MR Imaging at 3.0T in the Assessment of Knee Osteoarthritis

The National Institute of Health Osteoarthritis Initiative (NIH OAI) is a large cohort study which has enrolled over 5,000 subjects either at-risk of developing osteoarthritis (OA) or with evidence of early OA. Their aims are to discover potential imaging, biochemical and genetic biomarkers signifying OA onset or progression. All the subjects are being scanned on Siemens Trio 3.0 Tesla MR scanners. In the UK, the 3.0 Tesla scanners in use are manufactured by three principal companies: Philips Medical Systems, GE Healthcare and Siemens. In order to perform and interpret future research on Philips and GE scanners in relation to the future results of the NIH OAI, a comparison study is required.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

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

The responsiveness of novel, dynamic, contrast-enhanced magnetic resonance measures of total knee synovitis after intra-articular corticosteroid for painful osteoarthritis

SummaryObjectiveSensitive biomarkers are needed to understand synovial response to therapy in osteoarthritis (OA). Dynamic, contrast-enhanced magnetic resonance imaging (DCE MRI) provides quantitative, novel measures of synovial inflammation. This exploratory study examined DCE-assessed synovial response to intra-articular corticosteroid (IACS).MethodsPeople with ACR clinical criteria OA knee underwent 3 T MRI pre- and 2 weeks post-IACS. Five MRI variables were assessed blindly: total synovial volume (semi-automated computer program), early enhancement rate (EER) and late enhancement ratio of the entire knee, synovial volume × late enhancement and a semi-quantitative (SQ) score (six sites scored 0–3). Clinical symptoms were assessed using pain visual analogue score (VAS) and WOMAC.Results13 participants (5 male, mean age 63, mean pain VAS 66 mm mean body mass index (BMI) 31.3 kg/m2) were included. The majority of MRIs demonstrated no change in SQ score although the DCE variables changed to some extent in all. There was generally a reduction in synovial volume ((Wilcoxon test) median (interquartile range (IQR)) reduction 14 cm3 (−1, 29)), EER (0.2% (−0.3, 0.6)) and late enhancement ratio (8% (−0.5, 41)). Synovial volume × late enhancement ratio demonstrated a substantive reduction (2250 (−930, 5630)) as well as the largest effect size, r = 0.45. There was a median 26% reduction in EER in participants with good symptomatic response to IACS, contrasting with a 23% increase in those who responded poorly.ConclusionsDCE MRI may be more sensitive than a SQ score at detecting post-therapy synovial changes. The association between EER and symptomatic response to IACS may reflect a closer relation of this biomarker to synovial inflammation than with volumetric assessment

Automatic segmentation of bones and inter-image anatomical correspondence by volumetric statistical modelling of knee MRI

The detection of cartilage loss due to disease progression in Osteoarthritis remains a challenging problem. We have shown previously that the sensitivity of detection from 3D MR images can be improved significantly by focusing on regions of `at risk' cartilage defined consistently across subjects and time-points. We define these regions in a frame of reference based on the bones, which requires that the bone surfaces are segmented in each image, and that anatomical correspondence is established between these surfaces. Previous results has shown that this can be achieved automatically using surface-based Active Appearance Models (AAMs) of the bones. In this paper we describe a method of refining the segmentations and correspondences by building a volumetric appearance model using the minimum message length principle. We present results from a study of 12 subjects which show that the new approach achieves a significant improvement in segmentation accuracy compared to the surface AAM approach, and reduce the variance in cartilage thickness measurements for key regions of interest. The study makes use of images of the same subjects obtained using different vendors' scanners, and also demonstrates the feasibility of multi-centre trial

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 UK. 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

Magnetic resonance transverse relaxation time T2 of knee cartilage in osteoarthritis at 3.0T : 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 UK. 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