scholarly journals Subchondral bone length in knee osteoarthritis: A deep learning derived imaging measure and its association with radiographic and clinical outcomes

2021 ◽  
Author(s):  
Gary H Chang ◽  
Lisa K Park ◽  
Nina A Le ◽  
Ray S Jhun ◽  
Tejus Surendran ◽  
...  
Keyword(s):  
Neural Network ◽  
Knee Osteoarthritis ◽  
Subchondral Bone ◽  
Joint Space ◽  
Knee Joints ◽  
Womac Pain ◽  
Odds Ratios ◽  
Bone Length ◽  
Osteoarthritis Initiative ◽  
Mri Sequences

Objective: Develop a bone shape measure that reflects the extent of cartilage loss and bone flattening in knee osteoarthritis (OA) and test it against estimates of disease severity. Methods: A fast region-based convolutional neural network was trained to crop the knee joints in sagittal dual-echo steady state MRI sequences obtained from the Osteoarthritis Initiative (OAI). Publicly available annotations of the cartilage and menisci were used as references to annotate the tibia and the femur in 61 knees. Another deep neural network (U-Net) was developed to learn these annotations. Model predictions were compared with radiologist-driven annotations on an independent test set (27 knees). The U-Net was applied to automatically extract the knee joint structures on the larger OAI dataset (9,434 knees). We defined subchondral bone length (SBL), a novel shape measure characterizing the extent of overlying cartilage and bone flattening, and examined its relationship with radiographic joint space narrowing (JSN), concurrent WOMAC pain and disability as well as subsequent partial or total knee replacement (KR). Odds ratios for each outcome were estimated using relative changes in SBL on the OAI dataset into quartiles. Result: Mean SBL values for knees with JSN were consistently different from knees without JSN. Greater changes of SBL from baseline were associated with greater pain and disability. For knees with medial or lateral JSN, the odds ratios between lowest and highest quartiles corresponding to SBL changes for future KR were 5.68 (95% CI:[3.90,8.27]) and 7.19 (95% CI:[3.71,13.95]), respectively. Conclusion: SBL quantified OA status based on JSN severity. It has promise as an imaging marker in predicting clinical and structural OA outcomes.

scholarly journals Interpretable and parameter optimized ensemble model for knee osteoarthritis assessment using radiographs

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Mohammed Bany Muhammad ◽  
Mohammed Yeasin
Keyword(s):  
Knee Osteoarthritis ◽  
Objective Assessment ◽  
Joint Space ◽  
Knee Joints ◽  
Ensemble Model ◽  
Scale Invariant ◽  
Substantial Impact ◽  
X Ray ◽  
Osteoarthritis Initiative

AbstractKnee osteoarthritis (KOA) is an orthopedic disorder with a substantial impact on mobility and quality of life. An accurate assessment of the KOA levels is imperative in prioritizing meaningful patient care. Quantifying osteoarthritis features such as osteophytes and joint space narrowing (JSN) from low-resolution images (i.e., X-ray images) are mostly subjective. We implement an objective assessment and quantification of KOA to aid practitioners. In particular, we developed an interpretable ensemble of convolutional neural network (CNN) models consisting of three modules. First, we developed a scale-invariant and aspect ratio preserving model to localize Knee joints. Second, we created multiple instances of "hyperparameter optimized" CNN models with diversity and build an ensemble scoring system to assess the severity of KOA according to the Kellgren–Lawrence grading (KL) scale. Third, we provided visual explanations of the predictions by the ensemble model. We tested our models using a collection of 37,996 Knee joints from the Osteoarthritis Initiative (OAI) dataset. Our results show a superior (13–27%) performance improvement compared to the state-of-the-art methods.

