High angular resolution diffusion imaging (HARDI) of porcine menisci: a comparison of diffusion tensor imaging and generalized q-sampling imaging.

Background: Diffusion magnetic resonance imaging (MRI) allows for the quantification of water diffusion properties in soft tissues. The goal of this study was to characterize the 3D collagen fiber network in the porcine meniscus using high angular resolution diffusion imaging (HARDI) acquisition with both diffusion tensor imaging (DTI) and generalized q-sampling imaging (GQI). Methods: Porcine menisci (n=7) were scanned ex vivo using a three-dimensional (3D) HARDI spin-echo pulse sequence with an isotropic resolution of 500 µm at 7.0 Tesla. Both DTI and GQI reconstruction techniques were used to quantify the collagen fiber alignment and visualize the complex collagen network of the meniscus. The MRI findings were validated with conventional histology. Results: DTI and GQI exhibited distinct fiber orientation maps in the meniscus using the same HARDI acquisition. We found that crossing fibers were only resolved with GQI, demonstrating the advantage of GQI over DTI to visualize the complex collagen fiber orientation in the meniscus. Furthermore, the MRI findings were consistent with conventional histology. Conclusions: HARDI acquisition with GQI reconstruction more accurately resolves the complex 3D collagen architecture of the meniscus compared to DTI reconstruction. In the future, these technologies have the potential to nondestructively assess both normal and abnormal meniscal structure.

Influence of running on femoroacetabular joint bone-to-bone distances.

There is limited data quantifying the influence of running on hip cartilage mechanics. The goal of this investigation was to quantify changes in hip joint bone-to-bone distance in response to a 3-mile treadmill run. We acquired magnetic resonance (MR) images of the dominant hip of eight young, asymptomatic runners (five males, three females) before and immediately after they ran 3 miles at a self-selected pace on a level treadmill. The femoral heads and acetabula were semiautomatically segmented from the pre- and post-exercise MR images to generate three-dimensional models of each participant's hip that were used to compute changes in the bone-to-bone distances incurred by the running exercise. We observed a significant 3% decrease in bone-to-bone distance from 3.47 ± 0.20 to 3.36 ± 0.22 mm between the femoral head and acetabulum after a 3-mile treadmill run (mean ± 95% confidence interval; p = 0.03). These findings provide new baseline data describing how running impacts the hip joint in young, asymptomatic runners.

The effects of a 6-month weight loss intervention on physical function and serum biomarkers in older adults with and without osteoarthritis.

Objective: To examine the effects of a 6-month weight loss intervention on physical function, inflammatory biomarkers, and metabolic biomarkers in both those with and without osteoarthritis (OA). Design: 59 individuals ≥60 years old with obesity and a functional impairment were enrolled into this IRB approved clinical trial and randomized into one of two 6-month weight loss arms: a higher protein hypocaloric diet or a standard protein hypocaloric diet. All participants were prescribed individualized 500-kcal daily-deficit diets, with a goal of 10% weight loss. Additionally, participants participated in three, low-intensity, exercise sessions per week. Physical function, serum biomarkers and body composition data were assessed at the baseline and 6-month timepoints. Statistical analyses assessed the relationships between biomarkers, physical function, body composition, and OA status as a result of the intervention. Results: No group effects of dietary intervention were detected on any outcome measures (multiple p â€‹> â€‹0.05). During the 6-month trial, participants lost 6.2 â€‹± â€‹4.0% of their bodyweight (p â€‹< â€‹0.0001) and experienced improved physical function on the Short-Performance-Physical-Battery (p â€‹< â€‹0.0001), 8-foot-up-and-go (p â€‹< â€‹0.0001), and time to complete 10-chair-stands (p â€‹< â€‹0.0001). Adiponectin concentrations (p â€‹= â€‹0.0480) were elevated, and cartilage oligomeric matrix protein (COMP) concentrations (p â€‹< â€‹0.0001) were reduced; further analysis revealed that reductions in serum COMP concentrations were greater in OA-negative individuals. Conclusions: These results suggest that weight loss in older adults with and without OA may provide a protective effect to cartilage and OA. In particular, OA-negative individuals may be able to mitigate changes associated with OA through weight loss.

