Pub Date : 2025-01-01DOI: 10.1016/j.ostima.2025.100336
K. Balaji , P.M. Vicente , S. Kukran , M. Mendoza , A.A. Bharath , P.J. Lally , N.K. Bangerter
<div><h3>INTRODUCTION</h3><div>Cartilage T<sub>2</sub> is a non-invasive MRI biomarker for KOA as it is sensitive to the underlying collagen hydration/organization. Cartilage microstructural changes seen in early KOA result in elevated T<sub>2</sub>. Cartilage T<sub>2</sub> maps could be used in DMOAD clinical trials.</div><div>Quantitative DESS (qDESS) simultaneously acquires 3D, morphological whole knee images and quantitative T<sub>2</sub> maps in ∼5 minutes. Recently, we developed RaFo-4 balanced Steady State Free Precession (RaFo-4 bSSFP) that also has the potential to simultaneously acquire 3D, morphological whole knee images with high SNR efficiency and quantitative cartilage T<sub>2</sub> maps in ∼5 minutes. RaFo-4 uses machine learning (Random Forest) to estimate voxel-level cartilage T<sub>2</sub> from bSSFP images. In this preliminary study, we compared qDESS and RaFo-4 bSSFP in morphological imaging and cartilage T<sub>2</sub> mapping.</div></div><div><h3>OBJECTIVE</h3><div>1) Which technique (qDESS or RaFo-4 bSSFP) has better test-retest repeatability of cartilage T<sub>2</sub> maps? 2) Which technique gives higher quality morphological images, as quantified using SNR of femoral, patellar, and tibial cartilage and CNR of cartilage-muscle, cartilage-synovial fluid, and synovial fluid-muscle?</div></div><div><h3>METHODS</h3><div>10 healthy volunteers (HVs: 7F, 3M, 20-40 age range) were scanned on a 3T Siemens Verio (Erlangen, Germany) using an 8-channel knee coil with ethics approval. Test-retest 3D (80 slices) sagittal knee images were acquired using qDESS (water excitation, 20° flip angle, 21.77 ms TR, 6 ms TE, 364 Hz/Px receiver bandwidth, 0 dummy scans per volume) and bSSFP (water excitation, 22° flip angle, 8.6 ms TR, 4.3 ms TE, 364 Hz/Px receiver bandwidth, 0 dummy scans per volume) for both knees of each HV with knee repositioning. qDESS and bSSFP were resolution- (0.4 × 0.4 × 1.5 mm<sup>3</sup> voxel volume, 150 × 150 × 120 mm<sup>3</sup> field of view) and scan time-matched (5:05 min. for qDESS and 5:04 min for bSSFP). 4 separate phase-cycled bSSFP images were acquired with phase cycling increments [0°, 90°, 180°, 270°]. Parallel imaging was used (GRAPPA R=2 for bSSFP and qDESS with 24 reference lines; 6/8<sup>th</sup> phase/slice partial Fourier for bSSFP). Cartilage in qDESS images was segmented using DOSMA and those segmentation masks were used on the bSSFP images. Test-retest repeatability was calculated using the ICC and coefficient of variation (CoV) after removing outlier T<sub>2</sub> estimates (T<sub>2</sub> < 20 ms, T<sub>2</sub> > 90 ms). The percentage of outlier estimates was also calculated. For quantitatively evaluating morphological image quality, SNR and CNR were calculated from the Root Sum of Squares (RSOS) of the two qDESS echos and four phase-cycled bSSFP images.</div></div><div><h3>RESULTS</h3><div>1) In Fig1, RaFo-4 preserves cartilage T<sub>2</sub> spatial variations seen in qDESS T<sub>2</sub> ma
{"title":"COMPARATIVE STUDY: QDESS VERSUS RAFO-4 PERFORMANCE IN 5-MINUTE, SIMULTANEOUS, RELIABLE 3D T2 MAPPING AND MORPHOLOGICAL MR IMAGING","authors":"K. Balaji , P.M. Vicente , S. Kukran , M. Mendoza , A.A. Bharath , P.J. Lally , N.K. Bangerter","doi":"10.1016/j.ostima.2025.100336","DOIUrl":"10.1016/j.ostima.2025.100336","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Cartilage T<sub>2</sub> is a non-invasive MRI biomarker for KOA as it is sensitive to the underlying collagen hydration/organization. Cartilage microstructural changes seen in early KOA result in elevated T<sub>2</sub>. Cartilage T<sub>2</sub> maps could be used in DMOAD clinical trials.</div><div>Quantitative DESS (qDESS) simultaneously acquires 3D, morphological whole knee images and quantitative T<sub>2</sub> maps in ∼5 minutes. Recently, we developed RaFo-4 balanced Steady State Free Precession (RaFo-4 bSSFP) that also has the potential to simultaneously acquire 3D, morphological whole knee images with high SNR efficiency and quantitative cartilage T<sub>2</sub> maps in ∼5 minutes. RaFo-4 uses machine learning (Random Forest) to estimate voxel-level cartilage T<sub>2</sub> from bSSFP images. In this preliminary study, we compared qDESS and RaFo-4 bSSFP in morphological imaging and cartilage T<sub>2</sub> mapping.</div></div><div><h3>OBJECTIVE</h3><div>1) Which technique (qDESS or RaFo-4 bSSFP) has better test-retest repeatability of cartilage T<sub>2</sub> maps? 2) Which technique gives higher quality morphological images, as quantified using SNR of femoral, patellar, and tibial cartilage and CNR of cartilage-muscle, cartilage-synovial fluid, and synovial fluid-muscle?</div></div><div><h3>METHODS</h3><div>10 healthy volunteers (HVs: 7F, 3M, 20-40 age range) were scanned on a 3T Siemens Verio (Erlangen, Germany) using an 8-channel knee coil with ethics approval. Test-retest 3D (80 slices) sagittal knee images were acquired using qDESS (water excitation, 20° flip angle, 21.77 ms TR, 6 ms TE, 364 Hz/Px receiver bandwidth, 0 dummy scans per volume) and bSSFP (water excitation, 22° flip angle, 8.6 ms TR, 4.3 ms TE, 364 Hz/Px receiver bandwidth, 0 dummy scans per volume) for both knees of each HV with knee repositioning. qDESS and bSSFP were resolution- (0.4 × 0.4 × 1.5 mm<sup>3</sup> voxel volume, 150 × 150 × 120 mm<sup>3</sup> field of view) and scan time-matched (5:05 min. for qDESS and 5:04 min for bSSFP). 4 separate phase-cycled bSSFP images were acquired with phase cycling increments [0°, 90°, 180°, 270°]. Parallel imaging was used (GRAPPA R=2 for bSSFP and qDESS with 24 reference lines; 6/8<sup>th</sup> phase/slice partial Fourier for bSSFP). Cartilage in qDESS images was segmented using DOSMA and those segmentation masks were used on the bSSFP images. Test-retest repeatability was calculated using the ICC and coefficient of variation (CoV) after removing outlier T<sub>2</sub> estimates (T<sub>2</sub> < 20 ms, T<sub>2</sub> > 90 ms). The percentage of outlier estimates was also calculated. For quantitatively evaluating morphological image quality, SNR and CNR were calculated from the Root Sum of Squares (RSOS) of the two qDESS echos and four phase-cycled bSSFP images.</div></div><div><h3>RESULTS</h3><div>1) In Fig1, RaFo-4 preserves cartilage T<sub>2</sub> spatial variations seen in qDESS T<sub>2</sub> ma","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100336"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523629","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 : 2025-01-01DOI: 10.1016/j.ostima.2025.100309
S. Quayyum , C.R. Dickerson , M.R. Maly , G.S. Athwal , N.K. Knowles
