Osteoarthritis imaging最新文献

{"title":"PATELLAR AND FEMORAL BONE MORPHOLOGY AND ITS ASSOCIATION WITH LOADING IN YOUNG ADOLESCENT BOYS AND GIRLS","authors":"R. van Paassen , N. Tumer , J. Hirvasniemi , T.M. Piscaer , A.A. Zadpoor , S. Klein , S.M.A. Bierma-Zeinstra , E.H.G. Oei , M. van Middelkoop","doi":"10.1016/j.ostima.2025.100354","DOIUrl":"10.1016/j.ostima.2025.100354","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>High levels of physical activity or high body mass index (BMI) during growth may negatively influence bone and cartilage, but little is known about how loading relates to the shape of the patella and femur. It is well established that bone shape is primarily determined during growth, and specific variations in bone shape are associated with a higher risk of osteoarthritis (OA). Therefore, we aim to identify the association between the 3D shape of the patella and femur bones and loading factors (i.e., body mass index (BMI) and sports participation) in young adolescents.</div></div><div><h3>OBJECTIVE</h3><div>Our objective is twofold: 1) to determine the differences in bone shape between boys and girls, and 2) to determine which bone shape variations are associated with loading parameters (i.e., BMI and sports participation).</div></div><div><h3>METHODS</h3><div>Data from 1912 participants, aged 14.1 (SD: 0.67), standardized BMI for age and sex (BMI-SDS) of 0.42 (1.20), were retrieved from the Generation R study. The Generation R study is a large population cohort study that follows children from fetal life until adulthood. A subset of participants who underwent knee MRI (3.0T, Discovery MR750w, GE Healthcare, Milwaukee, WI, USA) at the 13-year follow-up time point were included in the current study. Imaging was performed with two knees in full extension using a water excitation Gradient Recalled Acquisition in Steady State sequence. Patellae and distal femora were automatically segmented using a method that combines multi-atlas and appearance models. Two statistical shape models (SSM) were built based on the automatically segmented left and right patellae and femora. Shape modes explaining at least 1% of the total population variation were included in the analyses. Differences between boys and girls were determined using a 2-sample T-test. Generalized estimating equation models, separate for boys and girls, were used to analyze the association between BMI-SDS, sports participation (yes or no), and shape variation. Bonferroni correction was used to correct for multiple testing.</div></div><div><h3>RESULTS</h3><div>A total of 3638 patellae and 3355 femora were included in the shape models. Eleven patellar and fourteen femoral shape modes explained at least 1% of the total variation and were retained for analysis. Eight out of the eleven (modes 1-4, 6, 8, 10, and 11) patellar and twelve out of the fourteen (modes 1-10, 12, and 14) femoral shape modes showed significant differences between boys and girls. Four patella and two femur modes were significantly associated with BMI in both boys and girls, while four patella and seven femur modes were significantly associated in either boys or girls only (Table 1). Patella shape mode 1 was significantly associated with sports participation in both boys and girls, as well as BMI in boys only. Femur shape mode 1 was associated with sports participation in girls and BMI in both bo","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100354"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524181","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}

{"title":"STRUCTURAL EFFICACY OF INTRA-ARTICULAR SPRIFERMIN TREATMENT ON KNEE OSTEO-ARTHRITIS AS A FUNCTION OF SYMPTOMATIC AND RADIOGRAPHIC DISEASE SEVERITY - A POST-HOC ANALYSIS FROM THE FORWARD PHASE 2 RANDOMIZED CONTROLLED TRIAL","authors":"C. Knight , F. Eckstein , W. Wirth , C. Clemmensen , W. Ma , A. Collins , S. Basnet","doi":"10.1016/j.ostima.2025.100297","DOIUrl":"10.1016/j.ostima.2025.100297","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>A putative disease-modifying osteoarthritis drug, “Sprifermin” was studied by a phase 2B RCT (FORWARD - NCT01919164). Given at a 100µg dose, sprifermin increased cartilage thickness, both in absolute terms and compared with placebo [1]. In the full cohort with MRI results (mITT), this effect did, however, not lead to a pain relief greater than placebo [1]. FORWARD contained patients with a variety of radiographic disease stages (KLG 2 or 3, with a medial minimum joint space width (JSW) > 2.5mm). Although all patients had to display > 40mm pain levels at screening, not all of them exceeded that threshold at the actual baseline measurement [2].