Abstract
Cartilage MRI-based T1rho and T2 compositional measurements have been developed to characterize cartilage matrix quality and diagnose cartilage damage before irreversible defects are found, allowing intervention at an early, potentially reversible disease stage. Over the last 2 decades, this technology was investigated in numerous studies and was validated using specimen studies and arthroscopy; and longitudinal studies documented its ability to predict progression of degenerative disease and radiographic osteoarthritis (OA). While T1rho and T2 measurements have shown promise in early disease stages, several hurdles have been encountered to apply this technology clinically. These include (i) challenges with cartilage segmentation, (ii) long image acquisition times, (iii) a lack of standardization of imaging, and (iv) an absence of reference databases and definitions of abnormal cut-off values. Progress has been made by developing deep-learning based automatic cartilage segmentation and faster imaging methods, enabling the feasibility of T1rho and T2 imaging for clinical and scientific trial applications. Also, the Radiological Society of North America (RSNA) Quantitative Imaging Biomarker Alliance mechanism was used to establish standardized profiles for compositional T1rho and T2 imaging, and multi-center feasibility testing is work in progress. The last hurdles are the development of reference databases and establishing a definition of normal versus abnormal cartilage T1rho and T2 values. Finally, effective treatments for prevention and slowing progression of OA are required in order to establish T1rho and T2 as imaging biomarkers for initiating and monitoring therapies, analogous to the role of dual X-ray absorptiometry (DXA) bone mineral density measurements in the management of osteoporosis.
Key points
• T1rho and T2 cartilage measurements have been validated in characterizing cartilage degenerative change using histology and arthroscopy as a reference.
• They have also been shown to predict progression of cartilage degeneration and incidence of radiographic OA.
• Advances have been made to facilitate clinical and trial application of T 1rho and T 2 by improved standardization of imaging and by establishing deep learning-based automatic cartilage segmentation.
• Effective treatments with disease-modifying OA specific drugs may establish T 1rho and T 2 cartilage compositional measurements as biomarkers to initiate and monitor treatment.
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References
Hunter DJ, March L, Chew M. Osteoarthritis in 2020 and beyond: a Lancet Commission. Lancet. 2020;396(10264):1711–2.
Safiri S, Kolahi AA, Smith E, Hill C, Bettampadi D, Mansournia MA, et al. Global, regional and national burden of osteoarthritis 1990–2017: a systematic analysis of the Global Burden of Disease Study 2017. Ann Rheum Dis. 2020;79(6):819–28.
Hiligsmann M, Cooper C, Arden N, Boers M, Branco JC, Luisa Brandi M, et al. Health economics in the field of osteoarthritis: an expert’s consensus paper from the European Society for Clinical and Economic Aspects of Osteoporosis and Osteoarthritis (ESCEO). Semin Arthritis Rheum. 2013;43(3):303–13.
Mahmoudian A, Lohmander LS, Mobasheri A, Englund M, Luyten FP. Early-stage symptomatic osteoarthritis of the knee - time for action. Nat Rev Rheumatol. 2021;17(10):621–32.
Roos EM, Arden NK. Strategies for the prevention of knee osteoarthritis. Nat Rev Rheumatol. 2016;12(2):92–101.
Emanuel KS, Kellner LJ, Peters MJM, Haartmans MJJ, Hooijmans MT, Emans PJ. The relation between the biochemical composition of knee articular cartilage and quantitative MRI: a systematic review and meta-analysis. Osteoarthritis Cartilage. 2022;30(5):650–62.
Nieminen MT, Casula V, Nissi MJ. Compositional MRI of articular cartilage - current status and the way forward. Osteoarthritis Cartilage. 2022;30(5):633–5.
Link TM, Neumann J, Li X. Prestructural cartilage assessment using MRI. J Magn Reson Imaging. 2017;45(4):949–65.
Liebl H, Joseph G, Nevitt MC, Singh N, Heilmeier U, Subburaj K, et al. Early T2 changes predict onset of radiographic knee osteoarthritis: data from the osteoarthritis initiative. Ann Rheum Dis. 2014.
