Structural tissue damage and 24-month progression of semi-quantitative MRI biomarkers of knee osteoarthritis in the IMI-APPROACH cohort

Frank W Roemer, Mylène Jansen, Anne C A Marijnissen, Ali Guermazi, Rafael Heiss, Susanne Maschek, Agnes Lalande, Francisco J Blanco, Francis Berenbaum, Lotte A van de Stadt, Margreet Kloppenburg, Ida K Haugen, Christoph H Ladel, Jaume Bacardit, Anna Wisser, Felix Eckstein, Floris P J G Lafeber, Harrie H Weinans, Wolfgang Wirth, Frank W Roemer, Mylène Jansen, Anne C A Marijnissen, Ali Guermazi, Rafael Heiss, Susanne Maschek, Agnes Lalande, Francisco J Blanco, Francis Berenbaum, Lotte A van de Stadt, Margreet Kloppenburg, Ida K Haugen, Christoph H Ladel, Jaume Bacardit, Anna Wisser, Felix Eckstein, Floris P J G Lafeber, Harrie H Weinans, Wolfgang Wirth

Abstract

Background: The IMI-APPROACH cohort is an exploratory, 5-centre, 2-year prospective follow-up study of knee osteoarthritis (OA). Aim was to describe baseline multi-tissue semiquantitative MRI evaluation of index knees and to describe change for different MRI features based on number of subregion-approaches and change in maximum grades over a 24-month period.

Methods: MRIs were acquired using 1.5 T or 3 T MRI systems and assessed using the semi-quantitative MRI OA Knee Scoring (MOAKS) system. MRIs were read at baseline and 24-months for cartilage damage, bone marrow lesions (BML), osteophytes, meniscal damage and extrusion, and Hoffa- and effusion-synovitis. In descriptive fashion, the frequencies of MRI features at baseline and change in these imaging biomarkers over time are presented for the entire sample in a subregional and maximum score approach for most features. Differences between knees without and with structural radiographic (R) OA are analyzed in addition.

Results: Two hundred eighty-nine participants had readable baseline MRI examinations. Mean age was 66.6 ± 7.1 years and participants had a mean BMI of 28.1 ± 5.3 kg/m2. The majority (55.3%) of included knees had radiographic OA. Any change in total cartilage MOAKS score was observed in 53.1% considering full-grade changes only, and in 73.9% including full-grade and within-grade changes. Any medial cartilage progression was seen in 23.9% and any lateral progression on 22.1%. While for the medial and lateral compartments numbers of subregions with improvement and worsening of BMLs were very similar, for the PFJ more improvement was observed compared to worsening (15.5% vs. 9.0%). Including within grade changes, the number of knees showing BML worsening increased from 42.2% to 55.6%. While for some features 24-months change was rare, frequency of change was much more common in knees with vs. without ROA (e.g. worsening of total MOAKS score cartilage in 68.4% of ROA knees vs. 36.7% of no-ROA knees, and 60.7% vs. 21.8% for an increase in maximum BML score per knee).

Conclusions: A wide range of MRI-detected structural pathologies was present in the IMI-APPROACH cohort. Baseline prevalence and change of features was substantially more common in the ROA subgroup compared to the knees without ROA.

Trial registration: Clinicaltrials.gov identification: NCT03883568.

Keywords: Knee; MRI; Osteoarthritis; Progression; reliability.

Conflict of interest statement

The IMI-APPROACH project received a grant from Innovative Medicines Institute, grant agreement 11577.