Automated segmentation and prediction of intervertebral disc morphology and uniaxial deformations from MRI.

Objective: The measurement of in vivo intervertebral disc (IVD) mechanics may be used to understand the etiology of IVD degeneration and low back pain (LBP). To this end, our lab has developed methods to measure IVD morphology and uniaxial compressive deformation (% change in IVD height) resulting from dynamic activity, in vivo, using magnetic resonance images (MRI). However, due to the time-intensive nature of manual image segmentation, we sought to validate an image segmentation algorithm that could accurately and reliably reproduce models of in vivo tissue mechanics. Design: Therefore, we developed and evaluated two commonly employed deep learning architectures (2D and 3D U-Net) for the segmentation of IVDs from MRI. The performance of these models was evaluated for morphological accuracy by comparing predicted IVD segmentations (Dice similarity coefficient, mDSC; average surface distance, ASD) to manual (ground truth) measures. Likewise, functional reliability and precision were assessed by evaluating the intraclass correlation coefficient (ICC) and standard error of measurement (SEm) of predicted and manually derived deformation measures. Results: Peak model performance was obtained using the 3D U-net architecture, yielding a maximum mDSC â€‹= â€‹0.9824 and component-wise ASDx â€‹= â€‹0.0683 â€‹mm; ASDy â€‹= â€‹0.0335 â€‹mm; ASDz â€‹= â€‹0.0329 â€‹mm. Functional model performance demonstrated excellent reliability ICC â€‹= â€‹0.926 and precision SEm â€‹= â€‹0.42%. Conclusions: This study demonstrated that a deep learning framework can precisely and reliably automate measures of IVD function, drastically improving the throughput of these time-intensive methods.

Auto-segmentation of the tibia and femur from knee MR images via deep learning and its application to cartilage strain and recovery.

The ability to efficiently and reproducibly generate subject-specific 3D models of bone and soft tissue is important to many areas of musculoskeletal research. However, methodologies requiring such models have largely been limited by lengthy manual segmentation times. Recently, machine learning, and more specifically, convolutional neural networks, have shown potential to alleviate this bottleneck in research throughput. Thus, the purpose of this work was to develop a modified version of the convolutional neural network architecture U-Net to automate segmentation of the tibia and femur from double echo steady state knee magnetic resonance (MR) images. Our model was trained on a dataset of over 4,000 MR images from 34 subjects, segmented by three experienced researchers, and reviewed by a musculoskeletal radiologist. For our validation and testing sets, we achieved dice coefficients of 0.985 and 0.984, respectively. As further testing, we applied our trained model to a prior study of tibial cartilage strain and recovery. In this analysis, across all subjects, there were no statistically significant differences in cartilage strain between the machine learning and ground truth bone models, with a mean difference of 0.2 ± 0.7 % (mean ± 95 % confidence interval). This difference is within the measurement resolution of previous cartilage strain studies from our lab using manual segmentation. In summary, we successfully trained, validated, and tested a machine learning model capable of segmenting MR images of the knee, achieving results that are comparable to trained human segmenters.

Elevated In Vivo ACL Strain Is Associated With a Straight Knee in Both the Sagittal and the Coronal Planes.

