Pub Date : 2025-12-01DOI: 10.1016/j.ostima.2025.100385
Mikael J. Turunen , Alexander Paz , Lauri Stenroth , Santtu Mikkonen , Mimmi K. Liukkonen , Mika E. Mononen
Objective
Commonly used grading systems in knee osteoarthritis (OA) evaluation provide an overview of the disease severity with limited prognostic ability. Recently, efforts towards automated and objective deep- and machine-learning, and computational modeling-based prediction tools have been made, but they are complex and lack interpretability. This study aimed to identify knee joint morphology measures that can be easily quantified from plain radiographs and are indicative of the risk of radiographic OA development among subjects without definite radiographic OA, focusing especially on the asymmetry of the knees.
Materials and Methods
Knee joint dimensions and angles were measured from anterior-posterior weight-bearing knee radiographs at baseline and 8-year follow-up time point. The subjects were grouped based on Kellgren-Lawrence grades at the 8-year follow-up and compared with regard to the knee joint dimensions and angles and their asymmetries between the subjects’ knees.
Results
Absolute dimensions or angles at baseline were not associated with OA development. Instead, the asymmetry in the dimensions (relative difference between the left and right knee), was higher in subjects who developed radiographic knee OA during 8-year follow-up. The medial joint space asymmetry was associated with the development of advanced knee OA when it was over 10 % (OR = 1.87) or 15 % (OR = 3.27).
Conclusions
Medial joint space asymmetry between the left and right knee of over 10 % could be a potential risk factor for developing knee OA.
{"title":"Healthy knee asymmetry is a potential risk factor for knee osteoarthritis: Data from the osteoarthritis initiative","authors":"Mikael J. Turunen , Alexander Paz , Lauri Stenroth , Santtu Mikkonen , Mimmi K. Liukkonen , Mika E. Mononen","doi":"10.1016/j.ostima.2025.100385","DOIUrl":"10.1016/j.ostima.2025.100385","url":null,"abstract":"<div><h3>Objective</h3><div>Commonly used grading systems in knee osteoarthritis (OA) evaluation provide an overview of the disease severity with limited prognostic ability. Recently, efforts towards automated and objective deep- and machine-learning, and computational modeling-based prediction tools have been made, but they are complex and lack interpretability. This study aimed to identify knee joint morphology measures that can be easily quantified from plain radiographs and are indicative of the risk of radiographic OA development among subjects without definite radiographic OA, focusing especially on the asymmetry of the knees.</div></div><div><h3>Materials and Methods</h3><div>Knee joint dimensions and angles were measured from anterior-posterior weight-bearing knee radiographs at baseline and 8-year follow-up time point. The subjects were grouped based on Kellgren-Lawrence grades at the 8-year follow-up and compared with regard to the knee joint dimensions and angles and their asymmetries between the subjects’ knees.</div></div><div><h3>Results</h3><div>Absolute dimensions or angles at baseline were not associated with OA development. Instead, the asymmetry in the dimensions (relative difference between the left and right knee), was higher in subjects who developed radiographic knee OA during 8-year follow-up. The medial joint space asymmetry was associated with the development of advanced knee OA when it was over 10 % (OR = 1.87) or 15 % (OR = 3.27).</div></div><div><h3>Conclusions</h3><div>Medial joint space asymmetry between the left and right knee of over 10 % could be a potential risk factor for developing knee OA.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 4","pages":"Article 100385"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145712169","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01DOI: 10.1016/j.ostima.2025.100273
Samantha Chin , Jamie E. Collins
Knee osteoarthritis (OA) is a disease that can cause substantial pain and disability in patients. The progression of OA has been linked to inflammatory, mechanical, genetic, and metabolic factors, yet patterns of symptoms and structural damage vary considerably between knee OA patients. The heterogeneity of the disease presents a need for identifying and understanding patient subgroups to inform more personalized treatments. Identifying anatomical morphotypes, a type of classification defined by anatomical and morphological attributes, is critical for identifying subgroups of patients who are most likely to benefit from particular treatments. Cluster analysis is an unsupervised learning method that can be used to uncover subgroups in datasets without labeled outcomes to guide the analysis. In this perspective, we will review analytic challenges in identifying anatomical morphotypes using clustering methods, including finding patterns that are not clinically relevant, navigating the unique correlation structure of anatomical data, and working with high dimensional data. With the exciting applications of clustering methods to improve personalized medicine in knee OA, it is essential to consider these analytic challenges to ensure that analyses yield clinically actionable insights.