Competing interests outside the submitted work:

FWR is Chief Medical Officer and shareholder of BICL, LLC. He has received consulting honoraria from Calibr and Grünenthal; MJ did not declare any conflict of interest; ACAM did not declare any conflict of interest, AG has received consultancies, speaking fees, and/or honoraria from Sanofi-Aventis, Merck Serono, and TissuGene and is President and shareholder of Boston Imaging Core Lab (BICL), LLC a company providing image assessment services; RH did not declare any conflict of interest; SM is employee and shareholder of Chondrometrics GmbH; AL is employee of Institut de Recherches Internationales Servier; FJB reports grants from Gebro Pharma, grants from BIOIBERICA, grants from AB Science, grants from Abbvie, grants from Ablynx N.V., grants from Amgen, grants from Archigen Biotech Limited, grants from Boehringer, grants from Bristol-Myers, grants from Celgene Int., grants from Eli Lilly and Company, grants from F. Hoffmann- La Roche, grants from Galapagos, grants from Gedeon, grants from Genentech, grants from Gideal Sciences, NC, grants from Glaxosmithkline, grants from Hospira, grants from INC Research UK, grants from Inventiv Health Clinical, grants from Janssen, grants from Lilly, grants from Nichi-IKO Pharmaceutical, grants from Novartis, grants from ONO Pharma, grants from Pfizer, grants from Pharmaceutical Research, grants from Regeneron, grants from Roche, grants from SA UCB Pharma, grants from Sanofi, grants from TRB Chemedica, grants from UCB Biosciences GMBH, outside the submitted work; In addition, FJB has a patent Molecular block-matching method for gel image analysis issued, a patent Targeting A Specific Receptor On Cells With A Specific Compound For Use In The Treatment And/Or The Prevention Of Osteoarthritis And Rheumatoid Arthritis pending, a patent Genetic markers for osteoarthritis issued, a patent Method for the diagnosis of osteoarthritis issued, a patent Genetic markers for osteoarthritis pending, a patent Method for the diagnosing Arthrosis pending, a patent Method for diagnosing Arthrosis pending, a patent Method for the diagnosis of osteoarthritis pending, and a patent Anti-connexin compounds for use in the prevention and/or treatment of degenerative joint diseases. pending; FB reports personal fees from Boehringer, Bone Therapeutics, Expanscience, Galapagos, Gilead, GSK, Merck Sereno, MSD, Nordic, Novartis, Pfizer, Regulaxis, Roche, Sandoz, Sanofi, Servier, UCB, Peptinov, TRB Chemedica, 4P Pharma; LAvdS did not declare any conflict of interest; MK reports grants from IMI-APPROACH, grants from Dutch Arthritis Association, during the conduct of the study; other from GlaxoSmithKline, Pfizer, Merck-Serono, Kiniksa, Abbvie; IKH reports personal fees from AbbVie, grants from Pfizer; CL was employee of Merck KGaA, at start of the study; JB did not declare any conflict of interest; AW is employee of Chondrometrics GmbH; FE is CEO and shareholder of Chondrometrics GmbH and received personal fees from AbbVie, Galapagos NV, HealthLink, ICM, IRIS, Kolon TissueGene, Merck KGaA, Novartis, Roche and Samumed and grants from Foundation for the NIH, University of California, San Francisco, NIH/National Heart, Lung, and Blood Institute, Bioclinica, Galapagos NV, Novartis, TissueGene, Erlangen University Hospital, University of Sydney, CALIBR, University of Basel, University of Western Ontario, Stanford University, ICM Co., Ltd., UMC Utrecht, Federal Ministry of Education and Research, Germany; FPJGL did not declare any conflict of interest; HHW did not declare any conflict of interest; WW is employee and shareholder of Chondrometrics GmbH and received consulting fees from Galapagos NV.

© 2022. The Author(s).