<div><h3>INTRODUCTION</h3><div>Dual-energy computed tomography (DECT) allows for more accurate volumetric vBMD by accounting for marrow alterations with aging, disease and acute injuries. Tissue alterations, including vBMD, have been identified as potential biomarkers for early shoulder OA. Reconstruction kernel and energy pair images used in DECT alter vBMD and resulting estimated bone stiffness in image-based finite element models (FEMs). Prior to clinical investigation, the effect of imaging parameters must be understood.</div></div><div><h3>OBJECTIVE</h3><div>This study investigated how varying reconstruction kernel, and DECT monochromatic energy pair combinations influenced 1) vBMD, and 2) FEM estimated stiffness in the proximal humerus of cadaveric models.</div></div><div><h3>METHODS</h3><div>Cadaveric specimens (n = 7; 14 shoulders) were scanned bilaterally using DECT (GE Revolution HD GSI) with a K<sub>2</sub>HPO<sub>4</sub> calibration phantom. DECT images were reconstructed using bone sharpening (BONE) and standard (STD) kernels. Simulated monochromatic images were created at 40, 90, and 140 keV using the manufacturers GSI software and combined into energy pairs (40/90, 90/140, 40/140 keV). Images were processed with custom Python scripts and 3D Slicer software to segment and extract vBMD values in proximal humeral head and diaphysis locations. Image-based FEMs were used to compare estimated bone stiffness across models generated from each image. Results were compared using a two-way RM-ANOVA.</div></div><div><h3>RESULTS</h3><div>The highest vBMD values occurred in the humeral shaft diaphysis across all kernel and energy pair combinations (Table 1). There were significant differences in vBMD across energy pairs and kernels within the diaphysis region, with the greatest vBMD occurring with the 90/140 keV energy pair. No significant differences in mean vBMD values across energy pair combinations occurred for the anatomic neck. Increased vBMD input to FEMs resulted in similar trends, with the highest FEM stiffness in the diaphysis region, and those generated from 90/140 keV DECT images (Table 2). Significant differences remained in the diaphysis with no difference in the anatomic neck FEMs.</div></div><div><h3>CONCLUSION</h3><div>Higher vBMD values in the diaphysis reflect its cortical bone density, with significant differences by kernel and energy pair. Lower vBMD values in the anatomic neck, a trabecular-rich region, occur partially due to the heterogeneous composition, with minimal cortical bone. The BONE kernel at higher energy pairs (e.g., 90/140 keV) improved contrast but resulted in the greatest vBMD, a trend that was not observed with the other two energy pairs. Trends in vBMD persisted in FEMs indicating choice of energy pair combination has a large effect on vBMD and FEM stiffness in regions of high cortical bone, with the 90/140 keV energy pair, but little effect on trabecular regions within the proximal humerus of the cadavers
{"title":"THE EFFECT OF RECONSTRUCTION KERNEL AND MONOCHROMATIC ENERGY PAIRS USED IN DUAL ENERGY CT IMAGING OF THE PROXIMAL HUMERUS","authors":"S. Quayyum , C.R. Dickerson , M.R. Maly , G.S. Athwal , N.K. Knowles","doi":"10.1016/j.ostima.2025.100309","DOIUrl":"10.1016/j.ostima.2025.100309","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Dual-energy computed tomography (DECT) allows for more accurate volumetric vBMD by accounting for marrow alterations with aging, disease and acute injuries. Tissue alterations, including vBMD, have been identified as potential biomarkers for early shoulder OA. Reconstruction kernel and energy pair images used in DECT alter vBMD and resulting estimated bone stiffness in image-based finite element models (FEMs). Prior to clinical investigation, the effect of imaging parameters must be understood.</div></div><div><h3>OBJECTIVE</h3><div>This study investigated how varying reconstruction kernel, and DECT monochromatic energy pair combinations influenced 1) vBMD, and 2) FEM estimated stiffness in the proximal humerus of cadaveric models.</div></div><div><h3>METHODS</h3><div>Cadaveric specimens (n = 7; 14 shoulders) were scanned bilaterally using DECT (GE Revolution HD GSI) with a K<sub>2</sub>HPO<sub>4</sub> calibration phantom. DECT images were reconstructed using bone sharpening (BONE) and standard (STD) kernels. Simulated monochromatic images were created at 40, 90, and 140 keV using the manufacturers GSI software and combined into energy pairs (40/90, 90/140, 40/140 keV). Images were processed with custom Python scripts and 3D Slicer software to segment and extract vBMD values in proximal humeral head and diaphysis locations. Image-based FEMs were used to compare estimated bone stiffness across models generated from each image. Results were compared using a two-way RM-ANOVA.</div></div><div><h3>RESULTS</h3><div>The highest vBMD values occurred in the humeral shaft diaphysis across all kernel and energy pair combinations (Table 1). There were significant differences in vBMD across energy pairs and kernels within the diaphysis region, with the greatest vBMD occurring with the 90/140 keV energy pair. No significant differences in mean vBMD values across energy pair combinations occurred for the anatomic neck. Increased vBMD input to FEMs resulted in similar trends, with the highest FEM stiffness in the diaphysis region, and those generated from 90/140 keV DECT images (Table 2). Significant differences remained in the diaphysis with no difference in the anatomic neck FEMs.</div></div><div><h3>CONCLUSION</h3><div>Higher vBMD values in the diaphysis reflect its cortical bone density, with significant differences by kernel and energy pair. Lower vBMD values in the anatomic neck, a trabecular-rich region, occur partially due to the heterogeneous composition, with minimal cortical bone. The BONE kernel at higher energy pairs (e.g., 90/140 keV) improved contrast but resulted in the greatest vBMD, a trend that was not observed with the other two energy pairs. Trends in vBMD persisted in FEMs indicating choice of energy pair combination has a large effect on vBMD and FEM stiffness in regions of high cortical bone, with the 90/140 keV energy pair, but little effect on trabecular regions within the proximal humerus of the cadavers ","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100309"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524134","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 : 2025-01-01DOI: 10.1016/j.ostima.2025.100294
J.D. Johnston , A.E. Sacher , C.E. McLennan , J.A. Lynch , T. Neogi , D.J. Hunter , D.R. Wilson , S.A. Kontulainen
INTRODUCTION
The exact role of altered subchondral bone in OA pathogenesis and pain is unclear. Clinical quantitative CT (QCT) combined with depth-specific image processing has been previously used to study subchondral bone mineral density (BMD) at the proximal tibia and patella. Limited depth-specific QCT research has been completed at the OA distal femur.
OBJECTIVES
To 1) assess the short-term precision of automated, regional, depth-specific subchondral BMD measures at the distal femur in individuals with and without OA; and 2) determine whether regional and focal BMD metrics were able to discriminate differences in subchondral bone density patterns between normal and OA distal femora.
METHODS
Fourteen participants (3M:11F; mean age: 49.9 (SD: 11.9) years) were recruited and classified as normal (n=7) or OA (n=7). Each participant was scanned three times over two days using clinical QCT. Two BMD assessments were evaluated at the distal femur: mean regional density and peak focal density. BMD measures were assessed across three depths (0-2.5, 2.5-5, 5-7.5 mm) and six sub-regions of the distal femur (medial/lateral, anterior/central/posterior), as per the MOAKS approach (Fig.1). We assessed precision using root mean square coefficients of variation (CV%RMS). To explore potential differences between OA and normal distal femora, we performed parametric t-tests and non-parametric Mann-Whitney statistical analyses and also determined Cohen’s d effect sizes, with an absolute d > 0.8 considered clinically significant.
RESULTS
CV%RMS ranged from 1.6% to 3.6% (average: 2.2%) for measures of regional BMD while CV%RMS ranged from 1.6% to 6.9% (average: 2.7%) for measures of focal BMD. Statistical comparisons indicated lower BMD in OA distal femoral in the medial-anterior region at depths of 2.5-5 mm (regional: -17%; focal: -19%) and 5-7.5 mm (regional: -21%; focal: -25%) (Fig. 2). All other BMD measures were similar between normal and OA distal femora (p > 0.05). Cohen's d effect sizes ranged from -1.7 to 0.76.
CONCLUSION
This automated technique offers precise measures of subchondral BMD at the distal femur. This approach has potential to quantify and distinguish OA-related alterations in subchondral BMD at the distal femur.