{"title":"Analytic challenges in defining structural phenotypes in OA clinical trials: a perspective","authors":"Samantha Chin , Jamie E. Collins","doi":"10.1016/j.ostima.2025.100273","DOIUrl":"10.1016/j.ostima.2025.100273","url":null,"abstract":"<div><div>Knee osteoarthritis (OA) is a disease that can cause substantial pain and disability in patients. The progression of OA has been linked to inflammatory, mechanical, genetic, and metabolic factors, yet patterns of symptoms and structural damage vary considerably between knee OA patients. The heterogeneity of the disease presents a need for identifying and understanding patient subgroups to inform more personalized treatments. Identifying anatomical morphotypes, a type of classification defined by anatomical and morphological attributes, is critical for identifying subgroups of patients who are most likely to benefit from particular treatments. Cluster analysis is an unsupervised learning method that can be used to uncover subgroups in datasets without labeled outcomes to guide the analysis. In this perspective, we will review analytic challenges in identifying anatomical morphotypes using clustering methods, including finding patterns that are not clinically relevant, navigating the unique correlation structure of anatomical data, and working with high dimensional data. With the exciting applications of clustering methods to improve personalized medicine in knee OA, it is essential to consider these analytic challenges to ensure that analyses yield clinically actionable insights.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 4","pages":"Article 100273"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145712170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01DOI: 10.1016/j.ostima.2025.100375
{"title":"Erratum regarding missing Declaration of interests and Ethical approval statements in the previously published articles","authors":"","doi":"10.1016/j.ostima.2025.100375","DOIUrl":"10.1016/j.ostima.2025.100375","url":null,"abstract":"","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 4","pages":"Article 100375"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145712500","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01DOI: 10.1016/j.ostima.2025.100382
Antti Kemppainen , Vilja Kotkaranta , Olli Nykänen , Mika T. Nevalainen
Objective
To evaluate the agreement of cone-beam computed tomography arthrography (CBCTA) and magnetic resonance imaging (MRI) in detecting osteoarthritic changes of the knee.
Design
This comparative study included 58 knee joints in 54 symptomatic subjects with suspicion of knee osteoarthritis (OA). The symptomatic joints were imaged using CBCTA and 3T MRI and graded using the MRI Osteoarthritis Knee Score (MOAKS). Agreement between modalities was assessed using prevalence and bias adjusted kappa (PABAK), percentages of exact (PEA) and close agreement (PCA) of ±1 in MOAKS grades and participant-specific comparisons.
Results
CBCTA was performed with acceptable intra-articular concentration in 86.2 % (n = 50) knees in 48 subjects (68.6 % women, mean age 58.7 years). Definite tibiofemoral and patellofemoral OA was identified on MRI in 76 % (n = 38). For all cartilage lesions, PABAKs ranged between 0.80 and 0.96 (mean 0.90), with mean PEAs of 68.4 % and mean PCAs of 90.2 %. Full-thickness cartilage lesions demonstrated particularly strong agreement. Osteophyte detection yielded PABAKs between 0.92 and 0.98 (mean 0.95), mean PEA of 65.8 % and mean PCA of 99 %. For meniscal pathology, PABAKs ranged from 0.84 to 0.98 (mean 0.90), with mean PCA of 74.7 % and mean PEA of 81.7 %. For the anterior cruciate ligament, Baker cyst, and synovial hypertrophy, PABAKs were 0.97, 0.63, and 0.65, with high PEAs.
Conclusions
CBCTA demonstrates moderate to almost perfect agreement with 3T MRI for knee OA findings. Although 13.8 % of the arthrographies had failed in our study, CBCTA offers a practical alternative when MRI is contraindicated or unavailable.