Figures

Fig. 1
Fig. 1
Subregional division for cartilage and bone marrow lesion assessment using the MOAKS instrument. Both features are assessed in 14 articular subregions. A. Axial intermediate-weighted fat suppressed image shows subregional division of the patella into the medial (mP) and lateral patella (lP). Note that the patella apex is part of the medial patella. B. Sagittal intermediate-weighted fat suppressed image of the medial compartment shows the three femoral and three tibial subregions. The femur is subdivided into the anterior (amF), central (cmF) and posterior (pmF) subregions. The tibia is subdivided into the anterior (amT), central (cmT) and posterior (pmT) subregions. The lateral compartment is subdivided in corresponding fashion in the sagittal plane (not shown). C. Coronal intermediate-weighted fat suppressed image shows the central femoral and tibial subregions. The tibial S region (subspinous – adjacent to the tibial spines) is not considered for BML and cartilage evaluation

References

    1. Disease GBD, Injury I, Prevalence C. Global, regional, and national incidence, prevalence, and years lived with disability for 310 diseases and injuries, 1990–2015: a systematic analysis for the Global Burden of Disease Study 2015. Lancet. 2016;388(10053):1545–1602. doi: 10.1016/S0140-6736(16)31678-6.
    1. Hunter DJ, Schofield D, Callander E. The individual and socioeconomic impact of osteoarthritis. Nat Rev Rheumatol. 2014;10(7):437–441. doi: 10.1038/nrrheum.2014.44.
    1. Oo WM, Yu SP, Daniel MS, Hunter DJ. Disease-modifying drugs in osteoarthritis: current understanding and future therapeutics. Expert Opin Emerg Drugs. 2018;23(4):331–347. doi: 10.1080/14728214.2018.1547706.
    1. Bijlsma JW, Berenbaum F, Lafeber FP. Osteoarthritis: an update with relevance for clinical practice. Lancet. 2011;377(9783):2115–2126. doi: 10.1016/S0140-6736(11)60243-2.
    1. Roemer FW, Demehri S, Omoumi P, Link TM, Kijowski R, Saarakkala S, Crema MD, Guermazi A. State of the Art: Imaging of Osteoarthritis-Revisited 2020. Radiology. 2020;296(1):5–21. doi: 10.1148/radiol.2020192498.
    1. Guermazi A, Niu J, Hayashi D, Roemer FW, Englund M, Neogi T, Aliabadi P, McLennan CE, Felson DT. Prevalence of abnormalities in knees detected by MRI in adults without knee osteoarthritis: population based observational study (Framingham Osteoarthritis Study) BMJ. 2012;345:e5339. doi: 10.1136/bmj.e5339.
    1. Roemer FW, Kwoh CK, Hannon MJ, Hunter DJ, Eckstein F, Fujii T, Boudreau RM, Guermazi A. What comes first? Multitissue involvement leading to radiographic osteoarthritis: magnetic resonance imaging-based trajectory analysis over four years in the osteoarthritis initiative. Arthritis Rheumatol. 2015;67(8):2085–2096. doi: 10.1002/art.39176.
    1. Collins JE, Losina E, Nevitt MC, Roemer FW, Guermazi A, Lynch JA, Katz JN, Kent Kwoh C, Kraus VB, Hunter DJ. Semiquantitative Imaging Biomarkers of Knee Osteoarthritis Progression: Data From the Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium. Arthritis Rheumatol. 2016;68(10):2422–2431. doi: 10.1002/art.39731.
    1. Guermazi A, Roemer FW, Haugen IK, Crema MD, Hayashi D. MRI-based semiquantitative scoring of joint pathology in osteoarthritis. Nat Rev Rheumatol. 2013;9(4):236–251. doi: 10.1038/nrrheum.2012.223.
