The role of imaging in osteoarthritis.

Best Practice & Research Clinical Rheumatology 28 (2014) 31–60

Contents lists available at ScienceDirect

Best Practice & Research Clinical Rheumatology journal homepage: www.elsevierhealth.com/berh

3

The role of imaging in osteoarthritis Frank W. Roemer, MD a, b, c, *, Felix Eckstein, MD d, 3, Daichi Hayashi, MD, PhD a, e,1, Ali Guermazi, MD, PhD a, 2 a

Department of Radiology, Quantitative Imaging Center (QIC), Boston University School of Medicine, 820 Harrison Avenue, FGH Building, 3rd Floor, Boston, MA 02118, USA b Department of Radiology, University of Erlangen-Nuremberg, Maximiliansplatz 1, 91054 Erlangen, Germany c Department of Radiology, Klinikum Augsburg, Augsburg, Stenglinstr 2, 86156 Augsburg, Germany d Institute of Anatomy, Paracelsus Medical University, Strubergasse 21, 5020 Salzburg, Austria e Department of Radiology, Bridgeport Hospital, Yale University School of Medicine, 267 Grant Street, Bridgeport, CT 06610, USA

a b s t r a c t Keywords: Osteoarthritis Imaging Radiography MR imaging Ultrasound CT PET

Osteoarthritis (OA) is the most prevalent joint disorder with no approved disease-modifying treatment available. The importance of imaging in assessing all joint structures involved in the disease process, including articular cartilage, meniscus, subarticular bone marrow, and synovium for diagnosis, prognostication, and follow-up, has been well recognized. In daily clinical practice, conventional radiography is still the most commonly used imaging technique for the evaluation of a patient with known or suspected OA and radiographic outcome measures are still the only approved end point by regulatory authorities in clinical trials. The ability of magnetic resonance imaging (MRI) to visualize all joint structures in three-dimensional fashion including tissue ultrastructure has markedly deepened our understanding of the

* Corresponding author. Department of Radiology, Quantitative Imaging Center (QIC), Boston University School of Medicine, 820 Harrison Avenue, FGH Building, 3rd Floor, Boston, MA 02118, USA. Tel.: þ1 617 4144954/þ49 9131 8536065/þ49 821 400161358; fax: þ1 617 6386616/þ49 9131 8536068/þ49 821 4003312. E-mail addresses: [email protected], [email protected], [email protected] (F.W. Roemer), felix. [email protected] (F. Eckstein), [email protected] (D. Hayashi), [email protected] (A. Guermazi). 1 Tel.: þ1 617 4144957/þ1 203 384 3834; fax: þ1 617 6386616. 2 Tel.: þ1 617 4143893; fax: þ1 617 6386616. 3 Tel.: þ43 662 44 2002 1240; fax: þ43 662 44 2002 1249.

http://dx.doi.org/10.1016/j.berh.2014.02.002 1521-6942/Ó 2014 Elsevier Ltd. All rights reserved.

32

F.W. Roemer et al. / Best Practice & Research Clinical Rheumatology 28 (2014) 31–60

natural history of the disease. This article describes the roles and limitations of different imaging modalities for clinical practice and research in OA, with a focus on radiography and MRI and an emphasis on the knee joint. Ó 2014 Elsevier Ltd. All rights reserved .

Knee osteoarthritis (OA) is a major public health problem that primarily affects the elderly. Almost 10% of the U. S. population suffers from symptomatic knee OA by the age of 60 [1]. Its prevalence is increasing in the aging population and it is a frequent cause of dependency in lower-limb tasks [2–4]. In total, the health-care expenditures of this condition have been estimated at $US189 billion annually [5]. Despite this, there are no approved interventions that ameliorate structural progression of this disorder. The increasing importance of imaging in osteoarthritis for diagnosis, prognostication, and follow-up is well recognized by both clinicians and OA researchers. While conventional radiography is the gold standard imaging technique for the evaluation of known or suspected OA in clinical practice and research, it has limitations that have become apparent in the course of large magnetic resonance imaging (MRI)-based knee osteoarthritis studies [6,7]. Pathological changes may be evident in all structures of a joint with OA, although traditionally researchers have viewed articular cartilage as the central feature and as the primary target for intervention and measurement. Of the commonly employed imaging techniques, only MRI can assess all structures of the joint, including cartilage, meniscus, ligaments, muscle, subarticular bone marrow, and synovium, and thus can show the knee as a whole organ three-dimensionally. In addition, it can directly help in the assessment of cartilage morphology and composition. This imaging modality, therefore, plays a crucial role in increasing our understanding of the natural history of OA and in the development of new therapies. The advantages and limitations of conventional radiography, MRI, and other techniques, such as ultrasound, nuclear medicine, computed tomography (CT), and CT arthrography, in the imaging of OA in both clinical practice and research are described in this review article. Review criteria This a nonsystematic, narrative review based on a comprehensive literature search in PubMed, using the following search terms in various combinations: “radiography,” “magnetic resonance imaging”; “computed tomography,” “PET,” “osteoarthritis,” “semi-quantitative scoring”; “morphometry,” “knee”; “hand”; “hip” and “spine.” All articles identified were English-language full-text papers between 2000 and 2013, focusing on recent published research. The reference lists of identified papers were also used to identify further relevant articles, and relevant references published prior to 2000 were included where appropriate. Because of the abundance of publications on the topic over the past years, the authors had to prioritize inclusion of publications based on personal judgment of potential relevance to the readership. Radiography Radiography is the simplest, least-expensive, and most widely deployed imaging modality. It enables detection of OA-associated bony features, such as osteophytes, subchondral sclerosis, and cysts [8]. Radiography can also determine joint space width (JSW), a surrogate of cartilage thickness and meniscal integrity, but precise measurement of each of these articular structures is not possible by conventional Xray-based methods [6,7]. Despite this limitation, slowing of radiographically detected joint space narrowing (JSN) is the only structural end point currently approved by the U.S. Food and Drug Administration (FDA) to demonstrate efficacy of disease-modifying OA drugs in phase-III clinical trials. Osteoarthritis is radiographically defined by the presence of marginal osteophytes [9]. Progression of JSN is the most commonly used criterion for the assessment of structural OA progression, and the total loss of JSW (“bone-on-bone” appearance) is one of the indicators for joint replacement [10].


33

Recent research efforts revealed that cartilage loss is not the only contributor to joint space loss, but that changes in the meniscus, such as meniscal extrusion or subluxation, are also responsible for JSN (Fig. 1) [6,11]. The lack of sensitivity and specificity of radiography for the detection of OA-associated articular tissue damage and its poor sensitivity to change at follow-up imaging are important limitations of this modality. Variations in semi-flexed knee positioning, which occur during image acquisition despite standardization, can also be problematic. Such variations can affect the quantitative measurement of various radiographic parameters of OA including JSW [12]. Despite these limitations, radiography remains the gold standard for establishing an imaging-based diagnosis of OA and assessment of structural modification in clinical trials of knee OA (Fig. 2). Semiquantitative assessments The severity of radiographic OA can be assessed using semi-quantitative scoring systems. The Kellgren and Lawrence (KL) grading system [9] is a widely accepted scheme used for defining radiographic OA based on the presence of a definite osteophyte (¼grade 2) (Fig. 2). However, KL grading has its limitations; in particular, KL 3 summarizes a scale of JSN severity from “definite” to almost “bone-tobone” that cannot be accounted for. A modification of KL grading has been suggested to improve the sensitivity to change in longitudinal knee OA studies [13], with a recommendation that OA be defined by a combination of JSN and the presence of definite osteophytes in a knee that did not have this

Fig. 1. Comparison of magnetic resonance imaging (MRI) and radiography for visualization of knee osteoarthritis. A. Baseline posterior–anterior radiograph shows normal medial tibiofemoral joint space width (arrows). B. At 3-year follow-up, definite joint space narrowing is observed. C. Baseline MRI of same knee shows multiple tissues relevant to osteoarthritis not depicted by the radiograph: Cartilage is visualized in a direct fashion as a structure of intermediate signal intensity in this proton-density weighted coronal MRI image (white arrows). The anterior (white arrowhead) and posterior (black arrowhead) cruciate ligaments are clearly depicted as hypointense structures. In addition, the menisci are visualized as hypointense triangular structures in the medial and lateral joint spaces (black arrows). Note that the medial meniscus is aligned with the medial joint margin (white line). D. At the 3-year follow-up, the MRI shows incident meniscal extrusion of the medial meniscal body, responsible for radiographic joint space narrowing (arrowheads and white line). No cartilage loss is observed during the follow-up interval.

34


Fig 2. Radiographic diagnosis of osteoarthritis. Follow-up of a patient with anterior cruciate ligament disruption. A. At baseline, only a small equivocal osteophyte is depicted at the medial joint margin (arrowhead). B. At the follow-up examination 3 years later, definite osteophytes at the medial joint margin are observed at the tibia (arrow) and femur (arrowhead).

combination on the prior radiographic assessment. For OA progression, a focus on JSN alone using either a semi-quantitative [14] or a quantitative approach was recommended. The Osteoarthritis Research Society International (OARSI) atlas [8] uses a different approach and grades tibiofemoral JSN and osteophytes separately for each compartment (medial tibiofemoral, lateral tibiofemoral, and patellofemoral) of the knee. This compartmental scoring appears to be more sensitive


35

to longitudinal radiographic changes than KL grading [14]. A recent study using data from the Osteoarthritis Initiative (OAI) demonstrated that the centralized radiographic reading is important from the viewpoint of observer reliability, as even expert readers seem to apply different thresholds for JSN grading [15]. Quantitative assessments Quantitative JSW measurements can be accomplished either manually or by a software application. JSW is the distance between the projected femoral and tibial margins on the radiographic image. Quantification of JSW using image-processing software does require a digital image either, with digitized plain films or images acquired using fully digital modalities, such as computed radiography and digital radiography. Minimum JSW is the standard metric, but some groups have investigated the use of location-specific JSW [16,17]. Various degrees of responsiveness have been observed depending on the degree of OA severity, length of the follow-up period, and the knee positioning protocol [17,18]. Measurements of JSW obtained from knee radiographs have been found to be reliable, especially when the study lasted longer than 2 years and when the radiographs were obtained with the knee in a standardized flexed position [19]. Studies of hip OA have generated conflicting results when correlating JSW and symptoms. However, it has been shown that JSW can predict hip joint replacement [20]. MRI Because of high cost per examination, MRI is not routinely used in clinical initial assessment or during disease follow-up of OA patients. However, MRI has become a key imaging tool for OA research [21–24] thanks to its ability to visualize pathologies that are not detected on radiographs, that is, articular cartilage, menisci, ligaments, synovium, capsular structures, fluid collections, and bone marrow lesions (BMLs) [25–33]. MRI enables the following: the joint can be evaluated as a whole organ; multiple tissue changes can be monitored simultaneously over several time points; pathologic changes of pre-radiographic OA can be detected at a much earlier stage of the disease; physiologic changes within joint tissues (e.g., cartilage and menisci) can be assessed before morphologic changes become apparent. An important point to note is that one needs to select appropriate MRI pulse sequences for the purpose of each study. For example, focal cartilage defects and BMLs are best assessed using fluidsensitive fast spin echo sequences (e.g., T2-weighted, proton density-weighted or intermediateweighted) with fat suppression (Figs. 3 and 4) [24,34]. Meniscal tears are better visualized on standard turbo spin echo sequences compared to three-dimensional (3D) gradient echo sequences (Fig. 5). MR images may sometimes be affected by artifacts that mimic pathological findings. For example, socalled susceptibility artifacts can be misinterpreted as cartilage loss or meniscal tear if the observer is unaware of this phenomenon [35,36]. Gradient recalled echo sequences are known to be particularly prone to this type of artifact (Fig. 6) [37]. To ascertain optimal assessment of MRI-derived data, trained expert musculoskeletal radiologists should be consulted when designing imaging-based OA studies and interpreting data generated in those studies. An MRI-based definition of OA has recently been proposed [38]. Tibiofemoral OA on MRI is defined as either (a) the presence of both, definite osteophyte formation and full-thickness cartilage loss, or (b) the presence of one of the features in (a) and one of the following: subchondral BML or cyst not associated with meniscal or ligamentous attachments; meniscal subluxation, maceration or degenerative (horizontal) tear; partial-thickness cartilage loss; and bone attrition. In addition, with MRI, OA can be classified into hypertrophic and atrophic phenotypes, according to the size of the osteophytes [32]. Importantly, the use of MRI has led to significant findings about the association of pain with BMLs [39,40] and synovitis [41,42], with implications for future OA clinical trials. Systematic reviews have demonstrated that MRI biomarkers of OA have concurrent and predictive validity, with good responsiveness and reliability [43,44]. The OARSI–FDA Working Group now recommends MRI as a suitable imaging tool for cartilage morphology in clinical trials [22].