{"title":"Comparative evaluation of weight-bearing cone beam CT arthrography and supine 3T MRI in knee osteoarthritis","authors":"Antti Kemppainen , Vilja Kotkaranta , Olli Nykänen , Mika T. Nevalainen","doi":"10.1016/j.ostima.2025.100382","DOIUrl":"10.1016/j.ostima.2025.100382","url":null,"abstract":"<div><h3>Objective</h3><div>To evaluate the agreement of cone-beam computed tomography arthrography (CBCTA) and magnetic resonance imaging (MRI) in detecting osteoarthritic changes of the knee.</div></div><div><h3>Design</h3><div>This comparative study included 58 knee joints in 54 symptomatic subjects with suspicion of knee osteoarthritis (OA). The symptomatic joints were imaged using CBCTA and 3T MRI and graded using the MRI Osteoarthritis Knee Score (MOAKS). Agreement between modalities was assessed using prevalence and bias adjusted kappa (PABAK), percentages of exact (PEA) and close agreement (PCA) of ±1 in MOAKS grades and participant-specific comparisons.</div></div><div><h3>Results</h3><div>CBCTA was performed with acceptable intra-articular concentration in 86.2 % (<em>n</em> = 50) knees in 48 subjects (68.6 % women, mean age 58.7 years). Definite tibiofemoral and patellofemoral OA was identified on MRI in 76 % (<em>n</em> = 38). For all cartilage lesions, PABAKs ranged between 0.80 and 0.96 (mean 0.90), with mean PEAs of 68.4 % and mean PCAs of 90.2 %. Full-thickness cartilage lesions demonstrated particularly strong agreement. Osteophyte detection yielded PABAKs between 0.92 and 0.98 (mean 0.95), mean PEA of 65.8 % and mean PCA of 99 %. For meniscal pathology, PABAKs ranged from 0.84 to 0.98 (mean 0.90), with mean PCA of 74.7 % and mean PEA of 81.7 %. For the anterior cruciate ligament, Baker cyst, and synovial hypertrophy, PABAKs were 0.97, 0.63, and 0.65, with high PEAs.</div></div><div><h3>Conclusions</h3><div>CBCTA demonstrates moderate to almost perfect agreement with 3T MRI for knee OA findings. Although 13.8 % of the arthrographies had failed in our study, CBCTA offers a practical alternative when MRI is contraindicated or unavailable.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 4","pages":"Article 100382"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145712498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01DOI: 10.1016/j.ostima.2025.100378
Emily K Wright , Stacy E Smith , Molly Zgoda , Eric M Berkson , Simon Goertz , Morgan H Jones , Elizabeth G Matzkin , Bethany Wilcox , Christian Lattermann , Cale Jacobs
Objective
The purposes of this study were to evaluate the prevalence of persistent postoperative synovitis three months after anterior cruciate ligament reconstruction (ACLR) using ultrasonographic superb microvascular imaging (SMI) and evaluate the intra-rater reliability of SMI synovitis and the level of agreement with other ultrasound synovitis assessment methods.
Design
Twenty-three individuals who had undergone primary ACLR took part in this prospective, IRB-approved study (11 females, 12 males; age=28.7±9.7 y; BMI=25.6±3.3 kg/m2). Three months after surgery, longitudinal and transverse ultrasound scans of the suprapatellar recess were performed at midline, medial to midline, and lateral to the midline. In addition to Power Doppler and B mode measures of synovitis and effusion, SMI was graded on two separate occasions at least two weeks apart. SMI intra-rater reliability was assessed with weighted Kappa analyses, and Kappa analyses were also used to assess the agreement between SMI synovitis and Power Doppler synovitis and B mode effusion.
Results
Three months following ACLR, 2 (8.7%) participants had no SMI synovitis, 9 (39.1%) participants had mild synovitis, and 12 (52.2%) had moderate synovitis. SMI synovitis grades demonstrated excellent intra-rater reliability (Kappa=0.93 [95%CI: 0.80, 1.06]) but demonstrated little agreement with Power Doppler synovitis grades (Kappa=0.29) or B mode effusion grades (Kappa=0.14).
Conclusions
Persistent postoperative synovitis was common with half of patients demonstrating moderate synovitis. SMI synovitis grading was reliable, but little agreement was noted between SMI and other ultrasound grades of synovitis or effusion suggesting that the different techniques are identifying distinct features of postoperative inflammation.