</div></div><div><h3>OBJECTIVE</h3><div>To elucidate post-hoc whether structural treatment effects on cartilage (thickness) by sprifermin differ between severity strata of symptoms (WOMAC) and radiographic disease status. These observations may inform future clinical trials at which stage (sprifermin-) treatment is structurally and symptomatically most effective.</div></div><div><h3>METHODS</h3><div>Total femorotibial joint (TFTJ) cartilage thickness change at year (Y) 2 by MRI represented the primary endpoint; WOMAC pain was secondary [1]. Patients aged 40–85 with primary symptomatic TFTJ OA (KLG 2 or 3; medial mJSW ≥2.5 mm) were studied. Cartilage thickness was determined quantitatively from 1.5-3T MRI by expert readers, using proprietary software (Chondrometrics). The analysis focused on the 2Y MRI TFTJ cartilage thickness change for the two highest sprifermin dose groups (100µg given every 6 or 12 months combined) vs. placebo. The Hedges G (sample-size-independent effect size measure) was determined, with 95% CIs obtained by bootstrapping. We studied the modified intent to treat cohort with 24-month data (mITT), and the so-called “subcohort at risk” (SAR)[2] a subgroup with baseline WOMAC pain >40 and more severe radiographic involvement by mJSW criteria.</div></div><div><h3>RESULTS</h3><div>Of 549 FORWARD patients randomized, 474 completed 2Y follow-up. 69% of the mITT with 24M data were female; the median age was 67 and the medial BMI 29.6. The treatment effect on cartilage thickness was 45.6µm for the mITT (Hedges G=0.63). Participants with baseline WOMAC pain ≥ the median displayed a somewhat smaller effect (17±70 µm change over 2 years in treated vs. -15±55µm in placebo participants; Hedges G =0.49 [0.11, 0.86] than those with pain < median (37±69µm in treated vs. -27±84µm in placebo participants; Hedges G =0.86 [0.47, 1.25].</div><div>KLG2 subjects displayed a marginally greater treatment effect (30±75µm in treated vs. -16±46µm in placebo participants; Hedges G =0.68 [0.36, 1.00]) than KLG3 participants (13±68µm in treated vs. -33±110µm in placebo participants; Hedges G =0.55 [0.07, 1.03]). Those with JSN grade 0 (no JSN) showed a stronger treatment effect (50±59µm in those treated vs. -11±45µm in placebo participants; Hedges G =1.09 [0.63, 1.54] than those","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100297"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144521547","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}

{"title":"NEURAL SHAPE MODEL QUANTIFIES EARLY AND PROGRESSIVE BONE SHAPE CHANGES AFTER ACLR","authors":"S.A. Pai, M. Black, K. Young, S. Sherman, C. Chu, A. Williams, G. Gold, F. Kogan, B. Hargreaves, A. Chaudhari, A. Gatti","doi":"10.1016/j.ostima.2025.100342","DOIUrl":"10.1016/j.ostima.2025.100342","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Femoral bone shape scores (B-Score) derived from shape models quantify 3D structural features associated with OA<sup>1,2</sup>. A higher B-Score is indicative of more OA-like bone shape. B-Scores have high sensitivity to quantify OA progression and stratify patients for interventions<sup>1</sup>. Neural Shape Models (NSM) capture non-linear bone shape features and outperform traditional Statistical Shape Models (SSMs) in encoding OA-related shapes<sup>3</sup>. Prior work that used a SSM-based B-Score showed that anterior cruciate ligament reconstructed (ACLR) knees exhibit higher B-Scores than their contralateral knees 2 years post-surgery, reflecting OA-like bone shape features<sup>4</sup>. However, little is known about how femoral bone shape changes immediately following ACLR and how it progresses during the early post-surgical period—a critical window when post-traumatic osteoarthritis (PTOA) may still be most responsive to intervention.</div></div><div><h3>OBJECTIVE</h3><div>To use a Neural Shape Model-based B-Score to quantify femoral shape differences between ACLR and contralateral knees immediately post-surgery (3-weeks) and to detect early PTOA bone shape changes over 30 months.