36


Fig. 3. Longitudinal evaluation of focal cartilage lesion using MRI. Example shows development of small focal cartilage defect over a 2-year time period visualized by intermediate-weighted MRI, which is ideally suited to depict early focal cartilage surface changes. A. At baseline, very discrete surface indentation of cartilaginous surface is observed (arrowhead). B. At the 2-year follow-up, a definite fissure-like full thickness defect has developed, which undermines the chondral coverage representing partial delamination. The chondral fragment is at high risk of detachment.

Semiquantitative MRI assessment of knee OA A detailed review article focusing on semiquantitative MRI assessment of OA has been published recently [45], and we will give an essential summary of this approach in this article. In addition to the three well-established scoring systems – the Whole Organ Magnetic Resonance Imaging Score (WORMS) [46], the Knee Osteoarthritis Scoring System (KOSS) [47], and the Boston Leeds Osteoarthritis Knee Score (BLOKS) [48] – a new scoring system called the MR Imaging Osteoarthritis Knee Score (MOAKS) [49] has been added to the literature. Of the three systems, WORMS and BLOKS have been widely disseminated and used, though only a limited number of studies have directly compared the two systems. Two recent studies identified the relative strengths and weaknesses of the two systems in regard to certain features assumed to be most relevant to the natural history of the disease, including cartilage, meniscus, and BMLs [50,51]. WORMS and BLOKS have their weaknesses and it may be difficult for investigators to choose which is more suitable for the particular aims of the study they are planning. Additionally, both these systems have undergone unpublished modifications that make it


37

Fig. 4. Role of sequence selection in MRI assessment of different osteoarthritis features. A. Coronal fast low angle shot (FLASH) image shows an area of intrachondral low signal within the weight-bearing portion of the lateral femur (arrowhead). B. Corresponding coronal intermediate-weighted fat-saturated image shows that this signal change corresponds to a focal full-thickness defect that was not visualized on the FLASH image. Conventional spine echo sequences are superior in depicting focal cartilage lesions.

difficult for general readers to determine the differences between the original description and how they have been applied in later research. The use of within-grade changes for longitudinal assessment of cartilage damage and BMLs is a good example [52], which has also been applied to radiographic OA assessment in order to increase sensitivity to change [14]. Within-grade scoring describes progression or improvement of a lesion that does not meet the criteria of a full-grade change, but it does represent a

38


Fig. 5. Comparison of intermediate-weighted (IW) fat-suppressed image and dual echo at steady state (DESS) image for the detection of a meniscal tear. A. A horizontal oblique tear is shown at the posterior horn of the medial meniscus visualized as a hyperintense line reaching both the inferior and superior surfaces of the mensicus (arrows). B. The corresponding DESS image shows only intrameniscal hyperintensity (arrowhead), a nonspecific finding on unknown relevance.

definite visual change. It has become common practice to incorporate these within-grade changes whenever longitudinal cartilage assessment is contemplated, and a recent study demonstrated that within-grade changes in semiquantitative MRI assessment of cartilage and BMLs are valid and their use may increase the sensitivity of semiquantitative readings in detecting longitudinal changes in these structures [52].


39

Fig. 6. Artifacts on MRI. A. Coronal dual echo steady state (DESS) image shows a hypointense linear finding in the medial tibiofemoral joint space. So-called vacuum phenomenon is responsible for this artifact, which must not be mistaken as a solid structure. Assessment of the articular surface is impaired and signal loss with the cartilaginous contour must no be mistaken as a surface lesion (white arrow). B. Coronal IW image also shows artifact (arrow), but clearly depicts some remaining cartilage in the medial tibiofemoral joint.

By integrating expert readers’ experience with all of the available scoring tools and the published data comparing different scoring systems, MOAKS was developed as a refined scoring tool for crosssectional and longitudinal semiquantitative MR assessment of knee OA. It includes semiquantitative scoring of the following pathological features: BMLs; subchondral cysts; articular cartilage; osteophytes; Hoffa-synovitis and synovitis-effusion; meniscus; tendons and ligaments; and periarticular features such as cysts and bursitides. Using MOAKS, Bloecker and colleagues showed that knees with medial JSN were associated with greater meniscal extrusion and damage compared to knees without medial JSN [53]. Since MOAKS is a new scoring system, it needs more data to demonstrate its validity and reliability when applied to OA studies. Synovitis is an important feature of OA and shows a demonstrated association with pain [41,54]. The mechanically induced joint injury is thought to lead to variable inflammatory responses [55]. Although

40


synovitis can be evaluated with non-contrast-enhanced MRI by using the presence of signal changes in Hoffa fat pad or joint effusion as an indirect marker of synovitis, only contrast-enhanced MRI can reveal the true extent of synovial inflammation (Fig. 7) [56,57]. Scoring systems of synovitis based on contrast-enhanced MRI have been published [41,54], and these could potentially be used in clinical trials of new OA drugs that target synovitis. Semiquantitative MRI assessment of hand OA Radiography is still the imaging modality of choice clinically for OA of the hand, but the use of more sensitive imaging techniques such as ultrasound and MRI is becoming more common, especially in OA research (Fig. 8). However, the literature concerning MRI of pathological features of hand OA is still sparse, and studies have been performed without applying standardized methods [58,59]. In 2011, Haugen and colleagues proposed a semiquantitative MRI scoring system for hand OA features using an extremity 1.0 T MR system, called the Oslo Hand OA MRI Score (OHOA-MRI) [60]: it incorporates osteophyte presence and JSN (0–3 scale) and malalignment (absence/presence) similar to the OARSI atlas [8]. Scoring of key pathological features such as synovitis, flexor tenosynovitis, erosions, osteophytes, JSN, and BMLs showed good to very good intra- and inter-reader reliability. Using this scoring system, Haugen and colleagues showed that MRI could detect approximately twice as many joints with erosions and osteophytes as conventional radiography (p < 0.001), but identification of JSN, cysts, and malalignment was similar [61]. The same group of investigators showed in another study that MRIassessed moderate/severe synovitis, BMLs, erosions, attrition, and osteophytes were associated with joint tenderness independently of each other [62]. These studies demonstrated that some of the semiquantitatively assessed MRI features of hand OA may be potential targets for therapeutic interventions. Semiquantitative MRI assessment of hip OA The hip joint has a spherical structure and its very thin covering of articular hyaline cartilage makes MRI assessment of the hip much more difficult than the knee (Fig. 9). Roemer and colleagues developed a whole-organ semiquantitative multi-feature scoring method called the Hip Osteoarthritis MRI Scoring System (HOAMS) for use in observational studies and clinical trials of hip joints [63]. In HOAMS, 14 articular features are assessed: cartilage morphology, subchondral BMLs, subchondral cysts, osteophytes, acetabular labrum, synovitis (only scored when contrast-enhanced sequences were available), joint effusion, loose bodies, attrition, dysplasia, trochanteric bursitis/insertional tendonitis of the greater trochanter, labral hypertrophy, paralabral cysts and herniation pits at the supero-lateral femoral neck (Fig. 10). HOAMS demonstrated satisfactory reliability and good agreement concerning intra- and inter-observer assessment, but further validation, assessment of responsiveness, and iterative refinement of the scoring system are still needed to maximize its utility in clinical trials and epidemiological studies. MRI assessment of spine OA MRI enables imaging evaluation of the morphologic changes of the lumbar spine, including alterations of the disc and vertebral endplate, facet joint lesions, spinal canal narrowing, and nerve root compromise (Fig. 11). Pfirrmann et al. [64] proposed a five-level classification system specifically for lumbar intervertebral disc degeneration based on sagittal images from routine T2-weighted MRI with grade I representing normal findings and grade V corresponding to the most severe degenerative changes. More recently, Griffith et al. [65] conducted a reliability study for an eight-level modified Pfirrmann grading system that includes a description of the alterations expected for each grade and a panel of 24 reference images, demonstrating this method to be reliable and useful for discerning severity of disc degeneration in elderly subjects. Friedrich et al. [66] graded facet joint OA on a 0–3 scale following MRI evaluation of disc degeneration and herniation, scoliosis and anterolisthesis using criteria adapted from a CT-based scoring system [67]. The overall findings of this study suggested that degenerative changes of the facet joints


41

Fig. 7. Visualization of synovitis using non-enhanced and contrast-enhanced MRI. A. Axial proton-density weighted fat-saturated image shows marked hyperintensity within the joint cavity suggesting severe joint effusion (asterisk). In addition, there is a large subchondral cyst in the lateral facet of the patella (arrowhead) and diffuse bone marrow edema in the lateral patella and trochlea (arrows). B. Axial T1-weighted fat-saturated image after contrast administration clearly visualizes severe synovial thickening depicted as contrast enhancement (asterisks). The arrow points to true amount of effusion, which is only discrete and visualized as linear hypointensity within the joint cavity.

42


Fig. 8. Finger osteoarthritis. Distal interphalangeal joint shows characteristic radiographic signs of osteoarthritis including marginal osteophyte formation (arrows) and asymmetric joint space narrowing (arrowhead). Soft tissue changes such as synovitis are only poorly visualized by X-ray and are depicted as increased soft tissue opacity reflecting soft tissue swelling.