{"title":"Superb microvascular imaging in the assessment of persistent synovitis after anterior cruciate ligament reconstruction","authors":"Emily K Wright , Stacy E Smith , Molly Zgoda , Eric M Berkson , Simon Goertz , Morgan H Jones , Elizabeth G Matzkin , Bethany Wilcox , Christian Lattermann , Cale Jacobs","doi":"10.1016/j.ostima.2025.100378","DOIUrl":"10.1016/j.ostima.2025.100378","url":null,"abstract":"<div><h3>Objective</h3><div>The purposes of this study were to evaluate the prevalence of persistent postoperative synovitis three months after anterior cruciate ligament reconstruction (ACLR) using ultrasonographic superb microvascular imaging (SMI) and evaluate the intra-rater reliability of SMI synovitis and the level of agreement with other ultrasound synovitis assessment methods.</div></div><div><h3>Design</h3><div>Twenty-three individuals who had undergone primary ACLR took part in this prospective, IRB-approved study (11 females, 12 males; age=28.7±9.7 y; BMI=25.6±3.3 kg/m<sup>2</sup>). Three months after surgery, longitudinal and transverse ultrasound scans of the suprapatellar recess were performed at midline, medial to midline, and lateral to the midline. In addition to Power Doppler and B mode measures of synovitis and effusion, SMI was graded on two separate occasions at least two weeks apart. SMI intra-rater reliability was assessed with weighted Kappa analyses, and Kappa analyses were also used to assess the agreement between SMI synovitis and Power Doppler synovitis and B mode effusion.</div></div><div><h3>Results</h3><div>Three months following ACLR, 2 (8.7%) participants had no SMI synovitis, 9 (39.1%) participants had mild synovitis, and 12 (52.2%) had moderate synovitis. SMI synovitis grades demonstrated excellent intra-rater reliability (Kappa=0.93 [95%CI: 0.80, 1.06]) but demonstrated little agreement with Power Doppler synovitis grades (Kappa=0.29) or B mode effusion grades (Kappa=0.14).</div></div><div><h3>Conclusions</h3><div>Persistent postoperative synovitis was common with half of patients demonstrating moderate synovitis. SMI synovitis grading was reliable, but little agreement was noted between SMI and other ultrasound grades of synovitis or effusion suggesting that the different techniques are identifying distinct features of postoperative inflammation.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 4","pages":"Article 100378"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145712110","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01DOI: 10.1016/j.ostima.2025.100357
Eva A. Bax , H. Chien Nguyen , Roel J.H. Custers , Vahid Arbabi , Hassan Rayegan , Willem Paul Gielis , Claudia Lindner , Tim F. Cootes , Margreet Kloppenburg , Francisco J Blanco , Ida K. Haugen , Francis Berenbaum , Mylène P. Jansen , Simon C. Mastbergen , Frank W. Roemer , Felix Eckstein , Wolfgang Wirth , Moyo C. Kruyt , Harrie Weinans
Objective
Correlations between minimum joint space width (mJSW) and MRI-based cartilage thickness are strong in cross-sectional analyses and moderate in longitudinal analyses, possibly due to knee rotation and flexion. This study investigates the effect of knee positioning during radiographic acquisition on the difference between mJSW and MRI-based cartilage thickness.
Methods
Radiographic mJSW from the index knee was determined from baseline (265 patients) and 24-month follow-up (165 patients) on fixed-flexion radiographs from IMI-APPROACH (multicenter OA study) patients using automated software. Statistical Shape Models were used to quantify knee rotation and flexion on radiographs. Cartilage thickness was assessed by manual segmentation from MRI. Differences between mJSW (radiographs) and cartilage thickness (MRI) were assessed at baseline and follow-up. Multivariable linear regression was used to evaluate the impact of knee flexion and rotation on the difference between mJSW and cartilage thickness.
Results
In cross-sectional analysis, differences between X-ray and MRI were significantly influenced by knee rotation (β = -0.18, P < 0.001). Longitudinal change in differences between X-ray and MRI were associated with changes in knee flexion (β = 0.19, P=0.002). Increases of one standard deviation in internal rotation and extension at follow-up resulted in a 0.2 mm false surrogate measurement of cartilage changes on radiographs.
Conclusion
Quantified knee positioning significantly affects differences between mJSW measured on radiographs and MRI-based cartilage thickness. The longitudinal analyses revealed that knee flexion was related to these differences, while knee rotation was only related to cross-sectional differences. These findings highlight the importance of knee positioning during radiographic acquisition in contributing to false surrogate measurement of cartilage status and cartilage change.
