Search

Objective To investigate the effects of adding strength training to neuromuscular control exercises on thigh tissue composition and muscle properties in people with radiographic-symptomatic knee osteoarthritis (KOA). Methods In this exploratory secondary analysis of a randomized controlled trial, using a complete-case approach, participants performed 12 weeks of twice-weekly neuromuscular control exercise and patient education (NEMEX, n = 34) or NEMEX plus quadriceps strength training (NEMEX+ST, n = 29). Outcomes were MRI-measured inter- and intramuscular adipose tissue (InterMAT, IntraMAT), quadriceps muscle cross-sectional area (CSA), knee-extensor strength, specific strength (strength/lean CSA) and 30 s chair-stands. Between-group effects were compared using a mixed model analysis of variance. Results At 12 weeks, responses to NEMEX+ST overlapped with NEMEX for all outcomes. Both groups reduced InterMAT (NEMEX+ST=25 %, NEMEX=21 %); between-group difference: 0.8cm2 (95 % CI: -0.1, 1.7). NEMEX+ST decreased IntraMAT (2 %) and NEMEX increased IntraMAT (4 %); between-group difference 0.1 %-points (-0.3, 0.5). Both groups increased quadriceps CSA and lean CSA (CSA minus IntraMAT), improved knee-extensor strength and specific strength, and improved chair-stand performance with a trend towards greater effects in NEMEX+ST. Conclusion Adding strength training to 12 weeks of neuromuscular control exercises provided largely similar effects to neuromuscular control exercises alone in decreasing InterMAT and IntraMAT, in improving knee-extensor strength, CSA and in improving performance-based function in KOA persons, with a trend towards greater effects with additional strength training. Notably, both groups substantially reduced InterMAT and improved specific strength (an index of muscle quality). Our hypothesis-generating work warrants exploration of the roles played by InterMAT and IntraMAT in exercise effects in KOA., Objective: To investigate the effects of adding strength training to neuromuscular control exercises on thigh tissue composition and muscle properties in people with radiographic-symptomatic knee osteoarthritis (KOA). Methods: In this exploratory secondary analysis of a randomized controlled trial, using a complete-case approach, participants performed 12 weeks of twice-weekly neuromuscular control exercise and patient education (NEMEX, n = 34) or NEMEX plus quadriceps strength training (NEMEX+ST, n = 29). Outcomes were MRI-measured inter- and intramuscular adipose tissue (InterMAT, IntraMAT), quadriceps muscle cross-sectional area (CSA), knee-extensor strength, specific strength (strength/lean CSA) and 30 s chair-stands. Between-group effects were compared using a mixed model analysis of variance. Results: At 12 weeks, responses to NEMEX+ST overlapped with NEMEX for all outcomes. Both groups reduced InterMAT (NEMEX+ST=25 %, NEMEX=21 %); between-group difference: 0.8cm2 (95 % CI: -0.1, 1.7). NEMEX+ST decreased IntraMAT (2 %) and NEMEX increased IntraMAT (4 %); between-group difference 0.1 %-points (-0.3, 0.5). Both groups increased quadriceps CSA and lean CSA (CSA minus IntraMAT), improved knee-extensor strength and specific strength, and improved chair-stand performance with a trend towards greater effects in NEMEX+ST. Conclusion: Adding strength training to 12 weeks of neuromuscular control exercises provided largely similar effects to neuromuscular control exercises alone in decreasing InterMAT and IntraMAT, in improving knee-extensor strength, CSA and in improving performance-based function in KOA persons, with a trend towards greater effects with additional strength training. Notably, both groups substantially reduced InterMAT and improved specific strength (an index of muscle quality). Our hypothesis-generating work warrants exploration of the roles played by InterMAT and IntraMAT in exercise effects in KOA.

