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OSTEOARTHRITIS: Edited by Steven B. Abramson

Use of imaging techniques to predict progression in osteoarthritis

Ding, Changhaia,b; Zhang, Yuqingc; Hunter, Davidd

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Current Opinion in Rheumatology: January 2013 - Volume 25 - Issue 1 - p 127-135
doi: 10.1097/BOR.0b013e32835a0fe1
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Osteoarthritis is a common chronic disease that results in changes in the structures of whole joint with associated pain and deterioration of function [1,2]. Conventional approaches for the treatment of osteoarthritis range from conservative nonpharmacologic measures, analgesic relief, to surgical intervention including joint replacement. Currently, there is no regulatory approved treatment that can slow or arrest disease progression.

Traditionally, radiographs are utilized to monitor the progression of disease; however, they have been criticized as insensitive to change, not specific, and subject to measurement error because of change in positioning [3]. They also are incapable of detection of early disease [4]. Sensitive, valid, and reproducible imaging techniques that can visualize whole-joint structures are preferred to accurately measure disease progression from its earliest stages (Table 1). Foremost among these techniques is magnetic resonance imaging (MRI), a noninvasive three-dimensional modality for assessing whole-joint morphology that is supplanting the commonly used plain radiographs in epidemiological studies and clinical trials.

Table 1:
Osteoarthritis at different stages

In this narrative review, we will briefly introduce the methods of assessing osteoarthritis progression (Table 2) [2,5–9,10▪▪,11▪,12▪▪,13–17,18▪,19▪▪,20], focusing on MRI, and will then appraise traditional, structural, and some novel risk factors that may delineate individuals at risk of more rapid disease progression. Furthermore, we will discuss the methodological challenges in identifying the risk factors for progression, as well as consider how to apply progression assessments and the risk factor knowledge to clinical practice and clinical trials. We will focus on the primary research articles published over the preceding year and predominantly on the knee as that is the bulk of the literature on this topic.

Table 2:
Imaging methods for assessing OA disease progression
Box 1:
no caption available


Progression of osteoarthritis is typically defined as increasing structural disease severity. Usually, this is only defined in persons with preexisting radiographic change; however, as will be made clear this distinction may be unhelpful because the disease can initiate much earlier including from the compositional changes stage (Table 1).

Plain radiography

Radiographs can assess joint space width (JSW) or joint space narrowing (JSN) and provide an indirect estimate of cartilage thickness and meniscal integrity. Changes in JSW between the tibial and femoral margins are recommended to assess the disease progression of osteoarthritis [21]. Although some recent studies still utilize the Kellgren–Lawrence (K/L) grading system to assess osteoarthritis progression [6,7], this should be avoided because they are limited by invalid assumptions that osteoarthritis is a composite construct of osteophytes and JSN, and these radiographic changes are linear and equidistant over the course of the disease [20,21].

Progression of radiographic features of osteoarthritis has been summarized in Table 2.


MRI has been utilized to directly visualize joint structure and enable the examination of the whole joint and structural changes starting from their earliest stages (Table 1). These structural abnormalities can be assessed semi-quantitatively using different scoring systems with adequate sensitivity, specificity, and reliability [2,10▪▪,22]. Progression of these features can be detected, as shown in Table 2. The three-dimensional coverage by MRI allows the direct quantification of cartilage volume and thickness. Loss of cartilage volume has been utilized to monitor the progression of knee osteoarthritis (Table 2) and is far more sensitive than radiographic assessment of progression [23]. Changes in knee cartilage thickness between compartments or subregions display a great amount of spatial heterogeneity, some even gaining thickness over time (Table 2) [13].


While female gender, aging, previous injury, obesity, and genetics are well recognized risk factors for osteoarthritis, imaging factors such as malalignment, radiographic changes, meniscal tears, bone marrow lesions (BMLs), and synovitis have been suggested to increase osteoarthritis risks (Fig. 1). These risk factors could identify individuals at risk of faster progression [10▪▪,11▪,24]; however, evidence from systematic reviews have suggested that most traditional risk factors such as sex, age, BMI, knee injury, and muscle strength are not or inconsistently associated with radiographic progression [25,26▪]. These are in stark contrast to the findings from studies using MRI [10▪▪,11▪], suggesting MRI is a more powerful tool for studying risk factors for osteoarthritis progression.