Convolutional Neural Network-Based Automatic Measurement of Joint Space Width to Predict Radiographic Severity and Progression of Knee Osteoarthritis

2021 ◽  
Author(s):  
James Chung Wai Cheung ◽  
Yiu Chow TAM ◽  
Lok Chun CHAN ◽  
Ping Keung CHAN ◽  
Chunyi WEN
Keyword(s):  
Neural Network ◽  
Knee Osteoarthritis ◽  
Convolutional Neural Network ◽  
Pearson Correlation ◽  
Joint Space Width ◽  
Joint Space ◽  
Receiver Operating Curve ◽  
Radiographic Severity ◽  
X Ray ◽  
Space Width

Abstract Objectives To develop a deep convolutional neural network (CNN) for the segmentation of femur and tibia on plain x-ray radiographs, hence enabling an automated measurement of joint space width (JSW) to predict the severity and progression of knee osteoarthritis (KOA). Methods A CNN with ResU-Net architecture was developed for knee X-ray imaging segmentation. The efficiency was evaluated by the Intersection over Union (IoU) score by comparing the outputs with the annotated contour of the distal femur and proximal tibia. By leveraging imaging segmentation, the minimal and multiple JSWs in the tibiofemoral joint were estimated and then validated by radiologists’ measurements in the Osteoarthritis Initiative (OAI) dataset using Pearson correlation and Bland–Altman plot. The estimated JSWs were deployed to predict the radiographic severity and progression of KOA defined by Kellgren-Lawrence (KL) grades using the XGBoost model. The classification performance was assessed using F1 and area under receiver operating curve (AUC). Results The network has attained a segmentation efficiency of 98.9% IoU. Meanwhile, the agreement between the CNN-based estimation and radiologist’s measurement of minimal JSW reached 0.7801 (p < 0.0001). Moreover, the 32-point multiple JSW obtained the highest AUC score of 0.656 to classify KL-grade of KOA. Whereas the 64-point multiple JSWs achieved the best performance in predicting KOA progression defined by KL grade change within 48 months, with AUC of 0.621. The multiple JSWs outperform the commonly used minimum JSW with 0.587 AUC in KL-grade classification and 0.554 AUC in disease progression prediction. Conclusion Fine-grained characterization of joint space width of KOA yields comparable performance to the radiologist in assessing disease severity and progression. We provide a fully automated and efficient radiographic assessment tool for KOA.

scholarly journals A pilot study of peripheral blood DNA methylation models as predictors of knee osteoarthritis radiographic progression: data from the Osteoarthritis Initiative (OAI)

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Christopher M. Dunn ◽  
Michael C. Nevitt ◽  
John A. Lynch ◽  
Matlock A. Jeffries
Keyword(s):  
Dna Methylation ◽  
Pilot Study ◽  
Knee Osteoarthritis ◽  
Peripheral Blood ◽  
Radiographic Progression ◽  
Mononuclear Cells ◽  
Model Performance ◽  
Joint Space ◽  
Peripheral Blood Mononuclear ◽  
Osteoarthritis Initiative

AbstractKnee osteoarthritis (OA) is a leading cause of chronic disability worldwide, but no diagnostic or prognostic biomarkers are available. Increasing evidence supports epigenetic dysregulation as a contributor to OA pathogenesis. In this pilot study, we investigated epigenetic patterns in peripheral blood mononuclear cells (PBMCs) as models to predict future radiographic progression in OA patients enrolled in the longitudinal Osteoarthritis Initiative (OAI) study. PBMC DNA was analyzed from baseline OAI visits in 58 future radiographic progressors (joint space narrowing at 24 months, sustained at 48 months) compared to 58 non-progressors. DNA methylation was quantified via Illumina microarrays and beta- and M-values were used to generate linear classification models. Data were randomly split into a 60% development and 40% validation subsets, models developed and tested, and cross-validated in a total of 40 cycles. M-value based models outperformed beta-value based models (ROC-AUC 0.81 ± 0.01 vs. 0.73 ± 0.02, mean ± SEM, comparison p = 0.002), with a mean classification accuracy of 73 ± 1% (mean ± SEM) for M- and 69 ± 1% for beta-based models. Adjusting for covariates did not significantly alter model performance. Our findings suggest that PBMC DNA methylation-based models may be useful as biomarkers of OA progression and warrant additional evaluation in larger patient cohorts.