BACKGROUND: Noncontact anterior cruciate ligament (ACL) injuries typically occur during deceleration movements such as landing or cutting. However, conflicting data have left the kinematic mechanisms leading to these injuries unclear. Quantifying the influence of sagittal and coronal plane knee kinematics on in vivo ACL strain may help to elucidate noncontact ACL injury mechanisms. PURPOSE/HYPOTHESIS: The purpose of this study was to measure in vivo sagittal and coronal plane knee kinematics and ACL strain during a single-leg jump. We hypothesized that ACL strain would be modulated primarily by motion in the sagittal plane and that limited coronal plane motion would be measured during this activity. STUDY DESIGN: Descriptive laboratory study. METHODS: Seventeen healthy participants (8 male/9 female) underwent magnetic resonance imaging (MRI) followed by high-speed biplanar radiography, obtained as participants performed a single-leg jump. Three-dimensional models of the femur, tibia, and associated ACL attachment site footprints were created from the MRIs and registered to the radiographs to reproduce the position of the knee during the jump. ACL strain, knee flexion/extension angles, and varus/valgus angles were measured throughout the jump. Spearman rank correlations were used to assess relationships between mean ACL strain and kinematic variables. RESULTS: Mean ACL strain increased with decreasing knee flexion angle (ρ = -0.3; P = .002), and local maxima in ACL strain occurred with the knee in a straight position in both the sagittal and the coronal planes. In addition, limited coronal plane motion (varus/valgus angle) was measured during this activity (mean ± SD, -0.5°± 0.3°). Furthermore, we did not detect a statistically significant relationship between ACL strain and varus/valgus angle (ρ = -0.01; P = .9). CONCLUSION: ACL strain was maximized when the knee was in a straight position in both the sagittal and coronal planes. Participants remained in <1° of varus/valgus position on average throughout the jump. As a ligament under elevated strain is more vulnerable to injury, landing on a straight knee may be an important risk factor for ACL rupture. CLINICAL RELEVANCE: These data may improve understanding of risk factors for noncontact ACL injury, which may be useful in designing ACL injury prevention programs.

The Interplay of Biomechanical and Biological Changes Following Meniscus Injury.

PURPOSE OF REVIEW: Meniscus injury often leads to joint degeneration and post-traumatic osteoarthritis (PTOA) development. Therefore, the purpose of this review is to outline the current understanding of biomechanical and biological repercussions following meniscus injury and how these changes impact meniscus repair and PTOA development. Moreover, we identify key gaps in knowledge that must be further investigated to improve meniscus healing and prevent PTOA. RECENT FINDINGS: Following meniscus injury, both biomechanical and biological alterations frequently occur in multiple tissues in the joint. Biomechanically, meniscus tears compromise the ability of the meniscus to transfer load in the joint, making the cartilage more vulnerable to increased strain. Biologically, the post-injury environment is often characterized by an increase in pro-inflammatory cytokines, catabolic enzymes, and immune cells. These multi-faceted changes have a significant interplay and result in an environment that opposes tissue repair and contributes to PTOA development. Additionally, degenerative changes associated with OA may cause a feedback cycle, negatively impacting the healing capacity of the meniscus. Strides have been made towards understanding post-injury biological and biomechanical changes in the joint, their interplay, and how they affect healing and PTOA development. However, in order to improve clinical treatments to promote meniscus healing and prevent PTOA development, there is an urgent need to understand the physiologic changes in the joint following injury. In particular, work is needed on the in vivo characterization of the temporal biomechanical and biological changes that occur in patients following meniscus injury and how these changes contribute to PTOA development.

The Predicted Position of the Knee Near the Time of ACL Rupture Is Similar Between 2 Commonly Observed Patterns of Bone Bruising on MRI.