43

Fig. 9. Multimodality imaging of severe hip osteoarthritis with pathologic correlation. A. Anterior–posterior radiograph shows marked joint space narrowing and an aceteabular oseophyte. In addition, there are distinct subchondral cystic lesions in the femoral head (arrows) and acetabulum (arrowheads). B. Coronal proton-denisty-weighted MRI depicts these subchondral cysts as hyperintense, fluid-equivalent lesions in the acetabulum (large arrows) and femoral head (small arrows). Note in addition, there is marked diffuse bone marrow edema viaualized as areas of hyperintensity in the femoral head (asterisks). C. Corresponding hematoxylineosin stain of histologic cut of femoral head confirms large subchondral cysts of the femoral head (arrows). Eosinophilic changes of the femoral head in the subchondral bone represent a mixture of edema, subchondral sclerosis, and fibrosis (asterisks).

are mainly attributable to degenerative disc disease and that instability at a discovertebral joint is associated with stress and overload of the facet joints. A recent epidemiologic study from Japan reported a very high prevalence of MRI-detected disc degeneration (grades 4 and 5 in the Pfirrmann Classification) of >70% in people under 50 years and more than 90% in people older than 50 [68]. Age and obesity were associated with the presence of disk degeneration at all levels, and low back pain was associated with the presence of degenerative disc disease in the lumbar region.

Fig. 10. Hip osteoarthritis: Sagittal intermediate-weighted fat-suppressed image shows diffuse full-thickness cartilage loss at the central superior weight bearing part of the joint. Note that due to the physiologic very thin cartilage, a clear delineation of acetabular and femoral cartilage is not possible. In addition, there are subchondral BMLs in the femoral head (arrows) and acetabulum (arrowheads).

44


Fig. 11. Osteoarthritis of the lumbar spine. Sagittal T2-weighted MRI shows marked degenerative changes including narrowing of the intervertebral spaces (arrowheads), marked disk bulging (arrows), and osseous endplate changes representing lipomatous marrow conversion (Modic II changes). Multisegmental spinal canal stenosis is observed as a result of disk alterations. In comparison to CT, MRI superiorly depicts soft tissue changes and bone marrow alterations.

MRI assessment of shoulder OA To the authors’ knowledge, only one study has reported semiquantitative grading of acromioclavicular joint OA: de Abreu et al. [69] developed a scoring system in which, acromioclavicular joint OA severity on scale of 1–3 was defined according to the presence – and the size for selected features – of hyperintensity on T2-weighted images indicative of subchondral cysts, bone sclerosis, osteophytes, soft-tissue proliferation, and mass effect on the rotator cuff. Using this grading scheme, the researchers demonstrated that features of acromioclavicular joint OA are more frequently detected with MRI than


45

with conventional radiography and concluded that better evaluation of acromioclavicular joint OA and the effect of this disease on the underlying rotator cuff is possible with MRI (Fig. 12) [69]. Quantitative analysis of articular cartilage and other tissues Quantitative measurement of cartilage morphology requires high-resolution 3D imaging sequences that delineate the bone–cartilage interface and cartilage surface with adequate contrast. Such measurements have been validated in spoiled gradient echo images [70] and more recently in double echo steady-state images [71], and the sensitivity to change has been reported for both image contrasts [72,73]. Cartilage quantification requires segmentation of the hyaline cartilage tissue (Figs. 13 and 14) and exploits the 3D nature of MRI data sets to evaluate tissue dimensions (such as thickness, area volume, and others) as continuous variables. A nomenclature for MRI-based cartilage measures was proposed by Eckstein and colleagues [74]: for example, VC, cartilage volume; AC, area of cartilage surface; tAB, total area of subchondral bone; dAB, denuded area of subchondral bone; ThCtAB.Me, mean cartilage thickness over the tAB; and others. Because the above measures are partly correlated among each other, Buck et al. identified a core subset of measures that provide independent information cross-sectionally and longitudinally: these were ThCtAB.Me, tAB, and dAB [75]. Among these, dAB was shown to be associated with concurrent [76] and incident knee pain [77]. Change in ThCtAB.Me was also shown to be related to an important clinical outcome, that is, the likelihood of having knee replacement in the future [78,79], in particular when cartilage loss occurred in the central medial femorotibial compartment [80]. Analysis in total knee cartilage plates and compartments has been extended methodologically to reporting changes in defined subregions [81,82]. The spatial pattern of subregional cartilage change has been reported in various cohorts [83,84], including OAI participants with 1-, 2-, and 4-year follow-up [23,85–87]. These approaches have led to the observation that (regional) cartilage thickening, predominantly in the external medial femoral condyle, likely may be an early event in OA pathophysiology [86,88]. Based on subregional cartilage analysis, an (extended) ordered values approach was proposed for analyzing the magnitude of subregional changes in cartilage thickness independent of their anatomic location [90–92]. This approach was found more efficient in discriminating longitudinal rates of change between healthy knees and those with different radiographic OA grades [89,90], and superior in detecting risk factors of OA progression [91,92]. Among different predictors of structural progression [92,93], malalignment [93] and baseline medial or lateral radiographic JSN of the affected compartment [94] were particularly effective in identifying participants with a high risk of subsequent cartilage loss. This relationship is likely because of an association between high dynamic load and cartilage loss [95]. Systemic and subchondral bone density [96] and subchondral trabecular structure were also found to have an association with cartilage change [97], the latter also with the risk of knee replacement [98]. Distinct from these structural predictors, presence of frequent pain at baseline was independently associated with structural progression [99]. Further, the amount of physical activity, measured by a pedometer, was deleteriously related to knee structural change, but only in those with preexisting structural abnormalities and with low baseline cartilage thickness [100]. Further, weight gain was associated with greater cartilage loss, while weight loss was associated with less cartilage volume loss in subjects with meniscal tears; however, no such relationship was found in the (larger) subcohort without meniscal lesions [101]. The relationship between cartilage loss and endocrine factors has also been explored: In a crosssectional study, Wei et al. [102] observed that parity, but not the use of hormone replacement therapy or oral contraceptives, was independently associated with lower tibial cartilage volume. Stannus et al. [103] recently reported that serum leptin levels, high body mass index (BMI), and high trunk and high total body fat were negatively associated with knee cartilage thickness. The latter associations disappeared after adjustment for leptin, indicating that this “adipokine” may mediate the association between obesity and cartilage thickness. Baseline leptin levels were also associated with longitudinal cartilage thinning, and the authors suggested that leptin leads to catabolic cartilage degradation when present in excess, whereas it may involve anabolic chondrocyte activity and beneficial effects on cartilage under physiological conditions [104].

46


Fig. 12. MRI of shoulder osteoarthritis. A. Coronal non-fat-suppressed T1-weighted image of glenohumeral osteoarthritis. Bony pathology is well visualized on T1-weighted non-fat-suppressed MRI. A large inferior osteophyte is present at the humeral head (small arrow). A small calcified loose body is seen adjacent to osteophyte (white arrowhead). Subchondral sclerosis is depicted as linear hypointensity directly adjacent to humeral cortex (large arrows). B. Coronal T1-weighted fat-saturated image after intravenous contrast administration shows marked synovitis in the axillary recess and an additional osteophytes at the inferior glenoid that was not depicted on the T1 weighted non-fat-suppressed image (arrow). In addition, there is a complete tear of the supraspinatus tendon medial to the tendon attachment at the greater tubercle (arrowhead). Note areas of diffuse bone marrow edema in the humeral head (asterisks).


47

Fig. 13. High-resolution knee MRI obtained with spoiled gradient-echo (SPGR) sequences with water excitation, in the same person: (A) sagittal image; (B) axial image; (C) coronal image; (D) same coronal image with the medial tibial cartilage marked (i.e., segmented) blue, medial femoral cartilage marked yellow, lateral tibial cartilage marked green, and lateral femoral cartilage marked red.

Quantitative measurements of cartilage volume and thickness change have been used as outcomes in intervention studies, for instance, evaluating the effect of nonsteroidal anti-inflammatory drugs (NSAIDs) [105], celecoxib [106], physical exercise [107], licofelone [108], chondroitin sulfate [109], and sprifermin (fibroblast growth factor 18) [110] on articular cartilage. In these studies, drug effects [106,109,110] were observed laterally, but they mostly did not reach statistical significance in the medial compartment. Nevertheless, quantitative methods were reported to be superior to semiquantitative ones in assessing cartilage change and in detecting structure modification by drug treatment [111]. A 2month surgical joint distraction was found to be very effective in regenerating cartilage in participants with late-stage knee OA, increasing cartilage thickness and decreasing denuded areas [112]. A sustained benefit on cartilage structure after this intervention was observed also after a 2-year follow-up [113]. Quantitative MRI analysis of the meniscus Wirth and colleagues presented a technique for 3D quantitative analysis of meniscal shape, position, and signal intensity [114], which was shown to display adequate inter-observer and intra-observer precision [115]. Quantitative measures of extrusion were found to display moderate correlations with semiquantitative (MOAKS) extrusion scores [116]. However, both the quantitative and semiquantitative extrusion measures only partly explained coverage of tibial cartilage by the meniscus, and a negative

48


Fig. 14. (A, B) 3D reconstruction and visualization of knee cartilage plates from a sagittal MR imaging data set. A. View on to the medial side, B. view on to the lateral side: medial tibial cartilage marked blue, medial femoral cartilage marked yellow, lateral tibial cartilage marked green, lateral femoral cartilage marked red, femoral trochlear cartilage marked turquoise, and patellar cartilage marked magenta.

association between meniscus width and tibial coverage was observed, which was as strong as that of extrusion [116]. Semiautomatic segmentation approaches to the meniscus also have been explored [117]. When examining healthy reference subjects from the OAI, Bloecker et al. found the meniscus surface area to strongly correspond with tibial plateau area in the same compartment and tibial coverage by the meniscus to be similar between men and women (50% in the medial and 58% in the lateral compartment) [115]. In knees with medial radiographic JSN, medial tibial coverage was, however, only 36% in JSN1 and as little as 31% in JSN2/3 knees, compared with 45% in contralateral no-JSN knees [53]. The medial JSN knees showed greater meniscus extrusion and damage (MOAKS), but no significant difference in meniscus volume; no differences in lateral meniscus measures were observed between knees with and without medial JSN [53]. In the same cohort, side differences in medial radiographic JSW were found to be associated with the percentage of medial tibial plateau coverage by the meniscus (r2 z 25%), whereas lower correlation coefficients were observed for other meniscus measures, such as size and extrusion [118]. The between-knee differences of radiographic JSW most strongly correlated with side differences in cartilage thickness of the central medial, weight-bearing femur (r2 z 50%), whereas other femorotibial subregions displayed lower coefficients [118]. The exclusion of the knees with nonoptimal alignment (i.e., rim distance) between the tibial plateau and the X-ray beam improved the correlation with femoral cartilage thickness with radiographic JSW to z65%, whereas the relationship with meniscus measures was not affected [118]. These findings suggest that radiographic JSW provides a better representation of (central) femoral cartilage thickness when optimal radiographic positioning is achieved [118]. Comparing quantitative meniscus position, size, and shape measures between OA and healthy reference knees, the peripheral margin appeared more bulged, with lesser tibial coverage and greater extrusion in OA knees [119]. While no difference in medial meniscus size was observed, the lateral meniscus body displayed a slightly larger volume (as well as more bulging and extrusion) than healthy knees [119]. The authors also described an association between meniscal extrusion and presence/ absence of knee pain between contralateral knees with discordant pain and concordant radiographic knee OA status [120]. These results suggest that meniscus extrusion is associated with pain, independently of radiographic status, potentially through mechanical irritation of the joint capsule. Other than menisci, investigators have used quantitative MRI to assess BMLs [121], synovitis [122], and joint effusion [123]. However, it should be kept in mind that using segmentation approaches for illdefined lesions such as BMLs is more challenging than segmentation of clearly delineated structures, such as cartilage, menisci, and effusion.