Prasad AP, Nardo L, Schooler J, Joseph GB, Link TM. T(1)rho and T(2) relaxation times predict progression of knee osteoarthritis. Osteoarthritis Cartilage. 2013;21(1):69–76.
Razmjoo A, Caliva F, Lee J, Liu F, Joseph GB, Link TM, et al. T2 analysis of the entire osteoarthritis initiative dataset. J Orthop Res. 2021;39(1):74–85.
Owman H, Ericsson YB, Englund M, Tiderius CJ, Tjornstrand J, Roos EM, et al. Association between delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) and joint space narrowing and osteophytes: a cohort study in patients with partial meniscectomy with 11 years of follow-up. Osteoarthritis Cartilage. 2014;22(10):1537–41.
Crema MD, Hunter DJ, Burstein D, Roemer FW, Li L, Eckstein F, et al. Association of changes in delayed gadolinium-enhanced MRI of cartilage (dGEMRIC) with changes in cartilage thickness in the medial tibiofemoral compartment of the knee: a 2 year follow-up study using 3.0 T MRI. Ann Rheum Dis. 2014;73(11):1935–41.
Brinkhof S, Nizak R, Khlebnikov V, Prompers JJ, Klomp DWJ, Saris DBF. Detection of early cartilage damage: feasibility and potential of gagCEST imaging at 7T. Eur Radiol. 2018;28(7):2874–81.
Madelin G, Xia D, Brown R, Babb J, Chang G, Krasnokutsky S, et al. Longitudinal study of sodium MRI of articular cartilage in patients with knee osteoarthritis: initial experience with 16-month follow-up. Eur Radiol. 2018;28(1):133–42.
Eck BL, Yang M, Elias JJ, Winalski CS, Altahawi F, Subhas N, et al. Quantitative MRI for evaluation of musculoskeletal disease: cartilage and muscle composition, Joint Inflammation, and Biomechanics in Osteoarthritis. Invest Radiol. 2022.
Zijlstra F, Seevinck PR. Multiple-echo steady-state (MESS): extending DESS for joint T2 mapping and chemical-shift corrected water-fat separation. Magn Reson Med. 2021;86(6):3156–65.
Matzat SJ, McWalter EJ, Kogan F, Chen W, Gold GE. T2 Relaxation time quantitation differs between pulse sequences in articular cartilage. J Magn Reson Imaging. 2015;42(1):105–13.
Li X, Majumdar S. Quantitative MRI of articular cartilage and its clinical applications. J Magn Reson Imaging. 2013;38(5):991–1008.
Kim J, Mamoto K, Lartey R, Xu K, Nakamura K, Shin W, et al. Multi-vendor multi-site T1rho and T2 quantification of knee cartilage. Osteoarthritis Cartilage. 2020;28(12):1539–50.
David-Vaudey E, Ghosh S, Ries M, Majumdar S. T2 relaxation time measurements in osteoarthritis. Magn Reson Imaging. 2004;22(5):673–82.
Regatte RR, Akella SV, Lonner JH, Kneeland JB, Reddy R. T1rho relaxation mapping in human osteoarthritis (OA) cartilage: comparison of T1rho with T2. J Magn Reson Imaging. 2006;23(4):547–53.
Soellner ST, Goldmann A, Muelheims D, Welsch GH, Pachowsky ML. Intraoperative validation of quantitative T2 mapping in patients with articular cartilage lesions of the knee. Osteoarthritis Cartilage. 2017;25(11):1841–9.
Svard T, Lakovaara M, Pakarinen H, Haapea M, Kiviranta I, Lammentausta E, et al. Quantitative MRI of human cartilage in vivo: relationships with arthroscopic indentation stiffness and defect severity. Cartilage. 2018;9(1):46–54.
Li X, Cheng J, Lin K, Saadat E, Bolbos RI, Jobke B, et al. Quantitative MRI using T1rho and T2 in human osteoarthritic cartilage specimens: correlation with biochemical measurements and histology. Magn Reson Imaging. 2011;29(3):324–34.
