Assessment Of Knee Osteoarthritis Research Articles

Role of ultrasonography in evaluation of knee osteoarthritis

Objective To evaluate the role of ultrasonography (US) in assessing knee osteoarthritis (OA) compared with radiograph. Background Similar to renal or cardiac failures, OA is considered a common disorder in the joint as an organ. High-resolution US is used increasingly in musculoskeletal medicine owing to its value in the morphological and structural assessment of soft tissue in patients with arthritis. Patients and methods This study included 50 symptomatic knee joints from 50 patients (male/female24 / 26) with the clinical diagnosis of OA; all of them had knee pain and/or swelling. All patients underwent US examination on their knees. Weight-bearing anteroposterior and lateral knee radiographs were assessed for the Kellgren and Lawrence grading along with the potential presence of patellofemoral degenerative signs. Results US findings showed irregular articular surface and narrow joint space (72.0%), marginal osteophytes (64.0%), joint effusions (88.0%), decreased cartilage thickness (32.0%), synovial thickening (20.0%), meniscal lesions (70.0%), Baker's cyst (20.0%), and ligament and tendon injury (24.0%). Soft tissue changes could not be detected in radiograph (0.0%) but were identified clearly by the US in our study, with P value less than 0.001. Joint effusion, which was detected in 44 (88.0%) knees in the US only was detected in six (12.0%) knees in radiograph, with a P value less than 0.001. Kellgren and Lawrence grades (1–3) showed an increased incidence of joint effusion and meniscal lesion in the US, where all the grade 3 cases showed joint effusions and meniscal lesions. Conclusion US is a simple and reproducible technique for the assessment of periarticular and intra-articular abnormalities involved in the pathophysiology of knee OA.

The patient journey in knee osteoarthritis-variations in diagnosis, patient characteristics, and treatment by physician specialty

The patient journey in knee osteoarthritis-variations in diagnosis, patient characteristics, and treatment by physician specialty

Deep learning-based algorithm for assessment of knee osteoarthritis severity in radiographs matches performance of radiologists

A fully-automated deep learning algorithm matched performance of radiologists in assessment of knee osteoarthritis severity in radiographs using the Kellgren-Lawrence grading system. PurposeTo develop an automated deep learning-based algorithm that jointly uses Posterior-Anterior (PA) and Lateral (LAT) views of knee radiographs to assess knee osteoarthritis severity according to the Kellgren-Lawrence grading system. Materials and methodsWe used a dataset of 9739 exams from 2802 patients from Multicenter Osteoarthritis Study (MOST). The dataset was divided into a training set of 2040 patients, a validation set of 259 patients and a test set of 503 patients. A novel deep learning-based method was utilized for assessment of knee OA in two steps: (1) localization of knee joints in the images, (2) classification according to the KL grading system. Our method used both PA and LAT views as the input to the model. The scores generated by the algorithm were compared to the grades provided in the MOST dataset for the entire test set as well as grades provided by 5 radiologists at our institution for a subset of the test set. ResultsThe model obtained a multi-class accuracy of 71.90% on the entire test set when compared to the ratings provided in the MOST dataset. The quadratic weighted Kappa coefficient for this set was 0.9066. The average quadratic weighted Kappa between all pairs of radiologists from our institution who took part in the study was 0.748. The average quadratic-weighted Kappa between the algorithm and the radiologists at our institution was 0.769. ConclusionThe proposed model performed demonstrated equivalency of KL classification to MSK radiologists, but clearly superior reproducibility. Our model also agreed with radiologists at our institution to the same extent as the radiologists with each other. The algorithm could be used to provide reproducible assessment of knee osteoarthritis severity.

