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.

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.

Differential Diagnosis of Metatarsalgia.

Lesser (or central) metatarsalgia is defined as pain in the forefoot under or around the lesser metatarsals and their respective metatarsophalangeal joints. Two common causes of central metatarsalgia are Morton's neuroma (MN) and plantar plate (PP) injury. Because both clinical and imaging features overlap, establishing the correct differential diagnosis may be challenging. Imaging has a pivotal role in the detection and characterization of metatarsalgia. Different radiologic modalities are available to assess the common causes of forefoot pain, so the strengths and weakness of these imaging tools should be kept in mind. It is crucial to be aware of the pitfalls that can be encountered in daily clinical practice when dealing with these disorders. This review describes two main causes of lesser metatarsalgia, MN and PP injury, and their differential diagnoses.

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 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.

Prospective Multireader Evaluation of Photon-counting CT for Multiple Myeloma Screening.

Purpose To determine whether photon-counting CT (PCCT) acquisition of whole-body CT images provides similar quantitative image quality and reader satisfaction for multiple myeloma screening at lower radiation doses than does standard energy-integrating detector (EID) CT. Materials and Methods Patients with monoclonal gammopathy of undetermined significance prospectively underwent clinical noncontrast whole-body CT with EID and same-day PCCT (August-December 2021). Five axial scan locations were evaluated by seven radiologists, with 11% (eight of 70) of images including osteolytic lesions. Images were shown in randomized order, and each reader rated the following: discernibility of the osseous cortex and osseous trabeculae, perceived image noise level, and diagnostic confidence. Presence of lytic osseous lesions was indicated. Contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) were calculated. Comparisons were made using paired t tests and mixed linear effects models. Results Seven participants (four women) were included (mean age, 66 years ± 9 [SD]; body mass index, 30.1 kg/m2 ± 5.2). Mean cortical definition, trabecular definition, image noise, and image quality scores were 83, 67, 75, and 78 versus 84, 66, 74, and 76 for EID and PCCT, respectively (P = .65, .11, .26, and .11, respectively). PCCT helped identify more lesions (79% [22 of 28]) than did EID (64% [18 of 28]). CNRs and SNRs were similar between modalities. PCCT had lower radiation doses than EID (volume CT dose index: EID, 11.37 ± 2.8 vs PCCT, 1.8 ± 0.6 [P = .06]; dose-length product: EID, 1654.1 ± 409.6 vs PCCT, 253.4 ± 89.6 [P = .05]). Conclusion This pilot investigation suggests that PCCT affords similar quantitative and qualitative scores as EID at significantly lower radiation doses. Keywords: CT, CT-Spectral, Skeletal-Axial, Spine, Hematologic Diseases, Whole-Body Imaging, Comparative Studies Supplemental material is available for this article. © RSNA, 2022.

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.

Magic angle effect on diffusion tensor imaging in ligament and brain.

PURPOSE: To evaluate the magic angle effect on diffusion tensor imaging (DTI) measurements in rat ligaments and mouse brains. METHODS: Three rat knee joints and three mouse brains were scanned at 9.4 T using a modified 3D diffusion-weighted spin echo pulse sequence with the isotropic spatial resolution of 45 µm. The b value was 1000 s/mm2 for rat knee and 4000 s/mm2 for mouse brain. DTI model was used to investigate the quantitative metrics at different orientations with respect to the main magnetic field. The collagen fiber structure of the ligament was validated with polarized light microscopy (PLM) imaging. RESULTS: The signal intensity, signal-to-noise ratio (SNR), and DTI metrics in the ligament were strongly dependent on the collagen fiber orientation with respect to the main magnetic field from both simulation and actual MRI scans. The variation of fractional anisotropy (FA) was about ~32%, and the variation of mean diffusivity (MD) was ~11%. These findings were further validated with the numerical simulation at different SNRs (~10.0 to 86.0). Compared to the ligament, the DTI metrics showed little orientation dependence in mouse brains. CONCLUSION: Magic angle effect plays an important role in DTI measurements in the highly ordered collagen-rich tissues, while MD showed less orientation dependence than FA.

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.

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.

MRI nomenclature for musculoskeletal infection.

The Society of Skeletal Radiology (SSR) Practice Guidelines and Technical Standards Committee identified musculoskeletal infection as a White Paper topic, and selected a Committee, tasked with developing a consensus on nomenclature for MRI of musculoskeletal infection outside the spine. The objective of the White Paper was to critically assess the literature and propose standardized terminology for imaging findings of infection on MRI, in order to improve both communication with clinical colleagues and patient care.A definition was proposed for each term; debate followed, and the committee reached consensus. Potential controversies were raised, with formulated recommendations. The committee arrived at consensus definitions for cellulitis, soft tissue abscess, and necrotizing infection, while discouraging the nonspecific term phlegmon. For bone infection, the term osteitis is not useful; the panel recommends using terms that describe the likelihood of osteomyelitis in cases where definitive signal changes are lacking. The work was presented virtually to SSR members, who had the opportunity for review and modification prior to submission for publication.

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.

Effect of walking on in vivo tibiofemoral cartilage strain in ACL-deficient versus intact knees.

