Magnetic resonance image segmentation using semi-automated software for quantification of knee articular cartilage—initial evaluation of a technique for paired scans
- 218 Downloads
Software-based image analysis is important for studies of cartilage changes in knee osteoarthritis (OA). This study describes an evaluation of a semi-automated cartilage segmentation software tool capable of quantifying paired images for potential use in longitudinal studies of knee OA. We describe the methodology behind the analysis and demonstrate its use by determination of test–retest analysis precision of duplicate knee magnetic resonance imaging (MRI) data sets.
Test–retest knee MR images of 12 subjects with a range of knee health were evaluated from the Osteoarthritis Initiative (OAI) pilot MR study. Each subject was removed from the magnet between the two scans. The 3D DESS (sagittal, 0.456 mm × 0.365 mm, 0.7 mm slice thickness, TR 16.5 ms, TE 4.7 ms) images were obtained on a 3-T Siemens Trio MR system with a USA Instruments quadrature transmit–receive extremity coil. Segmentation of one 3D-image series was first performed and then the corresponding retest series was segmented by viewing both image series concurrently in two adjacent windows. After manual registration of the series, the first segmentation cartilage outline served as an initial estimate for the second segmentation. We evaluated morphometric measures of the bone and cartilage surface area (tAB and AC), cartilage volume (VC), and mean thickness (ThC.me) for medial/lateral tibia (MT/LT), total femur (F) and patella (P). Test–retest reproducibility was assessed using the root-mean square coefficient of variation (RMS CV%).
For the paired analyses, RMS CV % ranged from 0.9% to 1.2% for VC, from 0.3% to 0.7% for AC, from 0.6% to 2.7% for tAB and 0.8% to 1.5% for ThC.me.
Paired image analysis improved the measurement precision of cartilage segmentation. Our results are in agreement with other publications supporting the use of paired analysis for longitudinal studies of knee OA.
KeywordsOsteoarthritis Knee Cartilage MRI Segmentation
The Osteoarthritis Initiative (OAI) and this pilot study are conducted and supported by the National Institute of Arthritis and Musculoskeletal and Skin Diseases in collaboration with the OAI Investigators and Consultants. This manuscript has been reviewed by the OAI Publications committee for scientific content and data interpretation. The research reported in this article was supported in part by contracts N01-AR-2-2261, N01-AR-2-2262 and N01-AR-2-2258 from NIAMS. Support for this project was also provided by a contract with the NIAMS intramural program.
This work was also supported by a contract with the NIH/NIAMS intramural program. We would like to thank Raphaela Goldbach-Mansky of the NIH/NIAMS Intramural Research Program for her support in developing early versions of the software.
NIAMS funded this work in part (contracts N01-AR-2-2261, N01-AR-2-2262 and N01-AR-2-2258).
Conflict of Interest Statement
ES, RJ, JY, and CBE received direct salary support or had fee for service contracts associated with the OAI. In particular:
ES is the principal of SciTrials, LLC, is the NIAMS OAI Technical Advisor and is under contract to NIAMS for this
purpose; RJ and JU are at The Ohio State University that is under contract (N01-AR-2-2261) as a clinical center for the
OAI; CBE is at the Memorial Hospital of Rhode Island that is under contract (N01-AR-2-2262) as a clinical center for the OAI.
- 1.Cisternas M, Yelin E, Trupin L, Murphy L, Helmick CG. Direct and indirect costs of arthritis and other rheumatic conditions - United States, 1997. Report. Atlanta: Centers for Disease Control and Prevention; 2003 November 21, 2003 Contract No.: Document Number.Google Scholar
- 2.Pientka L. Arthrose als Volkskrankheit. Klin Forsch 2000; 6(Suppl 2): 2–3.Google Scholar
- 16.Raynauld JP, Kauffmann C, Beaudoin G, Berthiaume MJ, de Guise JA, Bloch DA, et al. Reliability of a quantification imaging system using magnetic resonance images to measure cartilage thickness and volume in human normal and osteoarthritic knees. Osteoarthr Cartil 2003; 11(5): 351–360.PubMedCrossRefGoogle Scholar
- 19.Wirth W, Hellio Le Graverand MP, Wyman BT, Maschek S, Hudelmaier M, Hitzl W, et al. Regional analysis of femorotibial cartilage loss in a subsample from the Osteoarthritis Initiative progression subcohort. Osteoarthr Cartil 2008 Sep 11 (in press).Google Scholar
- 21.Neogi T, Nevitt M, Niu J, LaValley MP, Hunter DJ, Terkeltaub R, et al. Lack of association between chondrocalcinosis and increased risk of cartilage loss in knees with osteoarthritis: results of two prospective longitudinal magnetic resonance imaging studies. Arthritis Rheum 2006; 54(6): 1822–1828.PubMedCrossRefGoogle Scholar
- 24.Eckstein F, Kunz M, Hudelmaier M, Jackson R, Yu J, Eaton CB, et al. Impact of coil design on the contrast-to-noise ratio, precision, and consistency of quantitative cartilage morphometry at 3 Tesla: a pilot study for the osteoarthritis initiative. Magn Reson Med 2007; 57(2): 448–454.PubMedCrossRefGoogle Scholar
- 25.Eckstein F, Maschek S, Wirth W, Hudelmaier M, Hitzl W, Wyman B, et al. One year change of knee cartilage morphology in the first release of participants from the Osteoarthritis Initiative Progression Subcohort—association with sex, Body Mass Index, symptoms, and radiographic OA status. Ann Rheum Dis. 2008 Jul 7 (in press).Google Scholar
- 33.Eckstein FCF, Raynauld JP, Waterton JC, Peterfy CG, eds. Magnetic resonance imaging (MRI) of articular cartilage in knee osteoarthritis (OA): Morphological assessment; 2006. Osteoarthr Cartil.Google Scholar