{"title":"REGIONAL DEPTH-SPECIFIC SUBCHONDRAL BONE DENSITY IN OA AND NORMAL DISTAL FEMORA: PRECISION AND PRELIMINARY COMPARISONS","authors":"J.D. Johnston , A.E. Sacher , C.E. McLennan , J.A. Lynch , T. Neogi , D.J. Hunter , D.R. Wilson , S.A. Kontulainen","doi":"10.1016/j.ostima.2025.100294","DOIUrl":"10.1016/j.ostima.2025.100294","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>The exact role of altered subchondral bone in OA pathogenesis and pain is unclear. Clinical quantitative CT (QCT) combined with depth-specific image processing has been previously used to study subchondral bone mineral density (BMD) at the proximal tibia and patella. Limited depth-specific QCT research has been completed at the OA distal femur.</div></div><div><h3>OBJECTIVES</h3><div>To 1) assess the short-term precision of automated, regional, depth-specific subchondral BMD measures at the distal femur in individuals with and without OA; and 2) determine whether regional and focal BMD metrics were able to discriminate differences in subchondral bone density patterns between normal and OA distal femora.</div></div><div><h3>METHODS</h3><div>Fourteen participants (3M:11F; mean age: 49.9 (SD: 11.9) years) were recruited and classified as normal (n=7) or OA (n=7). Each participant was scanned three times over two days using clinical QCT. Two BMD assessments were evaluated at the distal femur: mean regional density and peak focal density. BMD measures were assessed across three depths (0-2.5, 2.5-5, 5-7.5 mm) and six sub-regions of the distal femur (medial/lateral, anterior/central/posterior), as per the MOAKS approach (Fig.1). We assessed precision using root mean square coefficients of variation (CV%<sub>RMS</sub>). To explore potential differences between OA and normal distal femora, we performed parametric t-tests and non-parametric Mann-Whitney statistical analyses and also determined Cohen’s d effect sizes, with an absolute d > 0.8 considered clinically significant.</div></div><div><h3>RESULTS</h3><div>CV%<sub>RMS</sub> ranged from 1.6% to 3.6% (average: 2.2%) for measures of regional BMD while CV%<sub>RMS</sub> ranged from 1.6% to 6.9% (average: 2.7%) for measures of focal BMD. Statistical comparisons indicated lower BMD in OA distal femoral in the medial-anterior region at depths of 2.5-5 mm (regional: -17%; focal: -19%) and 5-7.5 mm (regional: -21%; focal: -25%) (Fig. 2). All other BMD measures were similar between normal and OA distal femora (p > 0.05). Cohen's d effect sizes ranged from -1.7 to 0.76.</div></div><div><h3>CONCLUSION</h3><div>This automated technique offers precise measures of subchondral BMD at the distal femur. This approach has potential to quantify and distinguish OA-related alterations in subchondral BMD at the distal femur.</div></div>","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100294"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524182","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 : 2025-01-01DOI: 10.1016/j.ostima.2025.100327
R. van Paassen , N. Tumer , J. Hirvasniemi , E.M. Macri , I. Bosch , E. Langius , A. Roos , T.M. Piscaer , A.A. Zadpoor , S.M.A. Bierma-Zeinstra , E.H.G. Oei , M. van Middelkoop
<div><h3>INTRODUCTION</h3><div>Proper knee alignment is crucial for knee joint function. Little is known about knee alignment and morphology during growth; most research and current normal values were determined in adults. Imaging-based landmarks have to be identified to determine knee alignment parameters such as bisect offset or patellar translation. Currently, these landmarks are often determined manually on 2D image slices, which is time-consuming and can lead to interrater variability. Automatic extraction of these landmarks in 3D could help overcome these inconsistencies.</div></div><div><h3>OBJECTIVE</h3><div>To determine the concurrent validity of automatically extracted alignment parameters and morphology measures from two previously developed 3D statistical shape models (SSMs) - one for the patella and one for the distal femur- and to establish normative values and evaluate sex-based differences in these parameters among a young adolescent population.</div></div><div><h3>METHODS</h3><div>We included data from 1912 participants (aged 14.1 ± 0.67) who underwent knee MRI in the Generation R study, a large prospective population cohort study that follows children from fetal life until adulthood. MRI was performed using a 3.0T MRI (Discovery MR750w, GE Healthcare, Milwaukee, WI, USA), with both knees fully extended, using a water excitation Gradient Recalled Acquisition in Steady State sequence. Using a combined multi-atlas and appearance-based segmentation technique, 3638 patellae and 3355 femora were segmented from MRI scans. The 3D reconstructed bone samples derived from these segmentations were used to create two separate SSMs: one for the patella and one for the distal femur. Six patella and ten femur landmarks were annotated on the mean patella and femur shapes. Using the automatically established correspondences across bone samples during the SSMs generation, the landmarks identified on the mean bone shapes were transferred to the individual bone samples used to build the SSMs. One researcher manually annotated 30 randomly selected MRIs twice (15 boys and 15 girls) to determine the reliability of landmarks automatically extracted from the SSMs. Using these landmarks, we calculated 17 alignment parameters and morphology measurements: bisect offset; epicondylar width; femoral notch depth; femoral notch width; medial and lateral inclination angles; lateral patellar tilt; medial and lateral anterior-posterior (AP) length to epicondylar width ratio; patellar lateral translation; patellar length, thickness, and width; patellar tilt angle; sulcus angle; sulcus depth; and trochlear angle. Inter-method concurrent validity between the manually annotated parameters (mean of the two annotations) and automatically calculated parameters was determined using the intraclass correlation coefficient (ICC) for absolute agreement, calculated with a two-way mixed-effects model for single rater measurements. For alignment and morphology parameters with an
正确的膝关节对齐对膝关节功能至关重要。在生长过程中对膝关节的排列和形态知之甚少；大多数研究和目前的正常值都是在成人中确定的。必须识别基于成像的标志，以确定膝关节对齐参数，如等分偏移或髌骨平移。目前，这些地标通常是在2D图像切片上手动确定的，这既耗时又会导致互变。在3D中自动提取这些地标可以帮助克服这些不一致。目的：确定从先前开发的两种3D统计形状模型（SSMs）（一个用于髌骨，一个用于股骨远端）中自动提取的对准参数和形态学测量的并发有效性，并建立规范性值，并评估这些参数在年轻青少年人群中的性别差异。方法：我们纳入了1912名参与者（年龄14.1±0.67）的数据，这些参与者在R世代研究中接受了膝关节MRI检查，这是一项大型前瞻性人群队列研究，从胎儿到成年。MRI使用3.0T MRI (Discovery MR750w, GE Healthcare, Milwaukee， WI， USA)，双膝完全伸展，使用稳态序列的水激发梯度回忆采集。采用多图谱和基于外观的分割技术，从MRI扫描中分割了3638个髌骨和3355个股骨。从这些片段中获得的三维重建骨样本用于创建两个独立的ssm：一个用于髌骨，一个用于股骨远端。在平均髌骨和股骨形状上标注6个髌骨和10个股骨标志。利用ssm生成过程中骨样本之间自动建立的对应关系，在平均骨形状上识别的地标被转移到用于构建ssm的单个骨样本中。一位研究人员对30个随机选择的核磁共振成像（15个男孩和15个女孩）进行了两次手工注释，以确定从ssm中自动提取的地标的可靠性。利用这些地标，我们计算了17个对准参数和形态学测量：等分偏移量；上髁的宽度;股沟深度；股沟宽度；内、外侧倾角；外侧髌骨倾斜；内外侧前后（AP）长度与上髁宽度之比；髌骨外侧平移；髌骨长度、厚度和宽度；髌骨倾斜角度；沟角;沟深度;滑车角。人工标注参数（两个标注的平均值）与自动计算参数之间的方法间并发效度采用绝对一致性的类内相关系数（ICC）来确定，该相关系数采用单参数测量的双向混合效应模型计算。对于ICC的对准和形貌参数>；0.75，参考值（均值（SD））和这些参数在男孩和女孩之间的差异采用双尾t检验。结果17个计算参数中有6个具有可靠的一致性，其中等分偏移量（ICC=0.86）、上髁宽度（ICC=0.91）、髌骨宽度（ICC=0.75）、股沟宽度（ICC=0.82）、内侧（ICC=0.88）和外侧髁厚度与上髁宽度之比（ICC=0.85）的ICC>；0.75。所有六个对齐参数在男孩和女孩之间显著不同（表1）。结论所计算的排列参数和形态测量值只有三分之一可靠。其中一个原因可能是两个特定标志的位置，即滑车沟最深点和髌骨最后点，强烈影响计算的角度。在二维分析中，滑车沟的最深点与股骨髁的最前后点注释在同一片上。在3D中，这些地标没有标注在2D切片上，而是在3D空间中，导致角度和距离不同。低icc不一定表明三维测量是不正确的；它们甚至可能更准确；它们不能直接与目前临床上使用的传统成像的二维测量相比较。
