Pub Date : 2025-01-01Epub Date: 2025-07-02DOI: 10.1016/j.ostima.2025.100333
Z. Zhou , X. He , Y. Hu , H.A. Khan , F. Liu , M. Jarraya
<div><h3>INTRODUCTION</h3><div>Manual assessment of meniscus extrusion (ME) in magnetic resonance (MR) images is time-consuming and prone to variability, limiting efficiency in clinical and research settings. While deep learning methods have shown promise in MR image segmentation, their reliance on task-specific training and large annotated datasets limits scalability and adaptability.</div></div><div><h3>OBJECTIVE</h3><div>Building upon our previously developed AI foundation model, we aim to establish a fully automated pipeline for quantifying ME in knee MRI with our model training and eliminate the need for large annotated datasets.</div></div><div><h3>METHODS</h3><div>By providing a support set including a minimal number of segmentation examples, the AI Foundation Model enables accurate segmentation of knee anatomy and reliable ME measurement in a training-free, few-shot manner. In the study, we analyzed 3T MR images acquired using either T2-weighted or proton density MR sequences from 10 patients with mild osteoarthritis. Manual segmentations of femur, tibia, medial, and lateral menisci were performed by experts. Two patients, one with T2-weighted and one with proton density images, were randomly selected to build the support set. The remaining 8 patients comprised the testing set, which was used for both automated segmentation and model evaluation. Segmentation performance was assessed using the Dice Coefficient. For ME evaluation, an experienced radiologist manually identified the slice containing the tibial spine and measured extrusion as the reference. Automated ME measurement was computed from the segmentation by detecting the femoral condyle and tibial plateau edge, then measuring the distance from the most medial point of the medial meniscus to a reference line connecting the femoral condyle and tibial plateau edge.</div></div><div><h3>RESULTS</h3><div>The average Dice Coefficient was 94.07 ± 3.97% for the femur, 97.09 ± 0.93% for the tibia, 82.91 ± 6.72% for the medial meniscus, and 85.49 ± 5.24% for the lateral meniscus. ME measurements predicted by the model were also compared with ground truth values. The human measured ME was 4.26 ± 1.46 mm, while the model-predicted ME was 4.18 ± 1.16 mm.</div></div><div><h3>CONCLUSION</h3><div>This study demonstrates that the foundation model enables reliable and fully automated quantification of meniscus extrusion from knee MR images without requiring training or large annotated datasets. With only two support examples, the model achieved accurate segmentation and ME measurement across eight testing subjects, underscoring its efficiency and strong generalization. Its consistent performance across key anatomical structures highlights its potential for expert-level evaluation in both clinical and research settings with minimal manual effort. Further work will explore semi-automated expansion of the support set and extension to diverse MRI protocols and osteoarthritis severities, and validation on
{"title":"AUTOMATED QUANTIFICATION OF MENISCUS EXTRUSION IN MRI VIA AI FOUNDATION MODEL: PROOF OF CONCEPT USING A TRAINING-FREE FEW-SHOT SEGMENTATION APPROACH","authors":"Z. Zhou , X. He , Y. Hu , H.A. Khan , F. Liu , M. Jarraya","doi":"10.1016/j.ostima.2025.100333","DOIUrl":"10.1016/j.ostima.2025.100333","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Manual assessment of meniscus extrusion (ME) in magnetic resonance (MR) images is time-consuming and prone to variability, limiting efficiency in clinical and research settings. While deep learning methods have shown promise in MR image segmentation, their reliance on task-specific training and large annotated datasets limits scalability and adaptability.</div></div><div><h3>OBJECTIVE</h3><div>Building upon our previously developed AI foundation model, we aim to establish a fully automated pipeline for quantifying ME in knee MRI with our model training and eliminate the need for large annotated datasets.</div></div><div><h3>METHODS</h3><div>By providing a support set including a minimal number of segmentation examples, the AI Foundation Model enables accurate segmentation of knee anatomy and reliable ME measurement in a training-free, few-shot manner. In the study, we analyzed 3T MR images acquired using either T2-weighted or proton density MR sequences from 10 patients with mild osteoarthritis. Manual segmentations of femur, tibia, medial, and lateral menisci were performed by experts. Two patients, one with T2-weighted and one with proton density images, were randomly selected to build the support set. The remaining 8 patients comprised the testing set, which was used for both automated segmentation and model evaluation. Segmentation performance was assessed using the Dice Coefficient. For ME evaluation, an experienced radiologist manually identified the slice containing the tibial spine and measured extrusion as the reference. Automated ME measurement was computed from the segmentation by detecting the femoral condyle and tibial plateau edge, then measuring the distance from the most medial point of the medial meniscus to a reference line connecting the femoral condyle and tibial plateau edge.</div></div><div><h3>RESULTS</h3><div>The average Dice Coefficient was 94.07 ± 3.97% for the femur, 97.09 ± 0.93% for the tibia, 82.91 ± 6.72% for the medial meniscus, and 85.49 ± 5.24% for the lateral meniscus. ME measurements predicted by the model were also compared with ground truth values. The human measured ME was 4.26 ± 1.46 mm, while the model-predicted ME was 4.18 ± 1.16 mm.</div></div><div><h3>CONCLUSION</h3><div>This study demonstrates that the foundation model enables reliable and fully automated quantification of meniscus extrusion from knee MR images without requiring training or large annotated datasets. With only two support examples, the model achieved accurate segmentation and ME measurement across eight testing subjects, underscoring its efficiency and strong generalization. Its consistent performance across key anatomical structures highlights its potential for expert-level evaluation in both clinical and research settings with minimal manual effort. Further work will explore semi-automated expansion of the support set and extension to diverse MRI protocols and osteoarthritis severities, and validation on","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100333"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524261","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 : 2025-01-01Epub Date: 2025-07-02DOI: 10.1016/j.ostima.2025.100290
J.T. Harvey , T.E. McAlindon , J. Baek , J. MacKay , M. Zhang , G.H. Lo , S.-H. Liu , C.B. Eaton , M.S. Harkey , J.C. Patarini , J.B. Driban
<div><h3>INTRODUCTION</h3><div>Meniscal degeneration predisposes knees without radiographic OA to develop a future meniscal tear and an accelerated onset and progression of OA. Understanding the relationship between meniscal degeneration and OA-related biomarkers in knees without radiographic OA is essential for improving early detection, monitoring disease progression, and developing intervention strategies to prevent or slow the progression of this debilitating condition.</div></div><div><h3>OBJECTIVE</h3><div>To explore the relationship between meniscal degeneration (intrameniscal signal alteration without a tear) and future OA pathology measured by composite scores based on MRI: disease activity (BM lesion and effusion-synovitis volumes) and cumulative damage (articular cartilage damage).</div></div><div><h3>METHODS</h3><div>Our sample included 225 participants from the OAI with intact menisci (defined as normal or meniscal degeneration without tear) on MRI and no radiographic knee OA at baseline. There were 110 participants with normal menisci (77% Female, 55 [SD 7] average years of age) and 115 with meniscal degeneration (60% Female, 61 [SD 9] average years of age). We used longitudinal MRIs from an existing study to calculate disease activity and cumulative damage. Negative values represent milder disease activity or cumulative damage than the average of a reference sample, among whom 93% had moderate-severe radiographic knee osteoarthritis (KLG = 3 or 4), and the average WOMAC knee pain score was 5.0 (SD=3.6). MR images were collected at each OAI site using Siemens 3.0 Tesla Trio MR systems and knee coils. Acquisitions included a sagittal IM fat-suppressed sequence (field of view=160mm, slice thickness=3mm, skip=0mm, flip angle=180 degrees, echo time=30ms, recovery time=3200ms, 313 × 448 matrix, x-resolution=0.357mm, y-resolution=0.357mm), which was used to measure BML and effusion-synovitis volumes. Cartilage damage was quantified using a 3D DESS sequence: field of view=140mm, slice thickness=0.7mm, skip=0mm, flip angle=25 degrees, echo time=4.7ms, recovery time=16.3ms, 307 × 384 matrix, x-resolution=0.365mm, y-resolution=0.365mm. We used robust regression models with M estimation and Huber weights to assess the association between baseline meniscal degeneration (exposure) and disease activity or cumulative damage at baseline and four annual follow-up visits (outcomes), adjusting for gender, race, age, static alignment, and body mass index.</div></div><div><h3>RESULTS</h3><div>Knees with meniscal degeneration were more likely to have, on average, 0.21 greater disease activity at 12 months than knees with normal menisci (parameter estimate=0.21, 95% confidence interval [CI]=0.09, 0.33); this association persisted over time. The association between meniscal degeneration and cumulative damage only became statistically significant at the 48-month visit (parameter estimate=0.74, 95% CI=0.18, 1.31).</div></div><div><h3>CONCLUSION</h3><div>This
