Longitudinal changes in intermuscular fat volume and quadriceps muscle volume in the thighs of women with knee osteoarthritis


  • This article was prepared using an Osteoarthritis Initiative public use data set and does not necessarily reflect the opinions or views of the Osteoarthritis Initiative investigators, the NIH, or the private funding partners.



To quantify rates of change in quadriceps muscle (QM) and intermuscular fat (IMF) volumes over 2 years in women in the Osteoarthritis Initiative (OAI) study and examine group differences between those with radiographic osteoarthritis (ROA) and those without ROA.


The OAI database was queried for women ≥50 years of age in the incident and progression cohorts with and without ROA at baseline. Midthigh magnetic resonance imaging scans (15 contiguous slices, 5 mm slice thickness) of eligible women were randomly selected and anonymized. Image pairs were registered. QM and IMF were segmented in the 12 most proximal matching slices with the segmenter blinded to image time point. Age-adjusted differences in QM and IMF volume changes between groups were tested using analysis of covariance.


Forty-one women without ROA (mean ± SD age 60.7 ± 7.6 years) and 45 women with ROA (mean ± SD age 64.5 ± 6.7 years) were included. Mean ± SD QM and IMF volume changes in the non-ROA group were −4.1 ± 11.1 cm3 and 3.4 ± 7.1 cm3, respectively, and −5.4 ± 13.5 cm3 and 3.1 ± 7.4 cm3 in the ROA group, respectively. Age-adjusted between-group differences in QM and IMF changes were not significant (P > 0.05).


Two-year changes in QM and IMF volumes appear consistent with aging and do not seem to be related to OA status. Direct comparison with a control cohort without OA risk factors could confirm this. Since group assignment was based on baseline data, there may have been women in the non-ROA group who developed ROA over followup, resulting in some overlap between groups.


Among the prominent risk factors for the onset of knee osteoarthritis (OA) are increasing age, female sex, previous joint trauma, obesity, and muscle weakness; obesity and muscle weakness are also implicated in OA progression (1–3). As a strong predictor of OA (4–6), the role of obesity was originally attributed to increased mechanical loading (4, 7). This theory has been supported by the discovery of mechanoreceptors, such as integrins, on chondrocytes that when activated stimulate the release of inflammatory mediators, including cytokines, matrix metalloproteinases (MMPs), and growth factors (4, 8, 9). However, obesity is also a risk factor for OA of non–weight-bearing joints such as the hand; therefore, adipose tissue is thought to play a metabolic role in OA (5, 10, 11). The characterization of adipose tissue as an endocrine organ has increased our understanding of the role of adipokines in OA. These adipokines are mainly proinflammatory and, accordingly, are implicated in OA pathophysiology (4, 5, 8, 12, 13). One widely studied adipokine, leptin, facilitates the release of metalloproteinases (e.g., MMP-9, MMP-13) that degrade articular cartilage (8, 14, 15). Additionally, leptin increases growth factor expression (e.g., insulin-like growth factor 1, transforming growth factor β). These growth factors, which stimulate chondrocyte repair, have also demonstrated harmful effects through stimulation of osteophyte formation (8, 14, 16). Obesity may also influence knee OA through adipose infiltration into thigh skeletal muscle, which is linked to poorer lower extremity performance in older individuals (17).

Like obesity, quadriceps weakness is implicated in knee OA incidence and progression (1–3, 18–22). Along with producing movement, the quadriceps muscles (QMs) provide shock absorption and dynamic stability of the knee joint by dissipating loads and decreasing joint contact forces (19, 20, 23). In individuals with quadriceps weakness, this action would be compromised (19, 20). Quadriceps weakness may result from a number of factors, including poor muscle activation and the aging-associated loss of muscle mass and increased fatty infiltration into muscle, referred to as sarcopenia (19, 24–26). Clinical findings support the involvement of quadriceps weakness in knee OA. Ikeda and colleagues found QM cross-sectional area (CSA) to be, on average, 12% smaller in asymptomatic women with incident radiographic OA (ROA) compared to age- and body mass–matched controls (27). Additionally, quadriceps weakness correlated better with pain and disability than ROA (18–22). Some studies have shown increased risk of disease initiation (22, 28). Quadriceps weakness has also been linked to the progression of knee OA through disuse atrophy of the quadriceps due to pain and disability, which are common consequences of knee OA (22). However, the amount of change in QM that occurs over time in individuals with knee OA remains unknown as previous studies have examined quadriceps CSA at a single time point (23). To the best of our knowledge, changes that occur in QM volume over time in a population with OA have not yet been reported.