Identification of region of interest for assessment of knee osteoarthritis in radiographic images

Identification of region of interest for assessment of knee osteoarthritis in radiographic images

Identification of region of interest for assessment of knee osteoarthritis in radiographic images

Osteoarthritis is the most common joint disorder in which smooth apparent on the closures of the bone wears away causing stiffness, swelling along with extreme pain. The assessment of osteoarthritis in the early stage is most essential which is little difficult and inappropriate. The main objective of the paper is to identify the region of interest, i.e., cartilage region for the detection of osteoarthritis. In this work, the database of 1,173 knee X-ray images are collected which are manually classified by two different medical experts as per Kellgren and Lawrence grading system. The histogram of oriented gradient method and local binary pattern (LBP) are used for computation. The computed features are classified using decision tree classifier. For the proposed method, the accuracy of 97.86% and 97.61% is obtained with respect to medical expert-I and medical expert-II opinion. The results are promising and competitive which are validated by the medical experts.

Assessment of knee osteoarthritis by ultrasonography and its association with knee pain.

Pain is a significant cause of disability in knee osteoarthritis. Conventional radiography is widely used in the assessment of knee osteoarthritis, however radiographic findings do not correlate well with pain. Ultrasonography can be used to evaluate the soft tissue structures of the knee that can be related to pain. To evaluate pain-related soft tissue structures of the knee with ultrasonography. This cross-sectional study included a total of 198 knees from 99 patients with knee osteoarthritis. Knee pain and functional status were evaluated by performing visual analogue scale (VAS) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). On the ultrasound, cartilaginous thickness, knee effusion and presence of Baker's cyst were assessed and the correlation to pain was investigated. Baker's cyst was significantly more frequent in symptomatic knees (13.9%) compared to asymptomatic knees (2.5%). Patients with Baker's cyst had a significantly more limited degree of knee flexion, significantly higher resting VAS pain scores and worse WOMAC scores compared to patients without Baker's cyst. In log-linear analysis, presence of Baker's cyst increased the risk of pain by 2.94 times. Ultrasound as a modality that is easily accessible, inexpensive and without radiation exposure is helpful to demonstrate factors related to pain in knee osteoarthritis by allowing assessment of soft tissue structures.

Deep semi-supervised learning for knee osteoarthritis severity assessment from plain radiographs

Purpose: Deep Learning (DL) methods based on Supervised Learning (SL) have been recently adapted to assess knee osteoarthritis (OA) severity from plain radiographs. However, SL methods require large amounts of annotated data given by radiologists. While it is time-consuming and costly to obtain large annotated datasets, unannotated data are much easier to acquire at a low cost. In this study, we propose to use Semi-Supervised Learning (SSL) to leverage unannotated data (plain knee radiographs) in a combination with small amount of annotated data for automatic knee OA severity assessment.

Relation of interleukin-15 with the severity of primary knee osteoarthritis

BackgroundInterleukin-15 (IL-15) is a proinflammatory cytokine. IL-15 could be considered a potential biomarker for primary knee osteoarthritis (OA).AimThis study aimed to assess the serum level of IL-15 in primary knee OA patients and assess its relation to clinical severity, functional disabilities, and radiological grading of knee OA.Patients and methodsThis study included 40 patients with primary knee OA and 40 apparently healthy individuals. Assessment of knee OA was performed using clinical examination, the Western Ontario and McMaster Universities Osteoarthritis Index score, and Health Assessment Questionnaire-Disability Index. Radiological assessment was performed using the Kellgren–Laurence grading scale. Serum level of IL-15 was measured in both patients and control participants.ResultsThere were no statistically significant differences between patients and the control group in sex (P=1.000) and age (P=0.247). The patient group had a statistically significantly higher serum IL-15 level than its level in the control group (P≤0.0001). Serum IL-15 level was significantly higher among patients with knee joint line tenderness and effusion (P≤0.0001). There were statistically significant positive correlations between serum IL-15 level with the Western Ontario and McMaster Universities Osteoarthritis Index total score (P≤0.0001), the Health Assessment Questionnaire-Disability Index score (P≤0.0001), and the Kellgren–Laurence grading scale (P≤0.0001).ConclusionSerum IL-15 is elevated and correlated positively with pain, stiffness, functional disabilities, as well as radiological damage in primary knee OA. This suggests that IL-15 plays an important critical role in the pathogenesis of primary knee OA-related pain, stiffness, and joint damage. IL-15 might be a potential biomarker for assessing the severity of primary knee OA.