Objective To investigate the effects of adding strength training to neuromuscular control exercises on thigh tissue composition and muscle properties in people with radiographic-symptomatic knee osteoarthritis (KOA). Methods In this exploratory secondary analysis of a randomized controlled trial, using a complete-case approach, participants performed 12 weeks of twice-weekly neuromuscular control exercise and patient education (NEMEX, n = 34) or NEMEX plus quadriceps strength training (NEMEX+ST, n = 29). Outcomes were MRI-measured inter- and intramuscular adipose tissue (InterMAT, IntraMAT), quadriceps muscle cross-sectional area (CSA), knee-extensor strength, specific strength (strength/lean CSA) and 30 s chair-stands. Between-group effects were compared using a mixed model analysis of variance. Results At 12 weeks, responses to NEMEX+ST overlapped with NEMEX for all outcomes. Both groups reduced InterMAT (NEMEX+ST=25 %, NEMEX=21 %); between-group difference: 0.8cm2 (95 % CI: -0.1, 1.7). NEMEX+ST decreased IntraMAT (2 %) and NEMEX increased IntraMAT (4 %); between-group difference 0.1 %-points (-0.3, 0.5). Both groups increased quadriceps CSA and lean CSA (CSA minus IntraMAT), improved knee-extensor strength and specific strength, and improved chair-stand performance with a trend towards greater effects in NEMEX+ST. Conclusion Adding strength training to 12 weeks of neuromuscular control exercises provided largely similar effects to neuromuscular control exercises alone in decreasing InterMAT and IntraMAT, in improving knee-extensor strength, CSA and in improving performance-based function in KOA persons, with a trend towards greater effects with additional strength training. Notably, both groups substantially reduced InterMAT and improved specific strength (an index of muscle quality). Our hypothesis-generating work warrants exploration of the roles played by InterMAT and IntraMAT in exercise effects in KOA., Objective: To investigate the effects of adding strength training to neuromuscular control exercises on thigh tissue composition and muscle properties in people with radiographic-symptomatic knee osteoarthritis (KOA). Methods: In this exploratory secondary analysis of a randomized controlled trial, using a complete-case approach, participants performed 12 weeks of twice-weekly neuromuscular control exercise and patient education (NEMEX, n = 34) or NEMEX plus quadriceps strength training (NEMEX+ST, n = 29). Outcomes were MRI-measured inter- and intramuscular adipose tissue (InterMAT, IntraMAT), quadriceps muscle cross-sectional area (CSA), knee-extensor strength, specific strength (strength/lean CSA) and 30 s chair-stands. Between-group effects were compared using a mixed model analysis of variance. Results: At 12 weeks, responses to NEMEX+ST overlapped with NEMEX for all outcomes. Both groups reduced InterMAT (NEMEX+ST=25 %, NEMEX=21 %); between-group difference: 0.8cm2 (95 % CI: -0.1, 1.7). NEMEX+ST decreased IntraMAT (2 %) and NEMEX increased IntraMAT (4 %); between-group difference 0.1 %-points (-0.3, 0.5). Both groups increased quadriceps CSA and lean CSA (CSA minus IntraMAT), improved knee-extensor strength and specific strength, and improved chair-stand performance with a trend towards greater effects in NEMEX+ST. Conclusion: Adding strength training to 12 weeks of neuromuscular control exercises provided largely similar effects to neuromuscular control exercises alone in decreasing InterMAT and IntraMAT, in improving knee-extensor strength, CSA and in improving performance-based function in KOA persons, with a trend towards greater effects with additional strength training. Notably, both groups substantially reduced InterMAT and improved specific strength (an index of muscle quality). Our hypothesis-generating work warrants exploration of the roles played by InterMAT and IntraMAT in exercise effects in KOA.

[Abstract] Objective: To determine the association between joint structure and gait in patients with knee osteoarthritis (OA). Methods: IMI-APPROACH recruited 297 clinical knee OA patients. Gait data was collected (GaitSmart®) and OA-related joint measures determined from knee radiographs (KIDA) and MRIs (qMRI/MOAKS). Patients were divided into those with/without radiographic OA (ROA). Principal component analyses (PCA) were performed on gait parameters; linear regression models were used to evaluate whether image-based structural and demographic parameters were associated with gait principal components. Results: Two hundred seventy-one patients (age median 68.0, BMI 27.0, 77% female) could be analyzed; 149 (55%) had ROA. PCA identified two components: upper leg (primarily walking speed, stride duration, hip range of motion [ROM], thigh ROM) and lower leg (calf ROM, knee ROM in swing and stance phases). Increased age, BMI, and radiographic subchondral bone density (sclerosis), decreased radiographic varus angle deviation, and female sex were statistically significantly associated with worse lower leg gait (i.e. reduced ROM) in patients without ROA (R2 = 0.24); in ROA patients, increased BMI, radiographic osteophytes, MRI meniscal extrusion and female sex showed significantly worse lower leg gait (R2 = 0.18). Higher BMI was significantly associated with reduced upper leg function for non-ROA patients (R2 = 0.05); ROA patients with male sex, higher BMI and less MRI synovitis showed significantly worse upper leg gait (R2 = 0.12). Conclusion: Structural OA pathology was significantly associated with gait in patients with clinical knee OA, though BMI may be more important. While associations were not strong, these results provide a significant association between OA symptoms (gait) and joint structure.

OBJECTIVE: The aim of the study was to determine whether tibiofemoral contact stress predicts risk for worsening knee pain over 84 ms in adults aged 50-79 yrs with or at elevated risk for knee osteoarthritis. DESIGN: Baseline tibiofemoral contact stress was estimated using discrete element analysis. Other baseline measures included weight, height, hip-knee-ankle alignment, Kellgren-Lawrence grade, and Western Ontario and McMaster Universities Osteoarthritis Index pain subscale. Logistic regression models assessed the association between baseline contact stress and 84-mo worsening of Western Ontario and McMaster Universities Osteoarthritis Index pain subscale. RESULTS: Data from the dominant knee (72.6% Kellgren-Lawrence grade 0/1 and 27.4% Kellgren-Lawrence grade ≥ 2) of 208 participants (64.4% female, mean ± SD body mass index = 29.6 ± 5.1 kg/m 2 ) were analyzed. Baseline mean and peak contact stress were 3.3 ± 0.9 and 9.4 ± 4.3 MPa, respectively. Forty-seven knees met the criterion for worsening pain. The highest tertiles in comparison with the lowest tertiles of mean (odds ratio [95% confidence interval] = 2.47 [1.03-5.95], P = 0.04) and peak (2.49 [1.03-5.98], P = 0.04) contact stress were associated with worsening pain at 84 mos, after adjustment for age, sex, race, clinic site, and baseline pain. Post hoc sensitivity analyses including adjustment for body mass index and hip-knee-ankle alignment attenuated the effect. CONCLUSIONS: These findings suggest that elevated tibiofemoral contact stress can predict the development of worsening of knee pain.