Given the importance of obesity and muscle weakness in knee OA, the ability to quantify muscle and intermuscular fat (IMF) volume changes longitudinally may be a critical factor in understanding OA initiation and progression. To our knowledge, such longitudinal changes have not been quantified in individuals at risk for or with established knee OA. As a result, this study aimed to quantify longitudinal changes in QM and IMF volumes in postmenopausal women at risk for and with existing knee OA over 2 years. Secondarily, we aimed to determine if longitudinal decreases in QM and increases in IMF volumes were greater in those with progressive knee OA than in those at risk for knee OA.

Significance & Innovations

  • Changes in intermuscular fat and quadriceps muscle volumes, the primary outcome measures in this study, are novel outcomes.

  • Most research has reported area derived from cross-sectional images as an outcome measure, which is less robust in measuring longitudinal change because even slight alterations in position of slice acquisition can significantly alter results.

  • This is the first time that longitudinal changes in thigh intermuscular fat and quadriceps muscle volumes have been quantified, and also for the first time in a population with knee ostoarthritis.

  • For the first time, comparisons in thigh tissue volume in individuals with established knee osteoarthritis are compared with a population at risk for knee osteoarthritis, using images acquired in the Osteoarthritis Initiative study.


Study participants.

Data used in the preparation of this article were obtained from the Osteoarthritis Initiative (OAI) database, which is available for public access at http://www.oai.ucsf.edu/. The OAI is a multicenter, longitudinal, observational cohort study designed to facilitate investigation of factors that influence OA incidence and progression. The OAI study population (n = 4,796) includes individuals 45–79 years of age and is divided into 3 cohorts: control, incident, and progression. Controls (n = 122) are an unexposed reference cohort with no radiographic evidence of OA and no risk factors, with the exception of age ≥70 years. The incident cohort (n = 3,285) includes individuals with risk factors for the development of OA. The progression cohort (n = 1,389) includes individuals with symptomatic and radiographic evidence of OA in at least 1 knee at baseline. Exclusion criteria for the OAI population included rheumatoid arthritis, magnetic resonance imaging (MRI) contraindication, and bilateral end-stage knee OA (29).

Baseline and 2-year followup thigh images were acquired for the entire OAI cohort from the OAI Coordinating Center located at the University of California, San Francisco. The online OAI participant database was queried for women ages 50 years and older who had both baseline and 2-year followup MRI thigh images available. Only those women in the incident and progression cohorts with no symptomatic and radiographic evidence of OA in the right knee were eligible for the non-ROA group, while women were eligible for the OA group only if they had both ROA and symptomatic OA in the right knee. The variables analyzed from the OAI database to determine symptomatic and ROA were the screening variables coded P01RSXKOA and P01RXRKOA, respectively. Upon the release of baseline Kellgren/Lawrence (K/L) grades determined from right knee radiographs, the groups were reclassified. Individuals with a K/L grade of 0 or 1 were classified as having no ROA in the right knee, but with risk factors, herein referred to as the non-ROA group. Individuals with a K/L grade of 2, 3, or 4 were classified as having symptomatic OA and ROA in the right knee, herein referred to as the ROA group. Of all women meeting these criteria, baseline and 2-year followup thigh images belonging to a random selection of eligible individuals were retrieved and saved on a computer. As shown in Figure 1, participants were excluded for 3 reasons based on quality control issues with the thigh MRI scans: inconsistent spatial resolution between baseline and followup scans, compressed or flattened thighs on either one of the 2 scans (Figure 2), and poor matches between baseline and followup scans (see image analysis protocol below). Participants were also excluded if a baseline K/L grade was not available.

Figure 1.

Flow diagram representing selection of Osteoarthritis Initiative (OAI) participants meeting inclusion/exclusion criteria. MRI = magnetic resonance imaging; K-L = Kellgren/Lawrence; OA = osteoarthritis.

