In Vivo Three-Dimensional Geometric Reconstruction of the Mouse Aortic Heart Valve.

Aortic valve (AV) disease is a common valvular lesion in the United States, present in about 5% of the population at age 65 with increasing prevalence with advancing age. While current replacement heart valves have extended life for many, their long-term use remains hampered by limited durability. Non-surgical treatments for AV disease do not yet exist, in large part because our understanding of AV disease etiology remains incomplete. The direct study of human AV disease remains hampered by the fact that clinical data is only available at the time of treatment, where the disease is at or near end stage and any time progression information has been lost. Large animal models, long used to assess replacement AV devices, cannot yet reproduce AV disease processes. As an important alternative mouse animal models are attractive for their ability to perform genetic studies of the AV disease processes and test potential pharmaceutical treatments. While mouse models have been used for cellular and genetic studies of AV disease, their small size and fast heart rates have hindered their use for tissue- and organ-level studies. We have recently developed a novel ex vivo micro-CT-based methodology to 3D reconstruct murine heart valves and estimate the leaflet mechanical behaviors (Feng et al. in Sci Rep 13(1):12852, 2023). In the present study, we extended our approach to 3D reconstruction of the in vivo functional murine AV (mAV) geometry using high-frequency four-dimensional ultrasound (4DUS). From the resulting 4DUS images we digitized the mAV mid-surface coordinates in the fully closed and fully opened states. We then utilized matched high-resolution µCT images of ex vivo mouse mAV to develop mAV NURBS-based geometric model. We then fitted the mAV geometric model to the in vivo data to reconstruct the 3D in vivo mAV geometry in the closed and open states in n = 3 mAV. Results demonstrated high fidelity geometric results. To our knowledge, this is the first time such reconstruction was ever achieved. This robust assessment of in vivo mAV leaflet kinematics in 3D opens up the possibility for longitudinal characterization of murine models that develop aortic valve disease.

Machine learning-based automated scan prescription of lumbar spine MRI acquisitions.

PURPOSE: High quality scan prescription that optimally covers the area of interest with scan planes aligned to relevant anatomical structures is crucial for error-free radiologic interpretation. The goal of this project was to develop a machine learning pipeline for oblique scan prescription that could be trained on localizer images and metadata from previously acquired MR exams. METHODS: A novel Multislice Rotational Region-based Convolutional Neural Network (MS-R2CNN) architecture was developed. Based on this architecture, models for automated prescription sagittal lumbar spine acquisitions from axial, sagittal, and coronal localizer slices were trained. The automated prescription pipeline was integrated with the scanner console software and evaluated in experiments with healthy volunteers (N = 3) and patients with lower-back pain (N = 20). RESULTS: Experiments in healthy volunteers demonstrated high accuracy of automated prescription in all subjects. There was good agreement between alignment and coverage of manual and automated prescriptions, as well as consistent views of the lumbar spine at different positions of the subjects within the scanner bore. In patients with lower-back pain, the generated prescription was applied in 18 cases (90% of the total number). None of the cases required major adjustment, while in 11 cases (55%) there were minor manual adjustments to the generated prescription. CONCLUSIONS: This study demonstrates the ability of oriented object detection-based models to be trained to prescribe oblique lumbar spine MRI acquisitions without the need of manual annotation or feature engineering and the feasibility of using machine learning-based pipelines on the scanner for automated prescription of MRI acquisitions.

Lessons learned from implementing a diversity, equity, and inclusion curriculum for health research professionals at a large academic research institution.

Objective: Despite advances in incorporating diversity and structural competency into medical education curriculum, there is limited curriculum for public health research professionals. We developed and implemented a four-part diversity, equity, and inclusion (DEI) training series tailored for academic health research professionals to increase foundational knowledge of core diversity concepts and improve skills. Methods: We analyzed close- and open-ended attendee survey data to evaluate within- and between-session changes in DEI knowledge and perceived skills. Results: Over the four sessions, workshop attendance ranged from 45 to 82 attendees from our 250-person academic department and represented a mix of staff (64%), faculty (25%), and trainees (11%). Most identified as female (74%), 28% as a member of an underrepresented racial and ethnic minority (URM) group, and 17% as LGBTQI. During all four sessions, attendees increased their level of DEI knowledge, and within sessions two through four, attendees' perception of DEI skills increased. We observed increased situational DEI awareness as higher proportions of attendees noted disparities in mentoring and opportunities for advancement/promotion. An increase in a perceived lack of DEI in the workplace as a problem was observed; but only statistically significant among URM attendees. Discussion: Developing applied curricula yielded measurable improvements in knowledge and skills for a diverse health research department of faculty, staff, and students. Nesting this training within a more extensive program of departmental activities to improve climate and address systematic exclusion likely contributed to the series' success. Additional research is underway to understand the series' longer-term impact on applying skills for behavior change.

Experimental dataset on the in-plane tensile, shear, and compressive properties of a carbon-epoxy twill woven composite.