</div></div><div><h3>METHODS</h3><div>ACLR and contralateral knees of 17 subjects (11M/6F, age=38±10 yrs, BMI=24±2 kg/m<sup>2</sup>) were scanned at 3 weeks (baseline), 3, 9, 18, and 30 months post-ACLR in a 3T MRI scanner (GE Healthcare, USA) using a qDESS sequence (TE/TR=6/22 ms<sub>,</sub> flip angle=25°, FOV=160 × 160 mm, bandwidth=31.25 kHz, pixel spacing=0.42 × 0.50 mm, slice thickness=1.5 mm). The femur was automatically segmented, and the B-Score was computed for each subject at all visits using a NSM that was trained on 9,376 femoral segmentations from the baseline DESS images in the OAI dataset<sup>1</sup>. To assess bone shape differences immediately after surgery, we compared B-Scores between the ACLR and contralateral knees at the baseline visit using a linear mixed effects model. To capture longitudinal bone shape changes after surgery, we calculated change in B-Score at each follow-up visit with respect to the baseline visit. We used a linear mixed effects model to assess the effect of knee-type and time post-surgery on B-Scores. Effect sizes [η<sub>p</sub><sup>2</sup> is small (0.01), medium (0.06), or large (0.14)] were computed for significant effects (p<0.05).</div></div><div><h3>RESULTS AND DISCUSSION</h3><div>At baseline, the ACLR knee B-Score was significantly lower than the contralateral knee (η<sub>p</sub><sup>2</sup>=0.40, p=0.005; Fig. 1A). Longitudinally, ACLR knees showed a significantly greater increase in B-Score than contralateral knees (η<sub>p</sub><sup>2</sup>=0.19, p<0.001; Fig 2A). The lower B-Scores in ACLR knees at baseline indicate that the surgical knee had a healthier, less OA-like bone shape than the contralateral knee. Visualization revealed that ACLR knees had a wider intercondylar no","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100342"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144522509","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}

{"title":"3-D LANDMARKING REPEATABILITY EMPHASIZES CHALLENGES IN SCAN POSITIONING DURING WEIGHT BEARING CT OF THE KNEE","authors":"A. Boddu , T. Whitmarsh , N.A. Segal , N.H. Degala , J.A. Lynch , T.D. Turmezei","doi":"10.1016/j.ostima.2025.100278","DOIUrl":"10.1016/j.ostima.2025.100278","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Weight bearing CT (WBCT) has shown promise in the evaluation of the knee joint instead of radiography. However, bringing weight bearing to 3-D imaging poses technical challenges that have to be overcome if repeatability is to be optimised. From prior study and experience, maintaining knee flexion angle (KFA) and centering in the vertical scan range with consistency can be difficult. One means to evaluate these distance and angle measurements from WBCT is to use a bone surface landmarking system.</div></div><div><h3>OBJECTIVE</h3><div>(1) To evaluate the repeatability of a manual WBCT landmarking system of the femur and tibia at the knee; and (2) from this develop a technique for evaluating repeatability of KFA and vertical scan range centering.</div></div><div><h3>METHODS</h3><div>14 individuals recruited and consented at the University of Kansas Medical Center had baseline and follow-up WBCT imaging suitable for analysis. Participant demographics were: mean ± SD age 61.3 ± 8.4 years, BMI 30.7 ± 4.3 kg/m<sup>2</sup> and male:female ratio 8:6. All scanning was performed on the same XFI WBCT scanner (Planmed Oy, Helsinki, Finland) with the mean ± SD interval between baseline and follow-up attendances 14.9 ± 8.1 days. A Synaflexer<sup>TM</sup> device was used to standardise knee positioning during scanning. Imaging acquisition parameters were 96 kV tube voltage, 51.4 mA tube current, 3.5 s exposure time. A standard bone algorithm was applied for reconstruction with 0.3 mm isotropic voxels and a 21 cm vertical scan range. Both knees were included in all analyses with SD adjustments made for multiple observations from the same individual. Participant identification and scan sequence were anonymised prior to analyses. A first observer (A.B.) placed 10 femoral and 12 tibial landmarks using Stradview. These landmarks were reviewed by a second observer (T.D.T.), who placed additional landmarks at the extremes of the vertical scan within the centre of the bone medullary cavities. Bone segmentations from ScanXM were used to register landmarks from follow-up to baseline in wxRegSurf; the follow-up-to-baseline femur registration was applied to the follow-up tibial co-ordinates to assess joint positioning. Landmark repeatability was taken as the mean ± SD distance (mm) between baseline and follow-up for each landmark. A method to extract KFA and valgus alignment was developed as the angle between the lines of the extreme scan range landmarks (F00 and T00) and the centre of gravity (CoG) of the rest of the landmarks in the same bone. Valgus alignment was taken from the anterior view (<180° laterally = valgus) and KFA from lateral.