Figure 2.

Example of baseline (A) and followup (B) right thigh images from the same participant where the posterior aspect of the thigh appears flattened out on the followup image.

Image analysis protocol.

Bilateral MRIs of the thighs include 15 consecutive T1-weighted axial slices (5 mm slice thickness covering a 7 cm region of interest) with an echo time/inversion time of 10 msec and spatial resolution of 0.977 mm × 0.977 mm, acquired using a published protocol (29, 30). For each individual, only the right thigh was segmented. While the scanning protocol dictated that the most distal slice of the thigh should be acquired at a distance of 10 cm proximally from the epiphyseal line of the distal femur, inconsistencies were observed in positioning of the scanned region of interest between baseline and 2-year followup scans. Given this, 3-dimensional volumetric image registration software (Analyze, Biomedical Imaging Resource at Mayo Clinic) was used to match the slice positions in the baseline and 2-year images (31). Axial images were reconstructed using the software and matched across the axial, sagittal, and coronal planes. Since the most distal slice of the baseline image did not always match with the most distal slice of the followup image, Analyze software was used to determine which slices should be segmented for tissue volume based on the number of slices that matched. Acceptable matches were considered those with at least 12 of 15 slices that matched (≥80%). Participants with fewer than 12 matching slices were excluded (referred to as poor matches in Figure 1). Participants with more than 12 matching slices were assessed based on the proximal 12 slices for consistency.

Thigh images were anonymized and analyzed for QM and IMF volumes using a semiautomated software program that features a watershed segmentation algorithm (sliceOmatic 4.3, TomoVision). As noted by Cotofana et al, the gold standard for measuring muscle volume is the segmentation of muscle from a series of contiguous MRI scans that are acquired perpendicular to a muscle region of interest (32). Right thigh images from each participant were analyzed in pairs, with the individual performing the segmentation blinded to the time point of image acquisition (baseline or followup). On each slice, tissues that were identified and segmented included cortical bone, bone marrow, QM, all remaining muscles, subcutaneous fat, and IMF. Subcutaneous fat was defined as fat immediately adjacent to the skin and external to the deep fascia around the thigh muscles, cortical bone was considered the dark area of bone surrounding the marrow, and IMF was considered as all tissue (including vessels) surrounding the muscles within the deep fascial layer. Fat located within the muscle (intramuscular fat) was included in the segmentation of the muscle because of limitations of the software's capabilities. Each tissue was tagged using a different color (Figure 3). Within sliceOmatic, the watershed algorithm was configured with thresholds set at 1 pixel surface and 0.01% mean difference. The morphologic segmentation of the first analyzed slice was propagated forward to the next 11 slices, which were adjusted manually according to changes in tissue orientation. For the purpose of this study, only the IMF volume and QM volume data were used.

Figure 3.

(A) Coronal magnetic resonance image (MRI) scout scan of the right thigh showing the region of interest. (B) An example of a segmented MRI of the right thigh. Red is cortical bone, green is bone marrow, orange is quadriceps muscles, blue is all other muscles, yellow is intermuscular fat, and pink is subcutaneous fat.


One trained research assistant segmented 72 right knee images belonging to 36 incident cohort participants and 36 progression cohort participants on 2 separate occasions separated by 1 week. During the second round of analyses, the segmenter was blinded to previous segmentations and results. A second research assistant, blinded to segmentation and results of the first segmenter, analyzed a random subset of the cohort (n = 18) to provide comparison for interrater reliability. Reliability was calculated for each tissue using the 2 analyses of the baseline images and expressed as a root mean square coefficient of variation percentage (RMSCV%) and type 2,1 intraclass correlation coefficient (ICC). A sample size of 36 was calculated based on an ICC of 0.85 (lower 95% confidence interval [95% CI] limit of 0.75) (33). To assess reliability of the change in QM and IMF volumes, one segmenter analyzed image pairs (baseline and 2-year followup images) on 2 separate occasions, 4 months apart. Again, type 1,2 ICCs were calculated.

Statistical analyses.