This data article presents experimental data on the in-plane mechanical behavior of a carbon-epoxy twill woven composite. Properties under tension, shear, and compression are measured and reported, which include force vs. stroke curves, stress vs. strain curves, in-plane on-axis and off-axis moduli, in-plane shear modulus, tensile and compressive strengths, post-peak residual stress under compression, and on-axis and off-axis Poisson ratios. Laminate plates of the composite were ordered from a commercial vendor and specimens of desired dimensions were cut using a waterjet cutter. Tests were conducted in accordance with ASTM standards D3039 and D6641, under on-axis and off-axis tension, and under on-axis compression. The data represents a complete set of in-plane mechanical properties for the composite and can be used directly as lamina level input to numerical FEA models and design analyses with woven composite laminates. It can also serve as benchmark for the calibration and validation of these models. It can be used to calculate properties for other off-axis configurations using transformation equations. Since the data is intended to be a lamina level input, it can be used to determine and model the in-plane behavior of any laminate layup with this composite. The data also serves to demonstrate the marked anisotropy and tension compression asymmetry exhibited by woven composites.

Uncovering associations between data-driven learned qMRI biomarkers and chronic pain.

Knee pain is the most common and debilitating symptom of knee osteoarthritis (OA). While there is a perceived association between OA imaging biomarkers and pain, there are weak or conflicting findings for this relationship. This study uses Deep Learning (DL) models to elucidate associations between bone shape, cartilage thickness and T2 relaxation times extracted from Magnetic Resonance Images (MRI) and chronic knee pain. Class Activation Maps (Grad-CAM) applied on the trained chronic pain DL models are used to evaluate the locations of features associated with presence and absence of pain. For the cartilage thickness biomarker, the presence of features sensitive for pain presence were generally located in the medial side, while the features specific for pain absence were generally located in the anterior lateral side. This suggests that the association of cartilage thickness and pain varies, requiring a more personalized averaging strategy. We propose a novel DL-guided definition for cartilage thickness spatial averaging based on Grad-CAM weights. We showed a significant improvement modeling chronic knee pain with the inclusion of the novel biomarker definition: likelihood ratio test p-values of 7.01 × 10-33 and 1.93 × 10-14 for DL-guided cartilage thickness averaging for the femur and tibia, respectively, compared to the cartilage thickness compartment averaging.

Deep learning for large scale MRI-based morphological phenotyping of osteoarthritis.

Osteoarthritis (OA) develops through heterogenous pathophysiologic pathways. As a result, no regulatory agency approved disease modifying OA drugs are available to date. Stratifying knees into MRI-based morphological phenotypes may provide insight into predicting future OA incidence, leading to improved inclusion criteria and efficacy of therapeutics. We trained convolutional neural networks to classify bone, meniscus/cartilage, inflammatory, and hypertrophy phenotypes in knee MRIs from participants in the Osteoarthritis Initiative (n = 4791). We investigated cross-sectional association between baseline morphological phenotypes and baseline structural OA (Kellgren Lawrence grade > 1) and symptomatic OA. Among participants without baseline OA, we evaluated association of baseline phenotypes with 48-month incidence of structural OA and symptomatic OA. The area under the curve of bone, meniscus/cartilage, inflammatory, and hypertrophy phenotype neural network classifiers was 0.89 ± 0.01, 0.93 ± 0.03, 0.96 ± 0.02, and 0.93 ± 0.02, respectively (mean ± standard deviation). Among those with no baseline OA, bone phenotype (OR: 2.99 (95%CI: 1.59-5.62)) and hypertrophy phenotype (OR: 5.80 (95%CI: 1.82-18.5)) each respectively increased odds of developing incident structural OA and symptomatic OA at 48 months. All phenotypes except meniscus/cartilage increased odds of undergoing total knee replacement within 96 months. Artificial intelligence can rapidly stratify knees into structural phenotypes associated with incident OA and total knee replacement, which may aid in stratifying patients for clinical trials of targeted therapeutics.

Towards understanding mechanistic subgroups of osteoarthritis: 8-year cartilage thickness trajectory analysis.

