IMU Sensor Fusion Algorithm for Monitoring Knee Kinematics in ACL Reconstructed Patients.

In this paper we propose a sensor embedded knee brace to monitor knee flexion and extension and other lower limb joint kinematics after anterior cruciate ligament (ACL) injury. The system can be easily attached to a standard post-surgical brace and uses a novel sensor fusion algorithm that does not require calibration. The wearable system and the sensor fusion algorithm were validated for various physical therapy exercises against a validated motion capture system. The proposed sensor fusion algorithm demonstrated significantly lower root-mean-square error (RMSE) than the benchmark Kalman filtering algorithm and excellent correlation coefficients (CCC and ICC). The demonstrated error for most exercises was lower than other devices in the literature. The quantitative measures obtained by this system can be used to obtain longitudinal range-of-motion and functional biomarkers. These biomarkers can be used to improve patient outcomes through the early detection of at-risk patients, tracking patient function outside of the clinic, and the identification of relationships between patient presentation, intervention, and outcomes.

Cartilage T1ρ and T2 relaxation times: longitudinal reproducibility and variations using different coils, MR systems and sites.

OBJECTIVE: To evaluate the longitudinal reproducibility and variations of cartilage T1ρ and T2 measurements using different coils, MR systems and sites. METHODS: Single-Site study: Phantom data were collected monthly for up to 29 months on four GE 3T MR systems. Data from phantoms and human subjects were collected on two MR systems using the same model of coil; and were collected on one MR system using two models of coils. Multi-site study: Three participating sites used the same model of MR systems and coils, and identical imaging protocols. Phantom data were collected monthly. Human subjects were scanned and rescanned on the same day at each site. Two traveling human subjects were scanned at all three sites. RESULTS: Single-Site Study: The phantom longitudinal RMS-CVs ranged from 1.8% to 2.7% for T1ρ and 1.8-2.8% for T2. Significant differences were found in T1ρ and T2 values using different MR systems and coils. Multi-Site Study: The phantom longitudinal RMS-CVs ranged from 1.3% to 2.6% for T1ρ and 1.2-2.7% for T2. Across three sites (n = 16), the in vivo scan-rescan RMS-CV was 3.1% and 4.0% for T1ρ and T2, respectively. Phantom T1ρ and T2 values were significantly different between three sites but highly correlated (R > 0.99). No significant difference was found in T1ρ and T2 values of traveling controls, with cross-site RMS-CV as 4.9% and 4.4% for T1ρ and T2, respectively. CONCLUSION: With careful quality control and cross-calibration, quantitative MRI can be readily applied in multi-site studies and clinical trials for evaluating cartilage degeneration.

Three-dimensional MRI-based statistical shape model and application to a cohort of knees with acute ACL injury.

OBJECTIVE: The aim of this study is to develop a novel 3D magnetic resonance imaging (MRI)-based Statistical Shape Modeling (SSM) and apply it in knee MRIs in order to extract and compare relevant shapes of the tibia and femur in patients with and without acute Anterior cruciate ligament (ACL) injuries. METHODS: Bilateral MR images were acquired and analyzed for 50 patients with acute ACL injuries and for 19 control subjects. A shape model was extracted for the tibia and femur using an SSM algorithm based on a set of matched landmarks that are computed in a fully automatic manner. RESULTS: Shape differences were detected between the knees in the ACL-injury group and control group, suggesting a common shape feature that may predispose these knees to injury. Some of the detected shape features that discriminate between injured and control knees are related to intercondylar width and posterior tibia slope, features that have been suggested in previous studies as ACL morphological risk factors. However, shape modeling has the great potential to quantify these characteristics with a comprehensive description of the surfaces describing complex 3D deformation that cannot be represented with simple geometric indexes. CONCLUSIONS: 3D MRI-based bone shape quantification has the ability to identify specific anatomic risk factors for ACL injury. A better understanding of the role in bony shape on ligamentous injuries could help in the identification of subjects with an increased risk for an ACL tear and to develop targeted prevention strategies, including education and training.

Prevalence of vertebral fractures on chest radiographs of elderly African American and Caucasian women.

The prevalence of vertebral fractures on routine chest radiographs of elderly Caucasian women was only 1.3 times higher than in African American (AA) women, a difference considerably smaller than reported in population studies. AAs with medical problems may have higher risk of vertebral fractures than previously suspected. INTRODUCTION: Earlier studies noted a 1.9- to 3.7-fold higher prevalence of vertebral fractures in Caucasian (CA) compared to African American (AA) women. These studies, however, may have suffered from selection bias. We reported that among women referred for bone density testing, the prevalence of vertebral fractures in AA was the same as in CA women. Suspecting that the latter might have been due to a referral bias, we examined the racial difference in the prevalence of vertebra fractures on chest radiographs of patients seeking general medical care, not selected for osteoporosis. METHODS: Consecutive chest radiographs (N = 1,200) of women over age 60 were evaluated using Genant's semi-quantitative method. Patients' race and the presence of diseases or medications associated with increased fracture risk were ascertained from the electronic medical records. RESULTS: Among 1,011 women (76% AA) with usable radiographs, 11% had moderate or severe vertebral fractures. The prevalence of vertebral fractures was 10.3% in 773 AA and 13% in 238 CA women (p = 0.248 for difference between races). The lack of difference persisted after controlling for age, smoking, use of glucocorticoids, or presence of cancer, rheumatoid arthritis, organ transplantation, and end-stage renal disease. Among all subjects, CA women were more likely to be diagnosed and treated for osteoporosis (p <0.001). CONCLUSION: Among subjects seeking medical care, the difference in the prevalence of vertebral fractures between AA and CA women is smaller than previously suspected. Greater attention to the detection of vertebral fractures and the management of osteoporosis is warranted in AA women with medical problems.