ObjectiveTo determine the optimal combination of imaging and biochemical biomarkers for use in the prediction of knee osteoarthritis (OA) progression.MethodsThe present study was a nested case-control trial from the Foundation of the National Institutes of Health OA Biomarkers Consortium that assessed study participants with a Kellgren/Lawrence grade of 1-3 who had complete biomarker data available (n = 539 to 550). Cases were participants' knees that had radiographic and pain progression between 24 and 48 months compared to baseline. Radiographic progression only was assessed in secondary analyses. Biomarkers (baseline and 24-month changes) that had a P value of <0.10 in univariate analysis were selected, including quantitative cartilage thickness and volume on magnetic resonance imaging (MRI), semiquantitative MRI markers, bone shape and area, quantitative meniscal volume, radiographic progression (trabecular bone texture [TBT]), and serum and/or urine biochemical markers. Multivariable logistic regression models were built using 3 different stepwise selection methods (complex models versus parsimonious models).ResultsAmong baseline biomarkers, the number of locations affected by osteophytes (semiquantitative), quantitative central medial femoral and central lateral femoral cartilage thickness, patellar bone shape, and semiquantitative Hoffa-synovitis predicted OA progression in most models (C statistic 0.641-0.671). In most models, 24-month changes in semiquantitative MRI markers (effusion-synovitis, meniscal morphologic changes, and cartilage damage), quantitative central medial femoral cartilage thickness, quantitative medial tibial cartilage volume, quantitative lateral patellofemoral bone area, horizontal TBT (intercept term), and urine N-telopeptide of type I collagen predicted OA progression (C statistic 0.680-0.724). A different combination of imaging and biochemical biomarkers (baseline and 24-month change) predicted radiographic progression only, whic

OBJECTIVE: To determine the optimal combination of imaging and biochemical biomarkers to predict knee osteoarthritis (OA) progression.METHODS: Nested case-control study from the FNIH OA Biomarkers Consortium of participants with Kellgren-Lawrence grade 1-3 and complete biomarker data (n=539 to 550). Cases were knees with radiographic and pain progression between 24-48 months from baseline. Radiographic progression only was assessed in secondary analyses. Biomarkers (baseline and 24-month changes) with p<0.10 in univariate analysis were selected, including MRI (quantitative (Q) cartilage thickness and volume; semi-quantitative (SQ) MRI markers; bone shape and area; Q meniscal volume), radiographic (trabecular bone texture (TBT)), and serum and/or urine biochemical markers. Multivariable logistic regression models were built using three different step-wise selection methods (complex vs. parsimonious models).RESULTS: Among baseline biomarkers, the number of locations affected by osteophytes (SQ), Q central medial femoral and central lateral femoral cartilage thickness, patellar bone shape, and SQ Hoffa-synovitis predicted progression in most models (C-statistics 0.641-0.671). 24-month changes in SQ MRI markers (effusion-synovitis, meniscal morphology, and cartilage damage), Q central medial femoral cartilage thickness, Q medial tibial cartilage volume, Q lateral patellofemoral bone area, horizontal TBT (intercept term), and urine NTX-I predicted progression in most models (C-statistics 0.680-0.724). A different combination of imaging and biochemical biomarkers (baseline and 24-month change) predicted radiographic progression only, with higher C-statistics (0.716-0.832).CONCLUSION: This study highlights the combination of biomarkers with potential prognostic utility in OA disease-modifying trials. Properly qualified, these biomarkers could be used to enrich future trials with participants likely to progress.

OBJECTIVE: To determine the optimal combination of imaging and biochemical biomarkers to predict knee osteoarthritis (OA) progression.METHODS: Nested case-control study from the FNIH OA Biomarkers Consortium of participants with Kellgren-Lawrence grade 1-3 and complete biomarker data (n=539 to 550). Cases were knees with radiographic and pain progression between 24-48 months from baseline. Radiographic progression only was assessed in secondary analyses. Biomarkers (baseline and 24-month changes) with p<0.10 in univariate analysis were selected, including MRI (quantitative (Q) cartilage thickness and volume; semi-quantitative (SQ) MRI markers; bone shape and area; Q meniscal volume), radiographic (trabecular bone texture (TBT)), and serum and/or urine biochemical markers. Multivariable logistic regression models were built using three different step-wise selection methods (complex vs. parsimonious models).RESULTS: Among baseline biomarkers, the number of locations affected by osteophytes (SQ), Q central medial femoral and central lateral femoral cartilage thickness, patellar bone shape, and SQ Hoffa-synovitis predicted progression in most models (C-statistics 0.641-0.671). 24-month changes in SQ MRI markers (effusion-synovitis, meniscal morphology, and cartilage damage), Q central medial femoral cartilage thickness, Q medial tibial cartilage volume, Q lateral patellofemoral bone area, horizontal TBT (intercept term), and urine NTX-I predicted progression in most models (C-statistics 0.680-0.724). A different combination of imaging and biochemical biomarkers (baseline and 24-month change) predicted radiographic progression only, with higher C-statistics (0.716-0.832).CONCLUSION: This study highlights the combination of biomarkers with potential prognostic utility in OA disease-modifying trials. Properly qualified, these biomarkers could be used to enrich future trials with participants likely to progress.