Many studies have validated cartilage thickness as a biomarker for knee osteoarthritis (OA); however, few studies investigate beyond cross-sectional observations or comparisons across two timepoints. By characterizing the trajectory of cartilage thickness changes over 8 years in healthy individuals from the OA initiative data set, this study discovers associations between the dynamics of cartilage changes and OA incidence. A fully automated cartilage segmentation and thickness measurement method were developed and validated against manual measurements: mean absolute error = 0.11-0.14 mm (n = 4129 knees) and automatic reproducibility = 0.04-0.07 mm (n = 316 knees). The mean thickness for the medial and lateral tibia (MT, LT), central weight-bearing medial and lateral femur (cMF, cLF), and patella (P) cartilage compartments were quantified for 1453 knees at seven timepoints. Trajectory subgroups were defined per cartilage compartment such as stable, thinning to thickening, accelerated thickening, plateaued thickening, thickening to thinning, accelerated thinning, or plateaued thinning. For tibiofemoral compartments, the stable (22%-36%) and plateaued thinning (22%-37%) trajectories were the most common, with an average initial velocity (µm/month), acceleration (µm/month2 ) for the plateaued thinning trajectories LT: -2.66, 0.0326; MT: -2.49, 0.0365; cMF: -3.51, 0.0509; and cLF: -2.68, 0.041. In the patella compartment, the plateaued thinning (35%) and thickening to thinning (24%) trajectories were the most common, with an average initial velocity, acceleration for each -4.17, 0.0424; 1.95, -0.0835. Knees with nonstable trajectories had higher adjusted odds of OA incidence than stable trajectories: accelerated thickening, accelerated thinning, and plateaued thinning trajectories of the MT had adjusted odds ratio (OR) of 18.9, 5.48, and 1.47, respectively; in the cMF, adjusted OR of 8.55, 10.1, and 2.61, respectively.

T2 analysis of the entire osteoarthritis initiative dataset.

While substantial work has been done to understand the relationships between cartilage T2 relaxation times and osteoarthritis (OA), diagnostic and prognostic abilities of T2 on a large population yet need to be established. Using 3921 manually annotated 2D multi-slice multi-echo spin-echo magnetic resonance imaging volume, a segmentation model for automatic knee cartilage segmentation was built and evaluated. The optimized model was then used to calculate T2 values on the entire osteoarthritis initiative (OAI) dataset composed of longitudinal acquisitions of 4796 unique patients, 25 729 magnetic resonance imaging studies in total. Cross-sectional relationships between T2 values, OA risk factors, radiographic OA, and pain were analyzed in the entire OAI dataset. The performance of T2 values in predicting the future incidence of radiographic OA as well as total knee replacement (TKR) were also explored. Automatic T2 values were comparable with manual ones. Significant associations between T2 relaxation times and demographic and clinical variables were found. Subjects in the highest 25% quartile of tibio-femoral T2 values had a five times higher risk of radiographic OA incidence 2 years later. Elevation of medial femur T2 values was significantly associated with TKR after 5 years (coeff = 0.10; P = .036; CI = [0.01,0.20]). Our investigation reinforces the predictive value of T2 for future incidence OA and TKR. The inclusion of T2 averages from the automatic segmentation model improved several evaluation metrics when compared to only using demographic and clinical variables.

Learning osteoarthritis imaging biomarkers from bone surface spherical encoding.

PURPOSE: To learn bone shape features from spherical bone map of knee MRI images using established convolutional neural networks (CNN) and use these features to diagnose and predict osteoarthritis (OA). METHODS: A bone segmentation model was trained on 25 manually annotated 3D MRI volumes to segment the femur, tibia, and patella from 47 078 3D MRI volumes. Each bone segmentation was converted to a 3D point cloud and transformed into spherical coordinates. Different fusion strategies were performed to merge spherical maps obtained by each bone. A total of 41 822 merged spherical maps with corresponding Kellgren-Lawrence grades for radiographic OA were used to train a CNN classifier model to diagnose OA using bone shape learned features. Several OA Diagnosis models were tested and the weights for each trained model were transferred to the OA Incidence models. The OA incidence task consisted of predicting OA from a healthy scan within a range of eight time points, from 1 y to 8 y. The validation performance was compared and the test set performance was reported. RESULTS: The OA Diagnosis model had an area-under-the-curve (AUC) of 0.905 on the test set with a sensitivity and specificity of 0.815 and 0.839. The OA Incidence models had an AUC ranging from 0.841 to 0.646 on the test set for the range from 1 y to 8 y. CONCLUSION: Bone shape was successfully used as a predictive imaging biomarker for OA. This approach is novel in the field of deep learning applications for musculoskeletal imaging and can be expanded to other OA biomarkers.

Patterns of Change Over Time in Knee Bone Shape Are Associated with Sex.