MRI features that predict future progression. Coronal fat suppressed fast spin echo proton density image with medially extruded and defunctioned medial meniscus (chevron), large bone marrow lesion in the medial tibia (block arrow), and cartilage loss over the medial femoral condyle and medial tibial plateau. A follow-up study done 10 months later showed that coronal fat suppressed fast spin echo proton density image with virtual loss of all articular cartilage over femoral and tibial surfaces as well as subchondral collapse (attrition) and bone marrow lesion in the proximal medial tibia.

Malalignment and mechanical loading

There is strong evidence that knee malalignment is an independent risk factor for radiographic and MRI-detected structural progression of knee osteoarthritis [27]. A recent study [28] in individuals with knee osteoarthritis reported that varus alignment was associated with greater loss of cartilage thickness over 2 years in the medial tibiofemoral compartments than neutral and valgus alignment, and the same for valgus alignment in the lateral tibiofemoral compartments.

Malalignment results in mechanical loading redistribution in the compartments of the joint. Bennell et al.[29] reported that a greater medial knee load reflected by a higher knee adduction moment impulse at baseline was independently associated with greater loss of medial tibial cartilage volume over 12 months in individuals with medial knee osteoarthritis, providing direct evidence that mechanical loading increases the risk of osteoarthritis progression.

Knee pain and radiographic osteoarthritis severity

Although there is conflicting evidence for knee pain as a predictor of radiographic osteoarthritis (ROA) progression [26▪], two recent cohort studies reported that knee pain was significantly associated with increased cartilage volume loss over 2.7 years [12▪▪] and cartilage thickness loss over 12 months [30]. Radiographic features afford strong evidence as predictors of ROA progression [26▪], recent studies have provided further evidence that radiographic measures including reduced JSW and higher scores of JSN, K/L, and osteophytes are associated with greater rates of cartilage volume/thickness loss or increases in cartilage defects over 1–3 years [12▪▪,14,15,31]. Older adults with evidence of ROA (any JSN or osteophytes) had greater tibial cartilage loss than those without evidence of ROA over 2.9 years (medial tibia: 4.0 vs. 2.2% per annum, lateral tibia: 3.5 vs. 1.6% per annum; both P < 0.01) [12▪▪].

MRI-assessed structural abnormalities

Effects of MRI-assessed structural abnormalities (including cartilage defects, BMLs, and meniscal damage) on osteoarthritis progression have been studied previously [10▪▪,11▪]. Further evidence has emerged recently.

Cartilage lesions

While reduced baseline cartilage thickness was associated with greater loss of cartilage thickness over 2 years in women with ROA [31], prevalent cartilage defects were associated with increased progression of cartilage defects in both tibiofemoral and patellofemoral compartments, even in a short period of 6 months [32▪▪].

Bone marrow lesions

BMLs predicted the progression of cartilage defects over 6 months [32▪▪], an increase in full thickness cartilage lesion area over 24 months [33], and cartilage defect progression and cartilage volume loss over 2.7 years [34]. Baseline BMLs were associated with cartilage defect progression and volume loss site-specifically in a dose–response manner, suggesting BMLs may have a local effect on cartilage loss [34].

Meniscal lesions

While meniscal extrusion was associated with a greater progression of tibiofemoral cartilage defects over 6 months in subjects with chronic knee pain [32▪▪], prevalent single meniscal tears and meniscal maceration were also associated with increased loss of cartilage thickness over 2 years in women over 40 years [35]. The detrimental effects of meniscal tears on loss of cartilage thickness were subregion specific, suggesting a focal protective role of meniscal tissue on articular cartilage integrity in knee osteoarthritis [36].

Effusion and synovitis

Joint effusion was associated with increased progression of patellofemoral cartilage defects in individuals with chronic knee pain over 6 months [32▪▪], and baseline joint effusion and synovitis assessed on nonenhanced MRI in knees without tibiofemoral ROA, but at risk of developing osteoarthritis predicted increased progression of tibiofemoral cartilage defects over 24 months [37].

These structural abnormalities may have additive effects on knee osteoarthritis progression, because there was a greater increase in cartilage loss when both larger cartilage defects and BMLs were present at baseline [34]. The MRI-detected structural abnormalities, including BMLs [17,38], meniscal tears [38], cartilage defects [2], denuded bone area [39▪], and loss of cartilage thickness [39▪] and volume over a period [2], predict progression to end-stage osteoarthritis which requires knee replacement.