[Abstract] Background. The IMI-APPROACH cohort is an exploratory, 5-centre, 2-year prospective follow-up study of knee osteoarthritis (OA). Aim was to describe baseline multi-tissue semiquantitative MRI evaluation of index knees and to describe change for different MRI features based on number of subregion-approaches and change in maximum grades over a 24-month period. Methods. MRIs were acquired using 1.5 T or 3 T MRI systems and assessed using the semi-quantitative MRI OA Knee Scoring (MOAKS) system. MRIs were read at baseline and 24-months for cartilage damage, bone marrow lesions (BML), osteophytes, meniscal damage and extrusion, and Hoffa- and effusion-synovitis. In descriptive fashion, the frequencies of MRI features at baseline and change in these imaging biomarkers over time are presented for the entire sample in a subregional and maximum score approach for most features. Differences between knees without and with structural radiographic (R) OA are analyzed in addition. Results. Two hundred eighty-nine participants had readable baseline MRI examinations. Mean age was 66.6 ± 7.1 years and participants had a mean BMI of 28.1 ± 5.3 kg/m2. The majority (55.3%) of included knees had radiographic OA. Any change in total cartilage MOAKS score was observed in 53.1% considering full-grade changes only, and in 73.9% including full-grade and within-grade changes. Any medial cartilage progression was seen in 23.9% and any lateral progression on 22.1%. While for the medial and lateral compartments numbers of subregions with improvement and worsening of BMLs were very similar, for the PFJ more improvement was observed compared to worsening (15.5% vs. 9.0%). Including within grade changes, the number of knees showing BML worsening increased from 42.2% to 55.6%. While for some features 24-months change was rare, frequency of change was much more common in knees with vs. without ROA (e.g. worsening of total MOAKS score cartilage in 68.4% of ROA knees vs. 36.7% of no-ROA knee

The ability of Minkowski Functionals to characterize local structure in different biological tissue types has been demonstrated in a variety of medical image processing tasks. We introduce anisotropic Minkowski Functionals (AMFs) as a novel variant that captures the inherent anisotropy of the underlying gray-level structures. To quantify the anisotropy characterized by our approach, we further introduce a method to compute a quantitative measure motivated by a technique utilized in MR diffusion tensor imaging, namely fractional anisotropy. We showcase the applicability of our method in the research context of characterizing the local structure properties of trabecular bone micro-architecture in the proximal femur as visualized on multi-detector CT. To this end, AMFs were computed locally for each pixel of ROIs extracted from the head, neck and trochanter regions. Fractional anisotropy was then used to quantify the local anisotropy of the trabecular structures found in these ROIs and to compare its distribution in different anatomical regions. Our results suggest a significantly greater concentration of anisotropic trabecular structures in the head and neck regions when compared to the trochanter region (p < 10-4). We also evaluated the ability of such AMFs to predict bone strength in the femoral head of proximal femur specimens obtained from 50 donors. Our results suggest that such AMFs, when used in conjunction with multi-regression models, can outperform more conventional features such as BMD in predicting failure load. We conclude that such anisotropic Minkowski Functionals can capture valuable information regarding directional attributes of local structure, which may be useful in a wide scope of biomedical imaging applications., Comment: SPIE Medical Imaging 2013. arXiv admin note: text overlap with arXiv:2002.07156

ObjectiveTo evaluate whether change in fixed-location measures of radiographic joint space width (JSW) and cartilage thickness by MRI predict knee replacement.MethodsKnees replaced between 36 and 60 months' follow-up in the Osteoarthritis Initiative were each matched with one control by age, sex and radiographic status. Radiographic JSW was determined from fixed flexion radiographs and subregional femorotibial cartilage thickness from 3 T MRI. Changes between the annual visit before replacement (T0) and 2 years before T0 (T-2) were compared using conditional logistic regression.ResultsOne hundred and nineteen knees from 102 participants (55.5 % women; age 64.2 ± 8.7 [mean ± SD] years) were studied. Fixed-location JSW change at 22.5 % from medial to lateral differed more between replaced and control knees (case-control [cc] OR = 1.57; 95 % CI: 1.23-2.01) than minimum medial JSW change (ccOR = 1.38; 95 % CI: 1.11-1.71). Medial femorotibial cartilage loss displayed discrimination similar to minimum JSW, and central tibial cartilage loss similar to fixed-location JSW. Location-independent thinning and thickening scores were elevated prior to knee replacement.ConclusionsDiscrimination of structural progression between knee pre-placement cases versus controls was stronger for fixed-location than minimum radiographic JSW. MRI displayed similar discrimination to radiography and suggested greater simultaneous cartilage thickening and loss prior to knee replacement.Key points• Fixed-location JSW predicts surgical knee replacement more strongly than minimum JSW. • MRI predicts knee replacement with similar accuracy to radiographic JSW. • MRI reveals greater cartilage thinning and thickening prior to knee replacement.