BACKGROUND: Knee osteoarthritis (OA) is more common in females than in males; however, the biological mechanisms for the difference in sex in patients with knee OA are not well understood. Knee shape is associated with OA and with sex, but the patterns of change in the bone's shape over time and their relation to sex and OA are unknown and may help inform how sex is associated with shape and OA and whether the effect is exerted early or later in life.Questions/purposes (1) Does knee shape segregate stably into different groups of trajectories of change (groups of knees that share similar patterns of changes in bone shape over time)? (2) Do females and males have different trajectories of bone shape changes? (3) Is radiographic OA at baseline associated with trajectories of bone shape changes? METHODS: We used data collected from the NIH-funded Osteoarthritis Initiative (OAI) to evaluate a cohort of people aged 45 to 79 years at baseline who had either symptomatic knee OA or were at high risk of having it. The OAI cohort included 4796 participants (58% females; n = 2804) at baseline who either had symptomatic knee OA (defined as having radiographic tibiofemoral knee OA and answering positively to the question "have you had pain, aching or stiffness around the knee on most days for at least one month during the past 12 months") or were at high risk of symptomatic knee OA (defined as having knee symptoms during the prior 12 months along with any of the following: overweight; knee injury; knee surgery other than replacement; family history of total knee replacement for OA; presence of Heberden's nodes; daily knee bending activity) or were part of a small nonexposed subcohort. From these participants, we limited the eligible group to those with radiographs available and read at baseline, 2 years, and 4 years, and randomly selected participants from each OAI subcohort in a manner to enrich representation in the study of the progression and nonexposed subcohorts, which were smaller in number than the OA incidence subcohort. From these patients, we randomly sampled 473 knees with radiographs available at baseline, 2 years, and 4 years. We outlined the shape of the distal femur and proximal tibia on radiographs at all three timepoints using statistical shape modelling. Five modes (each mode represents a particular type of knee bone shape variation) were derived for the proximal tibia and distal femur's shape, accounting for 78% of the total variance in shape. Group-based trajectory modelling (a statistical approach to identify the clusters of participants following a similar progression of change of bone shape over time, that is, trajectory group) was used to identify distinctive patterns of change in the bone shape for each mode. We examined the association of sex and radiographic OA at baseline with the trajectories of each bone shape mode using a multivariable polytomous regression model while adjusting for age, BMI, and race. RESULTS: Knee bone shape change trajectories segregated stably into different groups. In all modes, three distinct trajectory groups were derived, with the mean posterior probabilities (a measure of an individual's probability of being in a particular group and often used to characterize how well the trajectory model is working to describe the population) ranging from 84% to 99%, indicating excellent model fitting. For most of the modes of both the femur and tibia, the intercepts for the three trajectory groups were different; however, the rates of change were generally similar in each mode. Females and males had different trajectories of bone shape change. For Mode 1 in the femur, females were more likely to be in trajectory Groups 3 (odds ratio 30.2 [95% CI 12.2 to 75.0]; p < 0.001) and 2 than males (OR 4.1 [95% CI 2.3 to 7.1]; p < 0.001); thus, females had increased depth of the intercondylar fossa and broader shaft width relative to epicondylar width compared with males. For Mode 1 in the tibia, females were less likely to be in trajectory Group 2 (OR 0.5 [95% CI 0.3 to 0.9]; p = 0.01) than males (that is, knees of females were less likely to display superior elevation of tibial plateau or decreased shaft width relative to head width). Radiographic OA at baseline was associated with specific shape-change trajectory groups. For Mode 1 in the femur, knees with OA were less likely to be in trajectory Groups 3 (OR 0.4 [95% CI 0.2 to 0.8]; p = 0.008) and 2 (OR 0.6 [95% CI 0.3 to 1.0]; p = 0.03) than knees without OA; thus, knees with OA had decreased depth of the intercondylar fossa and narrower shaft width relative to epicondylar width compared with knees without OA. For Mode 1 in the tibia, knees with OA were not associated with trajectory. CONCLUSIONS: The shapes of the distal femur and proximal tibia did not change much over time. Sex and baseline knee radiographic OA status are associated with the trajectory of change in the bone's shape, suggesting that both may contribute earlier in life to the associations among trajectories observed in older individuals. Future studies might explore sex-related bone shape change earlier in life to help determine when the sex-specific shapes arise and also the degree to which these sex-related shapes are alterable by injury or other events. LEVEL OF EVIDENCE: Level III, prognostic study.

Development and Validation of a Multitask Deep Learning Model for Severity Grading of Hip Osteoarthritis Features on Radiographs.

Background A multitask deep learning model might be useful in large epidemiologic studies wherein detailed structural assessment of osteoarthritis still relies on expert radiologists' readings. The potential of such a model in clinical routine should be investigated. Purpose To develop a multitask deep learning model for grading radiographic hip osteoarthritis features on radiographs and compare its performance to that of attending-level radiologists. Materials and Methods This retrospective study analyzed hip joints seen on weight-bearing anterior-posterior pelvic radiographs from participants in the Osteoarthritis Initiative (OAI). Participants were recruited from February 2004 to May 2006 for baseline measurements, and follow-up was performed 48 months later. Femoral osteophytes (FOs), acetabular osteophytes (AOs), and joint-space narrowing (JSN) were graded as absent, mild, moderate, or severe according to the Osteoarthritis Research Society International atlas. Subchondral sclerosis and subchondral cysts were graded as present or absent. The participants were split at 80% (n = 3494), 10% (n = 437), and 10% (n = 437) by using split-sample validation into training, validation, and testing sets, respectively. The multitask neural network was based on DenseNet-161, a shared convolutional features extractor trained with multitask loss function. Model performance was evaluated in the internal test set from the OAI and in an external test set by using temporal and geographic validation consisting of routine clinical radiographs. Results A total of 4368 participants (mean age, 61.0 years ± 9.2 [standard deviation]; 2538 women) were evaluated (15 364 hip joints on 7738 weight-bearing anterior-posterior pelvic radiographs). The accuracy of the model for assessing these five features was 86.7% (1333 of 1538) for FOs, 69.9% (1075 of 1538) for AOs, 81.7% (1257 of 1538) for JSN, 95.8% (1473 of 1538) for subchondral sclerosis, and 97.6% (1501 of 1538) for subchondral cysts in the internal test set, and 82.7% (86 of 104) for FOS, 65.4% (68 of 104) for AOs, 80.8% (84 of 104) for JSN, 88.5% (92 of 104) for subchondral sclerosis, and 91.3% (95 of 104) for subchondral cysts in the external test set. Conclusion A multitask deep learning model is a feasible approach to reliably assess radiographic features of hip osteoarthritis. © RSNA, 2020 Online supplemental material is available for this article.

