template and local Z-score conversion were adopted for T1ρspatial and intensity normalization of all the images in the dataset. PCA was used as a data dimensionality reduction to obtain a description of all subjects in a 10-dimensional feature space. Logistic linear regression was used to identify distinctive features of OA and ACL subjects.
  
  
  RESULTS
  Global prolongation of the Z-score was observed in both OA and ACL subjects compared to controls [higher values in 1stprincipal component (PC1); P=0.01]. In addition, relaxation time differences between superficial and deep cartilage layers of the lateral tibia and trochlea were observed to be significant distinctive features between OA and ACL subjects. OA subjects demonstrated similar values between the two cartilage layers [higher value in 2ndprincipal component (PC2); P=0.008], while ACL reconstructed subjects showed T1ρprolongation specifically in the cartilage superficial layer (lower values in PC2; P<0.0001). T1ρelevation located outside of the weight-bearing area, located in the posterior and anterior aspects of the lateral femoral compartment, was also observed to be a key feature in distinguishing OA subjects from controls [higher value in 6thprincipal component (PC6); P=0.007].
  
  
  CONCLUSIONS
  This study is the first example of T1ρlocal/regional pattern analysis and data-driven feature extraction in knees with cartilage degeneration. Our results revealed similarities and differences between OA and ACL relaxation patterns that could be potentially useful to better understand the pathogenesis of post-traumatic cartilage degeneration and the identification of imaging biomarkers for the early stratification of subjects at risk for developing post-traumatic OA.
authors.affiliation: Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
authors.forename: Valentina
authors.initials: V
authors.lastname: Pedoia
authors.affiliation: Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
authors.forename: Colin
authors.initials: C
authors.lastname: Russell
authors.affiliation: Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
authors.forename: Allison
authors.initials: A
authors.lastname: Randolph
authors.affiliation: Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
authors.forename: Xiaojuan
authors.initials: X
authors.lastname: Li
authors.affiliation: Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA.
authors.forename: Sharmila
authors.initials: S
authors.lastname: Majumdar
keywords: T1ρ; anterior cruciate ligament (ACL); osteoarthritis (OA); principal component analysis (PCA); voxel based relaxometry