{"title":"FROM MENISCAL DEGENERATION TO OSTEOARTHRITIS: TRACKING EARLY DISEASE PROGRESSION WITH MRI-BASED COMPOSITE SCORES: DATA FROM THE OSTEOARTHRITIS INITIATIVE","authors":"J.T. Harvey , T.E. McAlindon , J. Baek , J. MacKay , M. Zhang , G.H. Lo , S.-H. Liu , C.B. Eaton , M.S. Harkey , J.C. Patarini , J.B. Driban","doi":"10.1016/j.ostima.2025.100290","DOIUrl":"10.1016/j.ostima.2025.100290","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Meniscal degeneration predisposes knees without radiographic OA to develop a future meniscal tear and an accelerated onset and progression of OA. Understanding the relationship between meniscal degeneration and OA-related biomarkers in knees without radiographic OA is essential for improving early detection, monitoring disease progression, and developing intervention strategies to prevent or slow the progression of this debilitating condition.</div></div><div><h3>OBJECTIVE</h3><div>To explore the relationship between meniscal degeneration (intrameniscal signal alteration without a tear) and future OA pathology measured by composite scores based on MRI: disease activity (BM lesion and effusion-synovitis volumes) and cumulative damage (articular cartilage damage).</div></div><div><h3>METHODS</h3><div>Our sample included 225 participants from the OAI with intact menisci (defined as normal or meniscal degeneration without tear) on MRI and no radiographic knee OA at baseline. There were 110 participants with normal menisci (77% Female, 55 [SD 7] average years of age) and 115 with meniscal degeneration (60% Female, 61 [SD 9] average years of age). We used longitudinal MRIs from an existing study to calculate disease activity and cumulative damage. Negative values represent milder disease activity or cumulative damage than the average of a reference sample, among whom 93% had moderate-severe radiographic knee osteoarthritis (KLG = 3 or 4), and the average WOMAC knee pain score was 5.0 (SD=3.6). MR images were collected at each OAI site using Siemens 3.0 Tesla Trio MR systems and knee coils. Acquisitions included a sagittal IM fat-suppressed sequence (field of view=160mm, slice thickness=3mm, skip=0mm, flip angle=180 degrees, echo time=30ms, recovery time=3200ms, 313 × 448 matrix, x-resolution=0.357mm, y-resolution=0.357mm), which was used to measure BML and effusion-synovitis volumes. Cartilage damage was quantified using a 3D DESS sequence: field of view=140mm, slice thickness=0.7mm, skip=0mm, flip angle=25 degrees, echo time=4.7ms, recovery time=16.3ms, 307 × 384 matrix, x-resolution=0.365mm, y-resolution=0.365mm. We used robust regression models with M estimation and Huber weights to assess the association between baseline meniscal degeneration (exposure) and disease activity or cumulative damage at baseline and four annual follow-up visits (outcomes), adjusting for gender, race, age, static alignment, and body mass index.</div></div><div><h3>RESULTS</h3><div>Knees with meniscal degeneration were more likely to have, on average, 0.21 greater disease activity at 12 months than knees with normal menisci (parameter estimate=0.21, 95% confidence interval [CI]=0.09, 0.33); this association persisted over time. The association between meniscal degeneration and cumulative damage only became statistically significant at the 48-month visit (parameter estimate=0.74, 95% CI=0.18, 1.31).</div></div><div><h3>CONCLUSION</h3><div>This","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100290"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144522430","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 : 2025-01-01Epub Date: 2025-07-02DOI: 10.1016/j.ostima.2025.100281
C.B. Burson-Thomas
<div><h3>INTRODUCTION</h3><div>The geometry of the same joint varies substantially between people. Typical variation in merely how conforming the two subchondral bone surfaces are can increase the peak compressive stress on the articular cartilage by as much as the additional loading from becoming obese will. The mechanical environment of joint tissues is considered to play a central role in OA development. Quantifying joint geometry using repeatable, reliable, and accessible metrics supports better understanding of the relative importance (or unimportance) of this source of variability between people on their individual OA risk and this factor’s role at a population level.</div></div><div><h3>OBJECTIVE</h3><div>Previous methods of quantifying joint congruence (a measure of how conforming two surfaces are) have required detailed mathematical descriptions of the articulating surfaces and their relative position. We have developed a new method of measuring joint congruence that works directly from the 3D segmented point clouds. This has been applied to a joint in the thumb.</div></div><div><h3>METHODS</h3><div>The first step of the new methodology involves performing a Finite Element (FE) simulation of an elastic layer compressed between each set of segmented bones (Figure 1). The results of this are then interpreted using the elastic foundation model (Figure 2), enabling an equivalent, but far simpler, contact geometry to be identified. This far simpler equivalent geometry takes the form of a sphere contacting a flat surface. The identified congruence metric is the radius of this sphere, the ‘equivalent radius’, which produces an equivalent contact to that identified in each FE simulation. The minimal JSW (in this joint position) can also be estimated from the FE simulations. The new method has been applied to a small sample (n = 10) of healthy instances (5M:5F, mean age 31yrs) of the thumb metacarpophalangeal (MCP) joint (IRAS Ethics Ref: 14/LO/1059). Each participant’s right hand was CT scanned with near-isotropic voxel size (0.293 × 0.293 × 0.312 mm) and the bones segmented using a greyscale threshold.</div></div><div><h3>RESULTS</h3><div>To enable an appropriate reduction of the complex geometry represented in the 3D points clouds to one number (the radius of an equivalent ‘ball on flat’), this single parameter must continue to capture the joint’s geometry as the contact area increases. For all thumb MCP geometries tested, the force-displacement response of the elastic layer could be well-described by an identified equivalent radius, unique to that particular joint (Figure 3). The thumb MCPs had a mean equivalent radius of 17.9 mm (SD = 10.6 mm) and mean minimal JSW of 0.86 mm (SD = 0.24 mm). No relationship between congruence and joint space width was observed (Figure 4).</div></div><div><h3>CONCLUSION</h3><div>The new method can perform an efficient quantification of congruence, reducing two 3D point clouds to a single parameter. However, fu