Feasibility and Acceptability of Technology-Based Exercise and Posture Training in Older Adults With Age-Related Hyperkyphosis: Pre-Post Study.

Background: Hyperkyphosis is common among older adults, and is associated with multiple adverse health outcomes. A kyphosis-specific exercise and posture training program improves hyperkyphosis, but in-person programs are expensive to implement and maintain over longer-periods of time. It is unknown if a technology-based posture training program disseminated through a smartphone is a feasible or acceptable alternative to in-person training among older adults with hyperkyphosis. Objective: The primary purpose of this study was to assess the feasibility of subject recruitment, short-term retention and adherence, and the acceptability of a technology-based exercise and postural training program disseminated as video clip links and text messaging prompts via a smartphone. The secondary purpose was to explore the potential efficacy of this program on kyphosis, physical function and health-related quality of life in older adults with hyperkyphosis. Methods: This was a 6-week pre-post design pilot trial. We recruited community-dwelling adults ≥65 years with hyperkyphosis ≥40 (±5) degrees and access to a smartphone. The intervention had two parts: 1) exercise and posture training via video clips sent to participants daily via text messaging which included 6 weekly video clip links to be viewed on the participant's smartphone and 2) text messaging prompts to practice good posture. We determined subject recruitment, adherence, retention and acceptability of the intervention. Outcomes included change in kyphometer-measured kyphosis, occiput to wall (OTW), Short Physical Performance Battery (SPPB), Scoliosis Research Society SRS-30, Center for Epidemiological Studies Depression (CESD) and Physical Activity Scale for the Elderly (PASE). Results: 64 potential participants were recruited, 17 participants were enrolled and 12 completed post-intervention testing at 6-weeks. Average age was 71.6 (SD=4.9) years and 50% were female. Median adherence to daily video viewing was 100%, (range 14 to 100) and to practicing good posture 3 times or more per day was 71%, (range 0 to 100). Qualitative evaluation of acceptability of the intervention revealed the smartphone screen was too small for participants to view the videos well and daily prompts to practice posture were too frequent. Kyphosis, OTW and physical activity significantly improved after the 6-week intervention. Kyphosis decreased by 8 (95% CI: 12, 5) degrees (p<0.001), OTW decreased 1.9 (95% CI: 3.3, 0.7) cm (p=0.007), and physical activity measured by PASE increased 29 (95% CI: 3, 54) points (p=0.03). The health-related quality of life SRS-30 score increased 0.11 (SD=0.19) points, but it was not statistically significant, p=0.09. Conclusions: Technology-based exercise and posture training using video clip viewing and text messaging reminders is feasible and acceptable in a small cohort of older adults with hyperkyphosis. Technology-based exercise and posture training warrants further study as a potential self-management program for age-related hyperkyphosis that may be more easily disseminated than in-person training.

Associations between alcohol, smoking, and cartilage composition and knee joint morphology: Data from the Osteoarthritis Initiative.

Objective: To determine the cross-sectional associations of alcohol consumption and smoking history with magnetic resonance imaging (MRI) measures of cartilage composition (T2) and joint structure using data from the Osteoarthritis Initiative (OAI). Design: Subjects with radiographic Kellgren Lawrence right knee grades 0-2 were selected from the OAI database, and those with previously analyzed MRI cartilage T2 and semi-quantitative joint morphology gradings (WORMS) were included (n â€‹= â€‹2061). Alcohol consumption was categorized as: no drinks to <1 drink/week, 1-7 drinks/week, >7 drinks/week. Smoking history was categorized as none, current, or former. Linear regression was used to assess the relationships of alcohol consumption and smoking history with both WORMS scores and cartilage T2. Results: Subjects who consumed >7 drinks/week had significantly higher cartilage T2 than subjects who consumed <1 drink/week in the average of all cartilage regions and in three of five individual regions (coefficient range: 0.45-0.90, p â€‹< â€‹0.05). Subjects with moderate alcohol consumption (1-7 drinks per week) had higher cartilage and meniscus WORMS scores than subjects who consumed <1 drink/week (p â€‹< â€‹0.05). Current smokers had significantly higher cartilage T2 compared to non-smokers in the average of all cartilage regions and in three of five individual regions (coefficient range: 0.47-0.74, p â€‹< â€‹0.05). Conclusions: Alcohol consumption (1-7 drinks/week) was associated with worse cartilage and meniscus joint morphology, and >7 drinks/week was associated with elevated cartilage T2. Compared to non-smokers, current smokers had a more degenerated cartilage matrix as evidenced by greater cartilage T2.