49

Compositional MRI Compositional MRI allows visualization of the biochemical properties of different joint tissues. It is therefore very sensitive to early, pre-morphologic changes that cannot be seen on conventional MRI. The vast majority of studies applying compositional MRI has focused on cartilage, although the technique can also be used to assess other tissues, such as the meniscus or ligaments. Compositional imaging of cartilage matrix changes can be performed using advanced MRI techniques, such as delayed Gadolinium Enhanced Magnetic Resonance Imaging of Cartilage (dGEMRIC), T1 rho, and T2 mapping (Fig. 15) [21,124–126]. Today, compositional MRI techniques are not used in routine clinical practice and remain sophisticated research tools that are only available at a limited number of research institutions. Nevertheless, the application in clinical trials and observational studies has been ongoing. In a placebo-controlled double-blind pilot study of collagen hydrolysate for mild knee OA, McAlindon and colleagues [127] demonstrated that the dGEMRIC score increased in tibial cartilage regions of interest in patients receiving collagen hydrolysate and decreased in the placebo group. A significant difference was observed at 24 weeks. It will be interesting to see if macroscopic cartilage changes are associated with those early dGEMRIC findings in future studies. Van Ginckel and colleagues [128] showed an increase in dGEMRIC indices of knee cartilage in asymptomatic untrained women who were enrolled in a 10-week running program, when compared to sedentary controls. The same group recently presented a systematic overview of cartilage matrix adaptations measured by compositional MRI techniques after anterior cruciate ligament (ACL) injury that might potentially be relevant for later OA development [129]. Souza and colleagues [130] demonstrated that acute loading of the knee joint resulted in a significant decrease in T1 rho and T2 relaxation times of the medial tibiofemoral compartment, and especially in cartilage regions with small focal defects. These data suggest that changes of T1 rho values under mechanical loading may be related to the biomechanical and structural properties of cartilage. Hovis and colleagues reported that light exercise was associated with low cartilage T2 values, but moderate and strenuous exercise was associated with high T2 values in women, suggesting that activity levels can affect cartilage composition [131]. In an interventional study assessing the effect of weight loss on articular cartilage, Anandacoomarasamy and colleagues reported that improved articular cartilage quality was reflected as an increase in the dGEMRIC index over 1 year for the medial, but not the lateral compartment [132]. This finding highlights the role of weight loss in possible clinical and structural improvement. Williams and colleagues described intrameniscal biochemical alterations using ultra-short echo time-enhanced T2* mapping [133] and found significant elevations of ultrashort echo time-enhanced-T2* values in the menisci of subjects with ACL injuries, but who showed no clinical evidence of subsurface meniscal abnormality. Novel compositional techniques have been further explored. Raya and colleagues found that in vivo diffusion tensor imaging based on a 7T MR system could distinguish OA knees from non-OA knees better than T2 mapping [134]. Other work on 7T systems reported on the reproducibility of the method in vivo [135]. Another compositional technique that might reward further exploration is T2* mapping of cartilage [136]. These techniques show promise, but they will need to be practical and deployable using standard MRI systems before they can be widely used as a research or a clinical diagnostic tool. Ultrasound Ultrasound imaging enables real time, multiplanar imaging at a relatively low cost. It offers reliable assessment of OA-associated features, including inflammatory and structural abnormalities, without contrast administration or exposure to radiation [137]. Limitations of ultrasound are that it is an operator-dependent technique and that the physical properties of sound limit its ability to assess deeper articular structures and the subchondral bone (Fig. 16). Ultrasound is useful for evaluation of cortical erosive changes and synovitis in inflammatory arthritis. In OA, the ability to detect synovial pathology is the major advantage ultrasound has over conventional radiography. Current-generation ultrasound technology can detect synovial hypertrophy, increased vascularity, and the presence of synovial fluid in joints affected by OA [137]. The Outcome Measures in Rheumatoid Arthritis Clinical Trials (OMERACT) Ultrasonography Taskforce reported an

50


Fig. 15. Longitudinal assessment using compositional MRI. A. Baseline sagittal proton density-weighted fat-suppressed image shows horizontal–oblique tear of the posterior horn of the medial meniscus (arrow). B. Corresponding sagittal 3D inversion recoveryprepared spoiled gradient echo (SPGR) image (acquired 90 min after intravenous administration of gadolinium shows normal color coded articular cartilage coverage). C. At 24-month follow-up, decrease in the dGEMRIC index in the weight-bearing part of the medial femoral cartilage is observed, which is coded in red (white arrows), while the articular surface morphology remains intact. In addition, partial maceration of the posterior horn of the medial meniscus is observed (black arrowhead) likely responsible for biomechanical alterations leading to early cartilage damage.


51

Fig. 16. Sonographic image of the medial tibiofemoral joint space in advanced osteoarthritis. Image shows marked extrusion of the body of the medial meniscus (double headed arrow). In addition, a small femoral osteophyte is depicted (arrow). Note that there is sound extinction toward the more central parts of the joint (left in image), which does not allow for assessment of the cartilage surface and the ligaments in these areas of the joint.

ultrasound definition of synovial hypertrophy as “abnormal hypoechoic (relative to subdermal fat, but sometimes may be isoechoic or hyperechoic) intra-articular tissue that is non-displaceable and poorly compressible and which may exhibit Doppler.” [138] Although this definition was developed for use in rheumatoid arthritis, it may also be applied to OA because the difference in synovial inflammation between OA and rheumatoid arthritis is largely quantitative rather than qualitative [137]. A preliminary ultrasonographic scoring system for features of hand OA was published in 2008 [139]. This scoring system included evaluation of gray-scale synovitis and power Doppler signal in 15 joints of the hand. These features were assessed for their presence/absence, and if present, they were scored semiquantitatively using a 1–3 scale. Overall, the reliability exercise demonstrated moderately good intra- and inter-reader reliability. This study showed that an ultrasound outcome measure suitable for multicenter trials assessing hand OA is feasible and likely to be reliable, and has provided a foundation for further development. Ultrasound has been increasingly deployed for assessment of hand OA. Kortekaas and coworkers showed that ultrasound-detected osteophytes and JSN are associated with hand pain [140]. The same group of investigators also showed that signs of inflammation appear more frequently on ultrasound in erosive OA hands than in nonerosive OA hands [141]. This finding suggests the presence of an underlying

52


systemic cause for erosive evolution. Klauser and colleagues evaluated the efficacy of weekly ultrasoundguided intra-articular injections of hyaluronic acid [142]. A decrease in pain correlated with a decrease in synovial thickening and power Doppler ultrasound score between before and after therapy. Interestingly, Iagnocco and colleagues performed real-time fusion of ultrasound and MRI in hand and wrist OA, and found a high concordance of the bony profile visualization at the level of osteophytes [59]. Evaluation of OA features in the knee [143,144] and hip [145] has also been documented. A crosssectional, multicenter European study supported by European League Against Rheumatism (EULAR) analyzed 600 patients with painful knee OA and found that ultrasound-detected synovitis correlated with advanced radiographic OA and clinical symptoms and signs are suggestive of an inflammatory “flare.” [143] Saarakkala and colleagues evaluated the diagnostic performance of knee ultrasound for the detection of degenerative changes of articular cartilage, using arthroscopic findings as the reference [144]. They found that positive ultrasound findings are strong indicators of cartilage degeneration, but negative findings do not exclude cartilage degeneration. Wu and colleagues investigated the association of ultrasound features with pain and the functional scores in patients with equal radiographic grades of knee OA in both knees [146]. They showed that ultrasound-detected inflammatory features were positively and linearly associated with knee pain in motion. These findings confirmed the association between synovitis and knee pain, which has also been reported in MRI-based studies [41]. Ultrasound has also been used to assess clinical response to steroid injection [98], but further studies are needed to demonstrate the utility of ultrasound for this purpose. Nuclear medicine Use of 99mTc-hydroxymethane diphosphonate (HDP) scintigraphy and 2-18F fluoro-2-deoxy-Dglucose (18-FDG) or 18F-fluoride (18-F) positron emission tomography (PET) for assessing OA have been described in the literature [147]. Bone scintigraphy is a simple examination that can provide a full-body survey that helps to discriminate between soft tissues and bone origin of pain, and to locate the site of pain in patients with complex symptoms [147]. 18-FDG PET can demonstrate the site of synovitis and BMLs associated with OA [148] (Fig. 17). 18-F PET can be used for bone imaging; the amount of tracer uptake depends on the regional blood flow and bone remodeling conditions [149]. An in vivo study by Temmerman and colleagues demonstrated a significant increase in bone metabolism in the proximal femur of patients with symptomatic hip OA [150], showing that 18-F PET is a potentially useful technique for early detection of OA changes. Currently, researchers are searching for a cartilage-specific radiopharmaceutical agent to be used with single photon emission tomography (SPECT) for OA imaging [151].

Fig. 17. 2-18F-fluoro-2-deoxy–D-glucose (FDG) positron emission tomography (PET). A. Axial PET image of right knee shows marked glucose uptake in the intercondylar notch. B. Reconstructed low-resolution coronal computed tomography image depicts joint space narrowing of the medial tibiofemoral joint (arrows) and subchondral tibial sclerosis (asterisk). In addition, there is a small medial tibial osteophyte (arrowhead). C. Coronal fusion image of PET and CT localizes the pathologic glucose accumulation clearly to the intercondylar notch around the posterior cruciate ligament, the commonest site of synovitis in knee osteoarthritis. Hypermetabolic finding represents periligamentous synovitis. Note high sensitivity of PET for hypermetabolism, but low specificity and poor spatial localization without correlation with additional cross-sectional imaging (as CT or MRI).