{"title":"QUANTIFYING JOINT GEOMETRY IN HUMAN HANDS FROM IMAGING DATA","authors":"C.B. Burson-Thomas","doi":"10.1016/j.ostima.2025.100281","DOIUrl":"10.1016/j.ostima.2025.100281","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>The geometry of the same joint varies substantially between people. Typical variation in merely how conforming the two subchondral bone surfaces are can increase the peak compressive stress on the articular cartilage by as much as the additional loading from becoming obese will. The mechanical environment of joint tissues is considered to play a central role in OA development. Quantifying joint geometry using repeatable, reliable, and accessible metrics supports better understanding of the relative importance (or unimportance) of this source of variability between people on their individual OA risk and this factor’s role at a population level.</div></div><div><h3>OBJECTIVE</h3><div>Previous methods of quantifying joint congruence (a measure of how conforming two surfaces are) have required detailed mathematical descriptions of the articulating surfaces and their relative position. We have developed a new method of measuring joint congruence that works directly from the 3D segmented point clouds. This has been applied to a joint in the thumb.</div></div><div><h3>METHODS</h3><div>The first step of the new methodology involves performing a Finite Element (FE) simulation of an elastic layer compressed between each set of segmented bones (Figure 1). The results of this are then interpreted using the elastic foundation model (Figure 2), enabling an equivalent, but far simpler, contact geometry to be identified. This far simpler equivalent geometry takes the form of a sphere contacting a flat surface. The identified congruence metric is the radius of this sphere, the ‘equivalent radius’, which produces an equivalent contact to that identified in each FE simulation. The minimal JSW (in this joint position) can also be estimated from the FE simulations. The new method has been applied to a small sample (n = 10) of healthy instances (5M:5F, mean age 31yrs) of the thumb metacarpophalangeal (MCP) joint (IRAS Ethics Ref: 14/LO/1059). Each participant’s right hand was CT scanned with near-isotropic voxel size (0.293 × 0.293 × 0.312 mm) and the bones segmented using a greyscale threshold.</div></div><div><h3>RESULTS</h3><div>To enable an appropriate reduction of the complex geometry represented in the 3D points clouds to one number (the radius of an equivalent ‘ball on flat’), this single parameter must continue to capture the joint’s geometry as the contact area increases. For all thumb MCP geometries tested, the force-displacement response of the elastic layer could be well-described by an identified equivalent radius, unique to that particular joint (Figure 3). The thumb MCPs had a mean equivalent radius of 17.9 mm (SD = 10.6 mm) and mean minimal JSW of 0.86 mm (SD = 0.24 mm). No relationship between congruence and joint space width was observed (Figure 4).</div></div><div><h3>CONCLUSION</h3><div>The new method can perform an efficient quantification of congruence, reducing two 3D point clouds to a single parameter. However, fu","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100281"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523634","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 : 2025-01-01Epub Date: 2025-07-02DOI: 10.1016/j.ostima.2025.100345
S. Li , N.A. Segal , I. Tolstykh , M.C. Nevitt , T.D. Turmezei
INTRODUCTION
The B-score is a statistical score derived from non-weight-bearing MRI to assess femoral bone shape and its relationship with knee OA. However, CT scans may offer a more reliable and robust evaluations of bone shape, as they not only provide clearer differentiation between bone and soft tissue but also eliminate distortion artefact that can occur with MRI.
OBJECTIVE
To investigate a new “C-score” for femoral bone shape derived from CT as a predictive imaging biomarker for worsening knee pain in men and women with or at risk for knee osteoarthritis.
METHODS
This study included 649 knees from 389 participants (219 women) with a mean±SD age of 63.8±9.6 years and BMI of 28.5±5.0 kg/m². C-scores were calculated from baseline weight-bearing CT (WBCT) imaging of the knee joint: 0.37 mm voxels, FOV 30 × 20 cm, 120 kVp, 5.0 mA on a LineUp scanner, Curvebeam LLC, Warrington, PA. All distal femurs were segmented using Stradview to produce a surface mesh. A canonical distal femur mesh was registered using wxRegSurf to each individual femur to build the study population shape model. Each knee's C-score was derived from the distance along the vector for femur shape between the average KL0/1 and KL2/3/4 shapes from the study population using a custom script in MATLAB. A single unit of the C-score was standardized as 1SD along this vector for the KL0/1 population (Figure 1). Generalized estimating equations adjusted for age, sex, BMI and presence of up to 2 knees per participant were used to assess associations between baseline C-score and 2-year minimally clinically important worsening (MCIW) of the Western Ontario McMaster’s University Osteoarthritis Scale (WOMAC) pain subscore (2 points). MCIW is defined as the smallest difference on a pain scale that either patients perceive as worsening or requires change in treatment.
RESULTS
186 knees demonstrated pain worsening (32.71% women and 23.2% men). 98 knees had MCIW of pain (19.0% women and 9.8% men). C-scores ranged from -2.64 to +3.34 in women and -3.96 to +2.83 in men, with mean±SD values of 0.16±1.06 and -0.52±1.01 respectively (p-value for difference between sexes p=0.0003). Women without MCIW pain had a mean C-score of +0.31, while those with worsening pain had a mean C-score of +0.72. Men had mean C-scores of -0.03 and -0.01, respectively. In fully adjusted models, baseline C-score predicted 2-year MCIW pain (OR: 1.27, 95% CI: 1.00–1.62, p=0.047). In sex-stratified models, the odds ratios for 2-year MCIW pain in women and men were 1.49 (95% CI: 1.10–2.01, p=0.0159) and 1.01 (95% CI: 0.70–1.47, p=0.95), respectively.
CONCLUSION
Higher C-scores in women were significantly associated with worsening knee pain over 2 years, suggesting the C-score as a potential predictive biomarker for knee pain progression.
{"title":"BASELINE C-SCORE ON WEIGHT-BEARING CT PREDICTS 2-YEAR WORSENING OF KNEE PAIN IN WOMEN","authors":"S. Li , N.A. Segal , I. Tolstykh , M.C. Nevitt , T.D. Turmezei","doi":"10.1016/j.ostima.2025.100345","DOIUrl":"10.1016/j.ostima.2025.100345","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>The B-score is a statistical score derived from non-weight-bearing MRI to assess femoral bone shape and its relationship with knee OA. However, CT scans may offer a more reliable and robust evaluations of bone shape, as they not only provide clearer differentiation between bone and soft tissue but also eliminate distortion artefact that can occur with MRI.</div></div><div><h3>OBJECTIVE</h3><div>To investigate a new “C-score” for femoral bone shape derived from CT as a predictive imaging biomarker for worsening knee pain in men and women with or at risk for knee osteoarthritis.</div></div><div><h3>METHODS</h3><div>This study included 649 knees from 389 participants (219 women) with a mean±SD age of 63.8±9.6 years and BMI of 28.5±5.0 kg/m². C-scores were calculated from baseline weight-bearing CT (WBCT) imaging of the knee joint: 0.37 mm voxels, FOV 30 × 20 cm, 120 kVp, 5.0 mA on a LineUp scanner, Curvebeam LLC, Warrington, PA. All distal femurs were segmented using Stradview to produce a surface mesh. A canonical distal femur mesh was registered using wxRegSurf to each individual femur to build the study population shape model. Each knee's C-score was derived from the distance along the vector for femur shape between the average KL0/1 and KL2/3/4 shapes from the study population using a custom script in MATLAB. A single unit of the C-score was standardized as 1SD along this vector for the KL0/1 population (Figure 1). Generalized estimating equations adjusted for age, sex, BMI and presence of up to 2 knees per participant were used to assess associations between baseline C-score and 2-year minimally clinically important worsening (MCIW) of the Western Ontario McMaster’s University Osteoarthritis Scale (WOMAC) pain subscore (2 points). MCIW is defined as the smallest difference on a pain scale that either patients perceive as worsening or requires change in treatment.</div></div><div><h3>RESULTS</h3><div>186 knees demonstrated pain worsening (32.71% women and 23.2% men). 98 knees had MCIW of pain (19.0% women and 9.8% men). C-scores ranged from -2.64 to +3.34 in women and -3.96 to +2.83 in men, with mean±SD values of 0.16±1.06 and -0.52±1.01 respectively (p-value for difference between sexes p=0.0003). Women without MCIW pain had a mean C-score of +0.31, while those with worsening pain had a mean C-score of +0.72. Men had mean C-scores of -0.03 and -0.01, respectively. In fully adjusted models, baseline C-score predicted 2-year MCIW pain (OR: 1.27, 95% CI: 1.00–1.62, p=0.047). In sex-stratified models, the odds ratios for 2-year MCIW pain in women and men were 1.49 (95% CI: 1.10–2.01, p=0.0159) and 1.01 (95% CI: 0.70–1.47, p=0.95), respectively.</div></div><div><h3>CONCLUSION</h3><div>Higher C-scores in women were significantly associated with worsening knee pain over 2 years, suggesting the C-score as a potential predictive biomarker for knee pain progression.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100345"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523606","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 : 2025-01-01Epub Date: 2025-07-02DOI: 10.1016/j.ostima.2025.100331