{"title":"Impact of quantified knee positioning on the measurement of minimal joint space width using statistical shape models: A cross-sectional and longitudinal analysis in the IMI-APPROACH","authors":"Eva A. Bax , H. Chien Nguyen , Roel J.H. Custers , Vahid Arbabi , Hassan Rayegan , Willem Paul Gielis , Claudia Lindner , Tim F. Cootes , Margreet Kloppenburg , Francisco J Blanco , Ida K. Haugen , Francis Berenbaum , Mylène P. Jansen , Simon C. Mastbergen , Frank W. Roemer , Felix Eckstein , Wolfgang Wirth , Moyo C. Kruyt , Harrie Weinans","doi":"10.1016/j.ostima.2025.100357","DOIUrl":"10.1016/j.ostima.2025.100357","url":null,"abstract":"<div><h3>Objective</h3><div>Correlations between minimum joint space width (mJSW) and MRI-based cartilage thickness are strong in cross-sectional analyses and moderate in longitudinal analyses, possibly due to knee rotation and flexion. This study investigates the effect of knee positioning during radiographic acquisition on the difference between mJSW and MRI-based cartilage thickness.</div></div><div><h3>Methods</h3><div>Radiographic mJSW from the index knee was determined from baseline (265 patients) and 24-month follow-up (165 patients) on fixed-flexion radiographs from IMI-APPROACH (multicenter OA study) patients using automated software. Statistical Shape Models were used to quantify knee rotation and flexion on radiographs. Cartilage thickness was assessed by manual segmentation from MRI. Differences between mJSW (radiographs) and cartilage thickness (MRI) were assessed at baseline and follow-up. Multivariable linear regression was used to evaluate the impact of knee flexion and rotation on the difference between mJSW and cartilage thickness.</div></div><div><h3>Results</h3><div>In cross-sectional analysis, differences between X-ray and MRI were significantly influenced by knee rotation (β = -0.18, P < 0.001). Longitudinal change in differences between X-ray and MRI were associated with changes in knee flexion (β = 0.19, P=0.002). Increases of one standard deviation in internal rotation and extension at follow-up resulted in a 0.2 mm false surrogate measurement of cartilage changes on radiographs.</div></div><div><h3>Conclusion</h3><div>Quantified knee positioning significantly affects differences between mJSW measured on radiographs and MRI-based cartilage thickness. The longitudinal analyses revealed that knee flexion was related to these differences, while knee rotation was only related to cross-sectional differences. These findings highlight the importance of knee positioning during radiographic acquisition in contributing to false surrogate measurement of cartilage status and cartilage change.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 4","pages":"Article 100357"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145712502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01DOI: 10.1016/j.ostima.2025.100379
Jack Consolini , Kevin M. Koch , Alissa J. Burge , Erwin Xia , Sharmila Majumdar , Garry E. Gold , Hollis G. Potter , Matthew F. Koff
Objective
Magnetic resonance imaging (MRI) based radiomic evaluation of the infrapatellar fat pad (IPFP) has been shown to predict knee osteoarthritis. As IPFP abnormalities can arise from sport-related injuries, this study evaluated whether qualitatively identified knee structure abnormalities in young athletes can be detected by IPFP MRI-based radiomics.
Design
Bilateral knee MRIs using Dixon fat-water decomposition techniques were obtained from 46 NCAA Division 1 collegiate 46 basketball players (26 male, 20 female) and 21 swimmers (10 male, 11 female). Board-certified musculoskeletal radiologists evaluated anatomic features and patellar height using the modified Noyes score and Caton-Deschamps index. IPFP volumes were segmented, and fat fraction was computed. Radiomic features were calculated within 2D overlapping patches extracted from the IPFP in the fat and water images separately. Cross-validated logistic regression models were developed using IPFP radiomic features as predictors of an athlete’s sport and the occurrence of cartilage lesions, tendinopathy, or bone abnormalities as observed on MRI. Mann-Whitney U tests evaluated differences in fat fraction between sports and knee structure abnormalities.
Results
The area under the receiver operating characteristic (ROC) curve (AUC; maximum 0.79) indicated that IPFP radiomics from fat-only images can differentiate between basketball and swimming athletes. Tendinopathy was identified (AUC = 0.68 ± 0.05) at larger patch sizes. Qualitative radiological assessments of cartilage lesions and bone abnormalities were not distinguished (AUC < 0.57). Fat fraction did not differ across sports or knee structure abnormality (p > 0.49, mean difference < 0.5%).
