Magnetic resonance transverse relaxation time T2 of knee cartilage in osteoarthritis at 3-T: a cross-sectional multicentre, multivendor reproducibility study.

OBJECTIVE: The transverse relaxation time (T2) in MR imaging has been identified as a potential biomarker of hyaline cartilage pathology. This study investigates whether MR assessments of T2 are comparable between 3-T scanners from three different vendors. DESIGN: Twelve subjects with symptoms of knee osteoarthritis and one or more risk factors had their knee scanned on each of the three vendors' scanners located in three sites in the U.K. MR data acquisition was based on the United States National Institutes of Health Osteoarthritis Initiative protocol. Measures of cartilage T2 and R2 (inverse of T2) were computed for precision error assessment. Intrascanner reproducibility was also assessed with a phantom (all three scanners) and a cohort of 5 subjects (one scanner only). RESULTS: Whole-organ magnetic resonance (WORM) semiquantitative cartilage scores ranged from minimal to advanced degradation. Intrascanner R2 root-mean-square coefficients of variation (RMSCOV) were low, within the range 2.6 to 6.3% for femoral and tibial regions. For one scanner pair, mean T2 differences ranged from -1.2 to 2.8 ms, with no significant difference observed for the medial tibia and patella regions (p < 0.05). T2 values from the third scanner were systematically lower, producing interscanner mean T2 differences within the range 5.4 to 10.0 ms. CONCLUSION: Significant interscanner cartilage T2 differences were found and should be accounted for before data from scanners of different vendors are compared.

Comparison of 3T MR scanners in regional cartilage-thickness analysis in osteoarthritis: a cross-sectional multicenter, multivendor study.

INTRODUCTION: Cartilage thickness from MR images has been identified as a possible biomarker in knee osteoarthritis (OA) research. The ability to acquire MR data at multiple centers by using different vendors' scanners would facilitate patient recruitment and shorten the duration of OA trials. Several vendors manufacture 3T MR scanners, including Siemens, Philips Medical Systems, and GE Healthcare. This study investigates whether quantitative MR assessments of cartilage morphology are comparable between scanners of three different vendors. METHODS: Twelve subjects with symptoms of knee OA and one or more risk factors had their symptomatic knee scanned on each of the three vendor's scanners located in three sites in the UK: Manchester (Philips), York (GE), and Liverpool (Siemens). The NIH OAI study protocol was used for the Siemens scanner, and equivalent protocols were developed for the Philips and GE scanners with vendors' advice. Cartilage was segmented manually from sagittal 3D images. By using recently described techniques for Anatomically Corresponded Regional Analysis of Cartilage (ACRAC), a statistical model was used anatomically to align all the images and to produce detailed maps of mean differences in cartilage-thickness measures between scanners. Measures of cartilage mean thickness were computed in anatomically equivalent regions for each subject and scanner image. RESULTS: The ranges of mean cartilage-thickness measures for this cohort were similar for all regions and across all scanners. Philips intrascanner root-mean-square coefficients of variation were low in the range from 2.6% to 4.6%. No significant differences were found for thickness measures of the weight-bearing femorotibial regions from the Philips and Siemens images except for the central medial femur compartment (P = 0.04). Compared with the other two scanners, the GE scanner provided consistently lower mean thickness measures in the central femoral regions (mean difference, -0.16 mm) and higher measures in the tibial compartments (mean difference, +0.19 mm). CONCLUSIONS: The OAI knee-imaging protocol, developed on the Siemens platform, can be applied to research and trials by using other vendors' 3T scanners giving comparable morphologic results. Accurate sequence optimization, differences in image postprocessing, and extremity coil type are critical factors for interscanner precision of quantitative analysis of cartilage morphology. It is still recommended that longitudinal observations on individuals should be performed on the same scanner and that assessment of intra- and interscanner precision errors is undertaken before commencement of the main study.

Anatomically corresponded regional analysis of cartilage in asymptomatic and osteoarthritic knees by statistical shape modelling of the bone.

Magnetic resonance imaging (MRI) is emerging as the method of choice for measuring cartilage loss in osteoarthritis (OA), but current methods of analysis are imperfect for therapeutic clinical trials. In this paper, we present and evaluate, in two multicenter multivendor studies, a new method for anatomically corresponded regional analysis of cartilage (ACRAC) that allows analysis of knee cartilage morphology in anatomically corresponding focal regions defined on the bone surface. In our first study, 3-D knee MR Images were obtained from 19 asymptomatic female volunteers, followed by segmentations of the bone and cartilage. Minimum description length (MDL) statistical shape models (SSMs) were constructed from the segmented bone surfaces, providing mean bone shapes and a dense set of anatomically corresponding positions on each individual bone, the accuracy of which were measured using repeat images from a subset of the volunteers. Cartilage thicknesses were measured at these locations along 3-D normals to the bone surfaces, yielding corresponded cartilage thickness maps. Functional subregions of the joint were defined on the mean bone shapes, and propagated, using the correspondences, to each individual. ACRAC improved reproducibility, particularly in the central, load bearing subregions of the joint, compared with measures of volume obtained directly from the segmented cartilage surfaces. In our second study, MR Images were obtained from 31 female patient-volunteers with knee OA at baseline and six months. We obtained manual segmentations of the cartilage, and automatic segmentations of the bone using active appearance models (AAMs) built from the bone SSMs of the first study. ACRAC enabled the detection of significant thickness loss in the central, load-bearing regions of the whole femur (-5.57% p = 0.01, annualized) and the medial condyle (-13.08% , p = 0.024 Bonferroni corrected, annualized). We conclude that statistical shape modelling of bone surfaces defines correspondences invariant to individual joint size or shape, providing focal measures of cartilage with improved reproducibility compared to whole compartment measures. It permits the identification of anatomically equivalent regions, and provides the ability to identify the main load-bearing regions of the joint, based on the imputed premorbid state. The method permitted detection of tiny morphological change in cartilage thickness over six months in a small study, and may be useful for OA disease analysis and treatment monitoring.

Corresponding articular cartilage thickness measurements in the knee joint by modelling the underlying bone (commercial in confidence).

We present a method for corresponding and combining cartilage thickness readings from a population of patients using the underlying bone structure as a reference. Knee joint femoral bone and cartilage surfaces are constructed from a set of parallel slice segmentations of MR scans. Correspondence points across a population of bone surfaces are defined and refined by minimising an objective function based on the Minimum Description Length of the resulting statistical shape model. The optimised bone model defines a set of corresponding locations from which 3D measurements of the cartilage thickness can be taken and combined for a population of patients. Results are presented for a small group of patients demonstrating the feasibility and potential of the approach as a means of detecting sub-millimetre cartilage thickness changes due to disease progression.