Knee menisci segmentation and relaxometry of 3D ultrashort echo time cones MR imaging using attention U-Net with transfer learning.

To develop a deep learning-based method for knee menisci segmentation in 3D ultrashort echo time (UTE) cones MR imaging, and to automatically determine MR relaxation times, namely the T1, T1ρ , and parameters, which can be used to assess knee osteoarthritis (OA). Whole knee joint imaging was performed using 3D UTE cones sequences to collect data from 61 human subjects. Regions of interest (ROIs) were outlined by 2 experienced radiologists based on subtracted T1ρ -weighted MR images. Transfer learning was applied to develop 2D attention U-Net convolutional neural networks for the menisci segmentation based on each radiologist's ROIs separately. Dice scores were calculated to assess segmentation performance. Next, the T1, T1ρ , relaxations, and ROI areas were determined for the manual and automatic segmentations, then compared. The models developed using ROIs provided by 2 radiologists achieved high Dice scores of 0.860 and 0.833, while the radiologists' manual segmentations achieved a Dice score of 0.820. Linear correlation coefficients for the T1, T1ρ , and relaxations calculated using the automatic and manual segmentations ranged between 0.90 and 0.97, and there were no associated differences between the estimated average meniscal relaxation parameters. The deep learning models achieved segmentation performance equivalent to the inter-observer variability of 2 radiologists. The proposed deep learning-based approach can be used to efficiently generate automatic segmentations and determine meniscal relaxations times. The method has the potential to help radiologists with the assessment of meniscal diseases, such as OA.

Development of an Impulse Response Method for Assessing Knee Osteoarthritis at the Femorotibial Joint: Comparison Between Healthy Young Adults and Older Women with Clinical Knee Osteoarthritis

Because in patients with knee osteoarthritis (OA), the knee joint properties such as cartilage, meniscus, soft tissue and bone formation are assumed to degeneration change, the shock absorb might also decrease. The transmission of impulse from femur and tibia is thought to change in the knee joint. The purpose of the present study was to determine the differences between young healthy women and elderly women with knee OA using the impulse response method. Twenty-six older women with clinically diagnosed knee OA (OA group, age: 69 ± 6 years) and 26 young women without knee OA (young control [YC] group, age: 21 ± 1 years) participated in the study. The OA group fulfilled the knee OA classification criteria based on clinical findings. An input device provided an impulse to the subject while standing. The output value was measured using a single-axis accelerometer. The outcome measures were the input–output ratio and power spectrum. The input–output ratio did not significantly differ between the groups. The power spectrum at 21–30 Hz was significantly greater (p = 0.036) in the OA group than in the control group. Additionally, the power spectrum at 21–30 Hz correlated with knee pain (r = 0.39, p = 0.049). At 21–30 Hz, transmission of impulse from femur and tibia in the knee joint was lower in the OA group than in the control group. The IR method used in the present study could detect the transmission of impulse in early knee OA.

Evaluation of the Relationships Between Kellgren-Lawrence Radiographic Score and Knee Osteoarthritis-related Pain, Function, and Muscle Strength

Background: Knee osteoarthritis (OA) diagnosis using Kellgren-Lawrence scores is commonly used to help decision-making during assessment of the severity of OA with assessment of pain, function and muscle strength. The association between Kellgren-Lawrence scores and functional/clinical outcomes remains controversial in patients with knee OA. Objects: The purpose of this study was to examine the relationships between Kellgren-Lawrence scores and knee pain associated with OA, function during daily living and sports activities, quality of life, and knee muscle strength in patients with knee OA. Methods: We recruited 66 patients with tibiofemoral knee OA and determined knee joint Kellgren-Lawrence scores using standing anteroposterior radiographs. Self-reported knee pain, daily living function, sports/recreation function, and quality of life were measured using the knee injury and OA outcome score (KOOS). Knee extensors and flexors were assessed using a handheld dynamometer. We performed Spearman’s rank correlation analyses to evaluate the relationships between Kellgren-Lawrence and KOOS scores or muscle strength. Results: Kellgren-Lawrence scores were significantly negatively correlated with KOOS scores for knee pain, daily living function, sports/recreation function, and quality of life. Statistically significant negative correlations were found between Kellgren-Lawrence scores and knee extensor strength but not flexor strength. Conclusion: Higher Kellgren-Lawrence scores were associated with more severe knee pain and lower levels of function in daily living and sports/recreation, quality of life, and knee extensor strength in patients with knee OA. Therefore, we conclude that knee OA assessment via self-reported KOOS and knee extensor strength may be a cost-effective alternative to radiological exams.