W. Wirth , F. Eckstein
<div><h3>INTRODUCTION</h3><div>Location-independent measurements of cartilage thinning and thickening were shown to be more sensitive to differences in longitudinal change between groups than location-based measures [1,2]. They remove the link between the magnitude and direction of the change and its location, and hence are sensitive to local changes in the joint, independent of where they occur. Location-independent measures of T2 lengthening and shortening computed from 16 femorotibial subregions have been previously applied to a model of early OA. The model compared 3y T2 change in KLG 0 knees with contralateral (CL) joint space narrowing (JSN) vs that in KLG 0 knees with CL KLG 0 (controls) [3]. In this model, location-independent measures were found to provide similar discrimination between these two groups as location-based measures. However, location-independent measures obtained across all individual voxels in the joint (instead of subregions) have been previously suggested to provide more detailed insights into OA-related cartilage thickness changes [4], but no study previously evaluated the sensitivity of such voxel-based shortening and lengthening scores to differences in change of laminar T2.</div></div><div><h3>OBJECTIVE</h3><div>To compare the sensitivity of voxel-based location-independent lengthening and shortening T2 scores to between-group differences in longitudinal change vs. the previously established technique of subregion-based location-independent and location-based measures in the above early OA model.</div></div><div><h3>METHODS</h3><div>Multi-echo spin-echo (MESE) MRIs were acquired at year 1 and 4 in the OAI (3T Trio, Siemens). We studied 39 KLG 0 knees with CL JSN, and 39 matched controls (criteria: same sex pain frequency, similar age (±5y) and BMI (±5kg/m<sup>2</sup>)) with bilateral KLG 0 [2]. Segmentation of the 4 femorotibial cartilages (medial/lateral tibia: MT/LT and central medial/lateral femoral condyle: cMF/cLF) was performed manually by experienced readers. Laminar T2 was computed for each segmented cartilage voxel and classified as deep or superficial, based on the distance to the cartilage surfaces. Location-based and subregion-based location-independent measures were obtained as described previously [2]. Voxel-based location-independent changes in laminar T2 were derived, summarizing the negative/positive changes across all voxels, for each of the femorotibial cartilages using the voxel-based approach (Fig. 1) These were then summarized across the entire femorotibial joint (FTJ). Location-based, subregion-based location independent, and voxel-based location-independent laminar T2 change was compared between the CL JSN vs. control knees using Cohen's D as a measure of effect size with 95% confidence intervals obtained using boot-strapping.</div></div><div><h3>RESULTS</h3><div>In the deep layer, location-based longitudinal change in femorotibial T2 revealed a Cohen’s D between both groups of 0.37 [0.04, 0.
{"title":"CAN REGISTRATION-BASED LOCATION-INDEPENDENT MEASUREMENT INCREASE THE SENSITIVITY TO BETWEEN-GROUP DIFFERENCES IN LONGITUDINAL CHANGE OF LAMINAR CARTILAGE T2?","authors":"W. Wirth , F. Eckstein","doi":"10.1016/j.ostima.2025.100331","DOIUrl":"10.1016/j.ostima.2025.100331","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Location-independent measurements of cartilage thinning and thickening were shown to be more sensitive to differences in longitudinal change between groups than location-based measures [1,2]. They remove the link between the magnitude and direction of the change and its location, and hence are sensitive to local changes in the joint, independent of where they occur. Location-independent measures of T2 lengthening and shortening computed from 16 femorotibial subregions have been previously applied to a model of early OA. The model compared 3y T2 change in KLG 0 knees with contralateral (CL) joint space narrowing (JSN) vs that in KLG 0 knees with CL KLG 0 (controls) [3]. In this model, location-independent measures were found to provide similar discrimination between these two groups as location-based measures. However, location-independent measures obtained across all individual voxels in the joint (instead of subregions) have been previously suggested to provide more detailed insights into OA-related cartilage thickness changes [4], but no study previously evaluated the sensitivity of such voxel-based shortening and lengthening scores to differences in change of laminar T2.</div></div><div><h3>OBJECTIVE</h3><div>To compare the sensitivity of voxel-based location-independent lengthening and shortening T2 scores to between-group differences in longitudinal change vs. the previously established technique of subregion-based location-independent and location-based measures in the above early OA model.</div></div><div><h3>METHODS</h3><div>Multi-echo spin-echo (MESE) MRIs were acquired at year 1 and 4 in the OAI (3T Trio, Siemens). We studied 39 KLG 0 knees with CL JSN, and 39 matched controls (criteria: same sex pain frequency, similar age (±5y) and BMI (±5kg/m<sup>2</sup>)) with bilateral KLG 0 [2]. Segmentation of the 4 femorotibial cartilages (medial/lateral tibia: MT/LT and central medial/lateral femoral condyle: cMF/cLF) was performed manually by experienced readers. Laminar T2 was computed for each segmented cartilage voxel and classified as deep or superficial, based on the distance to the cartilage surfaces. Location-based and subregion-based location-independent measures were obtained as described previously [2]. Voxel-based location-independent changes in laminar T2 were derived, summarizing the negative/positive changes across all voxels, for each of the femorotibial cartilages using the voxel-based approach (Fig. 1) These were then summarized across the entire femorotibial joint (FTJ). Location-based, subregion-based location independent, and voxel-based location-independent laminar T2 change was compared between the CL JSN vs. control knees using Cohen's D as a measure of effect size with 95% confidence intervals obtained using boot-strapping.</div></div><div><h3>RESULTS</h3><div>In the deep layer, location-based longitudinal change in femorotibial T2 revealed a Cohen’s D between both groups of 0.37 [0.04, 0.","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100331"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523433","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}
In knee OA, radiographic JSW is used as a surrogate for MRI-measured cartilage thickness, though they often do not correlate well. Variations in positioning between radiography (weight-bearing semi-flexion) and MRI (non-weight-bearing extension) may contribute to discrepancies.
OBJECTIVE
This study aimed to evaluate differences in 3D JSW and cartilage thickness distribution between these positions in knee OA patients.
METHODS
21 symptomatic knee OA patients (KLG 2/3) were included. Exclusion criteria included prior knee surgery, MRI ineligibility, inability to stand unassisted for 15 minutes, or knee width > 15 cm (knee coil limit). A knee MRI protocol was performed using a 0.25T weight-bearing MRI system (G-scan Brio, Esaote). A coronal 3D dual-echo SSFP sequence (SHARC) was acquired to obtain images with an isotropic resolution of 0.66mm in both extended and flexed knee positions under weight-bearing conditions by rotating the system to 81°. Both scans were repeated under non-weight-bearing conditions by rotating the system to a horizontal position (0°). Knee flexion angles were measured, and the femur and tibia bones were segmented in 3D Slicer. 3D models were exported to Stradview to measure the tibia-femur distance at each vertex as a measure of JSW. The models and data were registered to canonical surfaces in wxRegSurf and further analyzed in MATLAB using the Surfstat package for statistical parametric mapping to derive p-values corrected for multiple vertex-wise comparisons.
