Patients with Symptomatic Hip Osteoarthritis Have Altered Kinematics during Stair Ambulation.

BACKGROUND: Osteoarthritis (OA) is a degenerative joint disease. Understanding contributing factors to slowing or stopping disease progression is crucial. There has been no research describing lower extremity kinematics of the hip, knee, and ankle during stair ambulation in individuals with hip OA. OBJECTIVE: To explore the differences in lower extremity kinematics between participants with clinical and morphological findings of hip OA and controls. DESIGN: A cross-sectional study. SETTING: Clinical research laboratory. PARTICIPANTS: Participants with radiographic and symptomatic signs of hip OA (n = 42) and healthy controls (n = 30) were enrolled. INTERVENTIONS: Participants underwent hip magnetic resonance imaging (MRI). The Scoring Hip Osteoarthritis with MRI (SHOMRI) method was used to assess cartilage abnormalities. Self-reported measures of hip pain and function were obtained using the Hip Disability and Osteoarthritis Outcome Score (HOOS). Participants were assigned into a symptomatic hip osteoarthritis group (HOA) with SHOMRI>0 and HOOS≤80, and a control group (CG) with SHOMRI = 0 and HOOS>90. Patients underwent 3D motion analysis during stair ascent/descent at self-selected speed. MAIN OUTCOME MEASURES: The primary outcome measurements were peak hip, knee, and ankle kinematics. General Estimation Equations were used to compare kinematics between groups (P ≤ .05). RESULTS: The HOA group ascended stairs with a more internally rotated hip (CG = 1.77 ± 6.3; HOA = 4.97 ± 4.2; P = .02), more abducted hip (CG = -5 ± 2.7, HOA = -3.5 ± 3; P = .02), and a more externally rotated knee (CG = -8.02 ± 3; HOA = -10.63 ± 6.3; P = .02) and ankle (CG = -11.8 ± 6.1; HOA = -16.3 ± 5.6; P = .01). Similarly, HOA participants descended stairs with a more extended knee (CG = -15.5 ± 4.9; HOA = -12 ± 4.9; P = .01), and more externally rotated knee (CG = -10.1 ± 4.4; HOA = -13.1 ± 6.6; P = .04) and ankle (CG = -13.5 ± 5.3; HOA = -17.9 ± 5.5; P = .002). CONCLUSION: Participants with hip OA-related morphology and symptoms ambulate stairs utilizing abnormal lower extremity mechanics.

Automatic hip abductor muscle fat fraction estimation and association with early OA cartilage degeneration biomarkers.

The aim of this study was to develop an automatic segmentation method for hip abductor muscles and find their fat fraction associations with early stage hip osteoarthritis (OA) cartilage degeneration biomarkers. This Institutional Review Board approved, Health Insurance Portability and Accountability Act compliant prospective study recruited 61 patients with evidence of hip OA or Femoroacetabular Impingement (FAI). Magnetic resonance (MR) images were acquired for cartilage segmentation, T1ρ and T2 relaxation times computation and grading of cartilage lesion scores. A 3D V-Net (Dice loss, Adam optimizer, learning rate = 1e-4 , batch size = 3) was trained to segment the three muscles (gluteus medius, gluteus minimus, and tensor fascia latae). The V-Net performance was measured using Dice, distance maps between manual and automatic masks, and Bland-Altman plots of the fat fractions and volumes. Associations between muscle fat fraction and T1ρ , T2 relaxation times values were found using voxel based relaxometry (VBR). A p < 0.05 was considered significant. The V-Net had a Dice of 0.90, 0.88, and 0.91 (GMed, GMin, and TFL). The VBR results found associations of fat fraction of all three muscles in early stage OA and FAI patients with T1ρ , T2 relaxation times. Using an automatic, validated segmentation model, the associations derived between OA biomarkers and muscle fat fractions provide insight into early changes that occur in OA, and show that hip abductor muscle fat is associated with markers of cartilage degeneration.

Multivariate functional principal component analysis identifies waveform features of gait biomechanics related to early-to-moderate hip osteoarthritis.

Clinicians often examine movement patterns to design hip osteoarthritis (OA) interventions, yet traditional biomechanical analyses only report a single timepoint. Multivariate principal component analysis (MFPCA) analyzes the entire waveform (i.e., movement pattern), which clinicians observe to direct treatment. This study investigated hip OA indicators, by (1) employing MFPCA to characterize variance across the hip, knee, and ankle angles in healthy and early-to-moderate hip OA participants; and (2) investigating relationships between these waveform features and hip cartilage health. Bilateral hip magnetic resonance images from 72 participants with Kellgren-Lawrence grades ranging from 0 to 3 were used to calculate mean T 1ρ and T 2 relaxation times in the femoral and acetabular cartilage. MFPCA was performed on lower-limb gait biomechanics and used to identify primary modes of variation, which were related to T 1ρ and T 2 relaxation times. Here, a MFPC = mode of variation = waveform feature. In the femoral cartilage, transverse plane MFPCs 3 and 5 and body mass index (BMI) was related to T 1ρ , while MFPC 2 and BMI were related to T 2 relaxation times. In the acetabular cartilage, sagittal plane MFPC 1 and BMI were related to T 1ρ , while BMI was related to T 2 relaxation times. Greater internal rotation was related to increased T 1ρ and T 2 relaxation times in the femoral cartilage, while the greater extension was related to increased T 1ρ relaxation times in the acetabular cartilage. This study established a data-driven framework to assess relationships between multi-joint biomechanics and quantitative assessments of cartilage health and identified waveform features that could be evaluated in future hip OA intervention studies.