53

Limitations of radioisotope methods include poor anatomical resolution and the use of ionizing radiation. However, there are ways to overcome these issues. Hybrid technologies such as PET–CT and PET–MRI combine functional imaging with high-resolution anatomical imaging. A study by Moon and coworkers demonstrated that PET–CT could detect active inflammation in patients with OA of the shoulder [152]. Techniques to achieve the optimum registration of PET and MRI images are under development [153]. Although originally developed for breast imaging, small-part scanners may be useful for imaging of joints [147]. The small-part PET scanners have the advantages of lower operating costs and lower radiation exposure, while retaining high spatial resolution and sensitivity for detection of lesions (Fig. 17). Computed tomography CT is the method of choice for depicting cortical bone and soft-tissue calcifications and has an established role in assessing facet joint OA of the spine in both clinical and research settings. Using a CT-based semiquantitative grading system of facet joint OA, Kalichman and colleagues showed a high prevalence of facet joint OA and that the prevalence of facet joint OA increases with age, with the highest prevalence at the L4–L5 spinal level [154]. Using the same cohort of subjects, several associations were observed: self-reported back pain with spinal stenosis [155]; obesity with higher prevalence of facet joint OA [156]; and increasing age with higher prevalence of disc narrowing, facet joint OA, and degenerative spondylolisthesis [156]. Kim and colleagues used micro-CT to assess the cartilage alterations in the facet joint of rats and showed that monosodium iodoacetate injection into facet joints provided a useful model for the study of OA changes in the facet joint and indicated that facet joint degeneration is a major cause of low back pain [157]. CT and MR arthrography CT or MR arthrography enables evaluation of damage to articular cartilage with a high anatomical resolution in a multiplanar fashion. CT arthrography can be performed using a single- (iodine alone) or double-contrast (iodine and air) technique [147]. To avoid beam-hardening artifacts, the contrast material can be diluted with saline or local anesthetics [147]. For MR arthrography, gadoliniumdiethylenetriamine pentaacetate (DTPA) is injected intra-articularly to visualize superficial cartilage defects. These arthrographic examinations have a low risk of infection from the intra-articular injection. Other risks include pain and vasovagal reactions and systemic allergic reactions. CT arthrography exposes patients to radiation but MR arthrography does not. At present, CT arthrography is the most accurate method for evaluating articular cartilage surface damage. It offers high spatial resolution and high contrast between the low attenuating cartilage and high attenuating superficial (contrast material filling the joint space) and deep (subchondral bone) boundaries [147]. Regarding subchondral changes, MR arthrography is the only technique that allows delineation of subchondral BMLs on the fluid-sensitive sequences with fat suppression [147]. CT arthrography is ideally suited to depict subchondral bone sclerosis and osteophytes. Both techniques enable visualization of central osteophytes, which are associated with more severe changes of OA than marginal osteophytes [158]. Because of the high cost, invasive nature and potential, albeit low, risk associated with intra-articular injection, arthrographic examinations are rarely used in large-scale clinical or epidemiological OA studies. Implementation of OA imaging research to clinical practice With many research efforts currently ongoing, which involve imaging evaluation on a large scale, it is to be expected that eventually more advanced imaging will find its role also in clinical management of patients with OA. Clinical evaluation and radiographic assessment are sufficient for a diagnosis of OA. With no effective disease-modifying compounds available, imaging has little role in monitoring disease progression from a clinical perspective. Advanced imaging methods such as MRI are implemented mainly for reasons of differential diagnosis and to rule out complications of a disease. As MRI findings may not necessarily translate into clinical symptoms, interpretation of these images always has to

54


account for the individual patient and patient symptoms need to be carefully correlated [159]. Whenever preventive strategies or structure modification are eventually implemented, it is to be expected that potentially more advanced techniques like compositional MRI will find their way into clinical practice. Summary In clinical and research settings, radiography is still commonly used to semiquantitatively and quantitatively evaluate structural OA features, such as osteophytes and JSN. Radiographic JSW measurement is still a recommended option for trials of structural modification in OA clinical trials, with the understanding that the concept of JSW represents a number of pathologies including cartilage and meniscal damage, and trial duration may be long. MRI is currently the most important imaging modality for research in OA, and investigators may select from semiquantitative, quantitative, and compositional assessment techniques. Ultrasound is commonly used in hand OA studies and is particularly useful for evaluation of synovitis. Nuclear medicine, CT, and CT–MR arthrography can also be used for evaluation of OA features, but they have very limited roles in large-scale clinical or epidemiological studies.

Practice points Radiography is still the most widely deployed imaging modality for diagnosis and clinical management of OA patients and often sufficient in a clinical context A reduction in the loss of JSW represents the only approved end point for structural disease progression in clinical trials by the US and European regulatory authorities The ability of MR to image the knee as a whole organ and to visualize cartilage morphology and composition plays a critical role in understanding the natural history of the disease and in the search for new, disease-altering therapies The main MRI-based assessment approaches of OA are semiquantitative, quantitative, and compositional MRI findings need to be carefully correlated with clinical manifestations of disease Ultrasound may be useful to evaluate synovial pathology in OA, particularly in the hand and helps in tailoring individualized treatment Other imaging modalities like CT play only a minor role in patient management

Research agenda Large ongoing OA studies including advanced imaging techniques such as the OA Initiative will enable researchers to better understand the natural history of disease and especially disease initiation The conundrum of imaging-assessed structural disease manifestation and clinical presentation will be focus of ongoing research efforts More detailed stratification of subject inclusion into clinical trials by advanced imaging will be paramount for success of disease modifying agents Paramount will be to disentangle the chronology of tissues affected leading to manifest OA Compositional MRI techniques will have to be assessed in patients with early disease in regard to predicting later disease outcomes and thus might eventually find their way into clinical application There is constant need for refining established imaging assessment methods and validate these against clinical outcomes


55

Conflict of interest Dr. Roemer is Chief Medical Officer and shareholder of Boston Imaging Core Lab (BICL), a company providing image assessment services. Dr. Eckstein has received consultancies, speaking fees, and/or honoraria from Merck Serono, Sanofi Aventis, Abbvie, and Medtronic, and is CEO and shareholder of Chondrometrics GmbH, a company providing image analysis services to academia and to the pharmaceutical industry. Dr. Guermazi has received consultancies, speaking fees, and/or honoraria from Genzyme, Stryker, Merck Serono, Novartis, and Astra Zeneca and is the President of BICL. He received a research grant from General Electric Healthcare. Role of the funding source No funding received. References [1] Losina E, Weinstein AM, Reichmann WM, et al. Lifetime risk and age at diagnosis of symptomatic knee osteoarthritis in the US. Arthritis Care Res (Hoboken) 2013;65:703–11. [2] Felson DT, Zhang Y, Hannan MT, et al. The incidence and natural history of knee osteoarthritis in the elderly. The Framingham Osteoarthritis Study. Arthritis Rheum 1995;38:1500–5. [3] Vos T, Flaxman AD, Naghavi M, et al. Years lived with disability (YLDs) for 1160 sequelae of 289 diseases and injuries 1990–2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012;380:2163–96. [4] Guccione AA, Felson DT, Anderson JJ, et al. The effects of specific medical conditions on the functional limitations of elders in the Framingham Study. Am J Public Health 1994;84:351–8. [5] Kotlarz H, Gunnarsson CL, Fang H, Rizzo JA. Insurer and out-of-pocket costs of osteoarthritis in the US: evidence from national survey data. Arthritis Rheum 2009;60:3546–53. [6] Hunter DJ, Zhang YQ, Tu X, et al. Change in joint space width: hyaline articular cartilage loss or alteration in meniscus? Arthritis Rheum 2006;54:2488–95. [7] Amin S, LaValley MP, Guermazi A, et al. The relationship between cartilage loss on magnetic resonance imaging and radiographic progression in men and women with knee osteoarthritis. Arthritis Rheum 2005;52:3152–9. *[8] Altman RD, Gold GE. Atlas of individual radiographic features in osteoarthritis, revised. Osteoarthritis Cartilage 2007; 15(Suppl. A):A1–56. *[9] Kellgren JH, Lawrence JS. Radiological assessment of osteo-arthrosis. Ann Rheum Dis 1957;16:494–502. [10] Carr AJ, Robertsson O, Graves S, et al. Knee replacement. Lancet 2012;379:1331–40. [11] Gale DR, Chaisson CE, Totterman SM, et al. Meniscal subluxation: association with osteoarthritis and joint space narrowing. Osteoarthritis Cartilage 1999;7:526–32. [12] Kinds MB, Vincken KL, Hoppinga TN, et al. Influence of variation in semiflexed knee positioning during image acquisition on separate quantitative radiographic parameters of osteoarthritis, measured by Knee Images Digital Analysis. Osteoarthritis Cartilage 2012;20:997–1003. [13] Felson DT, Niu J, Guermazi A, et al. Defining radiographic incidence and progression of knee osteoarthritis: suggested modifications of the Kellgren and Lawrence scale. Ann Rheum Dis 2011;70:1884–6. [14] Felson DT, Nevitt MC, Yang M, et al. A new approach yields high rates of radiographic progression in knee osteoarthritis. J Rheumatol 2008;35:2047–54. [15] Guermazi A, Hunter DJ, Li L, et al. Different thresholds for detecting osteophytes and joint space narrowing exist between the site investigators and the centralized reader in a multicenter knee osteoarthritis study – data from the Osteoarthritis Initiative. Skeletal Radiol 2012;41:179–86. [16] Duryea J, Zaim S, Genant HK. New radiographic-based surrogate outcome measures for osteoarthritis of the knee. Osteoarthritis Cartilage 2003;11:102–10. [17] Nevitt MC, Peterfy C, Guermazi A, et al. Longitudinal performance evaluation and validation of fixed-flexion radiography of the knee for detection of joint space loss. Arthritis Rheum 2007;56:1512–20. [18] Duryea J, Neumann G, Niu J, et al. Comparison of radiographic joint space width with magnetic resonance imaging cartilage morphometry: analysis of longitudinal data from the Osteoarthritis Initiative. Arthritis Care Res (Hoboken) 2010;62:932–7. [19] Reichmann WM, Maillefert JF, Hunter DJ, et al. Responsiveness to change and reliability of measurement of radiographic joint space width in osteoarthritis of the knee: a systematic review. Osteoarthritis Cartilage 2011;19:550–6. [20] Chu Miow Lin D, Reichmann WM, Gossec L, et al. Validity and responsiveness of radiographic joint space width metric measurement in hip osteoarthritis: a systematic review. Osteoarthritis Cartilage 2011;19:543–9. [21] Roemer FW, Crema MD, Trattnig S, Guermazi A. Advances in imaging of osteoarthritis and cartilage. Radiology 2011; 260:332–54. [22] Conaghan PG, Hunter DJ, Maillefert JF, et al. Summary and recommendations of the OARSI FDA osteoarthritis Assessment of Structural Change Working Group. Osteoarthritis Cartilage 2011;19:606–10. [23] Eckstein F, Wirth W, Nevitt MC. Recent advances in osteoarthritis imaging – the osteoarthritis initiative. Nat Rev Rheumatol 2012;8:622–30. [24] Hayashi D, Guermazi A, Roemer FW. MRI of osteoarthritis: the challenges of definition and quantification. Semin Musculoskelet Radiol 2012;16:419–30.