Obesity and body composition

Evidence for the association between BMI and osteoarthritis radiographic progression are conflicting [25,26▪], but BMI is a strong predictor for long-term radiographic progression (more than 3 years) [26▪]. Effect of BMI on osteoarthritis radiographic progression can be mediated by malalignment [40]. Effects of obesity on cartilage defect progression have been established [2], but on cartilage loss are less consistent. A higher BMI was associated with greater knee cartilage volume loss in individuals with higher baseline cartilage volume (most likely because of cartilage swelling) over 2 years [41]. In individuals with risk factors for knee osteoarthritis, increased BMI was significantly associated with a greater progression of cartilage defects and constantly elevated T2 entropy, a measure of compositional change, over 36 months [18▪]. BMI was also associated with cartilage loss in older adults [42▪▪]. Interestingly, when BMI is disentangled, body fat mass and lean mass at baseline have opposing effects on cartilage loss over 2 years, with body fat being detrimental and lean mass protective against cartilage loss [42▪▪].

Physical activity and leg muscle strength

There was strong evidence that physical activity was not associated with progression of JSN, but was associated with increased osteophytes and reduced cartilage defects [43]. The authors suggested that physical activity is beneficial, rather than detrimental, to joint health [43]. In contrast, a recent study [44▪▪] reported that steps per day were associated with increases in BMLs and meniscal damage and these effects were restricted in those who did at least 10 000 steps per day, suggesting frequent or strenuous physical activity may have detrimental effects on osteoarthritis progression.

Evidence of quadriceps muscle weakness as a risk factor of knee osteoarthritis progression is limited [26▪] and its effects maybe mediated by malalignment [10▪▪]. Greater quadriceps muscle was associated with less loss of cartilage volume in relatively healthy individuals [11▪]. This is supported by a recent study [45] in individuals with symptomatic knee osteoarthritis using cartilage defect progression as the outcome measure, suggesting quadriceps muscle weakness is a risk factor for cartilage loss in osteoarthritis.

Metabolic and inflammatory factors

Body and trunk fat was associated with increased knee cartilage loss, suggesting metabolic factors may play a role in osteoarthritis progression [42▪▪]. Indeed, those with at least three metabolic components (overweight, hypertension, dyslipidemia, and impaired glucose tolerance) had a 2.8-fold increased odds ratio (P < 0.001) of osteoarthritis progression compared with those without any component [46▪]. Furthermore, high-density lipoprotein cholesterol tended to be negatively associated with change in BMLs over 2.7 years [47].

Circulating adipokine levels have been associated with osteoarthritis progression. While baseline serum soluble leptin receptor levels were associated with reduced levels of a cartilage formation biomarker, an increase in cartilage defects and more loss of cartilage volume over 2 years in individuals with clinical knee osteoarthritis [48], high serum adiponectin levels were associated with reduced progression of hand osteoarthritis over 6 years [49].

Inflammatory cytokines are also associated with osteoarthritis progression. Serum levels of interleukin (IL)-6 were associated with ROA progression over 5–10 years in women [50], and predicted increased cartilage volume loss in older adults [51] and osteoarthritis patients [52]. Increased IL-1β and tumor necrosis factor (TNF)-α gene expressions in peripheral blood leukocytes are associated with increased risks of knee ROA progression, as measured by both changes in JSW and KL score over 24 months [53▪]. Similarly, IL-18 and TNF-α levels in synovial fluid were associated with an increase in osteophyte grade over 3 years in osteoarthritis patients [54].


To date, many risk factors have been identified to be associated with the risk of incident ROA [55]; however, most of these risk factors, particularly chronic or systemic ones (e.g. BMI), have been inconsistently associated with increased risk of ROA progression [26▪,40]. Interestingly, some risk factors (e.g. high bone density) increase the risk of incident knee ROA but are not associated with, or even decrease, the risk of ROA progression [56–58]. Although it is possible that the risk factors for incident ROA may be biologically different from those for disease progression, there are also compelling methodological explanations for such paradoxical phenomenon.