BACKGROUND: Bone bruises observed on magnetic resonance imaging (MRI) can provide insight into the mechanisms of noncontact anterior cruciate ligament (ACL) injury. However, it remains unclear whether the position of the knee near the time of injury differs between patients evaluated with different patterns of bone bruising, particularly with regard to valgus angles. HYPOTHESIS: The position of the knee near the time of injury is similar between patients evaluated with 2 commonly occurring patterns of bone bruising. STUDY DESIGN: Descriptive laboratory study. METHODS: Clinical T2- and T1-weighted MRI scans obtained within 6 weeks of noncontact ACL rupture were reviewed. Patients had either 3 (n = 20) or 4 (n = 30) bone bruises. Patients in the 4-bone bruise group had bruising of the medial and lateral compartments of the femur and tibia, whereas patients in the 3-bone bruise group did not have a bruise on the medial femoral condyle. The outer contours of the bones and associated bruises were segmented from the MRI scans and used to create 3-dimensional surface models. For each patient, the position of the knee near the time of injury was predicted by moving the tibial model relative to the femoral model to maximize the overlap of the tibiofemoral bone bruises. Logistic regressions (adjusted for sex, age, and presence of medial collateral ligament injury) were used to assess relationships between predicted injury position (quantified in terms of knee flexion angle, valgus angle, internal rotation angle, and anterior tibial translation) and bone bruise group. RESULTS: The predicted injury position for patients in both groups involved a flexion angle <20°, anterior translation >20 mm, valgus angle <10°, and internal rotation angle <10°. The injury position for the 3-bone bruise group involved less flexion (odds ratio [OR], 0.914; 95% CI, 0.846-0.987; P = .02) and internal rotation (OR, 0.832; 95% CI, 0.739-0.937; P = .002) as compared with patients with 4 bone bruises. CONCLUSION: The predicted position of injury for patients displaying both 3 and 4 bone bruises involved substantial anterior tibial translation (>20 mm), with the knee in a straight position in both the sagittal (<20°) and the coronal (<10°) planes. CLINICAL RELEVANCE: Landing on a straight knee with subsequent anterior tibial translation is a potential mechanism of noncontact ACL injury.

Use of a Novel Multimodal Imaging Technique to Model In Vivo Quadriceps Force and ACL Strain During Dynamic Activity.

BACKGROUND: Quadriceps loading of the anterior cruciate ligament (ACL) may play a role in the noncontact mechanism of ACL injury. Musculoskeletal modeling techniques are used to estimate the intrinsic force of the quadriceps acting at the knee joint. PURPOSE/HYPOTHESIS: The purpose of this paper was to develop a novel musculoskeletal model of in vivo quadriceps force during dynamic activity. We used the model to estimate quadriceps force in relation to ACL strain during a single-leg jump. We hypothesized that quadriceps loading of the ACL would reach a local maximum before initial ground contact with the knee positioned in extension. STUDY DESIGN: Descriptive laboratory study. METHODS: Six male participants underwent magnetic resonance imaging in addition to high-speed biplanar radiography during a single-leg jump. Three-dimensional models of the knee joint, including the femur, tibia, patellofemoral cartilage surfaces, and attachment-site footprints of the patellar tendon, quadriceps tendon, and ACL, were created from the magnetic resonance imaging scans. The bone models were registered to the biplanar radiographs, thereby reproducing the positions of the knee joint at the time of radiographic imaging. The magnitude of quadriceps force was determined for each knee position based on a 3-dimensional balance of the forces and moments of the patellar tendon and the patellofemoral cartilage contact acting on the patella. Knee kinematics and ACL strain were determined for each knee position. RESULTS: A local maximum in average quadriceps force of approximately 6500 N (8.4× body weight) occurred before initial ground contact. ACL strain increased concurrently with quadriceps force when the knee was positioned in extension. CONCLUSION: This novel participant-specific modeling technique provides estimates of in vivo quadriceps force during physiologic dynamic loading. A local maximum in quadriceps force before initial ground contact may tension the ACL when the knee is positioned in extension. CLINICAL RELEVANCE: These data contribute to understanding noncontact ACL injury mechanisms and the potential role of quadriceps activation in these injuries.

In vivo fluid transport in human intervertebral discs varies by spinal level and disc region.