Biomimicry of the Achilles tendon-bone interface (enthesis) is a promising approach to design attachment sites between mechanically dissimilar materials. This thesis aimed to characterize this outstanding biological hard-soft interface to provide guidelines for biomimicry of hard-soft interfaces. Biomolecular key structures of the enthesis were identified such as the geometrical and compositional transition of fibers at the interface as well as biomarkers of cell differentiation., Biomimetik des Achillessehnen-Knochen-Übergangs (Enthese) ist ein vielversprechender Lösungsansatz zur Entwicklung von Übergängen zwischen harten und weichen Materialien. Diese Dissertation charakterisierte den herausragenden biologischen hart-weich Übergang Enthese, um Richtlinien für Biomimetik von hart-weich Übergängen bereitzustellen. Biomolekulare Leitstrukturen der Enthese wurden identifiziert, unter anderem die Veränderung der Geometrie und Zusammensetzung der Fasern am Übergang sowie Biomarker der Zelldifferenzierung.

Biomimicry of the Achilles tendon-bone interface (enthesis) is a promising approach to design attachment sites between mechanically dissimilar materials. This thesis aimed to characterize this outstanding biological hard-soft interface to provide guidelines for biomimicry of hard-soft interfaces. Biomolecular key structures of the enthesis were identified such as the geometrical and compositional transition of fibers at the interface as well as biomarkers of cell differentiation., Biomimetik des Achillessehnen-Knochen-Übergangs (Enthese) ist ein vielversprechender Lösungsansatz zur Entwicklung von Übergängen zwischen harten und weichen Materialien. Diese Dissertation charakterisierte den herausragenden biologischen hart-weich Übergang Enthese, um Richtlinien für Biomimetik von hart-weich Übergängen bereitzustellen. Biomolekulare Leitstrukturen der Enthese wurden identifiziert, unter anderem die Veränderung der Geometrie und Zusammensetzung der Fasern am Übergang sowie Biomarker der Zelldifferenzierung.

Accurate segmentation of medical images is an important step towards analyzing and tracking disease related morphological alterations in the anatomy. Convolutional neural networks (CNNs) have recently emerged as a powerful tool for many segmentation tasks in medical imaging. The performance of CNNs strongly depends on the size of the training data and combining data from different sources is an effective strategy for obtaining larger training datasets. However, this is often challenged by heterogeneous labeling of the datasets. For instance, one of the dataset may be missing labels or a number of labels may have been combined into a super label. In this work we propose a cost function which allows integration of multiple datasets with heterogeneous label subsets into a joint training. We evaluated the performance of this strategy on thigh MR and a cardiac MR datasets in which we artificially merged labels for half of the data. We found the proposed cost function substantially outperforms a naive masking approach, obtaining results very close to using the full annotations., Comment: Accepted for presentation at 9th International Conference on Machine Learning in Medical Imaging (MLMI 2018)

Osteoarthritis (OA) is the most common joint disorder. The osteoarthritis initiative (OAI) is a multicentre, longitudinal, prospective observational cohort study of knee OA that aims to provide publicly accessible clinical datasets, images and biospecimens, to enable researchers to investigate factors that influence the onset and development of OA, and evaluate biomarkers that predict and track the course of the disease. In this Perspectives, we describe the rationale and design of the OAI and its cohort, discuss imaging protocols and summarize image analyses completed to date. We include descriptive analyses of publicly available longitudinal (2-year) data of changes in cartilage thickness in a core sample of 600 knees from 590 participants in the OAI progression subcohort. Furthermore, we describe published methodological and applied imaging research that has emerged from OAI pilot studies and OAI data releases, and how these studies might contribute to clinical development of biomarkers for assessing the efficacy of intervention trials.

PurposeTo assess whether magnetic resonance (MR) imaging-based cross-sectional measures of structural joint damage can be used to predict knee replacement during the following year.Materials and methodsParticipants were drawn from the Osteoarthritis Initiative, a longitudinal observational study that includes 4796 participants who have knee osteoarthritis or are at risk. The HIPAA-compliant protocol was approved by the institutional review boards of all participating centers, and written informed consent was obtained from all participants. During the 5 years of follow-up, 199 knees underwent knee replacement and were matched with 199 control knees that did not undergo knee replacement. Knees were matched according to radiographic disease stage and patient sex and age. All knees that underwent knee replacement and had MR images available from the year before surgery were included. MR images were assessed for cartilage damage, bone marrow lesions, meniscal damage, meniscal extrusion, synovitis, and effusion prior to reported knee replacement. Conditional logistic regression was applied to assess the risk of knee replacement. Analyses were performed on a compartmental and knee level.ResultsParticipants had a mean age ± standard deviation of 64.2 years ± 8.4 (range, 47-82 years) and were predominantly women (232 of 398 participants, 58.3%). Risk for knee replacement was significantly increased for knees that exhibited two or more subregions with severe cartilage loss (odds ratio [OR], 16.5; 95% confidence interval [CI]: 3.96, 68.76), more than two subregions with bone marrow lesions (OR, 4.00; 95% CI: 1.75, 9.16), medial meniscal maceration (OR, 1.84; 95% CI: 1.13, 2.99), effusion (OR, 4.75; 95% CI: 2.55, 8.85), or synovitis (OR, 2.17; 95% CI: 1.33, 3.56), but not extrusion (OR, 1.00; 95% CI: 0.60,1.67), when compared with knees that did not exhibit these features as the reference standard.ConclusionApart from meniscal extrusion, all features of tissue abnormalities at