</div></div><div><h3>RESULTS</h3><div>Landmark placement with their codes is shown in Figure 1a (in a left knee), with code definitions given in Table 1. An example of baseline and follow-up landmarking is shown on the same knee in Figure 1b with error results from all landmarks given in Table 1. Outsi","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100278"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144522639","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}

{"title":"REVEALING THE HIDDEN CULPRIT: CONTRALATERAL KNEE'S ROLE IN OSTEOARTHRITIS DISEASE ACTIVITY: DATA FROM THE OSTEOARTHRITIS INITIATIVE","authors":"J.B. Driban ,&nbsp;J. Baek ,&nbsp;J.C. Patarini ,&nbsp;E. Kirillov ,&nbsp;N. Vo ,&nbsp;M.J. Richard ,&nbsp;M. Zhang ,&nbsp;M.S. Harkey ,&nbsp;G.H. Lo ,&nbsp;S.-H. Liu ,&nbsp;C.B. Eaton ,&nbsp;J. MacKay ,&nbsp;M.F. Barbe ,&nbsp;T.E. McAlindon","doi":"10.1016/j.ostima.2025.100284","DOIUrl":"10.1016/j.ostima.2025.100284","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>An impediment to our current treatment strategies and clinical trials for people with knee OA is focusing only on one knee, often ignoring the contralateral knee. Failing to address the contralateral knee may explain why many localized therapeutic approaches fail to achieve optimal results.</div></div><div><h3>OBJECTIVE</h3><div>We explored whether an MRI-based composite score of BM lesion and effusion-synovitis volumes related to contralateral knee OA disease severity.</div></div><div><h3>METHODS</h3><div>Using data from the OAI, we conducted cross-sectional knee-based analyses among participants with bilateral knee MRIs and at least one knee with KLG ≥1 and a WOMAC pain score ≥10/100 (n=693). We included 1,386 knees from participants with an average age of 62 (SD=9) years. Most participants were overweight and had mild-to-moderate radiographic OA. 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. BM lesion and effusion-synovitis volumes on MRIs were used to calculate a composite score (“disease activity”). A disease activity score of 0 approximated the average score for a reference sample (n=2,787, 50% had radiographic knee OA, average [SD] WOMAC pain score = 2.8 [3.3]); lower scores (negative scores) indicate milder disease, while greater values indicate worse disease. We divided the disease activity score into tertiles. We used four separate multinomial logistic models to explore the association between disease activity in knees with and without radiographic OA (outcome) and the contralateral disease severity (KLG or disease activity; exposure).</div></div><div><h3>RESULTS</h3><div>Disease activity among knees without radiographic OA had statistically significant relationships with contralateral disease activity (range of odds ratios: 4.86-23.22) but not contralateral KLG (range of odds ratios: 0.86-1.01; Table). Disease activity among knees with radiographic OA had statistically significant relationships with contralateral disease activity and KLG; however, the association was stronger for contralateral disease activity than KLG (range of odds ratios: 3.67-21.29 versus 1.96-2.20; Table).</div></div><div><h3>CONCLUSION</h3><div>Contralateral knee OA severity is related to disease activity. Disease activity in the contralateral knee is a more informative measure of disease severity than relying on radiographs. Future studies need to explore how the contralateral knee could impact clinical trial screening, monitoring, and intervention strategies, especially when testing localized therapies.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100284"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523412","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}