56

F.W. Roemer et al. / Best Practice & Research Clinical Rheumatology 28 (2014) 31–60 *[25] Guermazi A, Niu J, Hayashi D, et al. Prevalence of abnormalities in knees detected by MRI in adults without knee osteoarthritis: population based observational study (Framingham Osteoarthritis Study). BMJ 2012;345:e5339. [26] Englund M, Roemer FW, Hayashi D, et al. Meniscus pathology, osteoarthritis and the treatment controversy. Nat Rev Rheumatol 2012;8:412–9. [27] Hayashi D, Roemer FW, Dhina Z, et al. Longitudinal assessment of cyst-like lesions of the knee and their relation to radiographic osteoarthritis and MRI-detected effusion and synovitis in patients with knee pain. Arthritis Res Ther 2010;12:R172. *[28] Roemer FW, Felson DT, Wang K, et al. Co-localisation of non-cartilaginous articular pathology increases risk of cartilage loss in the tibiofemoral joint – the MOST study. Ann Rheum Dis 2013;72:942–8. [29] Crema MD, Roemer FW, Felson DT, et al. Factors associated with meniscal extrusion in knees with or at risk for osteoarthritis: the Multicenter Osteoarthritis study. Radiology 2012;264:494–503. [30] Roemer FW, Kwoh CK, Hannon MJ, et al. Risk factors for magnetic resonance imaging-detected patellofemoral and tibiofemoral cartilage loss during a six-month period: the joints on glucosamine study. Arthritis Rheum 2012;64: 1888–98. [31] Felson DT, Parkes MJ, Marjanovic EJ, et al. Bone marrow lesions in knee osteoarthritis change in 6–12 weeks. Osteoarthritis Cartilage 2012;20:1514–8. *[32] Roemer FW, Guermazi A, Niu J, et al. Prevalence of magnetic resonance imaging-defined atrophic and hypertrophic phenotypes of knee osteoarthritis in a population-based cohort. Arthritis Rheum 2012;64:429–37. [33] Englund M, Felson DT, Guermazi A, et al. Risk factors for medial meniscal pathology on knee MRI in older US adults: a multicentre prospective cohort study. Ann Rheum Dis 2011;70:1733–9. [34] Hayashi D, Guermazi A, Kwoh CK, et al. Semiquantitative assessment of subchondral bone marrow edema-like lesions and subchondral cysts of the knee at 3T MRI: a comparison between intermediate-weighted fat-suppressed spin echo and Dual Echo Steady State sequences. BMC Musculoskelet Disord 2011;12:198. [35] Sakamoto FA, Winalski CS, Schils JP, et al. Vacuum phenomenon: prevalence and appearance in the knee with 3 T magnetic resonance imaging. Skeletal Radiol 2011;40:1275–85. [36] Patten RM. Vacuum phenomenon: a potential pitfall in the interpretation of gradient-recalled-echo MR images of the shoulder. Am J Roentgenol 1994;162:1383–6. [37] Hayashi D, Jarraya M, Guermazi A, Roemer F. Frequency and fluctuation of susceptibility artifacts in the tibiofemoral joint space in painful knees on 3T MRI and association with meniscal tears, radiographic joint space narrowing and calcifications. Arthritis Rheum 2012;64:S1030. [38] Hunter DJ, Arden N, Conaghan PG, et al. Definition of osteoarthritis on MRI: results of a Delphi exercise. Osteoarthritis Cartilage 2011;19:963–9. [39] Zhang Y, Nevitt M, Niu J, et al. Fluctuation of knee pain and changes in bone marrow lesions, effusions, and synovitis on magnetic resonance imaging. Arthritis Rheum 2011;63:691–9. [40] Felson DT, Chaisson CE, Hill CL, et al. The association of bone marrow lesions with pain in knee osteoarthritis. Ann Intern Med 2001;134:541–9. [41] Guermazi A, Roemer FW, Hayashi D, et al. Assessment of synovitis with contrast-enhanced MRI using a whole-joint semiquantitative scoring system in people with, or at high risk of, knee osteoarthritis: the MOST study. Ann Rheum Dis 2011;70:805–11. [42] Crema MD, Felson DT, Roemer FW, et al. Peripatellar synovitis: comparison between non-contrast-enhanced and contrast-enhanced MRI and association with pain. The MOST study. Osteoarthritis Cartilage 2013;21:413–8. *[43] Hunter DJ, Zhang W, Conaghan PG, et al. Systematic review of the concurrent and predictive validity of MRI biomarkers in OA. Osteoarthritis Cartilage 2011;19:557–88. [44] Hunter DJ, Zhang W, Conaghan PG, et al. Responsiveness and reliability of MRI in knee osteoarthritis: a meta-analysis of published evidence. Osteoarthritis Cartilage 2011;19:589–605. [45] Guermazi A, Roemer FW, Haugen IK, et al. MRI-based semiquantitative scoring of joint pathology in osteoarthritis. Nat Rev Rheumatol 2013;9:236–51. [46] Peterfy CG, Guermazi A, Zaim S, et al. Whole-organ magnetic resonance imaging score (WORMS) of the knee in osteoarthritis. Osteoarthritis Cartilage 2004;12:177–90. [47] Kornaat PR, Ceulemans RY, Kroon HM, et al. MRI assessment of knee osteoarthritis: knee osteoarthritis scoring system (KOSS) – inter-observer and intra-observer reproducibility of a compartment-based scoring system. Skeletal Radiol 2005;34:95–102. [48] Hunter DJ, Lo GH, Gale D, et al. The reliability of a new scoring system for knee osteoarthritis MRI and the validity of bone marrow lesion assessment: BLOKS (Boston Leeds Osteoarthritis Knee Score). Ann Rheum Dis 2008;67:206–11. *[49] Hunter DJ, Guermazi A, Lo GH, et al. Evolution of semi-quantitative whole joint assessment of knee OA: MOAKS (MRI osteoarthritis knee score). Osteoarthritis Cartilage 2011;19:990–1002. [50] Lynch JA, Roemer FW, Nevitt MC, et al. Comparison of BLOKS and WORMS scoring systems, part I. Cross sectional comparison of methods to assess cartilage morphology, meniscal damage and bone marrow lesions on knee MRI: data from the osteoarthritis initiative. Osteoarthritis Cartilage 2010;18:1393–401. [51] Felson DT, Lynch J, Guermazi A, et al. Comparison of BLOKS and WORMS scoring systems, part II. Longitudinal assessment of knee MRIs for osteoarthritis and suggested approach based on their performance: data from the Osteoarthritis Initiative. Osteoarthritis Cartilage 2010;18:1402–7. [52] Roemer FW, Nevitt MC, Felson DT, et al. Predictive validity of within-grade scoring of longitudinal changes of MRIbased cartilage morphology and bone marrow lesion assessment in the tibio-femoral joint – the MOST study. Osteoarthritis Cartilage 2012;20:1391–8. [53] Bloecker K, Guermazi A, Wirth W, et al. Tibial coverage, meniscus position, size and damage in knees discordant for joint space narrowing – data from the Osteoarthritis Initiative. Osteoarthritis Cartilage 2013;21:419–27. [54] Baker K, Grainger A, Niu J, et al. Relation of synovitis to knee pain using contrast-enhanced MRIs. Ann Rheum Dis 2010;69:1779–83. [55] Felson DT. Osteoarthritis as a disease of mechanics. Osteoarthritis Cartilage 2013;21:10–5.


57

[56] Loeuille D, Chary-Valckenaere I, Champigneulle J, et al. Macroscopic and microscopic features of synovial membrane inflammation in the osteoarthritic knee: correlating magnetic resonance imaging findings with disease severity. Arthritis Rheum 2005;52:3492–501. [57] Loeuille D, Sauliere N, Champigneulle J, et al. Comparing non-enhanced and enhanced sequences in the assessment of effusion and synovitis in knee OA: associations with clinical, macroscopic and microscopic features. Osteoarthritis Cartilage 2011;19:1433–9. [58] Wittoek R, Jans L, Lambrecht V, et al. Reliability and construct validity of ultrasonography of soft tissue and destructive changes in erosive osteoarthritis of the interphalangeal finger joints: a comparison with MRI. Ann Rheum Dis 2011;70: 278–83. [59] Iagnocco A, Perella C, D’Agostino MA, et al. Magnetic resonance and ultrasonography real-time fusion imaging of the hand and wrist in osteoarthritis and rheumatoid arthritis. Rheumatology (Oxf) 2011;50:1409–13. [60] Haugen IK, Lillegraven S, Slatkowsky-Christensen B, et al. Hand osteoarthritis and MRI: development and first validation step of the proposed Oslo Hand Osteoarthritis MRI score. Ann Rheum Dis 2011;70:1033–8. [61] Haugen IK, Boyesen P, Slatkowsky-Christensen B, et al. Comparison of features by MRI and radiographs of the interphalangeal finger joints in patients with hand osteoarthritis. Ann Rheum Dis 2012;71:345–50. [62] Haugen IK, Boyesen P, Slatkowsky-Christensen B, et al. Associations between MRI-defined synovitis, bone marrow lesions and structural features and measures of pain and physical function in hand osteoarthritis. Ann Rheum Dis 2012;71:899–904. [63] Roemer FW, Hunter DJ, Winterstein A, et al. Hip Osteoarthritis MRI Scoring System (HOAMS): reliability and associations with radiographic and clinical findings. Osteoarthritis Cartilage 2011;19:946–62. [64] Pfirrmann CW, Metzdorf A, Zanetti M, et al. Magnetic resonance classification of lumbar intervertebral disc degeneration. Spine (Phila Pa 1976) 2001;26:1873–8. [65] Griffith JF, Wang YX, Antonio GE, et al. Modified Pfirrmann grading system for lumbar intervertebral disc degeneration. Spine 2007;32:E708–12. [66] Friedrich KM, Nemec S, Peloschek P, et al. The prevalence of lumbar facet joint edema in patients with low back pain. Skeletal Radiol 2007;36:755–60. [67] Pathria M, Sartoris DJ, Resnick D. Osteoarthritis of the facet joints: accuracy of oblique radiographic assessment. Radiology 1987;64:227–30. [68] Teraguchi M, Yoshimura N, Hashizume H, et al. Prevalence and distribution of intervertebral disc degeneration over the entire spine in a population-based cohort: The Wakayama Spine Study. Osteoarthritis Cartilage; 2013 Nov 14. http://dx.doi.org/10.1016/j.joca.2013.10.019. pii: S1063-4584(13)01002-9 [Epub ahead of print]. [69] de Abreu MR, Chung CB, Wesselly M, et al. Acromioclavicular joint osteoarthritis: comparison of findings derived from MR imaging and conventional radiography. Clin Imaging 2005;29:273–7. [70] Graichen H, von Eisenhart-Rothe R, Vogl T, et al. Quantitative assessment of cartilage status in osteoarthritis by quantitative magnetic resonance imaging: technical validation for use in analysis of cartilage volume and further morphologic parameters. Arthritis Rheum 2004;50:811–6. [71] Eckstein F, Hudelmaier M, Wirth W, et al. Double echo steady state magnetic resonance imaging of knee articular cartilage at 3 Tesla: a pilot study for the Osteoarthritis Initiative. Ann Rheum Dis 2006;65:433–41. [72] Hudelmaier M, Wirth W, Wehr B, et al. Femorotibial cartilage morphology: reproducibility of different metrics and femoral regions, and sensitivity to change in disease. Cells Tissues Organs 2010;192:340–50. [73] Wirth W, Nevitt M, Hellio Le Graverand MP, et al. Sensitivity to change of cartilage morphometry using coronal FLASH, sagittal DESS, and coronal MPR DESS protocols – comparative data from the Osteoarthritis Initiative (OAI). Osteoarthritis Cartilage 2010;18:547–54. *[74] Eckstein F, Ateshian G, Burgkart R, et al. Proposal for a nomenclature for magnetic resonance imaging based measures of articular cartilage in osteoarthritis. Osteoarthritis Cartilage 2006;14:974–83. [75] Buck RJ, Wyman BT, Le Graverand MP, et al. An efficient subset of morphological measures for articular cartilage in the healthy and diseased human knee. Magn Reson Med 2010;63:680–90. [76] Cotofana S, Wyman BT, Benichou O, et al. Relationship between knee pain and the presence, location, size and phenotype of femorotibial denuded areas of subchondral bone as visualized by MRI. Osteoarthritis Cartilage 2013;21: 1214–22. [77] Moisio K, Eckstein F, Chmiel JS, et al. Denuded subchondral bone and knee pain in persons with knee osteoarthritis. Arthritis Rheum 2009;60:3703–10. [78] Raynauld JP, Martel-Pelletier J, Haraoui B, et al. Risk factors predictive of joint replacement in a 2-year multicentre clinical trial in knee osteoarthritis using MRI: results from over 6 years of observation. Ann Rheum Dis 2011;70:1382–8. [79] Pelletier JP, Cooper C, Peterfy C, et al. What is the predictive value of MRI for the occurrence of knee replacement surgery in knee osteoarthritis? Ann Rheum Dis 2013;72:1594–604. [80] Eckstein F, Kwoh CK, Boudreau RM, et al. Quantitative MRI measures of cartilage predict knee replacement: a case– control study from the Osteoarthritis Initiative. Ann Rheum Dis 2013;72:707–14. [81] Wirth W, Eckstein F. A technique for regional analysis of femorotibial cartilage thickness based on quantitative magnetic resonance imaging. IEEE Trans Med Imaging 2008;27:737–44. [82] Wirth W, Hellio Le Graverand MP, Wyman BT, et al. Regional analysis of femorotibial cartilage loss in a subsample from the Osteoarthritis Initiative progression subcohort. Osteoarthritis Cartilage 2009;17:291–7. [83] Eckstein F, Wirth W, Hudelmaier M, et al. Patterns of femorotibial cartilage loss in knees with neutral, varus, and valgus alignment. Arthritis Rheum 2008;59:1563–70. [84] Le Graverand MP, Buck RJ, Wyman BT, et al. Change in regional cartilage morphology and joint space width in osteoarthritis participants versus healthy controls: a multicentre study using 3.0 Tesla MRI and Lyon-Schuss radiography. Ann Rheum Dis 2010;69:155–62. [85] Cotofana S, Buck R, Dreher D, et al. Longitudinal (1-year) change in cartilage thickness in knees with early knee osteoarthritis: a within-person between-knee comparison-data from the OAI. Arthritis Care Res (Hoboken); 2013 Sep 19. http://dx.doi.org/10.1002/acr.22172 [Epub ahead of print].