RESULTS
The average knee angles of the 21 patients were 7.4±3.7° (extended) and 19.1±5.5° (flexed). The average JSW ranged from 3.1 mm to 14.7 mm across patients (Figure 1). A significantly smaller JSW for weight-bearing vs non-weight-bearing conditions, particularly in the outer medial and posterior lateral tibia for extended positions, and in the posterior medial tibia for flexed positions, was seen (Figure 2). Flexion increased the JSW in the anterior tibia and decreased it in the posterior tibia, particularly laterally in weight-bearing positions.
CONCLUSION
JSW distribution in knee OA patients varies significantly depending on both weight-bearing and knee flexion angle, and radiographic JSW measurements may not accurately reflect the joint space in non-weight-bearing positions, such as those used in MRI, especially in the lateral compartment. Currently ongoing cartilage analyses will indicate to which extent these JSW variations are attributable to changes in cartilage thickness or meniscal positioning.
{"title":"THE INFLUENCE OF WEIGHT-BEARING AND FLEXION ON 3D JOINT SPACE WIDTH IN KNEE OSTEOARTHRITIS","authors":"F.F.J. Simonis , W.M. Brink , F.F. Schröder , W.C. Verra , T.D. Turmezei , S.C. Mastbergen , M.P. Jansen","doi":"10.1016/j.ostima.2025.100320","DOIUrl":"10.1016/j.ostima.2025.100320","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>In knee OA, radiographic JSW is used as a surrogate for MRI-measured cartilage thickness, though they often do not correlate well. Variations in positioning between radiography (weight-bearing semi-flexion) and MRI (non-weight-bearing extension) may contribute to discrepancies.</div></div><div><h3>OBJECTIVE</h3><div>This study aimed to evaluate differences in 3D JSW and cartilage thickness distribution between these positions in knee OA patients.</div></div><div><h3>METHODS</h3><div>21 symptomatic knee OA patients (KLG 2/3) were included. Exclusion criteria included prior knee surgery, MRI ineligibility, inability to stand unassisted for 15 minutes, or knee width > 15 cm (knee coil limit). A knee MRI protocol was performed using a 0.25T weight-bearing MRI system (G-scan Brio, Esaote). A coronal 3D dual-echo SSFP sequence (SHARC) was acquired to obtain images with an isotropic resolution of 0.66mm in both extended and flexed knee positions under weight-bearing conditions by rotating the system to 81°. Both scans were repeated under non-weight-bearing conditions by rotating the system to a horizontal position (0°). Knee flexion angles were measured, and the femur and tibia bones were segmented in 3D Slicer. 3D models were exported to Stradview to measure the tibia-femur distance at each vertex as a measure of JSW. The models and data were registered to canonical surfaces in wxRegSurf and further analyzed in MATLAB using the Surfstat package for statistical parametric mapping to derive p-values corrected for multiple vertex-wise comparisons.</div></div><div><h3>RESULTS</h3><div>The average knee angles of the 21 patients were 7.4±3.7° (extended) and 19.1±5.5° (flexed). The average JSW ranged from 3.1 mm to 14.7 mm across patients (Figure 1). A significantly smaller JSW for weight-bearing vs non-weight-bearing conditions, particularly in the outer medial and posterior lateral tibia for extended positions, and in the posterior medial tibia for flexed positions, was seen (Figure 2). Flexion increased the JSW in the anterior tibia and decreased it in the posterior tibia, particularly laterally in weight-bearing positions.</div></div><div><h3>CONCLUSION</h3><div>JSW distribution in knee OA patients varies significantly depending on both weight-bearing and knee flexion angle, and radiographic JSW measurements may not accurately reflect the joint space in non-weight-bearing positions, such as those used in MRI, especially in the lateral compartment. Currently ongoing cartilage analyses will indicate to which extent these JSW variations are attributable to changes in cartilage thickness or meniscal positioning.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100320"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523455","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 : 2025-01-01Epub Date: 2025-07-02DOI: 10.1016/j.ostima.2025.100298
F. Kogan , K. Stevens , A. Williams , C. Chu
<div><h3>INTRODUCTION</h3><div>Synovitis is a recognized risk factor for post-traumatic osteoarthritis post-ACL reconstruction (ACLR). The reference standard for imaging synovitis is contrast enhanced MRI, but this adds time and cost and may be contraindicated in some patients, which may limit evaluation of this important finding. Recently, several non-contrast MRI methods have shown strong agreement with CE-MRI for semiquantitative assessment of synovitis.</div></div><div><h3>OBJECTIVE</h3><div>To evaluate the feasibility of quantitative double-echo in steady-state (qDESS) as a non-contrast MR technique to detect changes in synovitis in patients pre- and post-ACLR.</div></div><div><h3>METHODS</h3><div>14 males and 4 females (age:27±6 years, BMI:24±3 kg/m<sup>2</sup>) with ACL tears underwent ACLR surgery (mean time from injury to surgery 10±5 weeks) and were scanned on a 3T MR scanner at three timepoints: (1) baseline post ACL tear but before reconstruction, (2) 6-weeks and (3) 6-months after ACLR. At each time point, a 3D qDESS acquisition was performed with parameters: TR/TE1/TE2 = 20.5/6.4/34.6 ms; acquisition resolution = 0.4 × 0.4 × 1.5 mm<sup>3</sup>; 80 slices; Flip Angle = 20. qDESS synovitis hybrid images were created by a weighted subtraction of the 2<sup>nd</sup> echo signal from the 1<sup>st</sup> echo to null signal from joint fluid in order to provide contrast to the synovium. Synovitis was scored in the knee overall and in 4 regional locations by a blinded radiologist on a scale of 0-3 (0 = none to 3 = severe).</div></div><div><h3>RESULTS</h3><div>Figure 1 shows a representative case of qDESS synovitis-weighted hybrid images at the three timepoints and their corresponding scores. Figure 2a shows a table of the % of patients (out of 18) that were scored to have improved or worsened synovitis between baseline and 6-weeks post-ACLR and between 6-weeks and 6-months post-ACLR. Overall, there was a clear trend towards synovitis worsening 6-weeks after ACLR and then improving between 6-weeks and 6-months post-surgery. Furthermore, when the 6-week and 6-month timepoints for each patient were compared directly but blinded to order, an improvement in assessed synovitis was observed in a further 82% of overall impressions that were previously scored as no change in blinded and randomized assessments (Figure 2b). Repeated synovitis scoring assessments showed very strong agreement (Gwets AC2>0.80) in overall and sub-region assessments.</div></div><div><h3>DISCUSSION</h3><div>While ground-truth synovitis measures were not available, the qDESS hybrid method was able to detect both worsening synovitis that is expected after ACLR surgery and improvement in synovitis that is expected during the following 5 months of recovery. The lack of differentiation of synovitis changes between timepoints may partly be attributed to the coarseness of the 4-point semi-quantitative Likert-scale which is based on synovial hypertrophy and nodularity In overall a