{"title":"A SYSTEMATIC POST-PROCESSING APPROACH FOR T1Ρ IMAGING OF KNEE ARTICULAR CARTILAGE","authors":"J. Zhong ,&nbsp;Y. Yao ,&nbsp;F. Xiao ,&nbsp;T.Y.M. Ong ,&nbsp;K.W.K. Ho ,&nbsp;S. Li ,&nbsp;C. Huang ,&nbsp;Q. Chan ,&nbsp;J.F. Griffith ,&nbsp;W. Chen","doi":"10.1016/j.ostima.2025.100332","DOIUrl":"10.1016/j.ostima.2025.100332","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>T_1ρ imaging is an emerging technique in knee MRI for the evaluation of OA. This modality possesses the unique capability to image biochemical components, such as proteoglycans, facilitating early detection and post-treatment monitoring of knee OA. However, a significant challenge associated with T_1ρ imaging lies in the complexity of its post-processing, which encompasses parameter fitting, cartilage segmentation, and subregional parcellation.</div></div><div><h3>OBJECTIVE</h3><div>This abstract presents a systematic methodology for automating knee T_1ρ MRI post-processing by leveraging deep learning and advanced computational techniques.</div></div><div><h3>METHODS</h3><div>Our methodology automated the three primary steps of T_1ρ knee MRI post-processing and provided the mean T_1ρ values for 20 subregions of the femoral and tibial cartilage in the knee (Figure). In our experiments, we utilized four T_1ρ-weighted images to generate the T_1ρ map for 30 OA patients (age 67.63±5.80 years, BMI 26.00±4.08 kg/m²) and 10 healthy volunteers (age 24.90±2.59 years, BMI 22.75±4.51 kg/m²). For each subject, four T_1ρ-weighted images were acquired using a spin-lock frequency of 300 Hz and spin-lock times of 0, 10, 30, and 50 ms, with a resolution of 0.8 × 1 × 3 mm³, resulting in an image matrix size of 44 × 256 × 256 . The spin-lock preparation was followed by an FSE readout with TE/TR = 31/2000 ms. Additionally, we computed the mean of the four T_1ρ-weighted images and employed this mean for automated cartilage segmentation and subregion parcellation. We employed a nnU-Net trained with all 40 subjects for cartilage segmentation, while subregion parcellation was conducted using our previously published rule-based method, CartiMorph. The performance of the approach using deep learning segmentation was assessed using the Dice Coefficient Similarity (DSC), the root-mean-squared deviation (RMSD), and the coefficient of variance of RMSD (CV_RMSD) against the manual segmentation. We excluded 3 OA patients with full cartilage loss above 50% of one cartilage area (FC, MTC, or LTC) in subregion analysis.</div></div><div><h3>RESULTS</h3><div>Our experimental results demonstrated the satisfactory performance of our proposed approach. The mean DSC values for the FC, MTC and LTC in OA patients and healthy volunteers were 0.83, 0.80, and 0.82, respectively. Table 2 provides a comprehensive breakdown of the performance metrics of the agreement in T_1ρ quantification across 20 subregions.</div></div><div><h3>CONCLUSION</h3><div>We proposed a systematic approach for post-processing knee T_1ρ MRI data. The experimental results demonstrated the efficacy of the proposed approach.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100332"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523434","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}

{"title":"TRANSLATION OF X-RAY TO MRI: DIAGNOSTIC PERFORMANCE OF MRI-DEFINED SIMULATED KELLGREN-LAWRENCE GRADING","authors":"F.W. Roemer ,&nbsp;A. Guermazi ,&nbsp;C.K. Kwoh ,&nbsp;S. Demehri ,&nbsp;D.J. Hunter ,&nbsp;J.E. Collins","doi":"10.1016/j.ostima.2025.100312","DOIUrl":"10.1016/j.ostima.2025.100312","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;INTRODUCTION&lt;/h3&gt;&lt;div&gt;While it has been acknowledged that mild-to-moderate radiographic disease severity of knee osteoarthritis (OA), i.e. knees with grades 2 and 3 on the Kellgren-Lawrence (KL) scale – reflect a wide spectrum of tissue damage, it is unknown whether a knee MRI can easily be translated into a specific radiographic (r) KL grade (KLG). In order to potentially use MRI as a single screening tool for eligibility in clinical trials, it is necessary to define which knees correspond to the current inclusion criteria of rKLG 2 and 3.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;OBJECTIVE&lt;/h3&gt;&lt;div&gt;The aim of this study was to assess the diagnostic performance of a priori-determined definitions of MRI-assessed KLG based on osteophytes (OPs) and cartilage damage in the tibiofemoral joint (TFJ).