{"title":"AUTOMATIC EXTRACTION OF KNEE ALIGNMENT AND MORPHOLOGY MEASURES FROM 3D MODELS IN A YOUNG-ADOLESCENT OPEN-POPULATIONS COHORT STUDY","authors":"R. van Paassen , N. Tumer , J. Hirvasniemi , E.M. Macri , I. Bosch , E. Langius , A. Roos , T.M. Piscaer , A.A. Zadpoor , S.M.A. Bierma-Zeinstra , E.H.G. Oei , M. van Middelkoop","doi":"10.1016/j.ostima.2025.100327","DOIUrl":"10.1016/j.ostima.2025.100327","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Proper knee alignment is crucial for knee joint function. Little is known about knee alignment and morphology during growth; most research and current normal values were determined in adults. Imaging-based landmarks have to be identified to determine knee alignment parameters such as bisect offset or patellar translation. Currently, these landmarks are often determined manually on 2D image slices, which is time-consuming and can lead to interrater variability. Automatic extraction of these landmarks in 3D could help overcome these inconsistencies.</div></div><div><h3>OBJECTIVE</h3><div>To determine the concurrent validity of automatically extracted alignment parameters and morphology measures from two previously developed 3D statistical shape models (SSMs) - one for the patella and one for the distal femur- and to establish normative values and evaluate sex-based differences in these parameters among a young adolescent population.</div></div><div><h3>METHODS</h3><div>We included data from 1912 participants (aged 14.1 ± 0.67) who underwent knee MRI in the Generation R study, a large prospective population cohort study that follows children from fetal life until adulthood. MRI was performed using a 3.0T MRI (Discovery MR750w, GE Healthcare, Milwaukee, WI, USA), with both knees fully extended, using a water excitation Gradient Recalled Acquisition in Steady State sequence. Using a combined multi-atlas and appearance-based segmentation technique, 3638 patellae and 3355 femora were segmented from MRI scans. The 3D reconstructed bone samples derived from these segmentations were used to create two separate SSMs: one for the patella and one for the distal femur. Six patella and ten femur landmarks were annotated on the mean patella and femur shapes. Using the automatically established correspondences across bone samples during the SSMs generation, the landmarks identified on the mean bone shapes were transferred to the individual bone samples used to build the SSMs. One researcher manually annotated 30 randomly selected MRIs twice (15 boys and 15 girls) to determine the reliability of landmarks automatically extracted from the SSMs. Using these landmarks, we calculated 17 alignment parameters and morphology measurements: bisect offset; epicondylar width; femoral notch depth; femoral notch width; medial and lateral inclination angles; lateral patellar tilt; medial and lateral anterior-posterior (AP) length to epicondylar width ratio; patellar lateral translation; patellar length, thickness, and width; patellar tilt angle; sulcus angle; sulcus depth; and trochlear angle. Inter-method concurrent validity between the manually annotated parameters (mean of the two annotations) and automatically calculated parameters was determined using the intraclass correlation coefficient (ICC) for absolute agreement, calculated with a two-way mixed-effects model for single rater measurements. For alignment and morphology parameters with an ","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100327"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524201","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 : 2025-01-01DOI: 10.1016/j.ostima.2025.100285
J. Duryea
<div><h3>INTRODUCTION</h3><div>Knee radiography is a low cost, convenient, and widely available modality for assessing KOA change longitudinally. Although seen on MRI, soft tissues such as cartilage and the meniscus are invisible radiographically and their change is measured indirectly as loss of radiographic JSW. This indirect association has the potential to reduce the responsiveness to change for JSW. JSW loss is likely due to a combination of cartilage and meniscus change but the level of contribution from each structure is not currently discernable from a radiograph.</div></div><div><h3>OBJECTIVE</h3><div>To develop and validate new measurements of JSW with improved responsiveness to change compared to the current method. We also hope this will begin to shed light on the individual contributions of cartilage and meniscus to JSW loss by systematically evaluating different JSW locations across the knee joint.</div></div><div><h3>METHODS</h3><div>We randomly placed all 4,796 OAI participants into either a training or testing group and selected all knees where fixed-location JSW (fJSW) was available at the x=0.15 to 0.3 (medial compartment) and x=0.7 (inner-most lateral compartment) locations at each of 6 follow-up time points (12, 24, 36, 48, 72, and 96 months). We defined a new JSW metric (JSW<sub>New</sub>) that was a linear combination of three individual fJSW measures:</div><div>JSW<sub>New</sub>= fJSW(x=0.25) + w<sub>1</sub> × fJSW(x=0.7) + w<sub>2</sub> × fJSW(x=x<sub>i</sub>),</div><div>where x<sub>i</sub> was one of 6 values in the medial compartment: 0.15, 0.175, 0.2, 0.225, 0.275 or 0.3; lower x<sub>i</sub> values corresponded to more peripheral locations. Using the training group, we varied w<sub>1</sub>, w<sub>2</sub> and x<sub>i</sub> to achieve the maximum responsiveness, defined as the magnitude of the standardized response mean (SRM) for baseline to the follow-up time point. Once optimized, the performance was evaluated using the independent testing set and compared in the test group to the SRM found for fJSW(x=0.25), which is generally considered the most responsive fixed location JSW. We performed separate optimization and testing for the 5 different baseline KL values and 6 distinct follow-up time points.</div></div><div><h3>RESULTS</h3><div>Table 1 summarizes the results. There is substantial improvement in the responsiveness (magnitude of the SRM values) for all follow-up time points and KL values. We did not observe a consistent pattern for the x<sub>i</sub> values other than the absence of x=0.15 (most peripheral) as an optimal value. w<sub>1</sub> was generally negative for KL4 knees suggesting that JSW<sub>New</sub> may be capturing pseudo-widening (seesaw effect) or possibly medial compartment meniscus extrusion for these knees. w<sub>2</sub>, the weight factor for the other medial compartment locations, was consistently positive although no discernable dependence on KL or follow-up time point was observed. Positive w<
{"title":"NEW JSW MEASUREMENTS INCREASE RESPONSIVENSS TO CHANGE","authors":"J. Duryea","doi":"10.1016/j.ostima.2025.100285","DOIUrl":"10.1016/j.ostima.2025.100285","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Knee radiography is a low cost, convenient, and widely available modality for assessing KOA change longitudinally. Although seen on MRI, soft tissues such as cartilage and the meniscus are invisible radiographically and their change is measured indirectly as loss of radiographic JSW. This indirect association has the potential to reduce the responsiveness to change for JSW. JSW loss is likely due to a combination of cartilage and meniscus change but the level of contribution from each structure is not currently discernable from a radiograph.</div></div><div><h3>OBJECTIVE</h3><div>To develop and validate new measurements of JSW with improved responsiveness to change compared to the current method. We also hope this will begin to shed light on the individual contributions of cartilage and meniscus to JSW loss by systematically evaluating different JSW locations across the knee joint.</div></div><div><h3>METHODS</h3><div>We randomly placed all 4,796 OAI participants into either a training or testing group and selected all knees where fixed-location JSW (fJSW) was available at the x=0.15 to 0.3 (medial compartment) and x=0.7 (inner-most lateral compartment) locations at each of 6 follow-up time points (12, 24, 36, 48, 72, and 96 months). We defined a new JSW metric (JSW<sub>New</sub>) that was a linear combination of three individual fJSW measures:</div><div>JSW<sub>New</sub>= fJSW(x=0.25) + w<sub>1</sub> × fJSW(x=0.7) + w<sub>2</sub> × fJSW(x=x<sub>i</sub>),</div><div>where x<sub>i</sub> was one of 6 values in the medial compartment: 0.15, 0.175, 0.2, 0.225, 0.275 or 0.3; lower x<sub>i</sub> values corresponded to more peripheral locations. Using the training group, we varied w<sub>1</sub>, w<sub>2</sub> and x<sub>i</sub> to achieve the maximum responsiveness, defined as the magnitude of the standardized response mean (SRM) for baseline to the follow-up time point. Once optimized, the performance was evaluated using the independent testing set and compared in the test group to the SRM found for fJSW(x=0.25), which is generally considered the most responsive fixed location JSW. We performed separate optimization and testing for the 5 different baseline KL values and 6 distinct follow-up time points.</div></div><div><h3>RESULTS</h3><div>Table 1 summarizes the results. There is substantial improvement in the responsiveness (magnitude of the SRM values) for all follow-up time points and KL values. We did not observe a consistent pattern for the x<sub>i</sub> values other than the absence of x=0.15 (most peripheral) as an optimal value. w<sub>1</sub> was generally negative for KL4 knees suggesting that JSW<sub>New</sub> may be capturing pseudo-widening (seesaw effect) or possibly medial compartment meniscus extrusion for these knees. w<sub>2</sub>, the weight factor for the other medial compartment locations, was consistently positive although no discernable dependence on KL or follow-up time point was observed. Positive w<","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100285"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523413","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 : 2025-01-01DOI: 10.1016/j.ostima.2025.100337