{"title":"FEASIBILITY OF NON-CONTRAST MRI TO DETECT CHANGES IN SYNOVITIS AFTER ACL RECONSTRUCTION SURGERY","authors":"F. Kogan , K. Stevens , A. Williams , C. Chu","doi":"10.1016/j.ostima.2025.100298","DOIUrl":"10.1016/j.ostima.2025.100298","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Synovitis is a recognized risk factor for post-traumatic osteoarthritis post-ACL reconstruction (ACLR). The reference standard for imaging synovitis is contrast enhanced MRI, but this adds time and cost and may be contraindicated in some patients, which may limit evaluation of this important finding. Recently, several non-contrast MRI methods have shown strong agreement with CE-MRI for semiquantitative assessment of synovitis.</div></div><div><h3>OBJECTIVE</h3><div>To evaluate the feasibility of quantitative double-echo in steady-state (qDESS) as a non-contrast MR technique to detect changes in synovitis in patients pre- and post-ACLR.</div></div><div><h3>METHODS</h3><div>14 males and 4 females (age:27±6 years, BMI:24±3 kg/m<sup>2</sup>) with ACL tears underwent ACLR surgery (mean time from injury to surgery 10±5 weeks) and were scanned on a 3T MR scanner at three timepoints: (1) baseline post ACL tear but before reconstruction, (2) 6-weeks and (3) 6-months after ACLR. At each time point, a 3D qDESS acquisition was performed with parameters: TR/TE1/TE2 = 20.5/6.4/34.6 ms; acquisition resolution = 0.4 × 0.4 × 1.5 mm<sup>3</sup>; 80 slices; Flip Angle = 20. qDESS synovitis hybrid images were created by a weighted subtraction of the 2<sup>nd</sup> echo signal from the 1<sup>st</sup> echo to null signal from joint fluid in order to provide contrast to the synovium. Synovitis was scored in the knee overall and in 4 regional locations by a blinded radiologist on a scale of 0-3 (0 = none to 3 = severe).</div></div><div><h3>RESULTS</h3><div>Figure 1 shows a representative case of qDESS synovitis-weighted hybrid images at the three timepoints and their corresponding scores. Figure 2a shows a table of the % of patients (out of 18) that were scored to have improved or worsened synovitis between baseline and 6-weeks post-ACLR and between 6-weeks and 6-months post-ACLR. Overall, there was a clear trend towards synovitis worsening 6-weeks after ACLR and then improving between 6-weeks and 6-months post-surgery. Furthermore, when the 6-week and 6-month timepoints for each patient were compared directly but blinded to order, an improvement in assessed synovitis was observed in a further 82% of overall impressions that were previously scored as no change in blinded and randomized assessments (Figure 2b). Repeated synovitis scoring assessments showed very strong agreement (Gwets AC2>0.80) in overall and sub-region assessments.</div></div><div><h3>DISCUSSION</h3><div>While ground-truth synovitis measures were not available, the qDESS hybrid method was able to detect both worsening synovitis that is expected after ACLR surgery and improvement in synovitis that is expected during the following 5 months of recovery. The lack of differentiation of synovitis changes between timepoints may partly be attributed to the coarseness of the 4-point semi-quantitative Likert-scale which is based on synovial hypertrophy and nodularity In overall a","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100298"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144521548","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 : 2025-01-01Epub Date: 2025-07-02DOI: 10.1016/j.ostima.2025.100315
F.R. Saunders , J. Parkinson , R.M. Aspden , T. Cootes , J.S. Gregory
INTRODUCTION
Chronic back pain is very common and affects over 600 million adults worldwide and has been partly attributed to OA. We have previously shown that the lateral spine has an intrinsic shape and that specific shapes have been shown to be associated with back pain in early old age. However, there is little evidence in the literature that directly links lateral spine shape with OA.
OBJECTIVE
To explore the relationships between OA, chronic back pain and lateral spine shape in a sub-cohort of the UK Biobank.
METHODS
Lateral spine iDXA scans (n=4784) from the UK Biobank imaging enhancement study were used. The cohort was 52.1% female, and the mean age was 62.2±7.5 years (Table 1). Images were annotated semi-automatically using a 143-point template encompassing the vertebral bodies from T7 to the superior margin of L5 using custom software (The University of Manchester). The points were subjected to Procrustes transform and then Principal Component Analysis to build a statistical shape model (SSM). Self-reported OA and chronic back pain (greater than 3 months duration) were taken from the questionnaire data provided at the imaging centre visit. Binary logistic regression was used to explore the associations between self-reported OA, chronic back pain, and the first 10 modes of variation. The model was adjusted for age, sex, height, weight and total spine BMD. We report odds ratios (OR) with 95% confidence intervals (CI) for each standard deviation change in mode.
RESULTS
537 participants reported OA (not site specific) and 630 reported chronic back pain. The first 10 SSM modes accounted for 88.9% of the total model variation. We found that three modes were associated with self-reported OA (modes 3,9 & 10) and a single mode was associated with chronic back pain (mode 3). It was observed that mode 3 (6.5% total model variation; Fig 1.), describing vertebral height and decreased vertebral column height was negatively associated with both self-reported OA [OR 0.88 95% CI 0.8-0.97, p=0.007] and chronic back pain [OR 0.81 95% CI 0.70-0.94, p=0.005]. Mode 3 also described a loss of spinal curvature (Fig. 1). Mode 9 (0.7% of total model variation), describing narrowing of the lumbar vertebrae) and mode 10 (0.5% of total model variation), describing a disconnect between lumbar and thoracic sections of the vertebral column were associated with an increased risk of OA [mode 9 OR 1.11 95% CI 1.01-1.022, p=0.031; mode 10 OR 1.12 95% CI 1.02-1.23, p=0.011].
CONCLUSION
We found that loss of spinal curvature and decreased vertebral body height were negatively associated with OA. Our data indicated that there was an increased risk of OA with rotation of the spine.
慢性背痛非常常见，影响了全球超过6亿成年人，部分原因是OA。我们之前已经证明，侧棘具有固有的形状，而特定的形状已被证明与老年早期的背痛有关。然而，文献中很少有证据表明侧脊柱形状与OA直接相关。目的在英国生物银行的一个亚队列中探讨OA、慢性背痛和侧脊柱形状之间的关系。方法采用来自UK Biobank成像增强研究的侧侧脊柱iDXA扫描（n=4784）。队列中女性占52.1%，平均年龄为62.2±7.5岁（表1）。使用定制软件（曼彻斯特大学），使用包含从T7到L5上缘椎体的143点模板对图像进行半自动注释。通过Procrustes变换和主成分分析建立统计形状模型（SSM）。自我报告的OA和慢性背痛（持续时间超过3个月）来自影像学中心访问时提供的问卷数据。采用二元逻辑回归来探讨自我报告的OA、慢性背痛和前10种变异模式之间的关系。模型根据年龄、性别、身高、体重和脊柱骨密度进行调整。我们报告了模式中每个标准差变化的95%置信区间（CI）的比值比（OR）。结果537名参与者报告OA（非部位特异性），630名报告慢性背痛。前10个SSM模态占总模态变化的88.9%。我们发现三种模式与自我报告的OA相关(模式3,9 &；10)单一模式与慢性背痛相关（模式3）。模型3的总变异率为6.5%；图1)，描述椎体高度和脊柱高度下降与自我报告的OA [OR 0.88 95% CI 0.8-0.97, p=0.007]和慢性背痛[OR 0.81 95% CI 0.70-0.94, p=0.005]呈负相关。模式3也描述了脊柱弯曲的丧失（图1）。模式9（占总模型变异的0.7%），描述腰椎变窄)和模式10（占总模型变异的0.5%），描述腰椎和胸椎段之间的分离，与OA的风险增加相关[模式9 OR 1.11 95% CI 1.01-1.022, p=0.031；模式10 OR 1.12 95% CI 1.02-1.23, p=0.011]。结论脊柱曲度降低和椎体高度降低与骨性关节炎呈负相关。我们的数据表明，脊柱旋转会增加骨性关节炎的风险。