    1. Roemer FW, Hunter DJ, Crema MD, Kwoh CK, Ochoa-Albiztegui E, Guermazi A. An illustrative overview of semi-quantitative MRI scoring of knee osteoarthritis: lessons learned from longitudinal observational studies. Osteoarthritis Cartilage. 2016;24(2):274–289. doi: 10.1016/j.joca.2015.08.011.
    1. Roemer FW, Collins J, Kwoh CK, Hannon MJ, Neogi T, Felson DT, Hunter DJ, Lynch JA, Guermazi A. MRI-based screening for structural definition of eligibility in clinical DMOAD trials: Rapid OsteoArthritis MRI Eligibility Score (ROAMES) Osteoarthritis Cartilage. 2020;28(1):71–81. doi: 10.1016/j.joca.2019.08.005.
    1. Wirth W, Maschek S, Wisser A, Guermazi A, Hunter DJ, Eckstein F, Roemer FW. MRI-based semi-quantitative assessment allows targeted selection of knees with accelerated quantitative cartilage thickness loss: data from the OAI FNIH biomarker consortium. Osteoarthritis Cartilage. 2022;30:S264–S265. doi: 10.1016/j.joca.2022.02.361.
    1. van Helvoort EM, van Spil WE, Jansen MP, Welsing PMJ, Kloppenburg M, Loef M, Blanco FJ, Haugen IK, Berenbaum F, Bacardit J, et al. Cohort profile: The Applied Public-Private Research enabling OsteoArthritis Clinical Headway (IMI-APPROACH) study: a 2-year, European, cohort study to describe, validate and predict phenotypes of osteoarthritis using clinical, imaging and biochemical markers. BMJ Open. 2020;10(7):e035101. doi: 10.1136/bmjopen-2019-035101.
    1. Wesseling J, Boers M, Viergever MA, Hilberdink WK, Lafeber FP, Dekker J, Bijlsma JW. Cohort Profile: Cohort Hip and Cohort Knee (CHECK) study. Int J Epidemiol. 2016;45(1):36–44. doi: 10.1093/ije/dyu177.
    1. van Helvoort EM, Ladel C, Mastbergen S, Kloppenburg M, Blanco FJ, Haugen IK, Berenbaum F, Bacardit J, Widera P, Welsing PMJ, et al. Baseline clinical characteristics of predicted structural and pain progressors in the IMI-APPROACH knee OA cohort. RMD Open. 2021;7(3):e001759. doi: 10.1136/rmdopen-2021-001759.
    1. Damman W, Liu R, Kroon FPB, Reijnierse M, Huizinga TWJ, Rosendaal FR, Kloppenburg M. Do Comorbidities Play a Role in Hand Osteoarthritis Disease Burden? Data from the Hand Osteoarthritis in Secondary Care Cohort. J Rheumatol. 2017;44(11):1659–1666. doi: 10.3899/jrheum.170208.
    1. Magnusson K, Hagen KB, Osteras N, Nordsletten L, Natvig B, Haugen IK. Diabetes is associated with increased hand pain in erosive hand osteoarthritis: data from a population-based study. Arthritis Care Res (Hoboken) 2015;67(2):187–195. doi: 10.1002/acr.22460.
    1. Oreiro-Villar N, Raga AC, Rego-Perez I, Pertega S, Silva-Diaz M, Freire M, Fernandez-Lopez C, Blanco FJ. PROCOAC (PROspective COhort of A Coruna) description: Spanish prospective cohort to study osteoarthritis. Reumatol Clin (Engl Ed) 2022;18(2):100–104. doi: 10.1016/j.reuma.2020.08.010.
    1. Sellam J, Maheu E, Crema MD, Touati A, Courties A, Tuffet S, Rousseau A, Chevalier X, Combe B, Dougados M, et al. The DIGICOD cohort: A hospital-based observational prospective cohort of patients with hand osteoarthritis - methodology and baseline characteristics of the population. Joint Bone Spine. 2021;88(4):105171. doi: 10.1016/j.jbspin.2021.105171.