A.K.O. Wong , S. Costa , D. Jain , M.E. Hernandez , A. Cagnoni , S. Liu , V. Anwari , A. Naraghi , R. Mohankumar , J.D. Johnston , L. Giangregorio
<div><h3>INTRODUCTION</h3><div>Previous studies have shown that bone turnover is elevated, and fracture risk is higher among knee osteoarthritis (KOA) patients, especially in later stages of disease. While there have been mixed findings with respect to areal bone mineral density (BMD)’s association with KOA severity, it remains unclear how volumetric bone morphometry at the knee is related to the development of radiographic disease features such as osteophytosis and attrition.</div></div><div><h3>OBJECTIVE</h3><div>It was hypothesized that having definite osteophytosis and attrition are each associated with compromised subchondral bone, including lower volumetric(v) BMD, apparent v.Tissue Mineral Density (vTMD) and a wider Tb.Sp.</div></div><div><h3>METHODS</h3><div>In this cross-sectional study, women 50-85 years old were recruited by convenience sample if they experienced knee pain ≥3 days a week, each lasting >3 hours, and if self-reported body mass index (BMI) was <30 kg/m<sup>2</sup>. On the knee with worse symptoms, they completed a peripheral quantitative CT (pQCT) knee scan, one slice (2.3±0.5mm, 200µm in-plane) prescribed per tibiofemoral compartment; and an anteroposterior knee X-ray for KLG, including breakdown semi-quantitative evaluation of osteophytosis, attrition, JSN, and sclerosis. pQCT knee images were analyzed using a previously reported iterative threshold-seeking algorithm (Tam et al. Skeletal Muscle 27(14) 2024) to separate trabecular bone from marrow. Apparent structural parameters were derived from bone volume, bone surface, and total volume according to equations by Parfitt’s model of parallel plates. General linear models examined how KLG and osteophyte score, and each of established (score > 2) KOA (KL), osteophytosis, and attrition were related to knee vBMD, vTMD, app: Tb.Sp, Tb.Th, Tb.N, and BV/TV. Models adjusted for age, BMI, use of pain medications, antiresorptives, glucocorticoids or intra-articular steroid injections.</div></div><div><h3>RESULTS</h3><div>Among 105 women (mean(SD) age: 62.6(9.0)yrs, BMI: 24.2(3.5)kg/m<sup>2</sup>, median KLG: 1(1,2), 41(39.1%) with established KOA), a higher KLG or established KOA were each associated with lower vBMD and vTMD (with effects larger for vTMD), and a larger app.Tb.Sp; though, only in advanced stage (KLG3/4) individuals (Table1). Attrition was only associated with larger Tb.Sp in the lateral femur. Having more advanced osteophytosis was dose-dependently linked to lower vBMD and larger app.Tb.Sp (Figure 1). These effects were only present at the femur and not the tibia, with magnitudes appearing larger in themedial compartment among moderate grade (score 2) knees, but dose-dependently only in the lateral compartment.</div></div><div><h3>CONCLUSION</h3><div>Among peri- to post-menopausal women without obesity, compromised bone characterized by lower apparent bone density and less intact trabecular structure, may be key correlates of having more advanced radiogra
{"title":"COMPROMISED TRABECULAR BONE OF THE KNEE IS A DOSE-DEPENDENT CORRELATE OF MORE SEVERE OSTEOPHYTES AND ADVANCED KLG","authors":"A.K.O. Wong , S. Costa , D. Jain , M.E. Hernandez , A. Cagnoni , S. Liu , V. Anwari , A. Naraghi , R. Mohankumar , J.D. Johnston , L. Giangregorio","doi":"10.1016/j.ostima.2025.100337","DOIUrl":"10.1016/j.ostima.2025.100337","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Previous studies have shown that bone turnover is elevated, and fracture risk is higher among knee osteoarthritis (KOA) patients, especially in later stages of disease. While there have been mixed findings with respect to areal bone mineral density (BMD)’s association with KOA severity, it remains unclear how volumetric bone morphometry at the knee is related to the development of radiographic disease features such as osteophytosis and attrition.</div></div><div><h3>OBJECTIVE</h3><div>It was hypothesized that having definite osteophytosis and attrition are each associated with compromised subchondral bone, including lower volumetric(v) BMD, apparent v.Tissue Mineral Density (vTMD) and a wider Tb.Sp.</div></div><div><h3>METHODS</h3><div>In this cross-sectional study, women 50-85 years old were recruited by convenience sample if they experienced knee pain ≥3 days a week, each lasting >3 hours, and if self-reported body mass index (BMI) was <30 kg/m<sup>2</sup>. On the knee with worse symptoms, they completed a peripheral quantitative CT (pQCT) knee scan, one slice (2.3±0.5mm, 200µm in-plane) prescribed per tibiofemoral compartment; and an anteroposterior knee X-ray for KLG, including breakdown semi-quantitative evaluation of osteophytosis, attrition, JSN, and sclerosis. pQCT knee images were analyzed using a previously reported iterative threshold-seeking algorithm (Tam et al. Skeletal Muscle 27(14) 2024) to separate trabecular bone from marrow. Apparent structural parameters were derived from bone volume, bone surface, and total volume according to equations by Parfitt’s model of parallel plates. General linear models examined how KLG and osteophyte score, and each of established (score > 2) KOA (KL), osteophytosis, and attrition were related to knee vBMD, vTMD, app: Tb.Sp, Tb.Th, Tb.N, and BV/TV. Models adjusted for age, BMI, use of pain medications, antiresorptives, glucocorticoids or intra-articular steroid injections.</div></div><div><h3>RESULTS</h3><div>Among 105 women (mean(SD) age: 62.6(9.0)yrs, BMI: 24.2(3.5)kg/m<sup>2</sup>, median KLG: 1(1,2), 41(39.1%) with established KOA), a higher KLG or established KOA were each associated with lower vBMD and vTMD (with effects larger for vTMD), and a larger app.Tb.Sp; though, only in advanced stage (KLG3/4) individuals (Table1). Attrition was only associated with larger Tb.Sp in the lateral femur. Having more advanced osteophytosis was dose-dependently linked to lower vBMD and larger app.Tb.Sp (Figure 1). These effects were only present at the femur and not the tibia, with magnitudes appearing larger in themedial compartment among moderate grade (score 2) knees, but dose-dependently only in the lateral compartment.</div></div><div><h3>CONCLUSION</h3><div>Among peri- to post-menopausal women without obesity, compromised bone characterized by lower apparent bone density and less intact trabecular structure, may be key correlates of having more advanced radiogra","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100337"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144523932","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 : 2025-01-01DOI: 10.1016/j.ostima.2025.100308
M. Pradeep , S. Das Gupta , T. Zhang , T. Liimatainen , V.M. Pohjanen , P. Lehenkari , S. Palosaari , M. Finnilä