Most risk factors for knee ROA (e.g. body weight and bone density) are chronic in nature. Their relation to the natural history of ROA development can be illustrated using a causal diagram (Fig. 2). To simplify our discussion on the studies of the effect of risk factor X on ROA progression among knees with mild ROA (i.e. K/L = 2), let's assume the risk factor X is a binary factor coded as ‘Present’ or ‘Absent’ (such as obese vs. nonobese); all other potential risk factors are evenly distributed between two categories of risk factor X (i.e. there is no confounder that will bias the association between risk factor X and development of severe ROA); and risk factor X could not cause knees to develop severe ROA without first causing knees to develop mild or moderate ROA (i.e. risk factor X occurred before knees developed mild ROA). Under such circumstance, assessing the effect of risk factor X on development of moderate or severe ROA (i.e. ROA progression) among knees with mild ROA is akin to performing a statistical analysis of adjusting for an intermediate variable (i.e. adjusting for mild ROA). By doing so, it would completely eliminate the effect of risk factor X on the risk of ROA progression. However, such a finding does not imply that risk factor X is not a cause of ROA progression. For example, if one assembles a group of individuals who have mild knee ROA and have BMI between 25 and 30 kg/m2. Individuals are randomly assigned into two groups: one will receive a well defined intervention program that attempts to reduce the participant's weight and another will receive the placebo (i.e. it is unlikely to reduce the weight). Such a study will let us test the hypothesis whether weight loss is a causal factor for ROA progression.

Risk factor in relation to the natural history of osteoarthritis.

If other risk factors for ROA (e.g. risk factors ‘U’) are present when assessing the effect of risk factor X, we can use the following diagram to depict the relationship between risk factor X, risk factor U, and progression of ROA (Fig. 3). As shown in this figure, both risk factor X and risk factor U are the causes for the development of mild ROA. However, these two factors are not associated before knees develop mild ROA, as there is no arrow linking X to U or vice versa. The only path between X and U is blocked by colliding arrow heads at their common outcome (i.e. mild ROA). As a result of limiting the eligible knees to those with mild ROA, however, risk factors X and U are no longer independent. Such practice opens an alternative noncausal path (or spurious association) between risk factor X and risk factor U (i.e. X --- U → ROA progression). This alternative path will bias the effect estimate of risk factor X on ROA progression unless the effect of risk factor U is appropriately adjusted for. In many studies, however, not all risk factors are measured or are known, therefore leading to biased direct effect estimate of risk factor X on ROA progression.

A causal diagram of an observational study showing the assessment of the effect of risk factor X on ROA progression among knees with mild ROA. Restriction of knees with mild ROA at baseline results in its causes (i.e. risk factors X and U) becoming directly associated, as indicated by a dotted line between X and U, even though these two factors are not associated before the knees developed mild ROA.


Examination of both clinical risk factors (such as obesity, muscle weakness, metabolic disorders, and inflammation) and joint structural factors (such as malalignment, cartilage defects, BMLs, meniscal pathology, and synovitis) of osteoarthritis may allow us to modify these risk factors, thus slowing disease progression in clinical practice. Some studies aiming to do this have been reported recently. For example, weight loss in knee osteoarthritis can modulate biochemical biomarkers of cartilage [59], inhibit low-grade inflammation [59], and improve the quality (increase delayed gadolinium-enhanced MRI of cartilage index) and quantity (reduced cartilage thickness loss) of cartilage [19▪▪], and potentially delay the progression of osteoarthritis. However, weight loss in knee osteoarthritis results in a decrease both in body fat mass and also in muscle mass [60]. A decrease in muscle mass would induce greater loss of cartilage volume over time [42▪▪], hence weight loss in patients with knee osteoarthritis should be followed by an exercise regimen to restore or increase muscle mass.

Reducing medial knee loading by lateral wedge insoles has been recommended to manage osteoarthritis by most clinical guidelines; however, a recent randomized controlled trial reported that lateral wedge insoles worn for 12 months provided no symptomatic relief or had no effects on disease progression (as assessed by the loss of cartilage volume) compared with flat control insoles [61▪]. Given malalignment and increased loading are potent risk factors for osteoarthritis progression, further research with a longer period and more sophisticated outcome measures is required to determine the effects of loading managements on disease progression.

Modification of metabolic and inflammatory factors may also delay the progression of knee osteoarthritis. A statin is able to modulate lipid metabolism, vascular pathology, and inflammation; a recent observational study [62] reported that statin use was associated with more than a 50% reduction in progression of knee osteoarthritis over 6.5 years. Clinical trials are required to confirm this finding.