scholarly journals Dietary Patterns and Progression of Knee Osteoarthritis: Data from the Osteoarthritis Initiative

2020 ◽  
Vol 111 (3) ◽  
pp. 667-676 ◽  
Author(s):  
Chang Xu ◽  
Nathalie E Marchand ◽  
Jeffrey B Driban ◽  
Timothy McAlindon ◽  
Charles B Eaton ◽  
...  
Keyword(s):  
Knee Osteoarthritis ◽  
Rhode Island ◽  
Dietary Patterns ◽  
Joint Space Width ◽  
Womac Score ◽  
Joint Space ◽  
Research Attention ◽  
Symptomatic Disease ◽  
Osteoarthritis Initiative ◽  
Grade Increase

ABSTRACT Background While some individual foods and nutrients have been associated with knee osteoarthritis (KOA) progression, the association between dietary patterns and KOA progression has received little research attention. Objective The objective of this study was to determine whether dietary patterns, derived by principal components analysis (PCA), are associated with KOA progression. Methods In the Osteoarthritis Initiative (OAI), a prospective cohort with clinical centers in Maryland, Ohio, Pennsylvania, and Rhode Island, 2757 participants with existing KOA (mean age 62 y) and diet assessed at baseline were followed for ≤72 mo. Using PCA, Western and prudent dietary patterns were derived. Radiographic KOA progression was assessed using 2 separate measures, 1 full Kellgren–Lawrence (KL) grade increase and loss in joint space width (JSW). Symptomatic KOA progression was defined as an increase in or remaining in 1 of the 2 highest classification categories of the Western Ontario and McMaster Universities Arthritis Index (WOMAC). Results Adherence to Western and prudent dietary patterns was significantly associated with radiographic and symptomatic progression of KOA. With increasing Western pattern score, there was increased KL-worsening risk (compared with quartile 1, HR for quartile 4: 1.30; 95% CI: 1.05, 1.61; P-trend &lt; 0.01) and increased odds of progression to higher WOMAC score (compared with quartile 1, OR for quartile 4: 1.39; 95% CI: 1.18, 1.63; P-trend &lt; 0.01) but no significant change in JSW loss. With increasing prudent pattern score there was decreased KL-worsening risk (compared with quartile 1, HR for quartile 4: 0.79; 95% CI: 0.64, 0.98; P-trend = 0.02), decreased JSW loss (quartile 1: 0.46 mm; quartile 4: 0.38 mm; P-trend &lt; 0.01), and decreased odds of higher WOMAC progression (compared with quartile 1, OR for quartile 4 0.73; 95% CI: 0.62, 0.86; P-trend &lt; 0.01) in multivariable adjusted models. Conclusions Adherence to a Western dietary pattern was associated with increased radiographic and symptomatic KOA progression, while following a prudent pattern was associated with reduced progression. In general, for people already diagnosed with KOA, eating a diet rich in fruits, vegetables, fish, whole grains, and legumes may be related to decreased radiographic and symptomatic disease progression.

scholarly journals Association of subchondral bone marrow lesion localisation with weight bearing pain in people with knee osteoarthritis: data from the Osteoarthritis Initiative

2021 ◽  
Author(s):  
Koji Aso ◽  
Seyed Mohsen Shahtaheri ◽  
Daniel F. McWilliams ◽  
David A. Walsh
Keyword(s):  
Bone Marrow ◽  
Knee Osteoarthritis ◽  
Knee Pain ◽  
Subchondral Bone ◽  
Negative Binomial ◽  
Weight Bearing ◽  
The Other ◽  
Knee Oa ◽  
Pain Scores ◽  
Osteoarthritis Initiative