We estimated the sample size to be 40 participants per group based on the following assumptions: Type I error = 0.05 (1-tailed given our directional alternate hypothesis), Type II error = 0.15, and an effect size of 0.60. Descriptive statistics of baseline height, weight, body mass index (BMI), and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores were calculated. Descriptive statistics of mean baseline, followup, and change (followup value minus baseline value) in QM and IMF volumes were also calculated. Independent t-tests were conducted to determine if baseline age, weight, BMI, WOMAC scores, QM volume, and IMF volume were significantly different between the non-ROA and ROA groups. Paired t-tests were conducted to determine if longitudinal changes in QM volume and IMF volume within each group were significant. These analyses were repeated using an analysis of covariance (ANCOVA) to adjust for age. Differences or changes were considered significant at a level of P less than 0.05. To determine whether longitudinal changes were greater in the ROA group than in the non-ROA group, an ANCOVA was performed. Given that age is associated with increases in fat and decreases in lean tissue, we adjusted for age in our analyses (24–26). Changes in QM and IMF volumes were analyzed separately.


In total, 86 participants were included in the analyses; 41 from the non-ROA group and 45 from the ROA group. Baseline descriptive statistics for the study sample are shown in Table 1. The ROA group was found to be significantly older, heavier, and more symptomatic at baseline than the non-ROA group.

Table 1. Descriptive statistics*
 Total sample (n = 86)Non-ROA group (n = 41)ROA group (n = 45)
  • *

    Values are the mean ± SD. ROA = radiographic osteoarthritis; BMI = body mass index; WOMAC = Western Ontario and McMaster Universities Osteoarthritis Index.

  • Significant differences (P < 0.05) between groups.

Age, years62.7 ± 7.360.7 ± 7.664.5 ± 6.7
Height, cm161.9 ± 6.0162.1 ± 6.6161.8 ± 5.3
Weight, kg71.4 ± 13.666.8 ± 12.275.6 ± 13.6
BMI, kg/m227.3 ± 5.125.6 ± 4.829.0 ± 4.9
WOMAC pain score (max score = 20)3.2 ± 3.42.1 ± 2.64.2 ± 3.6
WOMAC stiffness score (max score = 8)1.7 ± 1.51.1 ± 1.42.2 ± 1.4
WOMAC physical function score (max score = 68)9.8 ± 10.46.3 ± 8.113.0 ± 11.2

Baseline and 2-year followup data for QM and IMF volumes are displayed in Table 2. Baseline QM and IMF volumes were not significantly different between groups (P > 0.05). The mean QM volume decreased by 1.5% in the non-ROA group compared to a decrease of 2.1% in the ROA group. Concurrently, the mean IMF volume increased by 3.5% in the non-ROA group compared to 2.9% in the ROA group. Within each group, these longitudinal changes were significant (P < 0.05).

Table 2. Measurements of quadriceps muscle and intermuscular fat volumes and longitudinal changes*
 Total sample (n = 86)Non-ROA group (n = 41)ROA group (n = 45)
  • *

    Values are the mean ± SD. ROA = radiographic osteoarthritis.

  • Significant changes within each group from baseline without adjustment for age (P < 0.05).

Quadriceps muscle volume   
 Baseline, cm3248.6 ± 45.5245.3 ± 42.7251.6 ± 48.2
 Followup, cm3243.8 ± 44.8241.2 ± 41.5246.2 ± 48.0
 Change, cm3−4.8 ± 12.3−4.1 ± 11.1−5.4 ± 13.5
 % change−1.8 ± 5.0−1.5 ± 4.4−2.1 ± 5.5
Intermuscular fat volume   
 Baseline, cm3103.5 ± 36.095.2 ± 32.5111.1 ± 37.7
 Followup, cm3106.7 ± 37.998.6 ± 35.2114.1 ± 39.2
 Change, cm33.2 ± 7.23.4 ± 7.13.1 ± 7.4
 % change3.2 ± 7.43.5 ± 8.22.9 ± 6.7

After adjusting for age, longitudinal changes in QM and IMF volumes within each group were no longer significant (P > 0.05). The between-group difference in change in QM volume when adjusted for age was not statistically significant (ANCOVA: F[1,83] = 0.037, P = 0.848). Likewise, a significant difference between groups was not observed for the age-adjusted change in IMF volume (ANCOVA: F[1,83] = 0.000, P = 0.986).