{"title":"OSTEOARTHRITIS AND CHRONIC BACK PAIN ARE ASSOCIATED WITH LATERAL SPINE SHAPE: A STUDY USING THE UK BIOBANK","authors":"F.R. Saunders , J. Parkinson , R.M. Aspden , T. Cootes , J.S. Gregory","doi":"10.1016/j.ostima.2025.100315","DOIUrl":"10.1016/j.ostima.2025.100315","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Chronic back pain is very common and affects over 600 million adults worldwide and has been partly attributed to OA. We have previously shown that the lateral spine has an intrinsic shape and that specific shapes have been shown to be associated with back pain in early old age. However, there is little evidence in the literature that directly links lateral spine shape with OA.</div></div><div><h3>OBJECTIVE</h3><div>To explore the relationships between OA, chronic back pain and lateral spine shape in a sub-cohort of the UK Biobank.</div></div><div><h3>METHODS</h3><div>Lateral spine iDXA scans (n=4784) from the UK Biobank imaging enhancement study were used. The cohort was 52.1% female, and the mean age was 62.2±7.5 years (Table 1). Images were annotated semi-automatically using a 143-point template encompassing the vertebral bodies from T7 to the superior margin of L5 using custom software (The University of Manchester). The points were subjected to Procrustes transform and then Principal Component Analysis to build a statistical shape model (SSM). Self-reported OA and chronic back pain (greater than 3 months duration) were taken from the questionnaire data provided at the imaging centre visit. Binary logistic regression was used to explore the associations between self-reported OA, chronic back pain, and the first 10 modes of variation. The model was adjusted for age, sex, height, weight and total spine BMD. We report odds ratios (OR) with 95% confidence intervals (CI) for each standard deviation change in mode.</div></div><div><h3>RESULTS</h3><div>537 participants reported OA (not site specific) and 630 reported chronic back pain. The first 10 SSM modes accounted for 88.9% of the total model variation. We found that three modes were associated with self-reported OA (modes 3,9 & 10) and a single mode was associated with chronic back pain (mode 3). It was observed that mode 3 (6.5% total model variation; Fig 1.), describing vertebral height and decreased vertebral column height was negatively associated with both self-reported OA [OR 0.88 95% CI 0.8-0.97, p=0.007] and chronic back pain [OR 0.81 95% CI 0.70-0.94, p=0.005]. Mode 3 also described a loss of spinal curvature (Fig. 1). Mode 9 (0.7% of total model variation), describing narrowing of the lumbar vertebrae) and mode 10 (0.5% of total model variation), describing a disconnect between lumbar and thoracic sections of the vertebral column were associated with an increased risk of OA [mode 9 OR 1.11 95% CI 1.01-1.022, p=0.031; mode 10 OR 1.12 95% CI 1.02-1.23, p=0.011].</div></div><div><h3>CONCLUSION</h3><div>We found that loss of spinal curvature and decreased vertebral body height were negatively associated with OA. Our data indicated that there was an increased risk of OA with rotation of the spine.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100315"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524026","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 : 2025-01-01Epub Date: 2025-07-02DOI: 10.1016/j.ostima.2025.100291
A. Heald , L. Bogdan Solomon , R. Page , Y.N. Yum , M. Park , J. Myung , J.E. Collins , A. Guermazi , D.W. Kim
<div><h3>INTRODUCTION</h3><div>ICM-203, a recombinant AAV vector designed to express a truncated form of human Nkx3.2, a transcription factor which plays an important role in both chondrocyte and synoviocyte activity, is in clinical development as a potential DMOAD.</div></div><div><h3>OBJECTIVE</h3><div>An unblinded interim analysis of the low dose cohort of the first-in-human phase 1/2a study of ICM-203 was conducted to assess the safety, immunogenicity, and biological activity of ICM-203.</div></div><div><h3>METHODS</h3><div>In the low dose cohort of this phase 1/2a, double-blind, placebo-controlled, dose escalation study (NCT04875754), 8 subjects with Kellgren-Lawrence grade 3 osteoarthritis (OA) of the knee were randomized to receive a single intra-articular injection of ICM-203 or placebo in a 3:1 ratio. The primary safety endpoint was safety and tolerability of ICM-203 through assessment of treatment-emergent adverse events (TEAEs). Immunogenicity endpoints included measuring serum neutralizing antibody (NAb) titers and T-cell responses to ICM-203’s AAV capsid. As efficacy endpoints, changes in knee pain and function were assessed by the Knee Injury and Osteoarthritis Outcome Score (KOOS) pain subscale and KOOS activities of daily living (ADL) subscale, respectively; these KOOS scores were converted to calculate Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores. Imaging endpoints included Magnetic Resonance Imaging (MRI) Osteoarthritis Knee Scores (MOAKS) focusing on bone marrow lesions (BML), synovitis, articular cartilage damage, and osteophytes.</div></div><div><h3>RESULTS</h3><div>Of 11 screened subjects, 8 qualified and received a single intra-articular injection of ICM-203 (N=6) or placebo (N=2); all subjects completed 52 weeks of follow-up. Subject age ranged from 56 to 73 years; body mass index (BMI) ranged from 24.6 to 38.6 kg/m2. No significant concerns about safety or tolerability arose. The most common treatment-related TEAE was mild to moderate arthralgia, which occurred in 3 of 6 ICM-203 subjects and 1 of 2 placebo subjects. At baseline, 3 ICM-203 subjects had positive NAb responses to AAV capsid; no subjects had significant T-cell responses. All 6 ICM-203 subjects developed both a humoral and cellular response against AAV capsid, whereas neither placebo subject did. ICM-203 subjects with negative NAb at baseline (N=3) demonstrated greater improvement over placebo subjects (N=2) in KOOS pain, KOOS ADL, WOMAC, as well as in imaging endpoints, including MOAKS BML and synovitis. For articular cartilage and osteophytes, no significant changes were observed in any subject between baseline and week 52.</div></div><div><h3>CONCLUSION</h3><div>Intra-articular injections of ICM-203 were safe and well tolerated. ICM-203 appeared to show greater therapeutic activity over placebo in subjects with negative NAb at baseline. Current findings indicate ICM-203 may demonstrate potential as a disease-modifying osteoa
{"title":"A FIRST-IN-HUMAN PHASE 1/2A CLINICAL STUDY OF ICM-203 AAV GENE THERAPY: PROMISING SIGNALS AS A DMOAD CANDIDATE","authors":"A. Heald , L. Bogdan Solomon , R. Page , Y.N. Yum , M. Park , J. Myung , J.E. Collins , A. Guermazi , D.W. Kim","doi":"10.1016/j.ostima.2025.100291","DOIUrl":"10.1016/j.ostima.2025.100291","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>ICM-203, a recombinant AAV vector designed to express a truncated form of human Nkx3.2, a transcription factor which plays an important role in both chondrocyte and synoviocyte activity, is in clinical development as a potential DMOAD.</div></div><div><h3>OBJECTIVE</h3><div>An unblinded interim analysis of the low dose cohort of the first-in-human phase 1/2a study of ICM-203 was conducted to assess the safety, immunogenicity, and biological activity of ICM-203.</div></div><div><h3>METHODS</h3><div>In the low dose cohort of this phase 1/2a, double-blind, placebo-controlled, dose escalation study (NCT04875754), 8 subjects with Kellgren-Lawrence grade 3 osteoarthritis (OA) of the knee were randomized to receive a single intra-articular injection of ICM-203 or placebo in a 3:1 ratio. The primary safety endpoint was safety and tolerability of ICM-203 through assessment of treatment-emergent adverse events (TEAEs). Immunogenicity endpoints included measuring serum neutralizing antibody (NAb) titers and T-cell responses to ICM-203’s AAV capsid. As efficacy endpoints, changes in knee pain and function were assessed by the Knee Injury and Osteoarthritis Outcome Score (KOOS) pain subscale and KOOS activities of daily living (ADL) subscale, respectively; these KOOS scores were converted to calculate Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores. Imaging endpoints included Magnetic Resonance Imaging (MRI) Osteoarthritis Knee Scores (MOAKS) focusing on bone marrow lesions (BML), synovitis, articular cartilage damage, and osteophytes.</div></div><div><h3>RESULTS</h3><div>Of 11 screened subjects, 8 qualified and received a single intra-articular injection of ICM-203 (N=6) or placebo (N=2); all subjects completed 52 weeks of follow-up. Subject age ranged from 56 to 73 years; body mass index (BMI) ranged from 24.6 to 38.6 kg/m2. No significant concerns about safety or tolerability arose. The most common treatment-related TEAE was mild to moderate arthralgia, which occurred in 3 of 6 ICM-203 subjects and 1 of 2 placebo subjects. At baseline, 3 ICM-203 subjects had positive NAb responses to AAV capsid; no subjects had significant T-cell responses. All 6 ICM-203 subjects developed both a humoral and cellular response against AAV capsid, whereas neither placebo subject did. ICM-203 subjects with negative NAb at baseline (N=3) demonstrated greater improvement over placebo subjects (N=2) in KOOS pain, KOOS ADL, WOMAC, as well as in imaging endpoints, including MOAKS BML and synovitis. For articular cartilage and osteophytes, no significant changes were observed in any subject between baseline and week 52.</div></div><div><h3>CONCLUSION</h3><div>Intra-articular injections of ICM-203 were safe and well tolerated. ICM-203 appeared to show greater therapeutic activity over placebo in subjects with negative NAb at baseline. Current findings indicate ICM-203 may demonstrate potential as a disease-modifying osteoa","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100291"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523989","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 : 2025-01-01Epub Date: 2025-07-02DOI: 10.1016/j.ostima.2025.100350