Background: The lumbar discs are large, dense tissues that are primarily avascular, and cells residing in the central region of the disc are up to 6-8 mm from the nearest blood vessel in adults. To maintain homeostasis, disc cells rely on nutrient transport between the discs and adjacent vertebrae. Thus, diminished transport has been proposed as a factor in age-related disc degeneration. Methods: In this study, we used magnetic resonance imaging (MRI) to quantify diurnal changes in T2 relaxation time, an MRI biomarker related to disc hydration, to generate 3D models of disc fluid distribution and determine how diurnal changes in fluid varied by spinal level. We recruited 10 participants (five males/five females; age: 21-30 years; BMI: 19.1-29.0 kg/m2) and evaluated the T2 relaxation time of each disc at 8:00 AM and 7:00 PM, as well as degeneration grade (Pfirrmann). We also measured disc height, volume, and perimeter in a subset of individuals as a preliminary comparison of geometry and transport properties. Results: We found that the baseline (AM) T2 relaxation time and the diurnal change in T2 relaxation time were greatest in the cranial lumbar discs, decreasing along the lumbar spine from cranial to caudal. In cranial discs, T2 relaxation times decreased in each disc region (nucleus pulposus [NP], inner annulus fibrosus [IAF], and outer annulus fibrosus [OAF]), whereas in caudal discs, T2 relaxation times decreased in the NP but increased in the AF. Conclusions: Fluid transport varied by spinal level, where transport was greatest in the most cranial lumbar discs and decreased from cranial to caudal along the lumbar spine. Future work should evaluate what level-dependent factors affect transport.

Design and validation of a semi-automatic bone segmentation algorithm from MRI to improve research efficiency.

Segmentation of medical images into different tissue types is essential for many advancements in orthopaedic research; however, manual segmentation techniques can be time- and cost-prohibitive. The purpose of this work was to develop a semi-automatic segmentation algorithm that leverages gradients in spatial intensity to isolate the patella bone from magnetic resonance (MR) images of the knee that does not require a training set. The developed algorithm was validated in a sample of four human participants (in vivo) and three porcine stifle joints (ex vivo) using both magnetic resonance imaging (MRI) and computed tomography (CT). We assessed the repeatability (expressed as mean ± standard deviation) of the semi-automatic segmentation technique on: (1) the same MRI scan twice (Dice similarity coefficient = 0.988 ± 0.002; surface distance = - 0.01 ± 0.001 mm), (2) the scan/re-scan repeatability of the segmentation technique (surface distance = - 0.02 ± 0.03 mm), (3) how the semi-automatic segmentation technique compared to manual MRI segmentation (surface distance = - 0.02 ± 0.08 mm), and (4) how the semi-automatic segmentation technique compared when applied to both MRI and CT images of the same specimens (surface distance = - 0.02 ± 0.06 mm). Mean surface distances perpendicular to the cartilage surface were computed between pairs of patellar bone models. Critically, the semi-automatic segmentation algorithm developed in this work reduced segmentation time by approximately 75%. This method is promising for improving research throughput and potentially for use in generating training data for deep learning algorithms.

Lumbar intervertebral disc diurnal deformations and T2 and T1rho relaxation times vary by spinal level and disc region.

PURPOSE: Magnetic resonance imaging (MRI) is routinely used to evaluate spine pathology; however, standard imaging findings weakly correlate to low back pain. Abnormal disc mechanical function is implicated as a cause of back pain but is not assessed using standard clinical MRI. Our objective was to utilize our established MRI protocol for measuring disc function to quantify disc mechanical function in a healthy cohort. METHODS: We recruited young, asymptomatic volunteers (6 male/6 female; age 18-30 years; BMI < 30) and used MRI to determine how diurnal deformations in disc height, volume, and perimeter were affected by spinal level, disc region, MRI biomarkers of disc health (T2, T1rho), and Pfirrmann grade. RESULTS: Lumbar discs deformed by a mean of -6.1% (95% CI: -7.6%, -4.7%) to -8.0% (CI: -10.6%, -5.4%) in height and -5.4% (CI: -7.6%, -3.3%) to -8.5% (CI: -11.0%, -6.0%) in volume from AM to PM across spinal levels. Regional deformations were more uniform in cranial lumbar levels and concentrated posteriorly in the caudal levels, reaching a maximum of 13.1% at L5-S1 (CI:-16.1%, -10.2%). T2 and T1rho relaxation times were greatest in the nucleus and varied circumferentially within the annulus. T2 relaxation times were greatest at the most cranial spinal levels and decreased caudally. In this young healthy cohort, we identified a weak association between nucleus T2 and the diurnal change in the perimeter. CONCLUSIONS: Spinal level is a key factor in determining regional disc deformations. Interestingly, deformations were concentrated in the posterior regions of caudal discs where disc herniation is most prevalent.