    1. Widera P, Welsing PMJ, Ladel C, Loughlin J, Lafeber F, Petit Dop F, Larkin J, Weinans H, Mobasheri A, Bacardit J. Multi-classifier prediction of knee osteoarthritis progression from incomplete imbalanced longitudinal data. Sci Rep. 2020;10(1):8427. doi: 10.1038/s41598-020-64643-8.
    1. Eckstein F, Maschek S, Bay-Jensen A, Boere J, Hussaarts L, Ladel C, Lalande A, Larkin J, Loughlin J, Mobasheri A, et al. Intersite comparison and test-retest reliability of cartilage thickness and compostional analysis in the APPROACH study: a 2-year multicenter European exploratory study for phenotype characterizaton of knee osteoarthritis. Osteoarthritis Cartilage. 2019;27:S326–S327. doi: 10.1016/j.joca.2019.02.731.
    1. Hunter DJ, Guermazi A, Lo GH, Grainger AJ, Conaghan PG, Boudreau RM, Roemer FW. Evolution of semi-quantitative whole joint assessment of knee OA: MOAKS (MRI Osteoarthritis Knee Score) Osteoarthritis Cartilage. 2011;19(8):990–1002. doi: 10.1016/j.joca.2011.05.004.
    1. Roemer FW, Nevitt MC, Felson DT, Niu J, Lynch JA, Crema MD, Lewis CE, Torner J, Guermazi A. Predictive validity of within-grade scoring of longitudinal changes of MRI-based cartilage morphology and bone marrow lesion assessment in the tibio-femoral joint–the MOST study. Osteoarthritis Cartilage. 2012;20(11):1391–1398. doi: 10.1016/j.joca.2012.07.012.
    1. Felson DT, Chaisson CE, Hill CL, Totterman SM, Gale ME, Skinner KM, Kazis L, Gale DR. The association of bone marrow lesions with pain in knee osteoarthritis. Ann Intern Med. 2001;134(7):541–549. doi: 10.7326/0003-4819-134-7-200104030-00007.
    1. Yusuf E, Kortekaas MC, Watt I, Huizinga TW, Kloppenburg M. Do knee abnormalities visualised on MRI explain knee pain in knee osteoarthritis? A systematic review. Ann Rheum Dis. 2011;70(1):60–67. doi: 10.1136/ard.2010.131904.
    1. Foreman SC, Liu Y, Nevitt MC, Neumann J, Joseph GB, Lane NE, McCulloch CE, Link TM. Meniscal Root Tears and Extrusion Are Significantly Associated with the Development of Accelerated Knee Osteoarthritis: Data from the Osteoarthritis Initiative. Cartilage. 2021;13(1_suppl):239S–248S. doi: 10.1177/1947603520934525.
    1. Driban JB, Davis JE, Lu B, Price LL, Ward RJ, MacKay JW, Eaton CB, Lo GH, Barbe MF, Zhang M, et al. Accelerated Knee Osteoarthritis Is Characterized by Destabilizing Meniscal Tears and Preradiographic Structural Disease Burden. Arthritis Rheumatol. 2019;71(7):1089–1100. doi: 10.1002/art.40826.
    1. Roemer FW, Guermazi A, Collins JE, Losina E, Nevitt MC, Lynch JA, Katz JN, Kwoh CK, Kraus VB, Hunter DJ. Semi-quantitative MRI biomarkers of knee osteoarthritis progression in the FNIH biomarkers consortium cohort - Methodologic aspects and definition of change. BMC Musculoskelet Disord. 2016;17(1):466. doi: 10.1186/s12891-016-1310-6.
    1. Roemer FW, Maschek S, Wisser A, Guermazi A, Hunter DJ, Wirth W. Relevance of within-grade cartilage assessment using the moaks scoring instrument and corresponding quantitative cartilage thickness loss: Data from the OAI FNIH Biomarkers Consortium Study. Osteoarthritis Cartilage. 2022;30:S267–S268. doi: 10.1016/j.joca.2022.02.365.