&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;METHODS&lt;/h3&gt;&lt;div&gt;We included MRI readings from the following Osteoarthritis Initiative substudies: FNIH Biomarker consortium, POMA and BEAK. Included are visits with centrally read rKLG and available MOAKS readings. In order to match the anteroposterior (a.p.) radiograph, four locations for OPs assessed in the coronal plane (central medial femur, central medial tibia, central lateral femur, central lateral tibia) were considered. Eight subregions were considered for cartilage damage to mirror the weight bearing tibiofemoral joints on X-ray: anterior medial tibia, central medial tibia, posterior medial tibia, central medial femur, anterior lateral tibia, central lateral tibia, posterior lateral tibia and central lateral femur. Cartilage damage was classified as minor: focal damage only (MOAKS 0, 1.0, 1.1); moderate: damage with no advanced full thickness wide-spread damage (MOAKS 2.0, 2.1, 3.0, 3.1); and severe: full thickness wide-spread damage (MOAKS 2.2, 3.2, 3.3).&lt;/div&gt;&lt;div&gt;The definitions were derived based on expert consensus opinion as follows:&lt;/div&gt;&lt;div&gt;MRI KL0: no OP (=grade 0 in all 4 locations), minor cartilage damage only&lt;/div&gt;&lt;div&gt;MRI KL1: grade 1 OP in at least 1 of 4 TFJ locations, maximum OP grade 1, minor cartilage damage only&lt;/div&gt;&lt;div&gt;MRI KL2: grade 1, 2 or 3 OP in at least 1 of 4 TFJ locations, moderate cartilage damage&lt;/div&gt;&lt;div&gt;MRI KL2a (“atrophic”): no OP (=grades 0 in all 4 TFJ locations), moderate cartilage damage&lt;/div&gt;&lt;div&gt;MRI KL 3: grade 1, 2 or 3 OP in at least 1 of 4 TFJ locations, severe cartilage damage in at least 1 of 8 subregions.&lt;/div&gt;&lt;div&gt;MRI KL3a (“atrophic”): no OP (=grades 0 in all 4 TFJ locations), severe cartilage damage in at least 1 of 8 subregions&lt;/div&gt;&lt;div&gt;MRI KL 4: grade 1, 2 or 3 OP in at least 1 of 4 TFJ locations, severe cartilage damage in at least 2 of 4 corresponding subregions medially or laterally or both.&lt;/div&gt;&lt;div&gt;Sensitivity, specificity, negative and positive predictive values were determined using radiographic KLG as the reference.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;RESULTS&lt;/h3&gt;&lt;div&gt;In total, the dataset includes 4924 visits from 1981 participants contributing 2276 knees for up to 4 timepoints. The rKL dis","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100312"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523432","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}

{"title":"PHOTON-COUNTING CT-BASED TRABECULAR BONE ANALYSIS IN THE KNEE: A COMPARATIVE STUDY OF ADVANCED OSTEOARTHRITIS AND HEALTHY CONTROLS","authors":"M. Jarraya ,&nbsp;W. Issa ,&nbsp;C. Chane ,&nbsp;A. Zheng ,&nbsp;D. Guermazi ,&nbsp;K. Sariahmed ,&nbsp;M. Mohammadian ,&nbsp;M. Kim ,&nbsp;K.A. Flynn ,&nbsp;T.L. Redel ,&nbsp;F. Liu ,&nbsp;M. Loggia","doi":"10.1016/j.ostima.2025.100344","DOIUrl":"10.1016/j.ostima.2025.100344","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;INTRODUCTION&lt;/h3&gt;&lt;div&gt;The advent of photon counting CT is a major advance in the development of CT technology. Its enhanced spatial resolution, compared to conventional CT, and its much-reduced radiation dose make it a promising tool for in vivo assessment of bone microarchitecture in clinical settings. For example, prior studies relying on HR-pQCT and Micro CT have shown greater volumetric bone mineral density (vBMD) and trabecular (Tb) thickness (Th) were significantly higher in the medial compartment and associated with increased disease severity. There is no data on trabecular bone structure using photon counting CT in patients with osteoarthritis (OA).&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;OBJECTIVE&lt;/h3&gt;&lt;div&gt;To compare High-Resolution PCCT-defined trabecular bone microstructure between patients with advanced OA versus healthy controls.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;METHODS&lt;/h3&gt;&lt;div&gt;We used data from the ongoing DIAMOND knee study which investigates the role of neuroinflammation in chronic postoperative pain after TKR. To date, 9 healthy controls and 36 patients with advanced knee OA scheduled for total knee replacements have been recruited, including 7 patients who underwent unilateral PCCT. All other patients and healthy controls had bilateral knee scans. We used a Naeotom 144 Alpha PCCT scanner manufactured by Siemens Healthineers (Erlangen, Germany). Scans were performed with a tube voltage of (120 keV) and, to provide maximum scan performance and minimum noise deterioration, slice increments of 0.2 were used. We also utilized a slice thickness of 0.2 mm, rotation time 0.5 seconds, and pitch 0.85 Images were reconstructed with sharp bone kernel Br89 and matrix 1024 × 1024.. The field of view varied depending on the patient’s size, thus resulting in a variable voxel in plane dimension (0.2-0.4 