58


[86] Buck RJ, Wirth W, Dreher D, et al. Frequency and spatial distribution of cartilage thickness change in knee osteoarthritis and its relation to clinical and radiographic covariates – data from the osteoarthritis initiative. Osteoarthritis Cartilage 2013;21:102–9. [87] Eckstein F, Mc Culloch CE, Lynch JA, et al. How do short-term rates of femorotibial cartilage change compare to longterm changes? Four year follow-up data from the osteoarthritis initiative. Osteoarthritis Cartilage 2012;20:1250–7. [88] Buck RJ, Wyman BT, Le Graverand MP, et al. Osteoarthritis may not be a one-way-road of cartilage loss – comparison of spatial patterns of cartilage change between osteoarthritic and healthy knees. Osteoarthritis Cartilage 2010;18:329–35. [89] Buck RJ, Wyman BT, Le Graverand MP, et al. Does the use of ordered values of subregional change in cartilage thickness improve the detection of disease progression in longitudinal studies of osteoarthritis? Arthritis Rheum 2009;61:917–24. [90] Wirth W, Buck R, Nevitt M, et al. MRI-based extended ordered values more efficiently differentiate cartilage loss in knees with and without joint space narrowing than region-specific approaches using MRI or radiography – data from the OA initiative. Osteoarthritis Cartilage 2011;19:689–99. [91] Buck RJ, Wyman BT, Hellio Le Graverand MP, et al. Using ordered values of subregional cartilage thickness change increases sensitivity in detecting risk factors for osteoarthritis progression. Osteoarthritis Cartilage 2010;19:302–8. *[92] Eckstein F, Le Graverand MP, Charles HC, et al. Clinical, radiographic, molecular and MRI-based predictors of cartilage loss in knee osteoarthritis. Ann Rheum Dis 2011;70:1223–30. [93] Sharma L, Eckstein F, Song J, et al. Relationship of meniscal damage, meniscal extrusion, malalignment, and joint laxity to subsequent cartilage loss in osteoarthritic knees. Arthritis Rheum 2008;58:1716–26. [94] Wirth W, Nevitt M, Hellio Le Graverand MP, et al. Lateral and medial joint space narrowing predict subsequent cartilage loss in the narrowed, but not in the non-narrowed femorotibial compartment – data from the Osteoarthritis Initiative. Osteoarthritis Cartilage; 2013 Nov 1. http://dx.doi.org/10.1016/j.joca.2013.10.011. pii: S1063-4584(13)009849 [Epub ahead of print]. [95] Bennell KL, Bowles KA, Wang Y, et al. Higher dynamic medial knee load predicts greater cartilage loss over 12 months in medial knee osteoarthritis. Ann Rheum Dis 2011;70:1770–4. [96] Cao Y, Stannus OP, Aitken D, et al. Cross-sectional and longitudinal associations between systemic, subchondral bone mineral density and knee cartilage thickness in older adults with or without radiographic osteoarthritis. Ann Rheum Dis; 2013 Jul 31. http://dx.doi.org/10.1136/annrheumdis-2013-203691 [Epub ahead of print]. *[97] Kraus VB, Feng S, Wang S, et al. Subchondral bone trabecular integrity predicts and changes concurrently with radiographic and magnetic resonance imaging-determined knee osteoarthritis progression. Arthritis Rheum 2013; 65:1812–21. [98] Podsiadlo P, Cicuttini FM, Wolski M, et al. Trabecular bone texture detected by plain radiography is associated with an increased risk of knee replacement in patients with osteoarthritis: a 6 year prospective follow up study. Osteoarthritis Cartilage; 2013 Nov 8. http://dx.doi.org/10.1016/j.joca.2013.10.017. pii: S1063-4584(13)01000-5 [Epub ahead of print]. [99] Eckstein F, Cotofana S, Wirth W, et al. Greater rates of cartilage loss in painful knees than in pain-free knees after adjustment for radiographic disease stage: data from the osteoarthritis initiative. Arthritis Rheum 2011;63:2257–67. [100] Dore DA, Winzenberg TM, Ding C, et al. The association between objectively measured physical activity and knee structural change using MRI. Ann Rheum Dis 2013;72:1170–5. [101] Teichtahl AJ, Wluka AE, Wang Y, et al. The longitudinal relationship between changes in body weight and changes in medial tibial cartilage, and pain among community-based adults with and without meniscal tears. Ann Rheum Dis; 2013 Jun 6 [Epub ahead of print]. [102] Wei S, Venn A, Ding C, et al. The associations between parity, other reproductive factors and cartilage in women aged 50–80 years. Osteoarthritis Cartilage 2011;19:1307–13. [103] Stannus OP, Jones G, Blizzard L, et al. Associations between serum levels of inflammatory markers and change in knee pain over 5 years in older adults: a prospective cohort study. Ann Rheum Dis 2013;72:535–40. [104] Stannus OP, Cao Y, Antony B, et al. Cross-sectional and longitudinal associations between circulating leptin and knee cartilage thickness in older adults. Ann Rheum Dis; 2013 Sep 27. http://dx.doi.org/10.1136/annrheumdis-2013-203308 [Epub ahead of print]. [105] Ding C, Cicuttini F, Jones G. Do NSAIDs affect longitudinal changes in knee cartilage volume and knee cartilage defects in older adults? Am J Med 2009;122:836–42. [106] Raynauld JP, Martel-Pelletier J, Beaulieu A, et al. An open-label pilot study evaluating by magnetic resonance imaging the potential for a disease-modifying effect of celecoxib compared to a modelized historical control cohort in the treatment of knee osteoarthritis. Semin Arthritis Rheum 2010;40:185–92. [107] Cotofana S, Ring-Dimitriou S, Hudelmaier M, et al. Effects of exercise intervention on knee morphology in middle-aged women: a longitudinal analysis using magnetic resonance imaging. Cells Tissues Organs 2010;192:64–72. [108] Raynauld JP, Martel-Pelletier J, Bias P, et al. Protective effects of licofelone, a 5-lipoxygenase and cyclo-oxygenase inhibitor, versus naproxen on cartilage loss in knee osteoarthritis: a first multicentre clinical trial using quantitative MRI. Ann Rheum Dis 2009;68:938–47. [109] Wildi LM, Raynauld JP, Martel-Pelletier J, et al. Chondroitin sulphate reduces both cartilage volume loss and bone marrow lesions in knee osteoarthritis patients starting as early as 6 months after initiation of therapy: a randomised, double-blind, placebo-controlled pilot study using MRI. Ann Rheum Dis 2011;70:982–9. [110] Mc Pherson R, Flechsenhar K, Hellot S, Eckstein F. A randomized, double blind, placebo-controlled multicenter study of RHFGF18 administered intraarticularly using single or multiple ascending doses in patients with primary knee osteoarthritis (OA), not expected to require knees surgery within 1 year. Osteoarthritis Cartilage 2011;19:S35. [111] Wildi LM, Martel-Pelletier J, Abram F, et al. Assessment of cartilage changes over time in knee osteoarthritis diseasemodifying osteoarthritis drug trials using semiquantitative and quantitative methods: pros and cons. Arthritis Care Res (Hoboken) 2013;65:686–94. *[112] Intema F, Van Roermund PM, Marijnissen AC, et al. Tissue structure modification in knee osteoarthritis by use of joint distraction: an open 1-year pilot study. Ann Rheum Dis 2011;70:1441–6. [113] Wiegant K, van Roermund PM, Intema F, et al. Sustained clinical and structural benefit after joint distraction in the treatment of severe knee osteoarthritis. Osteoarthritis Cartilage 2013;21:1660–7.