Hip joint muscle forces during gait in patients with femoroacetabular impingement syndrome are associated with patient reported outcomes and cartilage composition.

Femoroacetabular impingement syndrome (FAIS) consists of abnormal hip joint morphology and pain during activities of daily living. Abnormal gait mechanics and potentially abnormal muscle forces within FAI patients leads to articular cartilage damage. Therefore, there is a necessity to understand the effects of FAI on hip joint muscle forces during gait and the link between muscle forces, patient reported outcomes (PRO) and articular cartilage health. The purposes of this study were to assess: (1) hip muscle forces between FAI patients and healthy controls and (2) the associations between hip muscle forces with PRO and cartilage composition (T1ρ/T2 mapping) within FAI patients. Musculoskeletal simulations were used to estimate peak muscle forces during the stance phase of gait in 24 FAI patients and 24 healthy controls. Compared to controls, FAI patients ambulated with lower vasti (30% body-weight, p = 0.01) and higher sartorius (4.0% body-weight, p < 0.01) forces. Within FAI patients, lower peak gluteus medius, gluteus minimus, sartorius and iliopsoas forces were associated with worse hip joint pain and function (R = 0.43-0.70, p = 0-0.04), while lower muscle forces were associated with increased T1ρ and T2 values (i.e. altered cartilage composition) within the hip joint cartilage (R = -0.44 to -0.58, p = 0.006-0.05). Although FAI patients demonstrate abnormal muscle forces, it is unknown whether or not these altered muscle force patterns are associated with pain avoidance or weak musculature. Further investigation is required in order to better understand the effects of FAI on hip joint muscle forces and the associations with hip joint cartilage degeneration.

Abnormal Joint Loading During Gait in Persons With Hip Osteoarthritis Is Associated With Symptoms and Cartilage Lesions.

BACKGROUND: Hip joint loading in persons with hip osteoarthritis (OA) is not well studied, and its associations with symptoms and lesions are unknown. OBJECTIVES: To determine whether hip joint loading differs between people with and without radiographic hip OA, and to identify its associations with patients' symptoms and cartilage morphology. METHODS: Forty-eight patients (28 male; mean ± SD age, 56.0 ± 12.2 years) with hip OA and 95 controls (40 male; age, 43.2 ± 13.6 years) participated in this cross-sectional analysis. Pelvic radiographs, questionnaires, magnetic resonance imaging (MRI), and gait analysis were conducted. The Hip disability and Osteoarthritis Outcome Score (HOOS) was used to assess symptoms. Cartilage morphology was graded on MRI scans using the Scoring Hip Osteoarthritis with Magnetic Resonance Imaging (SHOMRI) system. Biomechanical variables included peak external hip joint moment (Newton meters per kilogram) and moment impulses (Newton meters times milliseconds per kilogram) in all planes. Generalized estimating equations were used to compare the biomechanical characteristics between groups. In the patients with OA, associations of moment impulses with HOOS and SHOMRI scores were assessed with partial correlations. RESULTS: The OA group exhibited higher peak external hip flexion and adduction moments (P<.001) and higher hip flexion, adduction, and external rotation moment impulses (P = .001-.039). Increased hip flexion moment impulses were correlated with worse HOOS subscale scores (r = -0.361 to -0.424, P<.05) and worse femoral SHOMRI grades (ρ = 0.256-0.315, P<.05). Increased hip external rotation moment impulses were correlated with worse femoral SHOMRI grades (ρ = 0.283-0.372, P<.05). CONCLUSION: Persons with hip OA exhibited abnormally high hip joint loads during walking, and high loads were associated with worse self-reported symptoms and cartilage morphology. J Orthop Sports Phys Ther 2019;49(12):917-924. Epub 14 Oct 2019. doi:10.2519/jospt.2019.8945.

Implicit video feedback produces positive changes in landing mechanics.