<div><h3>INTRODUCTION</h3><div>One of the typical hallmarks of osteoarthritis progression is the inflammation of the synovial membrane, also known as synovitis. Pathological synovitis assessment is usually performed with traditional 2D histopathology, which provides limited orientation-dependent information, requires chemical labeling, and is destructive in nature. Tissue clearing of the whole synovial biopsy and non-destructive optical sectioning using multiphoton microscopy (MPM) can overcome the limitations of 2D histological approaches. MPM offers high spatial resolution and utilizes the second harmonic signal (SHG) to provide specific information about collagen fibers. This study aims to establish a tissue-clearing approach to analyze pathological human synovial tissue using label-free MPM.</div></div><div><h3>OBJECTIVE</h3><div>The objectives of the study are: 1) to optimize a clearing-enabled label-free MPM protocol for synovial biopsies by comparing the clearing performance of a hydrophilic reagent (CUBIC protocol) and hydrophobic reagents Ethyl Cinnamate (ECi). 2) To quantitatively evaluate autofluorescence (AF) and SHG signals from synovium to understand synovial tissue morphology, cellularity, and fibrosis.</div></div><div><h3>METHODS</h3><div>For tissue-clearing protocol optimization, one synovial biopsy was cut into two sections. After formalin fixation, one section underwent CUBIC clearing protocol, and the other was dehydrated and immersed in ECi. For the MPM study, 12 synovial biopsies (6 OA, 6 rheumatoid arthritis [RA]) were formalin-fixed, dehydrated, and cleared with ECi solution. All samples were collected from total knee replacement surgeries at Oulu University Hospital, Finland. MPM was conducted using a 900 nm laser, capturing the SHG signal at 450 nm and the AF signal between 470–600 nm. A 16X/0.6 NA water-immersion objective was used for imaging, with a pixel size of 0.7 µm. At first, mosaics of the whole sample were acquired at depths of 600, 1000, and 1300 µm from the sample surface. Subsequently, Z-stack images (depth: 1mm; step size: 200 microns) of the AF channel that includes the lining layer were collected and used for 3D cell segmentation. Maximum intensity projections of the Z-stack were processed through intensity thresholding, binary masking, and watershed segmentation. Only particles with an area less than 500 µm² were considered individual cells. Moreover, adipocytes and vascularity within the sub-lining layer from the 2D mosaic images were manually identified. Further, the heat maps for SHG intensity and area fraction were calculated. Finally, the tissue clearing was reserved, and the standard histopathological assessment of synovitis (Krenn scoring system) was performed.</div></div><div><h3>RESULTS</h3><div>ECi clearing achieved complete transparency of a synovial biopsy in 3 days (cleared around 1.2 mm), while the CUBIC protocol was still partially opaque tissue even after 3 weeks (cleared around 500 µm),
{"title":"A NEW LENS ON SYNOVITIS: LABEL-FREE IMAGING OF WHOLE-MOUNT HUMAN PATHOLOGICAL SYNOVIAL MEMBRANE WITH MULTIPHOTON MICROSCOPY","authors":"M. Pradeep , S. Das Gupta , T. Zhang , T. Liimatainen , V.M. Pohjanen , P. Lehenkari , S. Palosaari , M. Finnilä","doi":"10.1016/j.ostima.2025.100308","DOIUrl":"10.1016/j.ostima.2025.100308","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>One of the typical hallmarks of osteoarthritis progression is the inflammation of the synovial membrane, also known as synovitis. Pathological synovitis assessment is usually performed with traditional 2D histopathology, which provides limited orientation-dependent information, requires chemical labeling, and is destructive in nature. Tissue clearing of the whole synovial biopsy and non-destructive optical sectioning using multiphoton microscopy (MPM) can overcome the limitations of 2D histological approaches. MPM offers high spatial resolution and utilizes the second harmonic signal (SHG) to provide specific information about collagen fibers. This study aims to establish a tissue-clearing approach to analyze pathological human synovial tissue using label-free MPM.</div></div><div><h3>OBJECTIVE</h3><div>The objectives of the study are: 1) to optimize a clearing-enabled label-free MPM protocol for synovial biopsies by comparing the clearing performance of a hydrophilic reagent (CUBIC protocol) and hydrophobic reagents Ethyl Cinnamate (ECi). 2) To quantitatively evaluate autofluorescence (AF) and SHG signals from synovium to understand synovial tissue morphology, cellularity, and fibrosis.</div></div><div><h3>METHODS</h3><div>For tissue-clearing protocol optimization, one synovial biopsy was cut into two sections. After formalin fixation, one section underwent CUBIC clearing protocol, and the other was dehydrated and immersed in ECi. For the MPM study, 12 synovial biopsies (6 OA, 6 rheumatoid arthritis [RA]) were formalin-fixed, dehydrated, and cleared with ECi solution. All samples were collected from total knee replacement surgeries at Oulu University Hospital, Finland. MPM was conducted using a 900 nm laser, capturing the SHG signal at 450 nm and the AF signal between 470–600 nm. A 16X/0.6 NA water-immersion objective was used for imaging, with a pixel size of 0.7 µm. At first, mosaics of the whole sample were acquired at depths of 600, 1000, and 1300 µm from the sample surface. Subsequently, Z-stack images (depth: 1mm; step size: 200 microns) of the AF channel that includes the lining layer were collected and used for 3D cell segmentation. Maximum intensity projections of the Z-stack were processed through intensity thresholding, binary masking, and watershed segmentation. Only particles with an area less than 500 µm² were considered individual cells. Moreover, adipocytes and vascularity within the sub-lining layer from the 2D mosaic images were manually identified. Further, the heat maps for SHG intensity and area fraction were calculated. Finally, the tissue clearing was reserved, and the standard histopathological assessment of synovitis (Krenn scoring system) was performed.</div></div><div><h3>RESULTS</h3><div>ECi clearing achieved complete transparency of a synovial biopsy in 3 days (cleared around 1.2 mm), while the CUBIC protocol was still partially opaque tissue even after 3 weeks (cleared around 500 µm), ","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100308"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524133","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 : 2025-01-01DOI: 10.1016/j.ostima.2025.100339
A. Guermazi , P.G. Conaghan , C.M. Perkins , C. Herholdt , I. Bombelka , S.L. Westbrook
<div><h3>Introduction</h3><div>LEVI-04 is a first-in-class fusion protein (p75NTR-Fc) that supplements the endogenous p75NTR binding protein, providing analgesia via inhibition of NT-3 activity. Like p75NTR, LEVI-04 binds all the neurotrophins (NTs) with differing affinities, with highest to NT-3 and lowest affinity and reversibly to NGF, distinguishing the LEVI-04 mechanism of action from that of anti-NGF antibodies. As serious joint adverse events were seen in the anti-NGF trials, rigorous surveillance of joint safety was performed in this study. In order to properly categorise the risk of adverse joint events with LEVI-04, participants with potentially confounding findings at screening were excluded. LEVI-04 was well tolerated, with no increased incidence of joint pathologies compared to placebo.<sup>1</sup></div></div><div><h3>Methods</h3><div>This was a phase II multicentre (Europe and Hong Kong) RCT in adults with knee OA. Participants were randomized to 4-weekly IV placebo or 0.3, 1, or 2 mg/kg LEVI-04 through week 16, with the final visit at week 20 and a telephone safety follow-up at week 30. Participants who met initial clinical inclusion criteria underwent X-rays of bilateral shoulders, hips and knees, and then MRI of both knees (in some cases, MRI was performed in parallel with X-rays). All images were read centrally and assessed for eligibility. At week 20, all X-rays were repeated, and MRI of the target knee was performed.</div></div><div><h3>Results</h3><div>1598 people with painful knees were screened and 518 participants enrolled. 1080 people (86%) did not proceed past screening. 345 people exited the study before X-rays were performed (151 due to not meeting initial minimum pain in at least one knee, others due to other entry criteria, or sponsor, investigator or participant decision), such that a total of 1253 participants had X-rays of the large joints (Table 1). 514 (41%) people had knee exclusion criteria on X-ray, however this included 207 (left) and 188 (right) knees of KL grade<2. Only one knee was required to have KL grade >2, resulting in 108 (8.6%) people failing on KL grade. Excessive malalignment and atrophic OA were the next highest criteria, with 43 (3.4%) and 42 (3.3%) failures respectively. 766 people proceeded to MRI of both knees. 234 (30.5%) of these failed, 168 (22.9%) due to meniscal root tear, and 42 (5.4%) due to subchondral insufficiency fracture. There were 7 (0.9%) cases of findings suggestive of primary or metastatic tumor detected on MRI and 1 (0.1%) on knee X-ray. 30 (2.4%) people were excluded on hip and 4 (0.3%) on shoulder X-rays. 5 hip and 24 knee joints had arthroplasty, but these were not exclusionary. Several people exhibited more than one pathology, so reasons for exclusion slightly exceed the total number of people excluded.</div></div><div><h3>Conclusion</h3><div>A significant proportion of people with OA show radiologic findings at screening. Excluding these patients is important to