59

[114] Wirth W, Frobell RB, Souza RB, et al. A three-dimensional quantitative method to measure meniscus shape, position, and signal intensity using MR images: a pilot study and preliminary results in knee osteoarthritis. Magn Reson Med 2010;63:1162–71. [115] Bloecker K, Englund M, Wirth W, et al. Revision 1 size and position of the healthy meniscus, and its correlation with sex, height, weight, and bone area – a cross-sectional study. BMC Musculoskelet Disord 2011;12:248. [116] Bloecker K, Guermazi A, Wirth W, et al. Correlation of semiquantitative vs quantitative MRI meniscus measures in osteoarthritic knees: results from the Osteoarthritis Initiative. Skeletal Radiol; 2013 Nov 21 [Epub ahead of print]. [117] Swanson MS, Prescott JW, Best TM, et al. Semi-automated segmentation to assess the lateral meniscus in normal and osteoarthritic knees. Osteoarthritis Cartilage 2010;18:344–53. [118] Bloecker K, Wirth W, Hunter DJ, et al. Contribution of regional 3D meniscus and cartilage morphometry by MRI to joint space width in fixed flexion knee radiography – a between-knee comparison in subjects with unilateral joint space narrowing. Eur J Radiol 2013;82:e832–9. [119] Wenger A, Wirth W, Hudelmaier M, et al. Meniscus body position, size, and shape in persons with and persons without radiographic knee osteoarthritis: quantitative analyses of knee magnetic resonance images from the osteoarthritis initiative. Arthritis Rheum 2013;65:1804–11. [120] Wenger A, Englund M, Wirth W, et al. Relationship of 3D meniscal morphology and position with knee pain in subjects with knee osteoarthritis: a pilot study. Eur Radiol 2012;22:211–20. [121] Roemer FW, Khrad H, Hayashi D, et al. Volumetric and semiquantitative assessment of MRI-detected subchondral bone marrow lesions in knee osteoarthritis: a comparison of contrast-enhanced and non-enhanced imaging. Osteoarthritis Cartilage 2010;18:1062–6. [122] Fotinos-Hoyer AK, Guermazi A, Jara H, et al. Assessment of synovitis in the osteoarthritic knee: comparison between manual segmentation, semiautomated segmentation, and semiquantitative assessment using contrast-enhanced fatsuppressed T1-weighted MRI. Magn Reson Med 2010;64:604–9. [123] Habib S, Guermazi A, Ozonoff A, et al. MRI-based volumetric assessment of joint effusion in knee osteoarthritis using proton density-weighted fat-suppressed and T1-weighted contrast-enhanced fat-suppressed sequences. Skeletal Radiol 2011;40:1581–5. [124] Crema MD, Roemer FW, Marra MD, et al. Articular cartilage in the knee: current MR imaging techniques and applications in clinical practice and research. Radiographics 2011;31:37–61. [125] Burstein D, Gray M, Mosher T, Dardzinski B. Measures of molecular composition and structure in osteoarthritis. Radiol Clin North Am 2009;47:675–86. [126] Trattnig S, Domayer S, Welsch GW, et al. MR imaging of cartilage and its repair in the knee – a review. Eur Radiol 2009; 19:1582–94. [127] McAlindon TE, Nuite M, Krishnan N, et al. Change in knee osteoarthritis cartilage detected by delayed gadolinium enhanced magnetic resonance imaging following treatment with collagen hydrolysate: a pilot randomized controlled trial. Osteoarthritis Cartilage 2011;19:399–405. [128] Van Ginckel A, Baelde N, Almqvist KF, et al. Functional adaptation of knee cartilage in asymptomatic female novice runners compared to sedentary controls. A longitudinal analysis using delayed Gadolinium Enhanced Magnetic Resonance Imaging of Cartilage (dGEMRIC). Osteoarthritis Cartilage 2010;18:1564–9. [129] Van Ginckel A, Verdonk P, Witvrouw E. Cartilage adaptation after anterior cruciate ligament injury and reconstruction: implications for clinical management and research? A systematic review of longitudinal MRI studies. Osteoarthritis Cartilage 2013;21:1009–24. [130] Souza RB, Stehling C, Wyman BT, et al. The effects of acute loading on T1rho and T2 relaxation times of tibiofemoral articular cartilage. Osteoarthritis Cartilage 2010;18:1557–63. [131] Hovis KK, Stehling C, Souza RB, et al. Physical activity is associated with magnetic resonance imaging-based knee cartilage T2 measurements in asymptomatic subjects with and those without osteoarthritis risk factors. Arthritis Rheum 2011;63:2248–56. [132] Anandacoomarasamy A, Leibman S, Smith G, et al. Weight loss in obese people has structure-modifying effects on medial but not on lateral knee articular cartilage. Ann Rheum Dis 2012;71:26–32. [133] Williams A, Qian Y, Golla S, Chu CR. UTE-T2* mapping detects sub-clinical meniscus injury after anterior cruciate ligament tear. Osteoarthritis Cartilage 2012;20:486–94. [134] Raya JG, Horng A, Dietrich O, et al. Articular cartilage: in vivo diffusion-tensor imaging. Radiology 2012;262:550–9. [135] Madelin G, Babb JS, Xia D, et al. Reproducibility and repeatability of quantitative sodium magnetic resonance imaging in vivo in articular cartilage at 3 T and 7 T. Magn Reson Med 2012;68:841–9. [136] Newbould RD, Miller SR, Toms LD, et al. T2* measurement of the knee articular cartilage in osteoarthritis at 3T. J Magn Reson Imaging 2012;35:1422–9. [137] Keen HI, Conaghan PG. Ultrasonography in osteoarthritis. Radiol Clin North Am 2009;47:581–94. [138] Wakefield RJ, Balint PV, Szkudlarek M, et al. Musculoskeletal ultrasound including definitions for ultrasonographic pathology. J Rheumatol 2005;32:2485–7. [139] Keen HI, Lavie F, Wakefield RJ, et al. The development of a preliminary ultrasonographic scoring system for features of hand osteoarthritis. Ann Rheum Dis 2008;67:651–5. [140] Kortekaas MC, Kwok WY, Reijnierse M, et al. Osteophytes and joint space narrowing are independently associated with pain in finger joints in hand osteoarthritis. Ann Rheum Dis 2011;70:1835–7. [141] Kortekaas MC, Kwok WY, Reijnierse M, et al. In erosive hand osteoarthritis more inflammatory signs on ultrasound are found than in the rest of hand osteoarthritis. Ann Rheum Dis 2013;72:930–4. [142] Klauser AS, Faschingbauer R, Kupferthaler K, et al. Sonographic criteria for therapy follow-up in the course of ultrasound-guided intra-articular injections of hyaluronic acid in hand osteoarthritis. Eur J Radiol 2012;81:1607–11. [143] Conaghan PG, D’Agostino MA, Le Bars M, et al. Clinical and ultrasonographic predictors of joint replacement for knee osteoarthritis: results from a large, 3-year, prospective EULAR study. Ann Rheum Dis 2010;69:644–7. [144] Saarakkala S, Waris P, Waris V, et al. Diagnostic performance of knee ultrasonography for detecting degenerative changes of articular cartilage. Osteoarthritis Cartilage 2012;20:376–81.

60

F.W. Roemer et al. / Best Practice & Research Clinical Rheumatology 28 (2014) 31–60 [145] Iagnocco A, Filippucci E, Riente L, et al. Ultrasound imaging for the rheumatologist XLI. Sonographic assessment of the hip in OA patients. Clin Exp Rheumatol 2012;30:652–7. [146] Wu PT, Shao CJ, Wu KC, et al. Pain in patients with equal radiographic grades of osteoarthritis in both knees: the value of gray scale ultrasound. Osteoarthritis Cartilage 2012;20:1507–13. [147] Omoumi P, Mercier GA, Lecouvet F, et al. CT arthrography, MR arthrography, PET, and scintigraphy in osteoarthritis. Radiol Clin North Am 2009;47:595–615. [148] Nakamura H, Masuko K, Yudoh K, et al. Positron emission tomography with 18F-FDG in osteoarthritic knee. Osteoarthritis Cartilage 2007;15:673–81. [149] Umemoto Y, Oka T, Inoue T, Saito T. Imaging of a rat osteoarthritis model using (18)F-fluoride positron emission tomography. Ann Nucl Med 2010;24:663–9. [150] Temmerman OP, Raijmakers PG, Kloet R, et al. In vivo measurements of blood flow and bone metabolism in osteoarthritis. Rheumatol Int 2013;33:959–63. [151] Cachin F, Boisgard S, Vidal A, et al. First ex vivo study demonstrating that 99mTc-NTP 15-5 radiotracer binds to human articular cartilage. Eur J Nucl Med Mol Imaging 2011;38:2077–82. [152] Moon YL, Lee SH, Park SY, et al. Evaluation of shoulder disorders by 2-[F-18]-fluoro-2-deoxy-D-glucose positron emission tomography and computed tomography. Clin Orthop Surg 2010;2:167–72. [153] Magee D, Tanner SF, Waller M, et al. Combining variational and model-based techniques to register PET and MR images in hand osteoarthritis. Phys Med Biol 2010;55:4755–69. [154] Kalichman L, Li L, Kim DH, et al. Facet joint osteoarthritis and low back pain in the community-based population. Spine (Phila Pa 1976) 2008;33:2560–5. [155] Kalichman L, Kim DH, Li L, et al. Computed tomography-evaluated features of spinal degeneration: prevalence, intercorrelation, and association with self-reported low back pain. Spine J 2010;10:200–8. [156] Kalichman L, Guermazi A, Li L, Hunter DJ. Association between age, sex, BMI and CT-evaluated spinal degeneration features. J Back Musculoskelet Rehabil 2009;22:189–95. [157] Kim JS, Kroin JS, Buvanendran A, et al. Characterization of a new animal model for evaluation and treatment of back pain due to lumbar facet joint osteoarthritis. Arthritis Rheum 2011;63:2966–73. [158] McCauley TR, Kornaat PR, Jee WH. Central osteophytes in the knee: prevalence and association with cartilage defects on MR imaging. Am J Roentgenol 2001;176:359–64. [159] Jensen MC, Brant-Zawadzki MN, Obuchowski N, et al. Magnetic resonance imaging of the lumbar spine in people without back pain. N Engl J Med 1994;331:69–73.

Quantitative imaging of osteoarthritis.

Unraveling the role of Mg(++) in osteoarthritis.

Imaging of Osteoarthritis in Geriatric Patients.

Role of modern imaging techniques in hand osteoarthritis research and clinical practice.

Osteoblast role in osteoarthritis pathogenesis.

The evolving role of biomarkers for osteoarthritis.

The role of arthroscopy in the management of knee osteoarthritis.

The Role of Aging in the Development of Osteoarthritis.

Role of vasoactive intestinal peptide in osteoarthritis.

Role of Arthroscopy in the Treatment of Osteoarthritis of Knee.

Role of arthroscopy in osteoarthritis of the knee.

The role of small leucine-rich proteoglycans in osteoarthritis pathogenesis.

The Role of MicroRNAs and Their Targets in Osteoarthritis.

Imaging the hip joint in osteoarthritis: A place for ultrasound?

What has imaging contributed to the epidemiological understanding of osteoarthritis?

Role of autophagy in the progression of osteoarthritis: The autophagy inhibitor, 3-methyladenine, aggravates the severity of experimental osteoarthritis.

The protective role of autophagy in experimental osteoarthritis, and the therapeutic effects of Torin 1 on osteoarthritis by activating autophagy.

The role of US in breast imaging.

Semiquantitative Imaging Biomarkers of Knee Osteoarthritis Progression: Data From the Foundation for the National Institutes of Health Osteoarthritis Biomarkers Consortium.

The role of imaging in musculoskeletal emergencies.

Possible role of granulysin in pathogenesis of osteoarthritis.

Role of hyaluronic Acid in early diagnosis of knee osteoarthritis.

Role of HIF-1α and HIF-2α in osteoarthritis.

Role of exercise in patients with symptomatic knee osteoarthritis.