Association of baseline and change in tibial and femoral cartilage thickness and development of widespread full-thickness cartilage loss in knee osteoarthritis - data from the Osteoarthritis Initiative

Exploratory neutron tomography of articular cartilage

OBJECTIVE

To investigate the feasibility of using neutron tomography to gain new knowledge of human articular cartilage degeneration in osteoarthritis (OA). Different sample preparation techniques were evaluated to identify maximum intra-tissue contrast.

DESIGN

Human articular cartilage samples from 14 deceased donors (18-75 years, 9 males, 5 females) and 4 patients undergoing total knee replacement due to known OA (all female, 61-75 years) were prepared using different techniques: control in saline, treated with heavy water saline, fixed and treated in heavy water saline, and fixed and dehydrated with ethanol. Neutron tomographic imaging (isotropic voxel sizes from 7.5 to 13.5 µm) was performed at two large scale facilities. The 3D images were evaluated for gradients in hydrogen attenuation as well as compared to images from absorption X-ray tomography, magnetic resonance imaging, and histology.

RESULTS

Cartilage was distinguishable from background and other tissues in neutron tomographs. Intra-tissue contrast was highest in heavy water-treated samples, which showed a clear gradient from the cartilage surface to the bone interface. Increased neutron flux or exposure time improved image quality but did not affect the ability to detect gradients. Samples from older donors showed high variation in gradient profile, especially from donors with known OA.

CONCLUSIONS

Neutron tomography is a viable technique for specialized studies of cartilage, particularly for quantifying properties relating to the hydrogen density of the tissue matrix or water movement in the tissue.

Contralateral knee osteoarthritis is a risk factor for ipsilateral knee osteoarthritis progressing: a case control study

BACKGROUND

Knee osteoarthritis (KOA) is a highly disabling disease, and studying its progression is crucial. However, it is still unclear whether the progression of ipsilateral knee osteoarthritis is influenced by contralateral knee osteoarthritis.

METHODS

Data were collected from the OAI database and divided into two study cohorts (right/left KOA cohort). Each cohort had a target knee (right/left knee) and was further divided into two groups (exposure/control group). The demographic data of both cohorts were balanced at baseline by propensity score matching (PSM), and the data included rating scale and radiographic and clinical data. After checking for balance in the matched variables, we then compared the differences between the two groups in each cohort. Our primary focus was on the minimum joint space width (mJSW) of the target knee, which was measured four years after baseline. The secondary outcome was the arthroplasty rate of the target knee within nine years.

RESULTS

In this study, a total of 678 participants were enrolled and matched. After 1:1 PSM of the baseline demographic data, 98 participants in the right KOA cohort (RKOAC) were successfully matched, and 117 participants in the left KOA cohort (LKOAC) were successfully matched. Furthermore, the standardized mean difference (SMD) of the matched variables in both cohorts was less than 0.25. After analyzing the outcome metrics, we found that the target knee had a significantly lower mJSW in the fourth year after baseline and a significantly greater arthroplasty rate within nine years in the exposed group than in the control group. RKOAC: mJSW (exposure: 2.6(1.1 ~ 3.6) vs. control: 3.3(2.0 ~ 4.2), P < 0.05), arthroplasty rate (exposure: 14(14.3%) vs. control: 4(4.1%), P < 0.05); LKOAC: mJSW (exposure: 3.1(2 ~ 3.9) vs. control: 3.4(2.6 ~ 4.2), P < 0.05), arthroplasty rate (exposure: 16(13.7%) vs. control: 7(6%), P < 0.05).

CONCLUSIONS

Patients with knee osteoarthritis experienced greater progression of osteoarthritis when the contralateral knee was also affected.