Bone shape mediates the relationship between sex and incident knee osteoarthritis.

BACKGROUND: Knee bone shape differs between men and women and the incidence of knee osteoarthritis (OA) is higher in women than in men. Therefore, the purpose of the present study was to determine whether the observed difference in the incidence of knee radiographic OA (ROA) between men and women is mediated by bone shape. METHODS: We randomly sampled 304 knees from the OAI with incident ROA (i.e., development of Kellgren/Lawrence grade ≥ 2 by month 48) and 304 knees without incident ROA. We characterized distal femur and proximal tibia shape on baseline radiographs using Statistical Shape Modeling. If a specific bone shape was associated with the risk of incident ROA, marginal structural models were generated to assess the mediation effect of that bone shape on the relation of sex and risk of incident knee ROA adjusting for baseline covariates. RESULTS: Case and control participants were similar by age, sex and race, but case knees were from higher body mass index (BMI) participants (29.4 vs. 27.0; p < 0.001). Women had 49% increased odds of incident knee ROA compared with men (adjusted odds ratio (OR) = 1.49, 95% Confidence Interval (C.I.): 1.04, 2.12). There was an inconsistent mediation effect for tibial mode 2 between sex and incident knee ROA, with an indirect effect OR of 0.96 (95% C.I.: 0.91-1.00) and a direct effect OR of 1.56 (95% C.I.: 1.08-2.27), suggesting a protective effect for this mode. Similar findings were also observed for the mediation effect of tibia mode 10 and femur mode 4. These shape modes primarily involved differences in the angular relation of the heads to the shafts of the femur and tibia. CONCLUSIONS: Distal femur and proximal tibia bone shapes partially and inconsistently mediated the relationship between sex and incident knee OA. Women had a higher risk of incident ROA, and specific bone shapes modestly protected them from even higher risk of ROA. The clinical significance of these findings warrant further investigation.

Association of weight change with progression of meniscal intrasubstance degeneration over 48 months: Data from the Osteoarthritis Initiative.

OBJECTIVES: To investigate the association of weight change over 48 months with progression of meniscal intrasubstance degeneration (MID). METHODS: We studied 487 subjects with MID at baseline and after 48 months using 3-T MRI with the same protocol (FSE sequences with and without fat suppression). These participants lost weight (≥3%, n = 141), had moderate weight gain (3-10%, n = 77), substantial weight gain (>10%, n = 15) or maintained stable weight (n = 254). Progression of MID to a meniscal tear was assessed using the WORMS grading system and compared among weight change groups using logistic regression. ANOVA and chi-square tests were used to study the differences in subjects' characteristics. RESULTS: Progression of MID increased from weight loss to substantial weight gain (p < 0.001) and was significantly more likely with both moderate weight gain (odds ratio [OR], 4.9; 95% confidence interval [CI] 2.4-8.9) and substantial weight gain (OR, 9.5; 95% CI 3.2-28.5) compared to stable weight. Results were similar in both menisci for moderate weight gain (medial: OR, 6.8; 95% CI 3.5-11.3; lateral: OR, 2.6; 95% CI 1.1-6.6) and substantial weight gain (medial: OR, 21.0; 95% CI 5.1-80.7; lateral: OR, 9.7; 95% CI 0.95-100.2). CONCLUSION: Weight gain is associated with an increased likelihood that meniscal intrasubstance degeneration will progress with the risk increasing with greater weight gain. KEY POINTS: • Subjects who gained weight were more likely to develop meniscal tears. • Greater amount of weight gain was associated with an increasing likelihood of progression. • Prevention of weight gain has health benefits for the meniscus.

Fine-mapping, novel loci identification, and SNP association transferability in a genome-wide association study of QRS duration in African Americans.