Defining thresholds for the Kellgren-Lawrence grading between 2 and 3 for the Japanese knee osteoarthritis measure questionnaire for urban inhabitants more than 65-year old

Purpose: According to the population-based cohort study in Japan, over 80 percent of 80-year old and above Japanese women have had a prevalence rate of knee osteoarthritis (OA). Knee OA is one of the most prevalent conditions resulting in disability particularly in the elder population, and it also leads to high economic costs and death further. To assess knee OA, Kellgren-Lawrence (KL) grading has been commonly used in many epidemiological studies, and the KL grade 2 is usually used as the disease threshold. Prevent knee joint degeneration progressing from KL grade 2 to KL grade 3 in healthy individuals may reduce high economic costs by receiving knee replacement surgery or interventional therapy, ensure elder inhabitant’s quality of life further. In addition, patient-reported outcome measures (PROMs) of the Japanese Knee Osteoarthritis Measure (JKOM) with its high reliability and validity, has been widely used to evaluate OA-related health domain. Physicians can assess knee OA with the KL grading and JKOM objectively. However, what JKOM scores indicating the process of knee OA were unclear. The purpose of this present study was to determine the KL grading thresholds between KL grade 2 and KL grade 3 for the JKOM for urban inhabitants more than 65-year old. Methods: Participants who completed the JKOM questionnaire, received X-ray and diagnosed as KL grade 2 or KL grade 3 of knee OA by the expert physician were included in this study. To determine the score that best distinguished those who were in KL grade 2 and who were in KL grade 3, the sensitivities and specificities for each of the potential scores were plotted as a receiver operating characteristic (ROC) curve. The maximal product of specificity and sensitivity was taken to be the KL grade 2-3 threshold. Results: A total of 754 out of 795 participants (mean age, SD= 73.0, 5.5; male vs female = 321 vs 433) were included in this study. Of these, 645 participants (85.5%, male vs female = 299 vs 346) were in KL grade 2 with the mean JKOM score (SD) of 5.6 (6.8) points, which was significantly lower than KL grade 3 group (mean score, SD= 11.9, 11.5, P value < 0.0001). In addition, mean score of the subscale of JKOM between KL grade 2 and KL grade 3 were also statistically significant (P value < 0.05). The KL 2-3 threshold (sensitivity, specificity) was 8 (0.54, 0.78) for the JKOM total score, 8 (0.57, 0.75) for the degree of knee pain (JKOM I), 1 (0.73, 0.62) for the pain and stiffness in knees (JKOM II), 4 (0.19, 0.89) for the condition in daily life (JKOM III), 1 (0.70, 0.62) for the general activities (JKOM IV), and 2 (0.50, 0.70) for the health conditions (JKOM V). Conclusions: Our results should provide additional information to interpretation what score indicates the progressing of knee joint degeneration in the healthy population.

Acoustic emissions and kinetic instability as new clinical biomarkers to noninvasively assess knee osteoarthritis

Acoustic emissions and kinetic instability as new clinical biomarkers to noninvasively assess knee osteoarthritis

Variable angle gray level co-occurrence matrix analysis of T2 relaxation time maps reveals degenerative changes of cartilage in knee osteoarthritis: Oulu knee osteoarthritis study.