CartiMorph: A framework for automated knee articular cartilage morphometrics

We introduce CartiMorph, a framework for automated knee articular cartilage morphometrics. It takes an image as input and generates quantitative metrics for cartilage subregions, including the percentage of full-thickness cartilage loss (FCL), mean thickness, surface area, and volume. CartiMorph leverages the power of deep learning models for hierarchical image feature representation. Deep learning models were trained and validated for tissue segmentation, template construction, and template-to-image registration. We established methods for surface-normal-based cartilage thickness mapping, FCL estimation, and rule-based cartilage parcellation. Our cartilage thickness map showed less error in thin and peripheral regions. We evaluated the effectiveness of the adopted segmentation model by comparing the quantitative metrics obtained from model segmentation and those from manual segmentation. The root-mean-squared deviation of the FCL measurements was less than 8%, and strong correlations were observed for the mean thickness (Pearson's correlation coefficient ρ∈[0.82,0.97]), surface area (ρ∈[0.82,0.98]) and volume (ρ∈[0.89,0.98]) measurements. We compared our FCL measurements with those from a previous study and found that our measurements deviated less from the ground truths. We observed superior performance of the proposed rule-based cartilage parcellation method compared with the atlas-based approach. CartiMorph has the potential to promote imaging biomarkers discovery for knee osteoarthritis.

Development and evaluation of nomograms for predicting osteoarthritis progression based on MRI cartilage parameters: data from the FNIH OA biomarkers Consortium

BACKGROUND

Osteoarthritis (OA) is a leading cause of disability worldwide. However, the existing methods for evaluating OA patients do not provide enough comprehensive information to make reliable predictions of OA progression. This retrospective study aimed to develop prediction nomograms based on MRI cartilage that can predict disease progression of OA.

METHODS

A total of 600 subjects with mild-to-moderate osteoarthritis from the Foundation for National Institute of Health (FNIH) project of osteoarthritis initiative (OAI). The MRI cartilage parameters of the knee at baseline were measured, and the changes in cartilage parameters at 12- and 24-month follow-up were calculated. The least absolute shrinkage and selection operator (LASSO) regression analysis was used to extract the valuable characteristic parameters at different time points including cartilage thickness, cartilage volume, subchondral bone exposure area and uniform cartilage thickness in different sub regions of the knee, and the MRI cartilage parameters score0, scoreΔ12, and scoreΔ24 at baseline, 12 months, and 24 months were constructed. ScoreΔ12, and scoreΔ24 represent changes between 12 M vs. baseline, and 24 M vs. baseline, respectively. Logistic regression analysis was used to construct the nomogram0, nomogramΔ12, and nomogramΔ24, including MRI-based score and risk factors. The area under curve (AUC) was used to evaluate the differentiation of nomograms in disease progression and subgroup analysis. The calibration curve and Hosmer-Lemeshow (H-L) test were used to verify the calibration of the nomograms. Clinical usefulness of each prediction nomogram was verified by decision curve analysis (DCA). The nomograms with predictive efficacy were analyzed by secondary analysis. Internal verification was assessed using bootstrapping validation.

RESULTS

Each nomogram included cartilage score, KL grade, WOMAC pain score, WOMAC disability score, and minimum joint space width. The AUC of nomogram0, nomogramΔ12, and nomogramΔ24 in predicing the progression of radiology and pain were 0.69, 0.64, and 0.71, respectively. All three nomograms had good calibration. Analysis by DCA showed that the clinical effectiveness of nomogramΔ24 was higher than others. Secondary analysis showed that nomogram0 and nomogramΔ24 were more capable of predicting OA radiologic progression than pain progression.

CONCLUSION

Nomograms based on MRI cartilage change were useful for predicting the progression of mild to moderate OA.

Quantitative T2 mapping magnetic resonance imaging of articular cartilage in patients with juvenile idiopathic arthritis

PURPOSE

We aimed to analyze the microstructure changes of knee cartilage in Juvenile idiopathic arthritis (JIA) patients with active synovitis using quantitative magnetic resonance imaging (MRI) T2 mapping technique.

MATERIALS AND METHODS

This study included 23 JIA patients, who underwent bilateral knee joints by using a MR imaging protocol with the addition of a coronal T2 mapping. The femorotibial joint cartilage of participants was divided into eight subregions. Twenty-four (52.17%) of 46 joints (non-synovitis group), and twenty-two (47.83%) joint cases (active-synovitis group) were respectively calculated the T2 mean values for each subregion. Student's T test or Mann-Whitney U test was used to determine the statistical differences of each subregion in the non-synovitis and active-synovitis groups, which is also applied to define the distribution differences of cartilage subregion in femoral and tibial.