The electrocardiographic QRS duration, a measure of ventricular depolarization and conduction, is associated with cardiovascular mortality. While single nucleotide polymorphisms (SNPs) associated with QRS duration have been identified at 22 loci in populations of European descent, the genetic architecture of QRS duration in non-European populations is largely unknown. We therefore performed a genome-wide association study (GWAS) meta-analysis of QRS duration in 13,031 African Americans from ten cohorts and a transethnic GWAS meta-analysis with additional results from populations of European descent. In the African American GWAS, a single genome-wide significant SNP association was identified (rs3922844, P = 4 × 10-14) in intron 16 of SCN5A, a voltage-gated cardiac sodium channel gene. The QRS-prolonging rs3922844 C allele was also associated with decreased SCN5A RNA expression in human atrial tissue (P = 1.1 × 10-4). High density genotyping revealed that the SCN5A association region in African Americans was confined to intron 16. Transethnic GWAS meta-analysis identified novel SNP associations on chromosome 18 in MYL12A (rs1662342, P = 4.9 × 10-8) and chromosome 1 near CD1E and SPTA1 (rs7547997, P = 7.9 × 10-9). The 22 QRS loci previously identified in populations of European descent were enriched for significant SNP associations with QRS duration in African Americans (P = 9.9 × 10-7), and index SNP associations in or near SCN5A, SCN10A, CDKN1A, NFIA, HAND1, TBX5 and SETBP1 replicated in African Americans. In summary, rs3922844 was associated with QRS duration and SCN5A expression, two novel QRS loci were identified using transethnic meta-analysis, and a significant proportion of QRS-SNP associations discovered in populations of European descent were transferable to African Americans when adequate power was achieved.

The association of distal femur and proximal tibia shape with sex: The Osteoarthritis Initiative.

OBJECTIVES: Risk of knee osteoarthritis (OA) is much higher in women than in men. Previous studies have shown that bone shape is a risk factor for knee OA. However, few studies have examined whether knee bone shape differs between men and women. The purpose of the present study was to determine whether there are differences between men and women in knee bone shape. METHODS: We used information from the NIH-funded Osteoarthritis Initiative (OAI), a cohort of persons aged 45-79 at baseline who either had symptomatic knee OA or were at high risk of it. Among participants aged between 45 and 60 years, we randomly sampled 340 knees without radiographic OA (i.e., Kellgren/Lawrence grade of 0 in central readings on baseline radiograph). We characterized distal femur and proximal tibia shape of these selected radiographs using statistical shape modeling (SSM). We performed linear regression analysis to examine the association between sex and each knee shape mode (proximal tibia and distal femur), adjusting for age, race, body mass index (BMI), and clinic site. RESULTS: The mean age was 52.7 years (±4.3 SD) for both men and women. There were 192 female and 147 male knees for the distal femur analysis. Thirteen modes were derived for femoral shape, accounting for 95.5% of the total variance. Distal femur mode 1 had the greatest difference in standardized score of knee shape between females and males (1.04, p < 0.01); modes 3, 5, 6, 8, and 12 were also significantly associated with sex. For tibial shape, 191 female knees and 149 male knees were used for the analysis. Overall, 10 modes explained 95.5% of shape variance. Of the significantly associated modes in the proximal tibia, mode 2 had the greatest difference in standardized score of bone shape between males and females (-0.30, p = 0.01); modes 3 and 4 were also significantly associated. CONCLUSION: The shapes of the distal femur and proximal tibia that form the knee joint differ by sex. Additional analyses are warranted to assess whether the difference in risk of OA between the sexes arises from bone shape differences.

Variations in Hip Shape Are Associated with Radiographic Knee Osteoarthritis: Cross-sectional and Longitudinal Analyses of the Johnston County Osteoarthritis Project.

OBJECTIVE: Hip shape by statistical shape modeling (SSM) is associated with hip radiographic osteoarthritis (rOA). We examined associations between hip shape and knee rOA given the biomechanical interrelationships between these joints. METHODS: Bilateral baseline hip shape assessments [for those with at least 1 hip with a Kellgren-Lawrence arthritis grading scale (KL) 0 or 1] from the Johnston County Osteoarthritis Project were available. Proximal femur shape was defined on baseline pelvis radiographs and evaluated by SSM, producing mean shape and continuous variables representing independent modes of variation (14 modes = 95% of shape variance). Outcomes included prevalent [baseline KL ≥ 2 or total knee replacement (TKR)], incident (baseline KL 0/1 with followup ≥ 2), and progressive knee rOA (KL increase of ≥ 1 or TKR). Limb-based logistic regression models for ipsilateral and contralateral comparisons were adjusted for age, sex, race, body mass index (BMI), and hip rOA, accounting for intraperson correlations. RESULTS: We evaluated 681 hips and 682 knees from 342 individuals (61% women, 83% white, mean age 62 yrs, BMI 29 kg/m(2)). Ninety-nine knees (15%) had prevalent rOA (4 knees with TKR). Lower modes 2 and 3 scores were associated with ipsilateral prevalent knee rOA, and only lower mode 3 scores were associated with contralateral prevalent knee rOA. No statistically significant associations were seen for incident or progressive knee rOA. CONCLUSION: Variations in hip shape were associated with prevalent, but not incident or progressive, knee rOA in this cohort, and may reflect biomechanical differences between limbs, genetic influences, or common factors related to both hip shape and knee rOA.

Femoroacetabular Impingement: Prevalent and Often Asymptomatic in Older Men: The Osteoporotic Fractures in Men Study.