ObjectiveTo explore whether baseline to 12-month followup change in femorotibial cartilage thickness differs between subjects who received a total knee arthroplasty (TKA) between 24 and 60 months from those without TKA (non-TKA).MethodsIn this prospective cohort study, 531 right knees from Osteoarthritis Initiative participants with definite radiographic knee osteoarthritis (Kellgren/Lawrence [K/L] grades 2-4) were studied. Segmentation was applied to coronal fast low-angle shot magnetic resonance images, to quantitatively determine cartilage thickness in 16 femorotibial subregions. Unadjusted P values (t-tests) and P values adjusted for age, baseline body mass index (BMI), K/L grade, and sex (generalized estimating equation models) were used to evaluate differences in longitudinal 1-year rates of cartilage thickness between TKAs and non-TKAs, with total knee arthroplasty status as fixed effect.ResultsOf the 531 participants (mean ± SD ages 63 ± 9 years, BMI 30 ± 4.8 kg/m(2)), 40 received a femorotibial TKA within 4 years. At baseline, TKAs had thinner medial and lateral femorotibial cartilage (-15%; P < 0.001) than non-TKAs. Longitudinal cartilage thickness change was significantly greater in TKAs than in non-TKAs in the total femorotibial joint (area under the curve [AUC] 0.64), the lateral compartment (AUC 0.66), both tibiae (AUC ≥ 0.61), and the first 9 (of 16) ordered values of subregion change (AUC 0.64-0.69). Discrimination was stronger for TKAs that occurred at 24 and 36 months (n = 18) than for those at 48 and 60 months (n = 22).ConclusionKnees with incident TKA displayed smaller baseline cartilage thickness and greater lateral as well as location-independent ordered value femorotibial cartilage loss than non-TKAs. Discrimination of cartilage loss was greater for TKAs occurring within 2 years after the measurement than for those occurring later.

Objectives: Finite-element-models (FEM) are a promising technology to predict bone strength and fracture risk. Usually, the highest spatial resolution technically available is used, but this requires excessive computation time and memory in numerical simulations of large volumes. Thus, FEM were compared at decreasing resolutions with respect to local strain distribution and prediction of failure load to (1) validate MDCT-based FEM and to (2) optimize spatial resolution to save computation time. Materials and methods: 20 cylindrical trabecular bone specimens (diameter 12 mm, length 15-20 mm) were harvested from elderly formalin-fixed human thoracic spines. All specimens were examined by micro-CT (isotropic resolution 30 pm) and whole-body multi-row-detector computed tomography (MDCT, 250 mu m x 250 mu m x 500 mu m). The resolution of all datasets was lowered in eight steps to similar to 2000 mu m x 2000 mu m x 500 mu m and FEM were calculated at all resolutions. Failure load was determined by biomechanical testing. Probability density functions of local micro-strains were compared in all datasets and correlations between FEM-based and biomechanically measured failure loads were determined. Results: The distribution of local micro-strains was similar for micro-CT and MDCT at comparable resolutions and showed a shift toward higher average values with decreasing resolution, corresponding to the increasing apparent trabecular thickness. Small micro-strains (epsilon(eff) < 0.005) could be calculated down to 250 mu m x 250 mu m x 500 mu m. Biomechanically determined failure load showed significant correlations with all FEM, up to r= 0.85 and did not significantly change with lower resolution but decreased with high thresholds, due to loss of trabecular connectivity. Conclusion: When choosing connectivity-preserving thresholds, both micro-CT- and MDCT-based finiteelement-models well predicted failure load and still accurately revealed the distribution of local microstrains

We investigate the use of different trabecular bone descriptors and advanced machine learning tech niques to complement standard bone mineral density (BMD) measures derived from dual-energy x-ray absorptiometry (DXA) for improving clinical assessment of osteoporotic fracture risk. For this purpose, volumes of interest were extracted from the head, neck, and trochanter of 146 ex vivo proximal femur specimens on multidetector computer tomography. The trabecular bone captured was characterized with (1) statistical moments of the BMD distribution, (2) geometrical features derived from the scaling index method (SIM), and (3) morphometric parameters, such as bone fraction, trabecular thickness, etc. Feature sets comprising DXA BMD and such supplemental features were used to predict the failure load (FL) of the specimens, previously determined through biomechanical testing, with multiregression and support vector regression. Prediction performance was measured by the root mean square error (RMSE); correlation with measured FL was evaluated using the coefficient of determination R2. The best prediction performance was achieved by a combination of DXA BMD and SIM-derived geometric features derived from the femoral head (RMSE: 0.869 ± 0.121, R2: 0.68 ± 0.079), which was significantly better than DXA BMD alone (RMSE: 0.948 ± 0.119, R2: 0.61 ± 0.101) (p < 10-4). For multivariate feature sets, SVR outperformed multiregression (p < 0.05). These results suggest that supplementing standard DXA BMD measurements with sophisticated femoral trabecular bone characterization and supervised learning techniques can significantly improve biomechanical strength prediction in proximal femur specimens.

