OBJECTIVE: The aim of this study was to evaluate the reliability of a software tool that assesses knee cartilage volumes using magnetic resonance (MR) images. The objectives were to assess measurement reliability by: (1) determining the differences between readings of the same image made by the same reader 2 weeks apart (test-retest reliability), (2) determining the differences between the readings of the same image made by different readers (between-reader agreement), and (3) determining the differences between the cartilage volume readings obtained from two MR images of the same knee image acquired a few hours apart (patient positioning reliability). METHODS: Forty-eight MR examinations of the knee from normal subjects, patients with different stages of symptomatic knee osteoarthritis (OA), and a subset of duplicate images were independently and blindly quantified by three readers using the imaging system. The following cartilage areas were analyzed to compute volumes: global cartilage, medial and lateral compartments, and medial and lateral femoral condyles. RESULTS: Between-reader agreement of measurements was excellent, as shown by intra-class correlation (ICC) coefficients ranging from 0.958 to 0.997 for global cartilage (P<0.0001), 0.974 to 0.998 for the compartments (P<0.0001), and 0.943 to 0.999 for the condyles(P<0.0001). Test-retest reliability of within-reader data was also excellent, with Pearson correlation coefficients ranging from 0.978 to 0.999 (P<0.0001). Patient positioning reliability was also excellent, with Pearson correlation coefficients ranging from 0.978 to 0.999 (P<0.0001). CONCLUSIONS: The results of this study establish the reliability of this MR imaging system. Test-retest reliability, between-reader agreement, and patient positioning reliability were all extremely high. This study represents a first step in the overall validation of an imaging system designed to follow progression of human knee OA.
OBJECTIVE: The aim of this study was to evaluate the reliability of a software tool that assesses knee cartilage volumes using magnetic resonance (MR) images. The objectives were to assess measurement reliability by: (1) determining the differences between readings of the same image made by the same reader 2 weeks apart (test-retest reliability), (2) determining the differences between the readings of the same image made by different readers (between-reader agreement), and (3) determining the differences between the cartilage volume readings obtained from two MR images of the same knee image acquired a few hours apart (patient positioning reliability). METHODS: Forty-eight MR examinations of the knee from normal subjects, patients with different stages of symptomatic knee osteoarthritis (OA), and a subset of duplicate images were independently and blindly quantified by three readers using the imaging system. The following cartilage areas were analyzed to compute volumes: global cartilage, medial and lateral compartments, and medial and lateral femoral condyles. RESULTS: Between-reader agreement of measurements was excellent, as shown by intra-class correlation (ICC) coefficients ranging from 0.958 to 0.997 for global cartilage (P<0.0001), 0.974 to 0.998 for the compartments (P<0.0001), and 0.943 to 0.999 for the condyles(P<0.0001). Test-retest reliability of within-reader data was also excellent, with Pearson correlation coefficients ranging from 0.978 to 0.999 (P<0.0001). Patient positioning reliability was also excellent, with Pearson correlation coefficients ranging from 0.978 to 0.999 (P<0.0001). CONCLUSIONS: The results of this study establish the reliability of this MR imaging system. Test-retest reliability, between-reader agreement, and patient positioning reliability were all extremely high. This study represents a first step in the overall validation of an imaging system designed to follow progression of human knee OA.
Authors: Yin Yin; Xiangmin Zhang; Rachel Williams; Xiaodong Wu; Donald D Anderson; Milan Sonka Journal: IEEE Trans Med Imaging Date: 2010-07-19 Impact factor: 10.048
Authors: Samuel K Van de Velde; Jeffrey T Bingham; Ali Hosseini; Michal Kozanek; Louis E DeFrate; Thomas J Gill; Guoan Li Journal: Arthritis Rheum Date: 2009-12
Authors: Caroline B Boulocher; Eric R Viguier; Rodrigo Da Rocha Cararo; Didier J Fau; Fabien Arnault; Fabien Collard; Pierre A Maitre; Olivier Roualdes; Marie-Eve Duclos; Eric P Vignon; Thierry W Roger Journal: BMC Med Imaging Date: 2010-01-20 Impact factor: 1.930