Intrarater reliability for QM volume was RMSCV% 0.40, ICC 1.00 (95% CI 1.00–1.00), and was RMSCV% 5.70, ICC 0.958 (95% CI 0.641–0.987) for IMF volume. Interrater reliability based on the subset of images was excellent for QM (RMSCV% 0.57, ICC 0.999 [95% CI 0.996–0.999]) and IMF (RMSCV% 2.79, ICC 0.997 [95% CI 0.992–0.999]). Reliability measures were similar between participants from both groups (data not shown). Reliability for changes in QM and IMF data was also calculated. For QM change, the ICC was 1.00 (95% CI 1.00–1.00), and for IMF change, the ICC was 1.00 (95% CI 1.00–1.00).


To our knowledge, this is the first study to quantify tissue volume in women at risk for knee OA and with progressive OA, to investigate the magnitude of change in QM and IMF volumes over 2 years, and to compare these longitudinal changes between the women with and without radiographic knee OA. Outcome measures of QM and IMF volumes were acquired from analyses of MRI scans of the midthigh region. While most research to date has reported area measurements derived from cross-sectional images as an outcome measure, such outcomes are less robust in quantifying longitudinal change because even slight alterations in position of slice acquisition can significantly alter results. Results of our analyses revealed that longitudinal changes in QM and IMF volumes were relatively small in absolute and relative magnitude for both groups. Given that increasing age is associated with increasing IMF and decreasing QM mass and strength, within-group changes in QM and IMF volumes were age adjusted and found to not be statistically significant. Additionally, longitudinal changes in QM and IMF volumes were not greater in magnitude in women with progressive radiographic knee OA than in women with risk factors for knee OA after adjustment for age.

Previous work conducted in populations without OA has reported longitudinal tissue changes, although the imaging modalities and outcome measures have varied. One previous study documenting longitudinal changes in IMF mass and skeletal muscle mass using MRI was identified. This study, conducted in 26 older (mean age 75 years) healthy African American women without knee OA, showed decreases in whole-body skeletal muscle mass and increases in IMF mass over 2 years (34). It should be noted that while skeletal muscle and IMF were imaged using MRI, scans were not acquired at the same thigh region of interest as those in the present study. Another study examining longitudinal changes in CSAs of thigh muscle and IMF in 1,678 well-functioning elderly men and women (mean age 73 years) measured from computed tomography (CT) scans (35) found mean ± SD 5-year changes of −3.2 ± 7.9% and 29.0 ± 43.6% for total thigh muscle and IMF areas, respectively. Additionally, a study conducted in 328 elderly men and women (mean age 74.6 years) using dual x-ray absorptiometry (DXA) scans to measure 3-year change in appendicular skeletal muscle mass reported a mean ± SD change of 1.9 ± 5.4% (36). Comparisons between our study and those previously published in otherwise healthy aging adults are difficult to assess given differences in population sex, age, imaging modality (i.e., DXA, CT) and outcome measures (i.e., CSA, mass).

The tissue changes observed here in women without ROA but with OA risk factors and in women with radiographic and symptomatic OA of concurrent losses in QM volume and gains in IMF volume appear consistent with sarcopenic changes observed in previously conducted longitudinal studies of aging in relatively healthy, populations without OA described in the previous paragraph (24, 34–36). In fact, after adjusting for age in our analyses, longitudinal changes in QM volume and IMF volume were not significant. Changes due to aging are associated with disuse atrophy, impaired muscle activation, and metabolic changes. However, it must be noted that, since there was no control group included in our study, longitudinal volume changes in QM and IMF yielded from analyses of midthigh MRI images that occur in otherwise healthy aging individuals without risk factors for knee OA were not assessed. Our results can be interpreted in 2 ways: tissue changes that occur due to the presence of risk factors for knee OA or progressive knee OA may not be greater than changes that are associated with aging, or 2-year changes that occur in women due to knee OA risk factors or the disease itself are small.