{"title":"PHASE II RCT OF LEVI-04, A NOVEL NEUROTROPHIN-3 INHIBITOR, IN PEOPLE WITH KNEE OSTEOARTHRITIS: IMAGING EXCLUSIONS DURING SCREENING","authors":"A. Guermazi , P.G. Conaghan , C.M. Perkins , C. Herholdt , I. Bombelka , S.L. Westbrook","doi":"10.1016/j.ostima.2025.100339","DOIUrl":"10.1016/j.ostima.2025.100339","url":null,"abstract":"<div><h3>Introduction</h3><div>LEVI-04 is a first-in-class fusion protein (p75NTR-Fc) that supplements the endogenous p75NTR binding protein, providing analgesia via inhibition of NT-3 activity. Like p75NTR, LEVI-04 binds all the neurotrophins (NTs) with differing affinities, with highest to NT-3 and lowest affinity and reversibly to NGF, distinguishing the LEVI-04 mechanism of action from that of anti-NGF antibodies. As serious joint adverse events were seen in the anti-NGF trials, rigorous surveillance of joint safety was performed in this study. In order to properly categorise the risk of adverse joint events with LEVI-04, participants with potentially confounding findings at screening were excluded. LEVI-04 was well tolerated, with no increased incidence of joint pathologies compared to placebo.<sup>1</sup></div></div><div><h3>Methods</h3><div>This was a phase II multicentre (Europe and Hong Kong) RCT in adults with knee OA. Participants were randomized to 4-weekly IV placebo or 0.3, 1, or 2 mg/kg LEVI-04 through week 16, with the final visit at week 20 and a telephone safety follow-up at week 30. Participants who met initial clinical inclusion criteria underwent X-rays of bilateral shoulders, hips and knees, and then MRI of both knees (in some cases, MRI was performed in parallel with X-rays). All images were read centrally and assessed for eligibility. At week 20, all X-rays were repeated, and MRI of the target knee was performed.</div></div><div><h3>Results</h3><div>1598 people with painful knees were screened and 518 participants enrolled. 1080 people (86%) did not proceed past screening. 345 people exited the study before X-rays were performed (151 due to not meeting initial minimum pain in at least one knee, others due to other entry criteria, or sponsor, investigator or participant decision), such that a total of 1253 participants had X-rays of the large joints (Table 1). 514 (41%) people had knee exclusion criteria on X-ray, however this included 207 (left) and 188 (right) knees of KL grade<2. Only one knee was required to have KL grade >2, resulting in 108 (8.6%) people failing on KL grade. Excessive malalignment and atrophic OA were the next highest criteria, with 43 (3.4%) and 42 (3.3%) failures respectively. 766 people proceeded to MRI of both knees. 234 (30.5%) of these failed, 168 (22.9%) due to meniscal root tear, and 42 (5.4%) due to subchondral insufficiency fracture. There were 7 (0.9%) cases of findings suggestive of primary or metastatic tumor detected on MRI and 1 (0.1%) on knee X-ray. 30 (2.4%) people were excluded on hip and 4 (0.3%) on shoulder X-rays. 5 hip and 24 knee joints had arthroplasty, but these were not exclusionary. Several people exhibited more than one pathology, so reasons for exclusion slightly exceed the total number of people excluded.</div></div><div><h3>Conclusion</h3><div>A significant proportion of people with OA show radiologic findings at screening. Excluding these patients is important to ","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100339"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524154","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 : 2025-01-01DOI: 10.1016/j.ostima.2025.100310
M. Raza , T. Laffaye , R. Stein , H. Ragati-Haghi , R. Amesbury , A. Mathiessen , C.K. Kwoh , J.E. Collins , J. Duryea
<div><h3>INTRODUCTION</h3><div>Clinical risk prediction models have been developed to predict knee OA progression with the goal of targeted treatment and clinical trial enrichment. It remains unclear whether, or how, OA in other joints affects knee OA progression.</div></div><div><h3>OBJECTIVE</h3><div>To evaluate whether imaging biomarkers from non-index joints add predictive value for knee OA progression beyond those from the index knee alone.</div></div><div><h3>METHODS</h3><div>We included 648 participants from the Osteoarthritis Initiative (OAI), randomly selected with baseline KL grade of 1, 2, or 3. OAI obtained bilateral knee and hip XR and index knee MRI. Baseline imaging biomarkers included quantitative measures of index and non-index knee and hip fixed location joint space width and femorotibial angle (FTA) from XR and quantitative measures of cartilage thickness from index knee MRI. Clinical covariates were age, sex, BMI, injury history, surgery history, family history of knee replacement, and clinical hand OA (based on presence of Heberden’s nodes at the baseline clinical examination). Outcomes were knee OA progression over 48 months defined as (1) decrease in medial minimum joint space width (JSW) of ≥ 0.7mm and (2) any increase in KL grade.</div><div>We used random forests to determine the combination of predictors that maximize AUC. Random forests can model complex non-linear associations, interactions among predictors, and work well in the setting of correlated data. We examined each set of biomarkers alone and in combination: clinical covariates, index knee XR, contralateral knee XR, index hip XR, contralateral hip XR, index knee MRI. Models were tuned with 5-fold cross-validation and AUCs were computed over 1000 bootstrap samples. We used permutation-based variable importance to rank the most important variables for prediction.</div></div><div><h3>RESULTS</h3><div>The 648 OAI participants were 23% KLG 1, 48% KLG 2, and 28% KLG 3. Average age was 61 (SD 9) and average BMI 29 (SD 5). 152 (23%) had a decrease in JSW ≥0.7mm and 119 (18%) had an increase in KL grade.</div><div>In considering sets of covariates on their own, models with index knee MRI had the highest AUC for both outcomes (model 8), followed by models with index knee XR (model 3, Table). Adding contralateral hip XR to models with index knee XR improved AUC. For example, in predicting JSW≥0.7mm, the AUC increased from 0.627 (model 9) to 0.648 (model 10). Adding hip XR biomarkers did not seem to improve model discrimination (model 10 to model 11). AUCs from models from hip XR biomarkers alone were modest, though higher than for models with only clinical covariates.</div><div>Variable importance for the 10 most important biomarkers for the model with all XR biomarkers (model 12) is shown in the Figure for JSW ≥0.7mm (panel A) and KLG increase (panel B). Baseline medial minimum JSW was the most important predictor for both models. Various measures of fixed location JSW i
{"title":"PREDICTING KNEE OSTEOARTHRITIS PROGRESSION USING STRUCTURAL BIOMARKERS FROM MULTIPLE JOINTS: DATA FROM THE OSTEOARTHRITIS INITIATIVE","authors":"M. Raza , T. Laffaye , R. Stein , H. Ragati-Haghi , R. Amesbury , A. Mathiessen , C.K. Kwoh , J.E. Collins , J. Duryea","doi":"10.1016/j.ostima.2025.100310","DOIUrl":"10.1016/j.ostima.2025.100310","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Clinical risk prediction models have been developed to predict knee OA progression with the goal of targeted treatment and clinical trial enrichment. It remains unclear whether, or how, OA in other joints affects knee OA progression.</div></div><div><h3>OBJECTIVE</h3><div>To evaluate whether imaging biomarkers from non-index joints add predictive value for knee OA progression beyond those from the index knee alone.</div></div><div><h3>METHODS</h3><div>We included 648 participants from the Osteoarthritis Initiative (OAI), randomly selected with baseline KL grade of 1, 2, or 3. OAI obtained bilateral knee and hip XR and index knee MRI. Baseline imaging biomarkers included quantitative measures of index and non-index knee and hip fixed location joint space width and femorotibial angle (FTA) from XR and quantitative measures of cartilage thickness from index knee MRI. Clinical covariates were age, sex, BMI, injury history, surgery history, family history of knee replacement, and clinical hand OA (based on presence of Heberden’s nodes at the baseline clinical examination). Outcomes were knee OA progression over 48 months defined as (1) decrease in medial minimum joint space width (JSW) of ≥ 0.7mm and (2) any increase in KL grade.