BACKGROUND: The epidemiology of femoroacetabular impingement (FAI) is important but incompletely understood, because most reports arise from symptomatic populations. Investigating the prevalence of FAI in a community-based cohort could help us better understand its epidemiology and in particular the degree to which it might or might not be associated with hip pain. QUESTIONS/PURPOSES: The purposes of this study were (1) to evaluate the proportion of older (≥65 years of age) men with morphologic abnormalities consistent with FAI; and (2) to assess the association of the morphologic abnormalities with prevalent radiographic hip osteoarthritis (OA) and hip pain. METHODS: Anteroposterior radiographs were obtained in 4140 subjects (mean age±SD, 77±5 years) from the Osteoporotic Fractures in Men study. We assessed each hip for cam, pincer, and mixed FAI types using validated radiographic definitions. Both intra- and interobserver reproducibility were >0.9. Radiographic hip OA was assessed by an expert reader (intraobserver reproducibility, 0.7-0.8) using validated methods, and summary grades of 2 or greater (on a scale from 0 to 4) were used to define radiographic hip OA. Covariates including hip pain in the last 30 days were collected by questionnaires that were answered by all patients included in this report. Logistic regressions with generalized estimating equations were performed to evaluate the association of radiographic features of FAI and arthrosis. RESULTS: Pincer, cam, or mixed types of radiographic FAI had a prevalence of 57% (1748 of 3053), 29% (886 of 3053), and 14% (419 of 3053), respectively, in this group of older men. Both pincer and mixed types of FAI were associated with arthrosis but not with hip pain (odds ratio [OR], 1.63; 95% confidence interval [CI], 1.25-2.13; p<0.001 for pincer and OR, 2.49; 95% CI, 1.65-3.76; p<0.001 for mixed type). Patients with hips characterized by cam-type FAI had slightly reduced hip pain without the presence of arthrosis compared with hips without FAI (OR, 0.82; 95% CI, 0.68-0.99; p=0.037). A center-edge angle>39° and a caput-collum-diaphyseal angle<125° were associated with arthrosis (OR, 1.53; 95% CI, 1.22-1.94; p<0.001 and OR, 2.09; 95% CI, 1.24-3.51; p=0.006, respectively), but not with hip pain (OR, 0.89; 95% CI, 0.77-1.03; p<0.108 and OR, 0.99; 95% CI, 0.67-1.45; p=0.945, respectively). An impingement angle<70° was associated with less hip pain compared with hips with an impingement angle≥70° (OR, 0.76; 95% CI, 0.61-0.95; p=0.015). CONCLUSIONS: FAI is common in older men and represents more of an anatomic variant rather than a symptomatic disease. This finding should raise questions on how age, activities, and this anatomic variant each contribute to result in symptomatic disease. LEVEL OF EVIDENCE: Level III, prognostic study.

Cartilage lesion score: comparison of a quantitative assessment score with established semiquantitative MR scoring systems.

PURPOSE: To describe a scoring system for quantification of cartilage lesions (Cartilage Lesion Score [CaLS]), to determine its reproducibility, to examine the association of CaLS-detected longitudinal change with known risk factors for osteoarthritis (OA) progression by comparing a group of subjects with OA risk factors with a group of subjects without OA risk factors, and to compare the CaLS system with the established semiquantitative Whole-Organ Magnetic Resonance Imaging Score (WORMS) and Boston-Leeds Osteoarthritis Knee Score (BLOKS) systems in terms of detection of cartilage defect progression. MATERIALS AND METHODS: All subjects provided written informed consent, and the local institutional review board approved this HIPAA-compliant study. Fifty-two subjects with and 25 subjects without risk factors for knee OA were randomly selected from the Osteoarthritis Initiative. Inclusion criteria were age of 45-60 years, body mass index of 19-27 kg/m(2), and no knee pain or OA on radiographs at baseline. Baseline and 24-month follow-up right knee 3-T magnetic resonance images were analyzed with WORMS, BLOKS, and CaLS systems. Progression of cartilage lesions with each scoring system was compared by using multilevel mixed-effects linear-regression models. κ values were calculated to determine reliability. RESULTS: Intraclass coefficient values for inter- and intraobserver reliability of the CaLS system were 0.86 and 0.91, respectively. Interobserver κ value range for individual features was 0.81-0.94. The CaLS system enabled significantly higher detection of cartilage lesion progression than did WORMS or BLOKS systems (P < .001); 51.8% (56 of 108), 17.6% (19 of 108), and 13.0% (14 of 108) of the lesions progressed when analyzed with the CaLS, WORMS, and BLOKS systems, respectively. With the CaLS system, subjects with OA risk factors had significantly higher odds of progression than did subjects without risk factors (odds ratio, 2.78; P = .005). CONCLUSION: The CaLS system is a reproducible scoring system for cartilage lesions that yields an improved detection rate for monitoring progression when compared with detection rates of semiquantitative WORMS and BLOKS systems.