    1. Roemer FW, Felson DT, Stefanik JJ, Rabasa G, Wang N, Crema MD, Neogi T, Nevitt MC, Torner J, Lewis CE, et al. Heterogeneity of cartilage damage in Kellgren and Lawrence grade 2 and 3 knees: the MOST study. Osteoarthritis Cartilage. 2022;30(5):714–723. doi: 10.1016/j.joca.2022.02.614.
    1. Maschek S, Roemer FW, Marijnissen AC, Jansen M, Wisser A, Lafeber F, Lalande A, Weinans HH, Blanco FJ, Berenbaum F, et al. Predictors of longitudinal MRI-based cartilage thickness change in the observational multicenter APPROACH cohort. Osteoarthritis Cartilage. 2022;30:S45–S46. doi: 10.1016/j.joca.2022.02.049.
    1. Crema MD, Roemer FW, Nevitt MC, Felson DT, Marra MD, et al. Cross-sectional and longitudinal reliability of semiquantitative osteoarthritis assessment at 1.0T extremity MRI: Multi-reader data from the MOST study. Osteoarthritis and Cartilage Open. 2021;3:100214.
    1. Runhaar J, Schiphof D, van Meer B, Reijman M, Bierma-Zeinstra SM, Oei EH. How to define subregional osteoarthritis progression using semi-quantitative MRI osteoarthritis knee score (MOAKS) Osteoarthritis Cartilage. 2014;22(10):1533–1536. doi: 10.1016/j.joca.2014.06.022.
    1. Pelletier JP, Roubille C, Raynauld JP, Abram F, Dorais M, Delorme P, Martel-Pelletier J. Disease-modifying effect of strontium ranelate in a subset of patients from the Phase III knee osteoarthritis study SEKOIA using quantitative MRI: reduction in bone marrow lesions protects against cartilage loss. Ann Rheum Dis. 2015;74(2):422–429. doi: 10.1136/annrheumdis-2013-203989.
    1. Lohmander LS, Hellot S, Dreher D, Krantz EF, Kruger DS, Guermazi A, Eckstein F. Intraarticular sprifermin (recombinant human fibroblast growth factor 18) in knee osteoarthritis: a randomized, double-blind, placebo-controlled trial. Arthritis Rheumatol. 2014;66(7):1820–1831. doi: 10.1002/art.38614.
    1. Gensburger D, Roux JP, Arlot M, Sornay-Rendu E, Ravaud P, Chapurlat R. Influence of blinding sequence of radiographs on the reproducibility and sensitivity to change of joint space width measurement in knee osteoarthritis. Arthritis Care Res (Hoboken) 2010;62(12):1699–1705. doi: 10.1002/acr.20311.
    1. Grossman JW, De Smet AA, Shinki K. Comparison of the accuracy rates of 3-T and 1.5-T MRI of the knee in the diagnosis of meniscal tear. AJR Am J Roentgenol. 2009;193(2):509–514. doi: 10.2214/AJR.08.2101.
    1. Nouri N, Bouaziz MC, Riahi H, Mechri M, Kherfani A, Ouertatani M, Ladeb MF. Traumatic Meniscus and Cruciate Ligament Tears in Young Patients: A Comparison of 3T Versus 15T MRI. J Belg Soc Radiol. 2017;101(1):14. doi: 10.5334/jbr-btr.1158.
    1. Sampson MJ, Jackson MP, Moran CJ, Shine S, Moran R, Eustace SJ. Three Tesla MRI for the diagnosis of meniscal and anterior cruciate ligament pathology: a comparison to arthroscopic findings. Clin Radiol. 2008;63(10):1106–1111. doi: 10.1016/j.crad.2008.04.008.
    1. Roemer FW, Lynch JA, Niu J, Zhang Y, Crema MD, Tolstykh I, El-Khoury GY, Felson DT, Lewis CE, Nevitt MC, et al. A comparison of dedicated 1.0 T extremity MRI vs large-bore 1.5 T MRI for semiquantitative whole organ assessment of osteoarthritis: the MOST study. Osteoarthritis Cartilage. 2010;18(2):168–174. doi: 10.1016/j.joca.2009.08.017.

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