mm). Regions of interests were defined for the proximal tibia and distal femur in a stack height defined by slices equivalent to 1/6&lt;sup&gt;th&lt;/sup&gt; to 1/4&lt;sup&gt;th&lt;/sup&gt; of the measured joint width, prescribed distally or proximally from the joint line, respectively. Images were analyzed using a previously reported iterative threshold-seeking algorithm with 3D connectivity check to separate trabecular bone from marrow. Apparent structural parameters were derived from bone volume (BV), bone surface (BS), and total volume (TV) according to equations by Parfitt’s model of parallel plates (Tb.Th, Tb.Separation, BV/TV). These trabecular bone measures were compared between OA and healthy knees using independent sample t-test or non-parametric Wilcoxon tests, depending on normality assumptions. All of the analyses were performed compartment-wise in all four ROIs. These images analyses steps were derived from methods previously published by Wong et al. (DOI: &lt;span&gt;&lt;span&gt;https://doi.org/10.1016/j.jocd.2018.04.001&lt;/span&gt;&lt;svg&gt;&lt;path&gt;&lt;/path&gt;&lt;/svg&gt;&lt;/span&gt;).&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;RESULTS&lt;/h3&gt;&lt;div&gt;We analyzed data from 12 knees of 12 patients with advanced knee OA (mean age 66.0 ± 9.4 years","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100344"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523924","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}

{"title":"UNCOVERING STRUCTURAL DISEASE PATTERNS OF EARLY POST-TRAUMATIC OSTEOARTHRITIS IN A DMM MOUSE MODEL USING CONTRAST-ENHANCED MICRO-COMPUTED TOMOGRAPHY","authors":"J.E. Schadow ,&nbsp;E.C. Boersma ,&nbsp;A.M. Cagnoni ,&nbsp;H. Liu ,&nbsp;R.A. Davey ,&nbsp;K.S. Stok","doi":"10.1016/j.ostima.2025.100316","DOIUrl":"10.1016/j.ostima.2025.100316","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;INTRODUCTION&lt;/h3&gt;&lt;div&gt;Contrast-enhanced micro-computed tomography (CECT) is a non-destructive method to assess cartilage degeneration seen in diseases such as OA whilst also allowing for analysis of bone changes [1, 2]. Application has been limited to &lt;em&gt;ex vivo&lt;/em&gt; and &lt;em&gt;in situ&lt;/em&gt; studies but using CECT &lt;em&gt;in vivo&lt;/em&gt; holds the potential to quantify and track structural cartilage and bone changes and illuminate new understanding of disease onset and progression.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;OBJECTIVE&lt;/h3&gt;&lt;div&gt;The aim of this study was to uncover structural disease patterns of early post-traumatic osteoarthritis in a destabilized medial meniscus (DMM) mouse model using time-lapse CECT.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;METHODS&lt;/h3&gt;&lt;div&gt;DMM (n=22) or sham surgery (n=22) was performed on ten-week-old C57Bl/6 mice. A further three mice did not undergo surgery but were euthanized at 10 weeks of age and processed for histology. Of the mice that had surgery, three mice per group were euthanised and processed for histology at seven-, 14-, 21- and 28-days post-surgery. The remaining ten mice per group received an intra-articular injection of Dotarem (Guerbet) and were scanned at 10.4 μm, 70 kVp, 114 μA using microCT (vivaCT80, Scanco Medical AG) at one-day pre-surgery and seven-, 14-, 21-, 28-, and 56-days post-surgery. After scanning at the final timepoint, three mice per group were euthanised after scanning at 56-days post-surgery and processed for histology. Safranin-O histology was used to score joints following the OARSI guidelines [3]. Mean attenuation of cartilage, joint alignment, joint space morphometry, subchondral bone morphometry, and osteophyte presence were analysed from microCT images. Mixed-effects analysis was used to investigate effects of osteoarthritis, time, and joint side (medial/lateral) on mean attenuation, joint space, subchondral bone, and osteophytes as well as the effects of osteoarthritis and time on joint alignment.