Franklin SP, Stoker AM, Lin ASP, Pownder SL, Burke EE, Bozynski CC, et al. T1rho, T2 mapping, and EPIC-microCT imaging in a canine model of knee osteochondral injury. J Orthop Res. 2020;38(2):368–77.
van Tiel J, Kotek G, Reijman M, Bos PK, Bron EE, Klein S, et al. Is T1rho mapping an alternative to delayed gadolinium-enhanced MR imaging of cartilage in the assessment of sulphated glycosaminoglycan content in human osteoarthritic knees? An in vivo validation study. Radiology. 2016;279(2):523–31.
Baum T, Joseph GB, Arulanandan A, Nardo L, Virayavanich W, Carballido-Gamio J, et al. Association of magnetic resonance imaging-based knee cartilage T2 measurements and focal knee lesions with knee pain: data from the Osteoarthritis Initiative. Arthritis Care Res (Hoboken). 2012;64(2):248–55.
Dunn TC, Lu Y, Jin H, Ries MD, Majumdar S. T2 relaxation time of cartilage at MR imaging: comparison with severity of knee osteoarthritis. Radiology. 2004;232(2):592–8.
Joseph GB, Baum T, Alizai H, Carballido-Gamio J, Nardo L, Virayavanich W, et al. Baseline mean and heterogeneity of MR cartilage T2 are associated with morphologic degeneration of cartilage, meniscus, and bone marrow over 3 years–data from the Osteoarthritis Initiative. Osteoarthritis Cartilage. 2012;20(7):727–35.
Mosher TJ, Dardzinski BJ. Cartilage MRI T2 relaxation time mapping: overview and applications. Semin Musculoskelet Radiol. 2004;8(4):355–68.
Gallo MC, Wyatt C, Pedoia V, Kumar D, Lee S, Nardo L, et al. T1rho and T2 relaxation times are associated with progression of hip osteoarthritis. Osteoarthritis Cartilage. 2016;24(8):1399–407.
Liebl H, Joseph G, Nevitt MC, Singh N, Heilmeier U, Subburaj K, et al. Early T2 changes predict onset of radiographic knee osteoarthritis: data from the osteoarthritis initiative. Ann Rheum Dis. 2015;74(7):1353–9.
Joseph G, Baum T, Alizai H, Nardo L, Virayavanich W, Lynch J, et al., editors. Joseph GB, Baum T, Alizai H, Nardo L, Virayavanich W, Lynch JA, Nevitt MC, McCulloch CE, Link TM. Elevated cartilage T2 and increased severity of cartilage defects at baseline are associated with the development of knee pain over 5 years. 16th World Congress on Osteoarthritis; 2013; Philadelphia, Pennsylvania.
Baum T, Joseph GB, Nardo L, Virayavanich W, Arulanandan A, Alizai H, et al. MRI-based knee cartilage T2 measurements and focal knee lesions correlate with BMI - 36 month follow-up data from the Osteoarthritis initiative. Arthritis Care Res (Hoboken). 2012.
Baum T, Stehling C, Joseph GB, Carballido-Gamio J, Schwaiger BJ, Muller-Hocker C, et al. Changes in knee cartilage T2 values over 24 months in subjects with and without risk factors for knee osteoarthritis and their association with focal knee lesions at baseline: data from the osteoarthritis initiative. J Magn Reson Imaging. 2012;35(2):370–8.
Lin W, Alizai H, Joseph GB, Srikhum W, Nevitt MC, Lynch JA, et al. Physical activity in relation to knee cartilage T2 progression measured with 3 T MRI over a period of 4 years: data from the Osteoarthritis Initiative. Osteoarthritis Cartilage. 2013;21(10):1558–66.
Serebrakian AT, Poulos T, Liebl H, Joseph GB, Lai A, Nevitt MC, et al. Weight loss over 48 months is associated with reduced progression of cartilage T2 relaxation time values: data from the osteoarthritis initiative. J Magn Reson Imaging. 2015;41(5):1272–80.
Stehling C, Luke A, Stahl R, Baum T, Joseph G, Pan J, et al. Meniscal T1rho and T2 measured with 3.0T MRI increases directly after running a marathon. Skeletal Radiol. 2011;40(6):725–35.