Conclusions
In the absence of inflammatory arthropathy, IPFP radiomics discriminated between sports but not cartilage lesions, tendinopathy, or bone abnormalities, suggesting structural adaptation to sport-specific loading. Abnormal IPFP signal intensity may not present in young athletes without traumatic injury or knee arthroscopy.
{"title":"Exploratory analysis of infrapatellar fat pad MRI-based radiomics for detection of knee structure abnormalities in collegiate basketball players and swimmers","authors":"Jack Consolini , Kevin M. Koch , Alissa J. Burge , Erwin Xia , Sharmila Majumdar , Garry E. Gold , Hollis G. Potter , Matthew F. Koff","doi":"10.1016/j.ostima.2025.100379","DOIUrl":"10.1016/j.ostima.2025.100379","url":null,"abstract":"<div><h3>Objective</h3><div>Magnetic resonance imaging (MRI) based radiomic evaluation of the infrapatellar fat pad (IPFP) has been shown to predict knee osteoarthritis. As IPFP abnormalities can arise from sport-related injuries, this study evaluated whether qualitatively identified knee structure abnormalities in young athletes can be detected by IPFP MRI-based radiomics.</div></div><div><h3>Design</h3><div>Bilateral knee MRIs using Dixon fat-water decomposition techniques were obtained from 46 NCAA Division 1 collegiate 46 basketball players (26 male, 20 female) and 21 swimmers (10 male, 11 female). Board-certified musculoskeletal radiologists evaluated anatomic features and patellar height using the modified Noyes score and Caton-Deschamps index. IPFP volumes were segmented, and fat fraction was computed. Radiomic features were calculated within 2D overlapping patches extracted from the IPFP in the fat and water images separately. Cross-validated logistic regression models were developed using IPFP radiomic features as predictors of an athlete’s sport and the occurrence of cartilage lesions, tendinopathy, or bone abnormalities as observed on MRI. Mann-Whitney U tests evaluated differences in fat fraction between sports and knee structure abnormalities.</div></div><div><h3>Results</h3><div>The area under the receiver operating characteristic (ROC) curve (AUC; maximum 0.79) indicated that IPFP radiomics from fat-only images can differentiate between basketball and swimming athletes. Tendinopathy was identified (AUC = 0.68 ± 0.05) at larger patch sizes. Qualitative radiological assessments of cartilage lesions and bone abnormalities were not distinguished (AUC < 0.57). Fat fraction did not differ across sports or knee structure abnormality (p > 0.49, mean difference < 0.5%).</div></div><div><h3>Conclusions</h3><div>In the absence of inflammatory arthropathy, IPFP radiomics discriminated between sports but not cartilage lesions, tendinopathy, or bone abnormalities, suggesting structural adaptation to sport-specific loading. Abnormal IPFP signal intensity may not present in young athletes without traumatic injury or knee arthroscopy.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 4","pages":"Article 100379"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145712497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01DOI: 10.1016/j.ostima.2025.100373
Sahar Sawani , Liubov Arbeeva , Katherine A. Yates , Carolina Alvarez , Todd A. Schwartz , Serena Savage-Guin , Jordan B. Renner , Catherine J. Bakewell , Minna J. Kohler , Janice Lin , Jonathan Samuels , Amanda E. Nelson
Objective
To identify phenotypes of knee osteoarthritis (KOA) based on demographic and clinical variables, symptoms, and ultrasound (US) features using a novel machine learning (ML) approach.
Design
Participants in the Johnston County Health Study provided demographics, symptomatic and functional assessments, and joint radiographs, which were transformed into the clinical data block. Standardized knee US were obtained, and US features composed the second data block. The Angle-based Joint and Individual Variation Explained (AJIVE) algorithm was used to identify shared and individual modes of variation. We focused on shared structure to explore how US features and non-US clinical data varied together overall, and in the subset with radiographic KOA (rKOA).
Results
This analysis included 861 participants (mean age 55 years, mean BMI 33 kg/m2); 335 (39 %) had rKOA. AJIVE identified two components of shared variation (subgroup and SC2). SC1 associated osteophytes and cartilage damage on US with higher BMI, older age, and worse symptoms and outcome scores. SC2 correlated effusion and synovitis but less cartilage damage on US, with better physical function and lower BMI. A similar pattern was seen in those with rKOA.