Texture analysis methods based on gray level co-occurrence matrices (GLCM) can be optimized to probe the spatial correspondence information from knee MRI T2 maps and the changes caused by osteoarthritis, and thus possibly leading to a more sensitive characterization of osteoarthritic cartilage. Curvature of the cartilage surfaces combined with the low image resolution in relation to cartilage thickness set special requirements for an effective texture analysis tool. To introduce a novel implementation of GLCM algorithm optimized for cartilage texture analysis; to evaluate the performance of the designed algorithm against mean T2 relaxation time analysis; and to identify the most suitable texture features for discerning osteoarthritic subjects and asymptomatic controls. Case control. Eighty symptomatic osteoarthritis patients and 64 asymptomatic controls. Multislice multiecho spin echo sequence on a 3T MRI system. The T2 relaxation time maps were manually segmented by an operator trained for the task. Texture analysis was performed using an in-house algorithm developed in MATLAB. Symptomatic and asymptomatic subjects were compared using Mann-Whitney U-test. Repeatability of different features was addressed using the concordance correlation coefficient (CCC). Spearman's correlations between the features were determined. The algorithm displayed excellent performance in discerning symptomatic and asymptomatic subjects. Fifteen features provided a significant difference between the groups (P ≤ 0.05) and 12 of those had P values smaller than the mean T2 differences. Most of the studied texture features were highly repeatable with CCC over 90%. For the features with significant differences, correlation with mean T2 was low or moderate (|r| ≤ 0.5). With careful parameter and feature selection and algorithm optimization, texture analysis provides a powerful tool for assessing knee osteoarthritis with more sensitive detection of cartilage degeneration compared to the mean value of the T2 relaxation times in an identical region of interest. 2 Technical Efficacy Stage 2 J. Magn. Reson. Imaging 2018;47:1316-1327.

Urinary C-terminal telopeptide of type II collagen, radiological severity, and functional assessment in knee osteoarthritis: are these related?

Introduction Osteoarthritis (OA) is a chronic, debilitating joint disease characterized by the degeneration of articular cartilage, sclerosis of the subchondral bone, and osteophyte formation. This work aimed at estimating the level of urinary C-terminal telopeptide of type II collagen (CTX-II) as a biomarker of cartilage turnover and to determine its relation with radiological and functional assessment of knee OA. Patients and methods The current study included 40 postmenopausal women with symptomatic knee OA fulfilling the American Rheumatism Association clinical diagnostic criteria for knee OA. A total of 20 healthy volunteers were enrolled as a control group. Patients were assessed radiologically using the Kellgren-Lawrence grading system and functionally using the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC). Urinary CTX-II was measured for the patient and control groups. Results There was no statistically significant difference as regards age and BMI between patients and controls. Disease duration affects both function assessed using the WOMAC and cartilage degradation assessed using urinary CTX-II. There was a statistically significant correlation between the WOMAC and urinary CTX-II, whereas there was no statistically significant correlation between the Kellgren-Lawrence scale and both urinary CTX-II and the WOMAC. Conclusion This study further confirms that urinary CTX-II is an index of early cartilage degradation in knee OA even before radiological changes occurs. The functional assessment using the WOMAC is an easy inexpensive method in reflecting cartilage degradation. Moreover, this work supports the lack of association between the functional status of knee OA patients assessed using the WOMAC and their radiological severity measured using the Kellgren-Lawrence grading scale.

Knee osteoarthritis active living assistant side force measurements as potential means for assessing knee osteoarthritis