Gersing AS, Solka M, Joseph GB, Schwaiger BJ, Heilmeier U, Feuerriegel G, et al. Progression of cartilage degeneration and clinical symptoms in obese and overweight individuals is dependent on the amount of weight loss: 48-month data from the Osteoarthritis Initiative. Osteoarthritis Cartilage. 2016;24(7):1126–34.
Shah RP, Stambough JB, Fenty M, Mauck RL, Kelly JD, Reddy R, et al. T1rho Magnetic resonance imaging at 3T detects knee cartilage changes after viscosupplementation. Orthopedics. 2015;38(7):e604–10.
Jungmann PM, Kraus MS, Nardo L, Liebl H, Alizai H, Joseph GB, et al. T(2) relaxation time measurements are limited in monitoring progression, once advanced cartilage defects at the knee occur: longitudinal data from the osteoarthritis initiative. J Magn Reson Imaging. 2013;38(6):1415–24.
Su F, Pedoia V, Teng HL, Kretzschmar M, Lau BC, McCulloch CE, et al. The association between MR T1rho and T2 of cartilage and patient-reported outcomes after ACL injury and reconstruction. Osteoarthritis Cartilage. 2016;24(7):1180–9.
van der Heijden RA, Oei EH, Bron EE, van Tiel J, van Veldhoven PL, Klein S, et al. No difference on quantitative magnetic resonance imaging in patellofemoral cartilage composition between patients with patellofemoral pain and healthy controls. Am J Sports Med. 2016;44(5):1172–8.
Dautry R, Bousson V, Manelfe J, Perozziello A, Boyer P, Loriaut P, et al. Correlation of MRI T2 mapping sequence with knee pain location in young patients with normal standard MRI. JBR-BTR. 2014;97(1):11–6.
Blumenkrantz G, Carballido-Gamio J, McCulloch C, Lynch J, Link T, Majumdar S, editors. The relationship between the spatial distribution of cartilage MR T2 and longitudinal changes in pain: data from the Osteoarthritis Initiative. ISMRM; 2009; Honolulu, Hawaii.
Kretzschmar M, Nevitt MC, Schwaiger BJ, Joseph GB, McCulloch CE, Link TM. Spatial distribution and temporal progression of T2 relaxation time values in knee cartilage prior to the onset of cartilage lesions - data from the Osteoarthritis Initiative (OAI). Osteoarthritis Cartilage. 2019;27(5):737–45.
Apprich SR, Schreiner MM, Szomolanyi P, Welsch GH, Koller UK, Weber M, et al. Potential predictive value of axial T2 mapping at 3 Tesla MRI in patients with untreated patellar cartilage defects over a mean follow-up of four years. Osteoarthritis Cartilage. 2020;28(2):215–22.
Wirth W, Maschek S, Roemer FW, Sharma L, Duda GN, Eckstein F. Radiographically normal knees with contralateral joint space narrowing display greater change in cartilage transverse relaxation time than those with normal contralateral knees: a model of early OA? - data from the Osteoarthritis Initiative (OAI). Osteoarthritis Cartilage. 2019;27(11):1663–8.
Desai AD, Caliva F, Iriondo C, Mortazi A, Jambawalikar S, Bagci U, et al. The international workshop on osteoarthritis imaging knee MRI segmentation challenge: a multi-institute evaluation and analysis framework on a standardized dataset. Radiol Artif Intell. 2021;3(3):e200078.
Ebrahimkhani S, Jaward MH, Cicuttini FM, Dharmaratne A, Wang Y, de Herrera AGS. A review on segmentation of knee articular cartilage: from conventional methods towards deep learning. Artif Intell Med. 2020;106:101851.
Gaj S, Yang M, Nakamura K, Li X. Automated cartilage and meniscus segmentation of knee MRI with conditional generative adversarial networks. Magn Reson Med. 2020;84(1):437–49.
Gatti AA, Maly MR. Automatic knee cartilage and bone segmentation using multi-stage convolutional neural networks: data from the osteoarthritis initiative. MAGMA. 2021;34(6):859–75.