Because of the limitations in the responsiveness of both radiographic and MRI measures of progression, efforts are being made to stratify those who are at highest risk of progression. This may facilitate clinical trial brevity by shortening the discovery and development timelines. As osteoarthritis is typically a very slowly progressive condition, one can optimize the trial efficiency by finding more responsive endpoint(s) and stratifying the study sample to further enhance efficiency. The impact of a screening test to enhance the responsiveness of a structural outcome in an osteoarthritis trial is seen most immediately when assessing the sample size requirements. Take the following theoretical example where we vary the rate of progression in the placebo group by selecting different standardized response means (SRMs). For this example, we have set the following parameters: 80% power, one-sided α = 0.05, and assume the drug causes a 50% drop in cartilage loss. If placebo-treated knees have an annual loss of cartilage with an SRM of 0.4 and a 50% drop in cartilage loss because of the active drug, this would yield an SRM of 0.2 for the active drug arm. The sample size estimate in a two-arm, 1-year parallel design trial would be 310 per arm. If we vary the placebo SRM and in this example it was 0.6, then we would need 139 per group. If the SRM was 0.8, then we would need 78 per group.


Although radiographic progression of osteoarthritis is still commonly used to ascertain risk factors and to assess the disease-modifying effect of treatments, MRI has enabled the opportunity to better examine and understand early and late aberrations in the joint, from the initial stage using compositional measurements to joint failure stage using quantitative measurements. Emerging new imaging techniques allow us to employ more sophisticated measures as outcomes in cohort studies and clinical trials to discover novel risk factors for prevention and innovative strategies for treatment, for example, change in cartilage volume being used as the primary outcome in recent trials [61▪,63,64]. These also allow us to stratify the risk factors in identifying those at risk of rapid progression using a number of different metrics including obesity, knee alignment, high metabolic and inflammatory status, knee pain, radiographic changes, meniscal lesions, and BMLs. Identifying persons at the greatest risk for progression may enhance the efficiency of clinical trials through reducing sample size and shortening follow-up period; however, the study findings using this method may not be generalizable and those with faster progression are usually at a late stage of disease, which may not be as responsive as at an early stage to the interventions.


A/Professor Ding and Professor Hunter are both funded by an Australian Research Council Future Fellowships.

The authors had full access to all the data in the study and had final responsibility for the decision to submit for publication. This is a narrative review, and the comments and editorial expressed herein represent those of the authors and do not reflect those of any official scientific role or institution that the authors may hold or be affiliated with.

This work was supported by the Australian Research Council Future Fellowship; National Health and Medical Research Council of Australia.

Conflicts of interest

None to declare.


Papers of particular interest, published within the annual period of review, have been highlighted as:

  • ▪ of special interest
  • ▪▪ of outstanding interest

Additional references related to this topic can also be found in the Current World Literature section in this issue (p. 155).


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A systematic review suggesting that malalignment, age, and radiographic features provide strong evidence to predict osteoarthritis progression, and BMI was a strong predictor only for long-term progression.

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This study suggested that frequent or strenuous physical activity (>10 000 steps per day) may have detrimental effects on disease progression.

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The study suggested that accumulation of metabolic components was significantly related to progression of knee osteoarthritis.

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A research paper indicating inflammatory mechanisms play roles in radiographic osteoarthritis progression.

54. Denoble AE, Huffman KM, Stabler TV, et al. Uric acid is a danger signal of increasing risk for osteoarthritis through inflammasome activation. Proc Natl Acad Sci US A 2011; 108:2088–2093.
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57. Hart DJ, Cronin C, Daniels M, et al. The relationship of bone density and fracture to incident and progressive radiographic osteoarthritis of the knee: the Chingford Study. Arthritis Rheum 2002; 46:92–99.
58. Nevitt MC, Zhang Y, Javaid MK, et al. High systemic bone mineral density increases the risk of incident knee OA and joint space narrowing, but not radiographic progression of existing knee OA: the MOST study. Ann Rheum Dis 2010; 69:163–168.
59. Richette P, Poitou C, Garnero P, et al. Benefits of massive weight loss on symptoms, systemic inflammation and cartilage turnover in obese patients with knee osteoarthritis. Ann Rheum Dis 2011; 70:139–144.
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A randomized controlled trial suggesting that lateral wedge insoles worn for 12 months may have no effects on disease progression (as assessed by loss of cartilage volume).

62. Clockaerts S, Van Osch GJ, Bastiaansen-Jenniskens YM, et al. Statin use is associated with reduced incidence and progression of knee osteoarthritis in the Rotterdam study. Ann Rheum Dis 2012; 71:642–647.
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disease progression; imaging; osteoarthritis; risk factors

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