Conclusions
We identified two shared directions of variation that may represent distinct phenotypes of KOA. The first is consistent with prior studies linking osteophytes and cartilage damage to worse symptoms and function. The second may represent an inflammatory subtype of KOA, with greater effusion and synovitis but less osteophytosis and cartilage damage. These clinically feasible phenotypes should be confirmed in future studies.
{"title":"Patterns of shared variation in knee ultrasound for osteoarthritis: a machine learning approach","authors":"Sahar Sawani , Liubov Arbeeva , Katherine A. Yates , Carolina Alvarez , Todd A. Schwartz , Serena Savage-Guin , Jordan B. Renner , Catherine J. Bakewell , Minna J. Kohler , Janice Lin , Jonathan Samuels , Amanda E. Nelson","doi":"10.1016/j.ostima.2025.100373","DOIUrl":"10.1016/j.ostima.2025.100373","url":null,"abstract":"<div><h3>Objective</h3><div>To identify phenotypes of knee osteoarthritis (KOA) based on demographic and clinical variables, symptoms, and ultrasound (US) features using a novel machine learning (ML) approach.</div></div><div><h3>Design</h3><div>Participants in the Johnston County Health Study provided demographics, symptomatic and functional assessments, and joint radiographs, which were transformed into the clinical data block. Standardized knee US were obtained, and US features composed the second data block. The Angle-based Joint and Individual Variation Explained (AJIVE) algorithm was used to identify shared and individual modes of variation. We focused on shared structure to explore how US features and non-US clinical data varied together overall, and in the subset with radiographic KOA (rKOA).</div></div><div><h3>Results</h3><div>This analysis included 861 participants (mean age 55 years, mean BMI 33 kg/m<sup>2</sup>); 335 (39 %) had rKOA. AJIVE identified two components of shared variation (subgroup and SC2). SC1 associated osteophytes and cartilage damage on US with higher BMI, older age, and worse symptoms and outcome scores. SC2 correlated effusion and synovitis but less cartilage damage on US, with better physical function and lower BMI. A similar pattern was seen in those with rKOA.</div></div><div><h3>Conclusions</h3><div>We identified two shared directions of variation that may represent distinct phenotypes of KOA. The first is consistent with prior studies linking osteophytes and cartilage damage to worse symptoms and function. The second may represent an inflammatory subtype of KOA, with greater effusion and synovitis but less osteophytosis and cartilage damage. These clinically feasible phenotypes should be confirmed in future studies.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 4","pages":"Article 100373"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145234303","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01DOI: 10.1016/j.ostima.2025.100384
Kaitlin G. Sofko , Ibukunoluwa O. Elebute , Lumeng Cui , Natasha M. Bzowey , Marianne S. Black , Emily J. McWalter
Objective
The purpose of this study is to assess the repeatability of focal changes in T2 relaxation time of knee articular cartilage with load and over time.
Design
A short-term repeatability study was conducted in five healthy participants. Images were acquired of the knee in an unloaded position and in loaded flexion with a custom, quantitative Double Echo Steady State (qDESS) MRI sequence on a 3T scanner. The protocol was carried out three times within a one-week period. T2 relaxation maps of the tibial and femoral articular cartilage were created and focal areas of change were identified using a cluster-based analysis approach; the outcome measure was defined as the percentage area covered by a cluster of pixels that change with load or over time. Average T2 relaxation time within anatomical regions was also calculated. Repeatability of the cluster-based and regional approach was described as the root mean square standard deviation (SDrms) of the trials.
Results
The SDrms of the percentage area of the entire cartilage surface covered by clusters when the knees were loaded was <9.5 %. The repeatability of the percentage area of the entire cartilage surface covered by clusters over time was <4.5 % for the unloaded knees and 7.4 % for the loaded knees. For the regional analysis, the average SDrms of the entire plate was <3.0 ms.
Conclusion
Cluster analysis provides important information on focal changes in cartilage with the application of load and over time, but at the cost of repeatability compared to regional approaches.