Abstract Background Subchondral bone marrow lesions (BMLs) detected on MRI in knee osteoarthritis (OA) are associated with knee pain. The prevalence and progression of subchondral BMLs are increased by mechanical knee load. However, associations of subchondral BML location with weight-bearing knee pain are currently unknown. In this study, we aim to demonstrate associations of subchondral BML location and size with weight-bearing knee pain in knee OA.Methods We analyzed 1412 and 582 varus knees from cross-sectional and longitudinal Osteoarthritis Initiative datasets, respectively. BML scores were semi-quantitatively analysed with the MRI Osteoarthritis Knee Score for 4 subchondral regions (median and lateral femorotibial, medial and lateral patellofemoral) and subspinous region. Weight-bearing and non-weight-bearing pain scores were derived from WOMAC pain items. Correlation and negative binomial regression models were used for analysis of associations between the BML scores and pain at baseline, and changes in the BML scores and changes in pain after 24-month follow up.Results Greater BML scores at medial femorotibial and lateral patellofemoral compartments were associated with greater weight-bearing pain scores, and statistical significance was retained after adjusting for BML scores at the other 4 joint compartments and other OA features, as well as for non-weight-bearing pain, age, sex and Body Mass Index (BMI) (medial femorotibial; B=0.08, p=0.02. patellofemoral; B=0.13, p=0.01). Subanalysis revealed that greater medial femorotibial BML scores were associated with greater pain on walking and standing (B=0.11, p=0.01, and B=0.10, p=0.04, respectively). Lateral patellofemoral BML scores were associated with pain on climbing, respectively B=0.14, p=0.02. Increases or decreases over 24 months in BML score in the medial femorotibial compartment were significantly associated with increases or decreases in weight-bearing pain severity after adjusting for non-weight-bearing pain, age, sex, baseline weight-bearing pain, BMI, and BML at the other 4 joint compartments (B=0.10, p=0.01). Conclusions Subchondral BML size at the medial femorotibial joint compartment was specifically associated with the severity and the change in weight-bearing pain, independent of non-weight-bearing pain, in knee OA. Specific associations of weight-bearing pain with subchondral BMLs in weight-bearing compartments of the knee indicate that BMLs in subchondral bone contribute to biomechanically-induced OA pain.

scholarly journals VITAMIN D SUPPLEMENTATION AND FUNCTIONAL KNEE OSTEOARTHRITIS PROGRESSION IN OLDER ADULTS WITH OBESITY: DATA FROM THE OSTEOARTHRITIS INITIATIVE

2015 ◽  
pp. 1-4
Author(s):  
A.J. Zbehlik ◽  
L.K. Barre ◽  
J.A. Batsis ◽  
E.A. Scherer ◽  
S.J. Bartels
Keyword(s):  
Older Adults ◽  
Vitamin D ◽  
Knee Osteoarthritis ◽  
The Elderly ◽  
Pain Scale ◽  
Primary Outcome Measure ◽  
Vitamin D Supplementation ◽  
Womac Pain ◽  
Increased Risk ◽  
Osteoarthritis Initiative

Objective: Older adults with obesity are at increased risk of knee osteoarthritis (KOA) and vitamin D deficiency, but data on the effect of vitamin D supplementation in this population are equivocal. This study evaluated the effect of vitamin D supplementation on functional progression of KOA in older adults with obesity. Participants with Body Mass Index ≥30 kg/m2 and aged ≥ 60 years from the Osteoarthritis Initiative progression cohort were stratified by baseline vitamin D use. The relationship between vitamin D supplementation and progression of KOA at 72 months was characterized. The Western Ontario McMaster University Osteoarthritis Index (WOMAC) pain scale was the primary outcome measure. Secondary measures included: WOMAC disability, Physical Activity Scale for the Elderly, gait speed and Knee injury and Osteoarthritis Outcome Score (KOOS) scales. In older adults with KOA and obesity, baseline supplemental vitamin D use did not predict functional progression of osteoarthritis at 72 months.

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