Liu F, Zhou Z, Jang H, Samsonov A, Zhao G, Kijowski R. Deep convolutional neural network and 3D deformable approach for tissue segmentation in musculoskeletal magnetic resonance imaging. Magn Reson Med. 2018;79(4):2379–91.
Norman B, Pedoia V, Majumdar S. Use of 2D U-Net convolutional neural networks for automated cartilage and meniscus segmentation of knee MR imaging data to determine relaxometry and morphometry. Radiology. 2018;288(1):177–85.
Chaudhari AS, Kogan F, Pedoia V, Majumdar S, Gold GE, Hargreaves BA. Rapid knee MRI acquisition and analysis techniques for imaging osteoarthritis. J Magn Reson Imaging. 2020;52(5):1321–39.
Zhou Y, Pandit P, Pedoia V, Rivoire J, Wang Y, Liang D, et al. Accelerating T1rho cartilage imaging using compressed sensing with iterative locally adapted support detection and JSENSE. Magn Reson Med. 2016;75(4):1617–29.
Zibetti MVW, Sharafi A, Otazo R, Regatte RR. Accelerating 3D–T1rho mapping of cartilage using compressed sensing with different sparse and low rank models. Magn Reson Med. 2018;80(4):1475–91.
Kim J, Zhang CA, Yang M, Li H, Li M, Lartey R, editors. Highly accelerated T1ρ imaging using kernel-based low-rank compressed sensing reconstruction in knees with and without osteoarthritis. Annual Conference of International Society of Magnetic Resonance in Medicine (ISMRM); 2021; virtual.
Sharafi A, Zibetti MVW, Chang G, Cloos M, Regatte RR. 3D MR-fingerprinting for rapid simultaneous T1, T2, and T1rho volumetric mapping of the human articular cartilage at 3T. NMR Biomed. 2022:e4800.
Li H, Yang M, Kim JH, Zhang C, Liu R, Huang P, et al. SuperMAP: deep ultrafast MR relaxometry with joint spatiotemporal undersampling. Magn Reson Med. 2022. Epub ahead of print (2022/09/22).
Liu F, Feng L, Kijowski R. MANTIS: model-augmented neural network with incoherent k-space sampling for efficient MR parameter mapping. Magn Reson Med. 2019;82(1):174–88.
Chalian M, Li X, Guermazi A, Obuchowski NA, Carrino JA, Oei EH, et al. The QIBA Profile for MRI-based compositional imaging of knee cartilage. Radiology. 2021;301(2):423–32.
Li X, Pedoia V, Kumar D, Rivoire J, Wyatt C, Lansdown D, et al. Cartilage T1rho and T2 relaxation times: longitudinal reproducibility and variations using different coils. MR systems and sites Osteoarthritis Cartilage. 2015;23(12):2214–23.
Joseph GB, McCulloch CE, Nevitt MC, Heilmeier U, Nardo L, Lynch JA, et al. A reference database of cartilage 3 T MRI T2 values in knees without diagnostic evidence of cartilage degeneration: data from the osteoarthritis initiative. Osteoarthritis Cartilage. 2015;23(6):897–905.
Joseph GB, McCulloch CE, Nevitt MC, Gersing AS, Schwaiger BJ, Kretzschmar M, et al. Medial femur T2 Z-scores predict the probability of knee structural worsening over 4–8 years: data from the osteoarthritis initiative. J Magn Reson Imaging. 2017;46(4):1128–36.
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XL is supported by NIH R01AR075422 and R01AR077452 and the Arthritis Foundation. GBJ is supported by NIH R01AR078917. TML is supported by NIH R01AR078917 and R01AR007452.
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Link, T.M., Joseph, G.B. & Li, X. MRI-based T1rho and T2 cartilage compositional imaging in osteoarthritis: what have we learned and what is needed to apply it clinically and in a trial setting?. Skeletal Radiol 52, 2137–2147 (2023). https://doi.org/10.1007/s00256-023-04310-x
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DOI: https://doi.org/10.1007/s00256-023-04310-x