RESULTS

The T2 mean values of the superficial and deep zone of cartilage for active synovitis group were respectively higher than those for non-synovitis group (P < 0.05), except for the deep zone of cartilage in lateral tibial plateau (LTP) (P > 0.05). The mean T2 values of the deep zone in femoral cartilage for active synovitis group were significantly higher than that of tibial (P < 0.05).

CONCLUSION

The finding of an increased average T2 values in active synovitis for JIA patients, especially in the deep cartilage of femoral condyle, which suggests that T2 values may reflect cartilage microstructure differences that occur in JIA. T2 mapping as an objective and quantitative method may allow for early detection of cartilage changes.

Femoral Cartilage Thickness in Knee Osteoarthritis Patients and Healthy Adults: An Ultrasound Measurement Comparison

Background

Currently, conventional radiography is still widely used to diagnose knee osteoarthritis and assess the grade according to Kallgren and Lawrence's criteria. Ultrasound is a simple, inexpensive, noninvasive, and dynamic modality for evaluating femoral cartilage (FC) thickness. This study aims to measure the FC thickness in knee osteoarthritis (OA) patients and compare it to healthy adults using ultrasound assessment.

Methods

An observational study with a cross-sectional design was conducted at the Department of Physical Medicine and Rehabilitation of Hajj General Hospital, Surabaya, Indonesia, from May to July 2022. Participants radiologically diagnosed with OA were included in the study and assigned to the OA group. Meanwhile, healthy adults without knee symptoms were included in the control group. FC thickness was measured using ultrasound scans at three sites: medial condyle (MC), intercondylar (IC), and lateral condyle (LC) on both sides of the knee.

Results

The mean age in the OA and control groups was 61.03 ± 8.6 and 33.93 ± 14.7 years, respectively. Most participants in both groups were female. The OA group exhibited a thinner FC (1.49-1.63 mm) than the control group (1.68-1.87 mm). There was a significant difference in the mean of the right and left MC in both groups (p < 0.05) but no significant difference in the IC and LC.

Conclusion

OA patients exhibited a thinner FC than healthy adults in the control group. There was a significant difference in the mean thickness of the MC between groups.

A Machine Learning Model to Predict Knee Osteoarthritis Cartilage Volume Changes over Time Using Baseline Bone Curvature

The hallmark of osteoarthritis (OA), the most prevalent musculoskeletal disease, is the loss of cartilage. By using machine learning (ML), we aimed to assess if baseline knee bone curvature (BC) could predict cartilage volume loss (CVL) at one year, and to develop a gender-based model. BC and cartilage volume were assessed on 1246 participants using magnetic resonance imaging. Variables included age, body mass index, and baseline values of eight BC regions. The outcome consisted of CVL at one year in 12 regions. Five ML methods were evaluated. Validation demonstrated very good accuracy for both genders (R ≥ 0.78), except the medial tibial plateau for the woman. In conclusion, we demonstrated, for the first time, that knee CVL at one year could be predicted using five baseline BC region values. This would benefit patients at risk of structural progressive knee OA.

Urbanization and Knee Cartilage Growth Among Children and Adolescents in Western Kenya

Objective

Previous studies have demonstrated that low physical activity levels during youth are associated with the development of thin knee cartilage, which may increase susceptibility to osteoarthritis later in life. Here, we propose and test the hypothesis that reductions in physical activity impair knee cartilage growth among people in developing countries experiencing urbanization and increased market integration.

Methods

Ultrasonography was used to measure knee cartilage thickness in 168 children and adolescents (aged 8‐17 years) from two groups in western Kenya: a rural, physically active group from a small‐scale farming community and an urban, less physically active group from the nearby city of Eldoret. We used general linear models to assess the relative effects of age on cartilage thickness in these two groups, controlling for sex and leg length.

Results

Both groups exhibited significant reductions in knee cartilage thickness with increasing age (P < 0.0001; 95% confidence interval [CI] 0.15‐0.06 mm), yet the rate of reduction was significantly less in the rural than in the urban group (P = 0.012; 95% CI 0.01‐0.10 mm).

Conclusion

The results support our hypothesis by showing that individuals from the more physically active rural group exhibited less knee cartilage loss during youth than the more sedentary urban group. Our findings suggest that reduced physical activity associated with urbanization in developing nations may affect adult knee cartilage thickness and thus could be a factor that increases susceptibility to osteoarthritis.