{"title":"Repeatability of focal changes in knee cartilage T2 relaxation times with load and time","authors":"Kaitlin G. Sofko , Ibukunoluwa O. Elebute , Lumeng Cui , Natasha M. Bzowey , Marianne S. Black , Emily J. McWalter","doi":"10.1016/j.ostima.2025.100384","DOIUrl":"10.1016/j.ostima.2025.100384","url":null,"abstract":"<div><h3>Objective</h3><div>The purpose of this study is to assess the repeatability of focal changes in T<sub>2</sub> relaxation time of knee articular cartilage with load and over time.</div></div><div><h3>Design</h3><div>A short-term repeatability study was conducted in five healthy participants. Images were acquired of the knee in an unloaded position and in loaded flexion with a custom, quantitative Double Echo Steady State (qDESS) MRI sequence on a 3T scanner. The protocol was carried out three times within a one-week period. T<sub>2</sub> relaxation maps of the tibial and femoral articular cartilage were created and focal areas of change were identified using a cluster-based analysis approach; the outcome measure was defined as the percentage area covered by a cluster of pixels that change with load or over time. Average T<sub>2</sub> relaxation time within anatomical regions was also calculated. Repeatability of the cluster-based and regional approach was described as the root mean square standard deviation (SDrms) of the trials.</div></div><div><h3>Results</h3><div>The SDrms of the percentage area of the entire cartilage surface covered by clusters when the knees were loaded was <9.5 %. The repeatability of the percentage area of the entire cartilage surface covered by clusters over time was <4.5 % for the unloaded knees and 7.4 % for the loaded knees. For the regional analysis, the average SDrms of the entire plate was <3.0 ms.</div></div><div><h3>Conclusion</h3><div>Cluster analysis provides important information on focal changes in cartilage with the application of load and over time, but at the cost of repeatability compared to regional approaches.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 4","pages":"Article 100384"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145712499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01DOI: 10.1016/j.ostima.2025.100376
Tijmen A. van Zadelhoff , Rianne A. van der Heijden , Sita M.A. Bierma-Zeinstra , P. Koen Bos , Edwin H.G. Oei
This paper summarizes the current evidence on genicular artery embolization (GAE) for the treatment of knee osteoarthritis (OA). The goal of this minimally invasive treatment is to reduce synovitis by embolizing peri‑genicular neovascularization and subsequently alleviate pain. Multiple uncontrolled case series have generally demonstrated a promising efficacy of GAE with substantial, lasting pain reduction and improved function. However, these studies lack control groups, making it difficult to distinguish between treatment effect and placebo effect. Three sham-controlled randomized clinical trials (RCTs) have been published to date, with varying methodologies. While the first reported positive results, the most recent two RCTs reported no significant effect of GAE compared to a sham treatment. Moreover, systematic reviews have generally supported the efficacy of GAE but did not include the two most recent RCTs. Given the lack of robust evidence from updated systematic reviews including the most recent published studies, the growing clinical adoption of GAE is not justified and, in our opinion, premature.
{"title":"Perspective: Genicular artery embolization for knee osteoarthritis - When the hype doesn’t match the evidence","authors":"Tijmen A. van Zadelhoff , Rianne A. van der Heijden , Sita M.A. Bierma-Zeinstra , P. Koen Bos , Edwin H.G. Oei","doi":"10.1016/j.ostima.2025.100376","DOIUrl":"10.1016/j.ostima.2025.100376","url":null,"abstract":"<div><div>This paper summarizes the current evidence on genicular artery embolization (GAE) for the treatment of knee osteoarthritis (OA). The goal of this minimally invasive treatment is to reduce synovitis by embolizing peri‑genicular neovascularization and subsequently alleviate pain. Multiple uncontrolled case series have generally demonstrated a promising efficacy of GAE with substantial, lasting pain reduction and improved function. However, these studies lack control groups, making it difficult to distinguish between treatment effect and placebo effect. Three sham-controlled randomized clinical trials (RCTs) have been published to date, with varying methodologies. While the first reported positive results, the most recent two RCTs reported no significant effect of GAE compared to a sham treatment. Moreover, systematic reviews have generally supported the efficacy of GAE but did not include the two most recent RCTs. Given the lack of robust evidence from updated systematic reviews including the most recent published studies, the growing clinical adoption of GAE is not justified and, in our opinion, premature.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 4","pages":"Article 100376"},"PeriodicalIF":0.0,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145712501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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