Objectives: Finite-element-models (FEM) are a promising technology to predict bone strength and fracture risk. Usually, the highest spatial resolution technically available is used, but this requires excessive computation time and memory in numerical simulations of large volumes. Thus, FEM were compared at decreasing resolutions with respect to local strain distribution and prediction of failure load to (1) validate MDCT-based FEM and to (2) optimize spatial resolution to save computation time. Materials and methods: 20 cylindrical trabecular bone specimens (diameter 12 mm, length 15-20 mm) were harvested from elderly formalin-fixed human thoracic spines. All specimens were examined by micro-CT (isotropic resolution 30 pm) and whole-body multi-row-detector computed tomography (MDCT, 250 mu m x 250 mu m x 500 mu m). The resolution of all datasets was lowered in eight steps to similar to 2000 mu m x 2000 mu m x 500 mu m and FEM were calculated at all resolutions. Failure load was determined by biomechanical testing. Probability density functions of local micro-strains were compared in all datasets and correlations between FEM-based and biomechanically measured failure loads were determined. Results: The distribution of local micro-strains was similar for micro-CT and MDCT at comparable resolutions and showed a shift toward higher average values with decreasing resolution, corresponding to the increasing apparent trabecular thickness. Small micro-strains (epsilon(eff) < 0.005) could be calculated down to 250 mu m x 250 mu m x 500 mu m. Biomechanically determined failure load showed significant correlations with all FEM, up to r= 0.85 and did not significantly change with lower resolution but decreased with high thresholds, due to loss of trabecular connectivity. Conclusion: When choosing connectivity-preserving thresholds, both micro-CT- and MDCT-based finiteelement-models well predicted failure load and still accurately revealed the distribution of local microstrains

A high degree of meniscal body extrusion on knee magnetic resonance imaging has been shown to be strongly associated with development of knee osteoarthritis. However, very little is known about meniscal position in the asymptomatic knee and its natural history. Hence our objective was to study meniscal body position and its change over 4 years in asymptomatic adults.

Background To determine the validity of a semi-automated segmentation of bone marrow lesions (BMLs) in the knee. Methods Construct validity of the semi-automated BML segmentation method was explored in two studies performed using sagittal intermediate weighted, turbo spine echo, fat-suppressed magnetic resonance imaging sequences obtained from the Osteoarthritis Initiative. The first study (n = 48) evaluated whether tibia BML volume was different across Boston Leeds Osteoarthritis Knee Scores (BLOKS) for tibia BMLs (semiquantitative grades 0 to 3). In the second study (n = 40), we evaluated whether BML volume change was associated with changes in cartilage parameters. The knees in both studies were segmented by one investigator. We performed Wilcoxon signed-rank tests to determine if tibia BML volume was different between adjacent BLOKS BML scores and calculated Spearman correlation coefficients to assess the relationship between 2-year BML volume change and 2-year cartilage morphometry change (significance was p ≤ 0.05). Results BML volume was significantly greater between BLOKS BML score 0 and 1 (z = 2.85, p = 0.004) and BLOKS BML scores 1 and 2 (z = 3.09, p = 0.002). There was no significant difference between BLOKS BML scores 2 and 3 (z = −0.30, p = 0.77). Increased tibia BML volume was significantly related to increased tibia denuded area (Spearman r = 0.42, p = 0.008), decreased tibia cartilage thickness (Spearman r = −0.46, p = 0.004), increased femur denuded area (Spearman r = 0.35, p = 0.03), and possibly decreased femur cartilage thickness (Spearman r = −0.30, p = 0.07) but this last finding was not statistically significant. Conclusion The new, efficient, and reliable semi-automated BML segmentation method provides valid BML volume measurements that increase with greater BLOKS BML scores and confirms previous reports that BML size is associated with longitudinal cartilage loss.