</div><div>We used random forests to determine the combination of predictors that maximize AUC. Random forests can model complex non-linear associations, interactions among predictors, and work well in the setting of correlated data. We examined each set of biomarkers alone and in combination: clinical covariates, index knee XR, contralateral knee XR, index hip XR, contralateral hip XR, index knee MRI. Models were tuned with 5-fold cross-validation and AUCs were computed over 1000 bootstrap samples. We used permutation-based variable importance to rank the most important variables for prediction.</div></div><div><h3>RESULTS</h3><div>The 648 OAI participants were 23% KLG 1, 48% KLG 2, and 28% KLG 3. Average age was 61 (SD 9) and average BMI 29 (SD 5). 152 (23%) had a decrease in JSW ≥0.7mm and 119 (18%) had an increase in KL grade.</div><div>In considering sets of covariates on their own, models with index knee MRI had the highest AUC for both outcomes (model 8), followed by models with index knee XR (model 3, Table). Adding contralateral hip XR to models with index knee XR improved AUC. For example, in predicting JSW≥0.7mm, the AUC increased from 0.627 (model 9) to 0.648 (model 10). Adding hip XR biomarkers did not seem to improve model discrimination (model 10 to model 11). AUCs from models from hip XR biomarkers alone were modest, though higher than for models with only clinical covariates.</div><div>Variable importance for the 10 most important biomarkers for the model with all XR biomarkers (model 12) is shown in the Figure for JSW ≥0.7mm (panel A) and KLG increase (panel B). Baseline medial minimum JSW was the most important predictor for both models. Various measures of fixed location JSW i","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100310"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524135","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 : 2025-01-01DOI: 10.1016/j.ostima.2025.100334
A. Goyal, Y. Vainberg, F. Belibi, A.A. Gatti, M.S. White, R. Shalit, F. Kogan
<div><h3>INTRODUCTION</h3><div>Osteoarthritis (OA) is increasingly recognized as a whole-joint disease, affecting cartilage, subchondral bone and periarticular muscles. While structural changes throughout the lifespan have been investigated in prior work, few studies have explored early cellular and molecular changes, such as bone metabolism, cartilage matrix composition, and muscle quality. In this study, we simultaneously assessed bone metabolic activity, cartilage microstructure, and muscle morphometry and composition in vivo, and examined their associations with key OA risk factors including age, body mass index (BMI), and sex.</div></div><div><h3>OBJECTIVE</h3><div>To characterize cellular and molecular features of bone, cartilage, and muscle in asymptomatic adults, and determine how these metrics vary with key OA risk factors of age, BMI, and sex.</div></div><div><h3>METHODS</h3><div>Forty-five asymptomatic subjects (23-79 years old, 22 female) with no history of knee injury or symptomatic arthritis underwent bilateral knee imaging on a 3T GE PET-MRI scanner (Figure 1). Quantitative DESS MR images (TEs 6 and 30.4 ms) were used to compute mean cartilage T2 relaxation time and thickness in femoral, tibial and patellar subregions, which were segmented using a previously validated automated pipeline. Dynamic [<sup>18</sup>F]NaF PET scans were acquired before and after a stair-climbing exercise (2.5mCi dose/injection) and were used to quantify Standardized Uptake Value measures (SUVmean, SUVmax) and their exercise-induced change: ΔSUVmean, ΔSUVmax. Iterative Decomposition of water and fat with Echo Assymetry and Least squares estimation (IDEAL) scans of the bilateral thighs were also acquired. The quadriceps, hamstrings, and hip adductors were segmented using an automated pipeline (MuscleMap) and muscle volume (normalized to BMI), fat fraction, and lean muscle mass were calculated for each muscle. Statistical analysis included a linear mixed effects model for each tissue outcome (cartilage, bone, and muscle metrics), where sex (male vs. female), age (years) and BMI (kg/m²) were included as fixed-effect predictors, and random intercepts for subject and for side nested within subject (to account for the paired left/right measures) captured within‐individual correlation. Significance threshold was set at p < 0.05 for this analysis.</div></div><div><h3>RESULTS</h3><div>Table 1 shows results from the linear mixed effects model.</div><div>1) Higher BMI was associated with markedly greater baseline (SUVmean and SUVmax) and post‐exercise bone tracer uptake (ΔSUVmean and ΔSUVmax), indicating increased bone turnover in individuals with higher body mass. Age was linked specifically to higher maximum uptake measures (SUVmax and ΔSUVmax), suggesting that focal sites of remodeling intensify with aging even if the overall mean uptake remains relatively stable.</div><div>2) In cartilage, T2 relaxation times rose progressively across whole, deep, and superfic
{"title":"THE AGING JOINT: QUANTITATIVE [18F]NAF PET-MR IMAGING OF CELLULAR & MOLECULAR CHANGES IN BONE, CARTILAGE AND MUSCLE ACROSS THE LIFESPAN","authors":"A. Goyal, Y. Vainberg, F. Belibi, A.A. Gatti, M.S. White, R. Shalit, F. Kogan","doi":"10.1016/j.ostima.2025.100334","DOIUrl":"10.1016/j.ostima.2025.100334","url":null,"abstract":"<div><h3>INTRODUCTION</h3><div>Osteoarthritis (OA) is increasingly recognized as a whole-joint disease, affecting cartilage, subchondral bone and periarticular muscles. While structural changes throughout the lifespan have been investigated in prior work, few studies have explored early cellular and molecular changes, such as bone metabolism, cartilage matrix composition, and muscle quality. In this study, we simultaneously assessed bone metabolic activity, cartilage microstructure, and muscle morphometry and composition in vivo, and examined their associations with key OA risk factors including age, body mass index (BMI), and sex.</div></div><div><h3>OBJECTIVE</h3><div>To characterize cellular and molecular features of bone, cartilage, and muscle in asymptomatic adults, and determine how these metrics vary with key OA risk factors of age, BMI, and sex.</div></div><div><h3>METHODS</h3><div>Forty-five asymptomatic subjects (23-79 years old, 22 female) with no history of knee injury or symptomatic arthritis underwent bilateral knee imaging on a 3T GE PET-MRI scanner (Figure 1). Quantitative DESS MR images (TEs 6 and 30.4 ms) were used to compute mean cartilage T2 relaxation time and thickness in femoral, tibial and patellar subregions, which were segmented using a previously validated automated pipeline. Dynamic [<sup>18</sup>F]NaF PET scans were acquired before and after a stair-climbing exercise (2.5mCi dose/injection) and were used to quantify Standardized Uptake Value measures (SUVmean, SUVmax) and their exercise-induced change: ΔSUVmean, ΔSUVmax. Iterative Decomposition of water and fat with Echo Assymetry and Least squares estimation (IDEAL) scans of the bilateral thighs were also acquired. The quadriceps, hamstrings, and hip adductors were segmented using an automated pipeline (MuscleMap) and muscle volume (normalized to BMI), fat fraction, and lean muscle mass were calculated for each muscle. Statistical analysis included a linear mixed effects model for each tissue outcome (cartilage, bone, and muscle metrics), where sex (male vs. female), age (years) and BMI (kg/m²) were included as fixed-effect predictors, and random intercepts for subject and for side nested within subject (to account for the paired left/right measures) captured within‐individual correlation. Significance threshold was set at p < 0.05 for this analysis.</div></div><div><h3>RESULTS</h3><div>Table 1 shows results from the linear mixed effects model.</div><div>1) Higher BMI was associated with markedly greater baseline (SUVmean and SUVmax) and post‐exercise bone tracer uptake (ΔSUVmean and ΔSUVmax), indicating increased bone turnover in individuals with higher body mass. Age was linked specifically to higher maximum uptake measures (SUVmax and ΔSUVmax), suggesting that focal sites of remodeling intensify with aging even if the overall mean uptake remains relatively stable.</div><div>2) In cartilage, T2 relaxation times rose progressively across whole, deep, and superfic","PeriodicalId":74378,"journal":{"name":"Osteoarthritis imaging","volume":"5 ","pages":"Article 100334"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144524179","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：