N. Spoelder , W. Wirth , T.D. Turmezei , F. Eckstein , D.A. Kessler , J.W. Mackay , M. Karperien , S.C. Mastbergen , M.P. Jansen
<div><h3>INTRODUCTION</h3><div>Knee OA is both more common and progresses faster in women than in men. While it is well known that men exhibit thicker cartilage, it remains unclear whether this difference is inherently sex-based or attributable to confounding factors such as age, BMI, and/or height.</div></div><div><h3>OBJECTIVE</h3><div>The aim of this study was to evaluate regional differences in knee cartilage thickness between men and women without radiographic OA, who were matched for age, BMI, and height.</div></div><div><h3>METHODS</h3><div>Participants without radiographic signs of knee OA were selected from the Osteoarthritis Initiative (OAI). Men and women were matched based on height (±1 cm), age (±5 years), and BMI (±2 kg/m²), yielding 63 male-female pairs (n = 126; mean age 57 ± 8 years, BMI 26 ± 4 kg/m², height 170 ± 5 cm). Right knee 3T MRI scans were processed using a deep learning model to generate preliminary automatic segmentations of the outer femoral and tibial contours and the inner cartilage boundaries. These segmentations were manually refined in Stradview and converted into 3D surface models. Cartilage thickness was computed at each vertex as the distance from the cartilage surface to the underlying bone, measured along the normal vector using model-based deconvolution. The femoral, medial tibial, and lateral tibial surfaces and their associated thickness maps were spatially aligned to canonical templates using wxRegSurf. Statistical analyses were performed in MATLAB using the SurfStat package, applying statistical parametric mapping (SPM) with linear mixed models to evaluate paired male-female differences. Significance was set at p < 0.05.</div></div><div><h3>RESULTS</h3><div>Figure 1 shows the average cartilage thickness in men and women, as well as the differences between sexes. The difference map is predominantly blue, indicating thicker cartilage in men. In both sexes, cartilage was thicker on the lateral side than on the medial side. The trochlea had the greatest thickness overall, with a maximum of 3.98 mm in men and 3.30 mm in women. Statistically significant differences in cartilage thickness between men and women were observed in specific regions of the femur, medial tibia, and lateral tibia (Figure 2). In those regions in the femur, cartilage was thicker in men, with a mean thickness of 2.77 mm compared to 2.42 mm in women, a difference of 0.36 mm (15%). In both the statistically significant different regions of the medial and lateral tibia, cartilage thickness was 0.09 mm (4%) greater in men than in women, with means of 2.26 mm versus 2.17 mm and 2.19 mm versus 2.10 mm, respectively.</div></div><div><h3>CONCLUSION</h3><div>Despite similar height, age, and BMI, men exhibited thicker femorotibial cartilage than women. Statistically significant differences were found across all three joint surfaces, with the largest difference observed in the trochlea. These findings underscore the need for further research in
{"title":"TOPOGRAPHY OF SEX-RELATED FEMOROTIBIAL CARTILAGE THICKNESS DIFFERENCES: A MATCHED MALE-FEMALE PAIR ANALYSIS CONTROLLING FOR AGE, BMI, AND HEIGHT","authors":"N. Spoelder , W. Wirth , T.D. Turmezei , F. Eckstein , D.A. Kessler , J.W. Mackay , M. Karperien , S.C. Mastbergen , M.P. Jansen","doi":"10.1016/j.ostima.2025.100350","DOIUrl":"10.1016/j.ostima.2025.100350","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Knee OA is both more common and progresses faster in women than in men. While it is well known that men exhibit thicker cartilage, it remains unclear whether this difference is inherently sex-based or attributable to confounding factors such as age, BMI, and/or height.</div></div><div><h3>OBJECTIVE</h3><div>The aim of this study was to evaluate regional differences in knee cartilage thickness between men and women without radiographic OA, who were matched for age, BMI, and height.</div></div><div><h3>METHODS</h3><div>Participants without radiographic signs of knee OA were selected from the Osteoarthritis Initiative (OAI). Men and women were matched based on height (±1 cm), age (±5 years), and BMI (±2 kg/m²), yielding 63 male-female pairs (n = 126; mean age 57 ± 8 years, BMI 26 ± 4 kg/m², height 170 ± 5 cm). Right knee 3T MRI scans were processed using a deep learning model to generate preliminary automatic segmentations of the outer femoral and tibial contours and the inner cartilage boundaries. These segmentations were manually refined in Stradview and converted into 3D surface models. Cartilage thickness was computed at each vertex as the distance from the cartilage surface to the underlying bone, measured along the normal vector using model-based deconvolution. The femoral, medial tibial, and lateral tibial surfaces and their associated thickness maps were spatially aligned to canonical templates using wxRegSurf. Statistical analyses were performed in MATLAB using the SurfStat package, applying statistical parametric mapping (SPM) with linear mixed models to evaluate paired male-female differences. Significance was set at p < 0.05.</div></div><div><h3>RESULTS</h3><div>Figure 1 shows the average cartilage thickness in men and women, as well as the differences between sexes. The difference map is predominantly blue, indicating thicker cartilage in men. In both sexes, cartilage was thicker on the lateral side than on the medial side. The trochlea had the greatest thickness overall, with a maximum of 3.98 mm in men and 3.30 mm in women. Statistically significant differences in cartilage thickness between men and women were observed in specific regions of the femur, medial tibia, and lateral tibia (Figure 2). In those regions in the femur, cartilage was thicker in men, with a mean thickness of 2.77 mm compared to 2.42 mm in women, a difference of 0.36 mm (15%). In both the statistically significant different regions of the medial and lateral tibia, cartilage thickness was 0.09 mm (4%) greater in men than in women, with means of 2.26 mm versus 2.17 mm and 2.19 mm versus 2.10 mm, respectively.</div></div><div><h3>CONCLUSION</h3><div>Despite similar height, age, and BMI, men exhibited thicker femorotibial cartilage than women. Statistically significant differences were found across all three joint surfaces, with the largest difference observed in the trochlea. These findings underscore the need for further research in","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100350"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523628","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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