Purpose: The lifetime risk of developing symptomatic knee osteoarthritis (KOA) has been estimated to be 45%. Knee abduction/adduction moment (KAM) is recognized as a primary marker of KOA progression. A 1% increase in peak external KAM has been linked to a greater than 6-fold increase in the risk of KOA progression. Due to high costs, and limited measurement granularity, established KAM measurement techniques are an impractical means for tracking KOA progression. Measurement of KAM is currently limited to gait laboratories, which utilize motion capture systems to determine knee moments. KOA often takes decades to develop. Identifying statistically significant changes in KAM on a year over year (or more frequent) basis therefore requires a higher degree of granularity than current techniques offer. Other attempts at measuring KAM during free ambulation have neither achieved complete independence from lab measurements, nor generated significantly greater granularity. In this work, a novel means of measuring a KAM proxy during free ambulation is presented, offering high measurement accuracy and granularity. We have developed an orthotic leg brace containing pressure sensors located on the inner and outer shank and thigh regions that measure side forces. From these side forces, we have measured the forces generated by the knee that are balanced by the legbrace. The purpose of this particular study was to assess the potential for this KAM proxy to differentiate between knees with diagnosed KOA and knees without KOA. We performed a preliminary test with a passive variant of a Knee OsteoArthritis Active Living Assistant (KOAALA) prototype (Figure 1) on a 75- year old male test subject with a differential KOA diagnosis between his left and right knee, and a young control subject in good health. Sessions were for 50 strides on a treadmill at 1m/s. The test subject walked one session with the sensorized legbrace on his left (afflicted) leg, then one session with the sensorized legbrace on his right (unafflicted) leg. The control subject walked one session with the sensorized legbrace on his left leg. Legbrace side force sensors were sampled at 4,608 samples per second and data was logged to a micro-secure-digital-card with a granularity of 4g. Additional Gait measures logged included: knee angle, shank tilt angle, shank lean angle, heel pressure, ball-of-foot pressure, foot angle and heel strike timing. After testing, data were processed using Wolfram’s Mathematica; processed data was compared. View Large Image Figure ViewerDownload Hi-res image Download (PPT) Results: The left/right panels of Figure 2 shows the data logged by KOAALA for average heel force (purple), ball-of-foot force (red) and average side force (blue) along with the minimum side force (gold) and maximum side force (green) versus percent of gait cycle of the test subject’s left and right legs respectively. Figure 3 shows the analogous data for the control subject. The side forces began in the lateral direction prior to heel strike and peaked immediately following heel strike and again peaked in the lateral direction prior to toe off. The left leg graph, however, has dramatically different characteristics from both the test subject’s right leg and the control subject. Specifically, in the healthy and in the unafflicted knee the pressure in the period between the peaks was nominal, while the test subject’s left leg (afflicted) side force measurements showed a substantial spike in the medial direction during the transition of support from heel to ball-of-foot. Conclusions: Our novel method for measuring a KAM proxy measures the primary discernable side forces exerted by the legbrace. Sensor calibration has not been established preventing analysis of relative pressures between the brace and traditional KAM measurement methods, but the series of spikes is not generally discernable in traditional methods. Further testing will be required to ascertain if these peaks are anomalous; peculiar to the brace/test; or are simply not detected by traditional methods. The high accuracy and fine granularity side force measurements our method provides has the potential of creating a novel means of tracking/managing KOA. The peak in the medial direction of the afflicted leg during the transitional support phase shows potential for this KAM proxy as a biomarker for KOA.

Symptom assessment in knee osteoarthritis needs to account for physical activity level.

Pain is not always correlated with severity of radiographic osteoarthritis (OA), possibly because people modify activities to manage symptoms. Measures of symptoms that consider pain in the context of activity level may therefore provide greater discrimination than a measure of pain alone. We undertook this study to compare discrimination provided by a measure of pain alone with that provided by combined measures of pain in the context of physical activity across radiographic OA severity levels. This was a cross-sectional study nested within the Osteoarthritis Initiative (OAI). The population was drawn from 2,127 persons enrolled in an OAI accelerometer monitoring substudy, including those with and those without knee OA. Two composite pain and activity knee symptom (PAKS) scores were calculated as the Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) pain score (plus 1) divided by a physical activity measure (step count for the first PAKS score [PAKS1 score] and activity count for the second PAKS score [PAKS2 score]). Symptom score discrimination across Kellgren/Lawrence (K/L) grades was evaluated using histograms and quantile regression. A total of 1,806 participants (55.5% of whom were women) were included (mean ± SD age 65.1 ± 9.1 years, mean ± SD body mass index 28.4 ± 4.8 kg/m(2) ). The WOMAC pain score, but not the PAKS scores, exhibited a floor effect. The adjusted median WOMAC pain scores by K/L grades 0-4 were 0, 0, 0, 1, and 3, respectively. The adjusted median PAKS1 scores were 24.9, 26.0, 32.4, 46.1, and 97.9, respectively, and the adjusted median PAKS2 scores were 7.2, 7.2, 9.2, 12.9, and 23.8, respectively. The PAKS scores had more statistically significant comparisons between K/L grades than did the WOMAC pain score. Symptom assessments incorporating pain and physical activity did not exhibit a floor effect and were better able to discriminate radiographic severity than an assessment of pain alone, particularly in milder disease. Pain in the context of physical activity level should be used to assess knee OA symptoms.