Anterior cruciate ligament (ACL) rupture alters knee kinematics and contributes to premature development of osteoarthritis. However, there is limited data regarding the in vivo biomechanical response of tibiofemoral cartilage to activities of daily living (ADLs) in ACL-deficient knees. In this study, eight otherwise healthy participants with chronic unilateral ACL deficiency completed a stress test to assess the effect of 20 min of level treadmill walking at a speed of 2.5 mph on tibiofemoral cartilage in their ACL-deficient and contralateral ACL-intact knees. Three-dimensional surface models developed from pre- and post-activity magnetic resonance (MR) images of the injured and uninjured knees were used to determine compressive strain across multiple regions of tibiofemoral cartilage (medial and lateral tibial plateaus, medial and lateral femoral condyles, medial aspect of femoral condyle adjacent to intercondylar notch of the femur). In the ACL-deficient knees, we observed significantly increased cartilage strain in the region of the medial femoral condyle adjacent to the intercondylar notch (6% in deficient vs. 2% in contralateral, p = 0.01) as well as across the medial and lateral tibial plateaus (4% vs. 3%, p = 0.01) relative to the contralateral ACL-intact knees. Increased compressive strain at the medial intercondylar notch and tibial plateau suggests alterations in mechanical loading or the response to load in these regions, presumably related to altered knee kinematics. These changes may disrupt cartilage homeostasis and contribute to subsequent development of osteoarthritis.

Dose and Recovery Response of Patellofemoral Cartilage Deformations to Running.

BACKGROUND: Running is a common recreational activity that provides many health benefits. However, it remains unclear how patellofemoral cartilage is affected by varied running distances and how long it takes the cartilage to recover to its baseline state after exercise. HYPOTHESIS: We hypothesized that patellofemoral cartilage thickness would decrease immediately after exercise and return to its baseline thickness by the following morning in asymptomatic male runners. We further hypothesized that we would observe a significant distance-related dose response, with larger compressive strains (defined here as the mean change in cartilage thickness measured immediately after exercise, divided by the pre-exercise cartilage thickness) observed immediately after 10-mile runs compared with 3-mile runs. STUDY DESIGN: Descriptive laboratory study. METHODS: Eight asymptomatic male participants underwent magnetic resonance imaging of their dominant knee before, immediately after, and 24 hours after running 3 and 10 miles at a self-selected pace (on separate visits). RESULTS: Mean patellar cartilage thicknesses measured before exercise and after the 24-hour recovery period were significantly greater than the thicknesses measured immediately after both the 3- and 10-mile runs (P < .001). This relationship was not observed in trochlear cartilage. Mean patellar cartilage compressive strains were significantly greater after 10-mile runs compared with 3-mile runs (8% vs 5%; P = .01). CONCLUSION: Patellar cartilage thickness decreased immediately after running and returned to its baseline thickness within 24 hours of running up to 10 miles. Furthermore, patellar cartilage compressive strains were dose-dependent immediately after exercise. CLINICAL RELEVANCE: These findings provide critical baseline data for understanding patellofemoral cartilage biomechanics in asymptomatic male runners that may be used to optimize exercise protocols and investigations targeting those with running-induced patellofemoral pain.

The Influence of Obesity and Meniscal Coverage on In Vivo Tibial Cartilage Thickness and Strain.

BACKGROUND: Obesity, which potentially increases loading at the knee, is a common and modifiable risk factor for the development of knee osteoarthritis. The menisci play an important role in distributing joint loads to the underlying cartilage. However, the influence of obesity on the role of the menisci in cartilage load distribution in vivo is currently unknown. PURPOSE: To measure tibial cartilage thickness and compressive strain in response to walking in areas covered and uncovered by the menisci in participants with normal body mass index (BMI) and participants with high BMI. STUDY DESIGN: Controlled laboratory study. METHODS: Magnetic resonance (MR) images of the right knees of participants with normal BMI (<25 kg/m2; n = 8) and participants with high BMI (>30 kg/m2; n = 7) were obtained before and after treadmill walking. The outer margins of the tibia, the medial and lateral cartilage surfaces, and the meniscal footprints were segmented on each MR image to create 3-dimensional models of the joint. Cartilage thickness was measured before and after walking in areas covered and uncovered by the menisci. Cartilage compressive strain was then determined from changes in thickness resulting from the walking task. RESULTS: Before exercise, medial and lateral uncovered cartilage of the tibial plateau was significantly thicker than covered cartilage in both BMI groups. In the uncovered region of the lateral tibial plateau, participants with high BMI had thinner preexercise cartilage than those with a normal BMI. Cartilage compressive strain was significantly greater in medial and lateral cartilage in participants with high BMI compared with those with normal BMI in both the regions covered and those uncovered by the menisci. CONCLUSION: Participants with high BMI experienced greater cartilage strain in response to walking than participants with normal BMI in both covered and uncovered regions of cartilage, which may indicate that the load-distributing function of the meniscus is not sufficient to moderate the effects of obesity. CLINICAL RELEVANCE: These findings demonstrate the critical effect of obesity on cartilage function and thickness in regions covered and uncovered by the menisci.