BACKGROUND: Implicit (IF) and explicit (EF) feedback are two motor learning strategies demonstrated to alter movement patterns. There is conflicting evidence on which strategy produces better outcomes. The purpose of this study was to examine the effects of reduced IF and EF video feedback on lower extremity landing mechanics. METHODS: Thirty participants (24 ± 2 years, 1.7 ± 0.1 m, 70 ± 11 kg) were randomly assigned to three groups: IF (n = 10), EF (n = 10), and control (CG) (n = 10). They performed twelve box-drop jumps three times a week on the training sessions for six weeks. Only IF and EF groups received video feedback on the training sessions. IF was cued to focus their attention on the overall jump, while EF was cued to focus on position of their knees. 3D lower extremity biomechanics were tested on testing sessions with no feedback. All sessions were at least 24 h apart from another. Testing sessions included baseline testing (pretest), testing after 3 training sessions with 100% feedback (pst1), testing after 6 training sessions with 33.3% feedback (pst2), testing after 6 training sessions with 16.6% feedback (Pst3), and testing 1 month after with no feedback (retention - ret). ANOVA compared differences between groups and time at initial contact and peak for hip flexion (HF, °) and abduction angle (HA, °), hip abduction moment (HAM, Nm/kgm), knee flexion (KF, °) and abduction angle (KA, °), knee abduction moment (KAM, Nm/kgm) and VGRF (N) (p < 0.05). RESULTS: A significant main effect for group was found between IF and EF groups for HA (IF = - 6.7 ± 4; EF = - 9.4 ± 4.1) and KAM (IF = 0.05 ± 0.2; EF = - 0.07 ± 0.2) at initial contact, and peaks HA (IF = - 3.5 ± 4.5; EF = - 7.9 ± 4.7) and HAM (IF = 1.1 ± 0.6; EF = 0.9 ± 0.4). A significant main effect for time at initial contact for HF (pre = 32.4 ± 3.2; pst2 = 36.9 ± 3.2; pst3 = 37.9 ± 3.7; ret. = 34.1 ± 3.7), HAM (pre = 0.1 ± 0.1; pst1 = 0.04 ± 0.1; pst3 = 0.1 ± 0.01), KA (pre = 0.7 ± 1.1; pst1 = 0.2 ± 1.2; pst3 = 1.7 ± 1), and KAM (pre = 0.003 ± 0.1; pst3 = 0.01 ± 0.1) was found. DISCUSSION/CONCLUSION: We found that implicit feedback produced positive changes in landing mechanics while explicit feedback degraded motor learning. Our results indicate that implicit feedback should be used in programs to lower the ACL injury risk. We suggest that implicit feedback should be frequent in the beginning and not be reduced as much following the acquisition phase.

iPhone Sensors in Tracking Outcome Variables of the 30-Second Chair Stand Test and Stair Climb Test to Evaluate Disability: Cross-Sectional Pilot Study.

BACKGROUND: Performance tests are important to characterize patient disabilities and functional changes. The Osteoarthritis Research Society International and others recommend the 30-second Chair Stand Test and Stair Climb Test, among others, as core tests that capture two distinct types of disability during activities of daily living. However, these two tests are limited by current protocols of testing in clinics. There is a need for an alternative that allows remote testing of functional capabilities during these tests in the osteoarthritis patient population. OBJECTIVE: Objectives are to (1) develop an app for testing the functionality of an iPhone's accelerometer and gravity sensor and (2) conduct a pilot study objectively evaluating the criterion validity and test-retest reliability of outcome variables obtained from these sensors during the 30-second Chair Stand Test and Stair Climb Test. METHODS: An iOS app was developed with data collection capabilities from the built-in iPhone accelerometer and gravity sensor tools and linked to Google Firebase. A total of 24 subjects performed the 30-second Chair Stand Test with an iPhone accelerometer collecting data and an external rater manually counting sit-to-stand repetitions. A total of 21 subjects performed the Stair Climb Test with an iPhone gravity sensor turned on and an external rater timing the duration of the test on a stopwatch. App data from Firebase were converted into graphical data and exported into MATLAB for data filtering. Multiple iterations of a data processing algorithm were used to increase robustness and accuracy. MATLAB-generated outcome variables were compared to the manually determined outcome variables of each test. Pearson's correlation coefficients (PCCs), Bland-Altman plots, intraclass correlation coefficients (ICCs), standard errors of measurement, and repeatability coefficients were generated to evaluate criterion validity, agreement, and test-retest reliability of iPhone sensor data against gold-standard manual measurements. RESULTS: App accelerometer data during the 30-second Chair Stand Test (PCC=.890) and gravity sensor data during the Stair Climb Test (PCC=.865) were highly correlated to gold-standard manual measurements. Greater than 95% of values on Bland-Altman plots comparing the manual data to the app data fell within the 95% limits of agreement. Strong intraclass correlation was found for trials of the 30-second Chair Stand Test (ICC=.968) and Stair Climb Test (ICC=.902). Standard errors of measurement for both tests were found to be within acceptable thresholds for MATLAB. Repeatability coefficients for the 30-second Chair Stand Test and Stair Climb Test were 0.629 and 1.20, respectively. CONCLUSIONS: App-based performance testing of the 30-second Chair Stand Test and Stair Climb Test is valid and reliable, suggesting its applicability to future, larger-scale studies in the osteoarthritis patient population.