Background To determine the validity of a semi-automated segmentation of bone marrow lesions (BMLs) in the knee. Methods Construct validity of the semi-automated BML segmentation method was explored in two studies performed using sagittal intermediate weighted, turbo spine echo, fat-suppressed magnetic resonance imaging sequences obtained from the Osteoarthritis Initiative. The first study (n = 48) evaluated whether tibia BML volume was different across Boston Leeds Osteoarthritis Knee Scores (BLOKS) for tibia BMLs (semiquantitative grades 0 to 3). In the second study (n = 40), we evaluated whether BML volume change was associated with changes in cartilage parameters. The knees in both studies were segmented by one investigator. We performed Wilcoxon signed-rank tests to determine if tibia BML volume was different between adjacent BLOKS BML scores and calculated Spearman correlation coefficients to assess the relationship between 2-year BML volume change and 2-year cartilage morphometry change (significance was p ≤ 0.05). Results BML volume was significantly greater between BLOKS BML score 0 and 1 (z = 2.85, p = 0.004) and BLOKS BML scores 1 and 2 (z = 3.09, p = 0.002). There was no significant difference between BLOKS BML scores 2 and 3 (z = −0.30, p = 0.77). Increased tibia BML volume was significantly related to increased tibia denuded area (Spearman r = 0.42, p = 0.008), decreased tibia cartilage thickness (Spearman r = −0.46, p = 0.004), increased femur denuded area (Spearman r = 0.35, p = 0.03), and possibly decreased femur cartilage thickness (Spearman r = −0.30, p = 0.07) but this last finding was not statistically significant. Conclusion The new, efficient, and reliable semi-automated BML segmentation method provides valid BML volume measurements that increase with greater BLOKS BML scores and confirms previous reports that BML size is associated with longitudinal cartilage loss.

ObjectiveTo explore and to compare the magnitude and spatial pattern of in vivo femorotibial cartilage deformation in healthy and in osteoarthritic (OA) knees.MethodsOne knee each in 30 women (age: 55 ± 6 years; BMI: 28 ± 2.4 kg/m(2); 11 healthy and 19 with radiographic femorotibial OA) was examined at 3Tesla using a coronal fat-suppressed gradient echo SPGR sequence. Regional and subregional femorotibial cartilage thickness was determined under unloaded and loaded conditions, with 50% body weight being applied to the knee in 20° knee flexion during imaging.ResultsCartilage became significantly (p < 0.05) thinner during loading in the medial tibia (-2.7%), the weight-bearing medial femur (-4.1%) and in the lateral tibia (-1.8%), but not in the lateral femur (+0.1%). The magnitude of deformation in the medial tibia and femur tended to be greater in osteoarthritic knees than in healthy knees. The subregional pattern of cartilage deformation was similar for the different stages of radiographic OA.ConclusionOsteoarthritic cartilage tended to display greater deformation upon loading than healthy cartilage, suggesting that knee OA affects the mechanical properties of cartilage. The pattern of in vivo deformation indicated that cartilage loss in OA progression is mechanically driven.

ObjectiveTo explore and to compare the magnitude and spatial pattern of in vivo femorotibial cartilage deformation in healthy and in osteoarthritic (OA) knees.MethodsOne knee each in 30 women (age: 55 ± 6 years; BMI: 28 ± 2.4 kg/m(2); 11 healthy and 19 with radiographic femorotibial OA) was examined at 3Tesla using a coronal fat-suppressed gradient echo SPGR sequence. Regional and subregional femorotibial cartilage thickness was determined under unloaded and loaded conditions, with 50% body weight being applied to the knee in 20° knee flexion during imaging.ResultsCartilage became significantly (p < 0.05) thinner during loading in the medial tibia (-2.7%), the weight-bearing medial femur (-4.1%) and in the lateral tibia (-1.8%), but not in the lateral femur (+0.1%). The magnitude of deformation in the medial tibia and femur tended to be greater in osteoarthritic knees than in healthy knees. The subregional pattern of cartilage deformation was similar for the different stages of radiographic OA.ConclusionOsteoarthritic cartilage tended to display greater deformation upon loading than healthy cartilage, suggesting that knee OA affects the mechanical properties of cartilage. The pattern of in vivo deformation indicated that cartilage loss in OA progression is mechanically driven.

Background: Meniscus extrusion or hypertrophy may occur in knee osteoarthritis (OA). However, currently no data are available on the position and size of the meniscus in asymptomatic men and women with normal meniscus integrity. Methods: Three-dimensional coronal DESSwe MRIs were used to segment and quantitatively measure the size and position of the medial and lateral menisci, and their correlation with sex, height, weight, and tibial plateau area. 102 knees (40 male and 62 female) were drawn from the Osteoarthritis Initiative "non-exposed" reference cohort, including subjects without symptoms, radiographic signs, or risk factors for knee OA. Knees with MRI signs of meniscus lesions were excluded. Results: The tibial plateau area was significantly larger (p < 0.001) in male knees than in female ones (+23% medially; +28% laterally), as was total meniscus surface area (p < 0.001, +20% medially; +26% laterally). Ipsi-compartimental tibial plateau area was more strongly correlated with total meniscus surface area in men (r=.72 medially; r=.62 laterally) and women (r=.67; r=.75) than contra-compartimental or total tibial plateau area, body height or weight. The ratio of meniscus versus tibial plateau area was similar between men and women (p=0.22 medially; p=0.72 laterally). Tibial coverage by the meniscus was similar between men and women (50% medially; 58% laterally), but "physiological" medial meniscal extrusion was greater in women (1.83 +/- 1.06mm) than in men (1.24mm +/- 1.18mm; p=0.011). Conclusions: These data suggest that meniscus surface area strongly scales with (ipsilateral) tibial plateau area across both sexes, and that tibial coverage by the meniscus is similar between men and women.