Fully automatic analysis of the knee articular cartilage T1ρ relaxation time using voxel-based relaxometry

• Published in: Journal of magnetic resonance imaging Vol. 43; no. 4; pp. 970 - 980
• Main Authors: Pedoia, Valentina, Li, Xiaojuan, Su, Favian, Calixto, Nathaniel, Majumdar, Sharmila
• Format: Journal Article
• Language: English
• Published: United States Blackwell Publishing Ltd 01.04.2016
• Subjects: ACL; Adult; Anterior Cruciate Ligament - pathology; Anterior Cruciate Ligament - surgery; Anterior Cruciate Ligament Reconstruction; atlas-based segmentation; Body Mass Index; Cartilage, Articular - diagnostic imaging; Cartilage, Articular - pathology; Cohort Studies; Female; Humans; Image Processing, Computer-Assisted - methods; Knee - diagnostic imaging; Knee - pathology; knee cartilage; Knee Injuries - diagnostic imaging; Knee Joint - diagnostic imaging; Knee Joint - pathology; Magnetic Resonance Imaging; Male; Menisci, Tibial - surgery; Middle Aged; osteoarthritis; Osteoarthritis, Knee - diagnostic imaging; Osteoarthritis, Knee - pathology; Pattern Recognition, Automated - methods; Software; T1ρ; voxel based relaxometry; Young Adult; ACL; atlas-based segmentation; T1ρ; knee cartilage; osteoarthritis; voxel based relaxometry
• ISSN: 1053-1807; 1522-2586
• DOI: 10.1002/jmri.25065

Purpose To develop and compare with the classical region of interest (ROI)‐based approach a fully automatic, local, and unbiased way of studying the knee T1ρ relaxation time by creating an atlas and using voxel‐based relaxometry (VBR) in osteoarthritis (OA) and anterior cruciate ligament (ACL) subjects. Materials and Methods In this study 110 subjects from two cohorts: 1) Mild OA 40 patients with mild‐OA Kellgren–Lawrence (KL) ≤ 2 and 15 controls KL ≤ 1; 2) ACL cohort (a model for early OA): 40 ACL‐injured patients imaged prior to ACL reconstruction and 1‐year postsurgery and 15 controls are analyzed. All the subjects were acquired at 3T with a protocol that includes: 3D‐FSE (CUBE) and 3D‐T1ρ. A nonrigid registration technique was applied to align all the images on a single template. This allows for performing VBR to assess local statistical differences of T1ρ values using z‐score analysis. VBR results were compared with those obtained with classical ROI‐based technique. Results ROI‐based results from atlas‐based segmentation were consistent with classical ROI‐based method (coefficient of variation [CV] = 3.83%). Voxel‐based group analysis revealed local patterns that were overlooked by the ROI‐based approach; eg, VBR showed posterior lateral femur and posterior lateral tibia significant T1ρ elevations in ACL‐injured patients (sample mean z‐score=9.7 and 10.3). Those elevations were overlooked by the classical ROI‐based approach (sample mean z‐score=1.87 and −1.73) Conclusion VBR is a feasible and accurate tool for the local evaluation of the biochemical composition of knee articular cartilage. VBR is capable of detecting specific local patterns on T1ρ maps in OA and ACL subjects. J. Magn. Reson. Imaging 2016;43:970–980