Predictors of Lumbar Spine Degeneration and Low Back Pain in the Community: The Johnston County Osteoarthritis Project.

OBJECTIVE: To determine the incidence and worsening of lumbar spine structure and low back pain (LBP) and whether they are predicted by demographic characteristics or clinical characteristics or appendicular joint osteoarthritis (OA). METHODS: Paired baseline (2003-2004) and follow-up (2006-2010) lumbar spine radiographs from the Johnston County Osteoarthritis Project were graded for osteophytes (OST), disc space narrowing (DSN), spondylolisthesis, and presence of facet joint OA (FOA). Spine OA was defined as at least mild OST and mild DSN at the same level for any level of the lumbar spine. LBP, comorbidities, and back injury were self-reported. Weibull models were used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) of spine phenotypes accounting for potential predictors including demographic characteristics, clinical characteristics, comorbidities, obesity, and appendicular OA. RESULTS: Obesity was a consistent and strong predictor of incidence of DSN (HR 1.80 [95% CI 1.09-2.98]), spine OA (HR 1.56 [95% CI 1.01-2.41]), FOA (HR 4.99 [95% CI 1.46-17.10]), spondylolisthesis (HR 1.87 [95% CI 1.02-3.43]), and LBP (HR 1.75 [95% CI 1.19-2.56]), and worsening of DSN (HR 1.51 [95% CI 1.09-2.09]) and LBP (HR 1.51 [95% CI 1.12-2.06]). Knee OA was a predictor of incident FOA (HR 4.18 [95% CI 1.44-12.2]). Spine OA (HR 1.80 [95% CI 1.24-2.63]) and OST (HR 1.85 [95% CI 1.02-3.36]) were predictors of incidence of LBP. Hip OA (HR 1.39 [95% CI 1.04-1.85]) and OST (HR 1.58 [95% CI 1.00-2.49]) were predictors of LBP worsening. CONCLUSION: Among the multiple predictors of spine phenotypes, obesity was a common predictor for both incidence and worsening of lumbar spine degeneration and LBP.

Immune cell profiles in synovial fluid after anterior cruciate ligament and meniscus injuries.

BACKGROUND: Anterior cruciate ligament (ACL) and meniscus tears are common knee injuries. Despite the high rate of post-traumatic osteoarthritis (PTOA) following these injuries, the contributing factors remain unclear. In this study, we characterized the immune cell profiles of normal and injured joints at the time of ACL and meniscal surgeries. METHODS: Twenty-nine patients (14 meniscus-injured and 15 ACL-injured) undergoing ACL and/or meniscus surgery but with a normal contralateral knee were recruited. During surgery, synovial fluid was aspirated from both normal and injured knees. Synovial fluid cells were pelleted, washed, and stained with an antibody cocktail consisting of fluorescent antibodies for cell surface proteins. Analysis of immune cells in the synovial fluid was performed by polychromatic flow cytometry. A broad spectrum immune cell panel was used in the first 10 subjects. Based on these results, a T cell-specific panel was used in the subsequent 19 subjects. RESULTS: Using the broad spectrum immune cell panel, we detected significantly more total viable cells and CD3 T cells in the injured compared to the paired normal knees. In addition, there were significantly more injured knees with T cells above a 500-cell threshold. Within the injured knees, CD4 and CD8 T cells were able to be differentiated into subsets. The frequency of total CD4 T cells was significantly different among injury types, but no statistical differences were detected among CD4 and CD8 T cell subsets by injury type. CONCLUSIONS: Our findings provide foundational data showing that ACL and meniscus injuries induce an immune cell-rich microenvironment that consists primarily of T cells with multiple T helper phenotypes. Future studies investigating the relationship between immune cells and joint degeneration may provide an enhanced understanding of the pathophysiology of PTOA following joint injury.