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;RESULTS&lt;/h3&gt;&lt;div&gt;OARSI score of medial tibia in DMM OA group increased compared to the lateral side in DMM OA group and medial side of sham controls (Figure 1A). Mean attenuation of medial tibial cartilage in DMM OA mice did not change over time whereas that of sham controls increased over time. The number of voxels in the thinnest joint space layer increased on the medial side of DMM OA group post-surgery but did not change on medial side of sham controls or lateral side of either group (Figure 1B). There was increased variability in dorsal axis and midsagittal axis angles α and γ of DMM OA mice at 14-, 21-, and 28-days post-surgery. There was no difference in shape κ and scale θ of osteophyte thickness distribution of DMM OA tibia compared to sham control, despite osteophyte development on the lateral and medial side of DMM OA tibiae and frontal side of both groups. Cortical porosity and trabecular thickness of medial tibia in DMM OA mice increased over time before decreasing at 56-days post-surg","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100316"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524027","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}

{"title":"EARLY DETECTION OF KNEE OA – THE ROLE OF A COMPOSITE DISEASE ACTIVITY SCORE: DATA FROM THE OSTEOARTHRITIS INITIATIVE","authors":"J.C. Patarini ,&nbsp;T.E. McAlindon ,&nbsp;J. Baek ,&nbsp;E. Kirillov ,&nbsp;N. Vo ,&nbsp;M.J. Richard ,&nbsp;M. Zhang ,&nbsp;M.S. Harkey ,&nbsp;G.H. Lo ,&nbsp;S.-H. Liu ,&nbsp;K. Lapane ,&nbsp;C.B. Eaton ,&nbsp;J. MacKay ,&nbsp;J.B. Driban","doi":"10.1016/j.ostima.2025.100306","DOIUrl":"10.1016/j.ostima.2025.100306","url":null,"abstract":"&lt;div&gt;&lt;h3&gt;INTRODUCTION&lt;/h3&gt;&lt;div&gt;BM lesions and effusion-synovitis are frequent and dynamic disease processes detected from early- to late-stage knee OA. These processes are associated with knee symptoms, representing the primary clinical manifestations of OA. Through a systematic and iterative process, we previously developed and validated a composite biomarker – the disease activity score – that combines BM lesions and effusion-synovitis volumes throughout a knee into an efficient continuous single score.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;OBJECTIVE&lt;/h3&gt;&lt;div&gt;To evaluate whether dynamic disease processes (effusion-synovitis volume and BM lesions), summarized by a validated efficient continuous composite score, are present in early OA and prognostic of incident symptomatic knee OA over the subsequent three years.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;METHODS&lt;/h3&gt;&lt;div&gt;We analyzed a convenience sample within the OAI of participants without symptomatic knee OA. Pain assessments and radiographs were collected annually. Among 913 knees (n=572 participants), most were female, white, and had a mean age of 61 (SD=9) and body mass index of 29.4 (SD=4.5) kg/m&lt;sup&gt;2&lt;/sup&gt;. MR images were collected at each OAI site using Siemens 3.0 Tesla Trio MR systems. We measured BM lesion and effusion-synovitis volumes on 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). Using MR images from the initial visit, we combined effusion-synovitis and BM lesion volumes to calculate a composite score, referred to as the disease activity score. A disease activity score of 0 approximated the average score for a reference sample (n=2,787, 50% had radiographic knee OA, average [SD] WOMAC pain score = 2.8 [3.3]); lower scores (negative scores) indicate milder disease, while greater values indicate worse disease. The outcome was incident symptomatic knee OA (the combined state of frequent knee pain and radiographic OA [KLG≥2]) within three years after the disease activity measurement. We used logistic regression with repeated measures to assess the association between disease activity (continuous measure) and incident symptomatic knee OA, adjusting for gender, age, and body mass index.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;RESULTS&lt;/h3&gt;&lt;div&gt;Disease activity ranged from -3.3 to 31.1 (lower values = less effusion-synovitis and BM lesions). Knees that developed incident symptomatic knee OA had greater disease activity (-0.3 [2.7] vs. -1.1 [2.8]): the adjusted relative risk=1.06 (per 1 unit of disease activity; 95% confidence interval: 1.02-1.10). Our stratified analyses revealed those with only radiographic OA (adjusted relative risk=1.37 [1.06-1.78]) or only symptoms (adjusted relative risk=1.15 [1.03-1.28]) at baseline drove the associations between disease activity and incident symptomatic knee OA.&lt;/div&gt;&lt;/div&gt;&lt;div&gt;&lt;h3&gt;CONCLUSION&lt;/h3&gt;&lt;div&gt;Our findings underscore the critical","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100306"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524131","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}