The absence of significant differences between the groups with and without ROA in the longitudinal change in QM and IMF volumes suggests that women with risk factors for knee OA experience similar tissue changes to those with progressive knee OA. IMF has been found to be associated with adverse metabolic effects due to mediators such as cytokines, and to negatively influence muscle strength, thus contributing to an increased risk of loss of mobility (17, 26, 37). Increases in IMF volume in women at risk for OA may contribute to worsening disease symptoms and progressive disease, although this must be investigated further in future studies. The same may be true for declines in QM volume in women at risk for knee OA where tissue decreases may precede declines in clinical symptoms or muscle strength and lower extremity function, which have been associated with increased joint pain and neuromuscular deficits in individuals with knee OA (20, 21). Slemenda and colleagues previously reported that increased quadriceps strength at baseline reduced the risk of developing knee OA by 55% over a 2.5-year followup, therefore suggesting a role for QM weakness in knee OA initiation (28). In fact, quadriceps weakness was found to predict joint space narrowing, but not incident knee symptoms, in the Multicenter Osteoarthritis Study (38–40). Associations between longitudinal changes in QM volume and concurrent changes in pain and functional decline have not yet been described.

Given our study objectives, several limitations were identified. Our study was underpowered to detect differences between groups based on the small effect sizes (0.01 and 0.02 for QM and IMF, respectively) revealed in this study, suggesting that a large sample size would be required to detect differences between groups. The study sample only included women and was drawn from a database of mainly white participants. Thigh MRI scans were acquired from a region of interest at a fixed distance above the epiphyseal line, rather than a relative distance, resulting in slightly different regions of interest given individual differences in leg lengths. We minimized the impact of these positioning differences by reporting tissue changes within individuals over time. Image acquisition inconsistency (poor region matches between time points, inconsistent pixel spacing in images between time points, and compressed thighs in images in either time point) resulted in the exclusion of a number of potential participants. QM volume was determined for a specified region of interest in the thigh rather than the entire thigh and thus may not be most representative of the region of the quadriceps that experiences the most change in knee OA. Additionally, intramuscular fat was not evaluated separately in this study due to limitations of software analysis techniques. It may be beneficial to evaluate intramuscular fat changes in future research. Finally, the OAI study population included a very small control group that was younger than the incident and progression groups. Since the vast majority of these participants were ineligible for our study because of a lack of available thigh MRI scans or because they did not meet our image inclusion criteria, a reference group was not available for comparison. Future longitudinal analyses of such a subgroup might allow the calculation of smallest detectable differences to determine the level of change in an individual that could be said to be a definite loss of volume.

Our study results provide novel data upon which to base plans for future research investigating longitudinal changes over a longer time period to gauge the pattern of the trajectory for soft tissue change in those at risk for and with existing knee ROA and symptomatic OA. Upon the release of more followup thigh images from the OAI (i.e., 4-year followup scans), it may be beneficial to identify subgroups of participants to further elucidate potential differences between individuals who progress to ROA during the study followup compared to those who do not and those with established progressive disease.

In conclusion, women at risk for knee OA and with progressive ROA demonstrate decreases in QM volume and increases in IMF volume over 2 years, which appear to be consistent with sarcopenic changes related to aging and not necessarily disease state. The magnitudes of these longitudinal changes appear similar, regardless of the presence of ROA and symptomatic OA. The inclusion of a group of women of similar ages without risk factors for knee OA may help determine whether tissue changes observed here are solely consequences of aging or whether tissue changes precede disease onset and continue thereafter. While questions remain about the long-term trajectory of thigh tissue changes in those at risk for and with progressive knee OA, these results have important implications in understanding this disease process in relation to integral thigh tissues supporting the knee joint. Future analyses of 4-year followup thigh images may help to address these questions.


All authors were involved in drafting the article or revising it critically for important intellectual content, and all authors approved the final version to be published. Dr. Beattie had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study conception and design. Beattie, MacIntyre, Maly.

Acquisition of data. Beattie, MacIntyre, Ramadan, Inglis.

Analysis and interpretation of data. Beattie, MacIntyre, Inglis, Maly.


The Osteoarthritis Initiative study sponsors (Merck Research Laboratories, Novartis Pharmaceuticals Corporation, GlaxoSmithKline, and Pfizer) had no role in the study design, data collection, data analysis, or writing of this manuscript. Publication of this article was not contingent on the approval of these sponsors.