Mechanical metrics may show improved ability to predict osteoarthritis compared to T1rho mapping.

Changes in cartilage structure and composition are commonly observed during the progression of osteoarthritis (OA). Importantly, quantitative magnetic resonance imaging (MRI) methods, such as T1rho relaxation imaging, can noninvasively provide in vivo metrics that reflect changes in cartilage composition and therefore have the potential for use in early OA detection. Changes in cartilage mechanical properties are also hallmarks of OA cartilage; thus, measurement of cartilage mechanical properties may also be beneficial for earlier OA detection. However, the relative predictive ability of compositional versus mechanical properties in detecting OA has yet to be determined. Therefore, we developed logistic regression models predicting OA status in an ex vivo environment using several mechanical and compositional metrics to assess which metrics most effectively predict OA status. Specifically, in this study the compositional metric analyzed was the T1rho relaxation time, while the mechanical metrics analyzed were the stiffness and recovery (defined as a measure of how quickly cartilage returns to its original shape after loading) of the cartilage. Cartilage recovery had the best predictive ability of OA status both alone and in a multivariate model including the T1rho relaxation time. These findings highlight the potential of cartilage recovery as a non-invasive marker of in vivo cartilage health and motivate future investigation of this metric clinically.

Diabetes is associated with a lower minimum moment of inertia among older women: An analysis of 3D reconstructions of clinical CT scans.

Hip fractures are a significant burden on the aging population, often resulting in reduced mobility, loss of independence, and elevated risk of mortality. While fracture risk is generally inversely related to bone mineral density (BMD), people with diabetes suffer a higher fracture rate despite having a higher BMD. To better understand the connection between diabetes and fracture risk, we developed a method to measure the minimum moment of inertia (mMOI; a geometric factor associated with fracture risk) from clinical CT scans of the pelvis. Since hip fractures are more prevalent in women, we focused on females in this study. We hypothesized that females with diabetes would have a lower mMOI along the femoral neck than those without diabetes, indicative of a higher fracture risk. Three-dimensional models of each hip were created from clinical CT scans of 40 older women (27 with diabetes: 10 fracture/17 non-fractured; 13 without diabetes: non-fractured controls). The mMOI of each hip (n = 80) was reported as the average from three trials. People with diabetes had an 18% lower mMOI as compared to those without diabetes after adjusting for age and BMI (p = 0.02). No differences in the mMOIs between the fractured and contralateral hips in the diabetic group were observed (p = 0.78). Similarly, no differences were observed between the fractured and non-fractured hips of people with diabetes (p = 0.29) when accounting for age and BMI. This suggests structural differences in the hips of individuals with diabetes (measured by the mMOI) may be associated with their elevated fracture risk.

Patellar Tendon Orientation and Strain Are Predictors of ACL Strain In Vivo During a Single-Leg Jump.