Validity and sensitivity to change of three scales for the radiographic assessment of knee osteoarthritis using images from the Multicenter Osteoarthritis Study (MOST)

The purpose of this study was to assess the concurrent validity and sensitivity to change of three knee osteoarthritis (OA) grading scales. The Kellgren-Lawrence (KL) and the Osteoarthritis Research Society International (OARSI) joint space narrowing (JSN) grading scales are well-established. The third scale, the compartmental grading scale for OA (CG) is a novel scale which grades JSN, femoral osteophytes, tibial erosion and subluxation to create a total score. One sample of 72 posteroanterior (PA) fixed-flexion radiographs displaying mild to moderate knee OA was selected from the Multicenter Osteoarthritis Study (MOST) to study validity. A second sample of 75 radiograph pairs, which showed an increase in OA severity over 30 months, was selected to study sensitivity to change. The three radiographic grading scales were applied to each radiograph in both samples. Spearman's rank correlation coefficients were used to correlate the radiographic grades and the change in grades over 30 months with a Whole-organ Magnetic Resonance Imaging Score (WORMS)-based composite score which included five articular features of knee OA. Correlations between the KL, OARSI JSN and CG grading scales and the magnetic resonance image (MRI)-based score were 0.836, 0.840 and 0.773 (P < 0.0001) respectively while correlations between change in the radiographic grading scales and change in the MRI-based score were 0.501, 0.525 and 0.492 (P < 0.0001). All three radiographic grading scales showed high validity and are suitable to assess knee OA severity. They showed moderate sensitivity to change; therefore caution should be taken when using ordinal radiographic grading scales to monitor knee OA over time.

SAT0434 Validation of A Proposed Ultrasonographic Grading Scale for Severity of Primary Knee Osteoarthritis

BackgroundConventional radiography (CR) is the standard imaging modality in the assessment of knee osteoarthritis (KOA), but Ultrasonography (US) is recognised as a useful imaging modality for the detection of synovitis...

The relationship between subchondral sclerosis detected with MRI and cartilage loss in a cohort of subjects with knee pain: the knee osteoarthritis progression (KOAP) study

To assess the association between subchondral sclerosis detected at baseline with MRI and cartilage loss over time in the same region of the knee in a cohort of subjects with knee pain. 163 subjects with knee pain participated in a longitudinal study to assess knee osteoarthritis progression (KOAP). Subjects received baseline knee radiographs as well as baseline and 3-year follow-up MRI examinations. Baseline subchondral sclerosis and bone marrow lesions (BMLs) were scored semiquantitatively on MRI in each region from 0 to 3. Cartilage morphology at baseline and follow-up was scored semiquantitatively from 0 to 4. The association between baseline subchondral sclerosis and cartilage loss in the same region of the knee was evaluated using logistic regression, adjusting the results for age, gender, body mass index, and the presence of concomitant BMLs. The prevalence of subchondral sclerosis detected by MRI in the regions of the knee varied between 1.6% (trochlea) and 17% (medial tibia). The occurrence of cartilage loss over time in regions varied between 6% (lateral tibia) and 13.1% (medial femur). The prevalence of radiographically-detected subchondral sclerosis in compartments varied from 2.9% (patellofemoral) to 14.2% (medial tibiofemoral). In logistic regression models, there were no significant associations between baseline subchondral sclerosis detected by MRI and cartilage loss in the same region of the knee. Baseline subchondral sclerosis as detected by MRI did not increase the risk of cartilage loss over time.