BACKGROUND: There is little in vivo data that describe the relationships between patellar tendon orientation, patellar tendon strain, and anterior cruciate ligament (ACL) strain during dynamic activities. Quantifying how the quadriceps load the ACL via the patellar tendon is important for understanding ACL injury mechanisms. HYPOTHESIS: We hypothesized that flexion angle, patellar tendon orientation, and patellar tendon strain influence ACL strain during a single-leg jump. Specifically, we hypothesized that patellar tendon and ACL strains would increase concurrently when the knee is positioned near extension during the jump. STUDY DESIGN: Descriptive laboratory study. METHODS: Models of the femur, tibia, ACL, patellar tendon, and quadriceps tendon attachment sites of 8 male participants were generated from magnetic resonance imaging (MRI). High-speed biplanar radiographs during a single-leg jump were obtained. The bone models were registered to the radiographs, thereby reproducing the in vivo positions of the bones, ligament, and tendon attachment sites. Flexion angle, patellar tendon orientation, patellar tendon strain, and ACL strain were measured from the registered models. ACL and patellar tendon strains were approximated by normalizing their length at each knee position to their length at the time of MRI. Two separate bivariate linear regression models were used to assess relationships between flexion angle and patellar tendon orientation and between ACL strain and patellar tendon strain. A multivariate linear regression model was used to assess whether flexion angle and patellar tendon strain were significant predictors of ACL strain during the inflight and landing portions of the jump. RESULTS: Both flexion angle and patellar tendon strain were significant predictors (P < .05) of ACL strain. These results indicate that elevated ACL and patellar tendon strains were observed concurrently when the knee was positioned near extension. CONCLUSION: Concurrent increases in patellar tendon and ACL strains indicate that the quadriceps load the ACL via the patellar tendon when the knee is positioned near extension. CLINICAL RELEVANCE: Increased ACL strain when the knee is positioned near extension before landing may be due to quadriceps contraction. Thus, landing with unanticipated timing on an extended knee may increase vulnerability to ACL injury as a taut ligament is more likely to fail.

Increasing BMI increases lumbar intervertebral disc deformation following a treadmill walking stress test.

High body mass index (BMI) and obesity have been implicated as risk factors for lumbar degenerative disc disease and low back pain. Despite this, there is limited in vivo data to quantify how obesity influences the mechanical function of intervertebral discs (IVD) in response to activities of daily living. Recently, our lab has developed methodologies to non-invasively measure in vivo IVD deformation resulting from activities of daily living using magnetic resonance (MR) imaging and solid modeling techniques. This pilot study expands on these methodologies to assess how BMI influences IVD deformation following treadmill walking in eight asymptomatic individuals. Ordinary least squares regression analyses revealed a statistically significant relationship between BMI and compressive deformation (strain (%)) in the L5-S1 IVD (R2 = 0.61, p < 0.05). This relationship was weaker in the L3-L4 (R2 = 0.28, p > 0.05) and L4-L5 IVDs (R2 = 0.28, p > 0.05). Importantly, no relationship between pre-exercise disc height and BMI was identified (p > 0.05). Therefore, the results of this study suggest that BMI may alter the mechanical response of lumbar spine IVDs, particularly at the L5-S1 level. Furthermore, the observed relationship between increased BMI and IVD compressive deformation, in the absence of a detected relationship between pre-exercise disc height and BMI, suggests that changes in IVD mechanical function may be more sensitive to alterations in disc health than static clinical imaging alone. This finding highlights the importance of quantifying disc mechanical function when examining the relationship between BMI and IVD degeneration.

Obesity alters the collagen organization and mechanical properties of murine cartilage.

Osteoarthritis is a debilitating disease characterized by cartilage degradation and altered cartilage mechanical properties. Furthermore, it is well established that obesity is a primary risk factor for osteoarthritis. The purpose of this study was to investigate the influence of obesity on the mechanical properties of murine knee cartilage. Two-month old wild type mice were fed either a normal diet or a high fat diet for 16 weeks. Atomic force microscopy-based nanoindentation was used to quantify the effective indentation modulus of medial femoral condyle cartilage. Osteoarthritis progression was graded using the OARSI system. Additionally, collagen organization was evaluated with picrosirius red staining imaged using polarized light microscopy. Significant differences between diet groups were assessed using t tests with p < 0.05. Following 16 weeks of a high fat diet, no significant differences in OARSI scoring were detected. However, we detected a significant difference in the effective indentation modulus between diet groups. The reduction in cartilage stiffness is likely the result of disrupted collagen organization in the superficial zone, as indicated by altered birefringence on polarized light microscopy. Collectively, these results suggest obesity is associated with changes in knee cartilage mechanical properties, which may be an early indicator of disease progression.