Correlation between knee anatomy and joint laxity using principal component analysis

Shalhoub, Sami; Cyr, Adam J.; Maletsky, Lorin P.

doi:10.1002/jor.25294

Cited by 5 publications

(14 citation statements)

References 38 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…13,14,16 Therefore, it appears that a flatter, extended tibia plateau allows for more rotation in the transverse plane before the femur reaches the edge of the plateau, while increases in femoral and intercondylar width allow for more rotation of the joint before engaging the soft tissue, as previously proposed. 14 Decreased tibial spines eminences heights further reduces the constraint on the joint to rotate internally and externally during motion.…”

Section: Discussionsupporting

confidence: 59%

“…Previous PCA-based analyses have similarly found overall size change to be a dominant mode of geometric variation in the tibiofemoral joint. [12][13][14]16,18 However, neither study found a correlation between knee size and abduction-adduction motion. Lynch et al 16 and Shalhoub et al 14 found no correlations between the modes of variation characterized by scaling of the geometry and motion, with no relationship found between size and the internal-external and abduction-adduction laxity envelope or kinematics during deep knee flexion.…”

Section: Discussionmentioning

confidence: 91%

“…Statistical shape and appearance models (SSAMs) have been used to investigate variation in knee bone geometry and motion of the patellofemoral and tibiofemoral joints. [11][12][13][14] SSAMs apply principal component analysis (PCA) to quantify major modes of variation in geometry and kinematic parameters within a population. SSAMs have determined prominent variations in the knee bone geometry including scaling of the bones, joint alignment, and condyle size and shape.…”

mentioning

confidence: 99%

“…SSAMs have also shown the influence of geometry on knee kinematics including the relationship between tibia plateau shape, internal-external rotation, and anterior-posterior translation during gait. 15 However, the SSAMs in these studies have predominantly used data from males participants only [12][13][14] or examined the relationship with kinematics during a dynamic loading activity. 13,16 The principal geometric determinants of passive motion with SSAMs in a data set of males and female participants has yet to be established.…”

mentioning

confidence: 99%

See 3 more Smart Citations

Determining the relationship between tibiofemoral geometry and passive motion with partial least squares regression

O’Rourke

Bucci

Burton

et al. 2023

Journal Orthopaedic Research

View full text Add to dashboard Cite

Tibiofemoral geometry influences knee passive motion and understanding their relationship can provide insight into knee function and mechanisms of injury. However, the complexity of the geometric constraints has made characterizing the relationship challenging. The aim of this study was to determine the tibiofemoral bone geometries that explain the variation in passive motion using a partial least squares regression (PLSR) model. The PLSR model was developed for 29 healthy cadaver specimens (10 female, 19 male) with femur and tibia geometries retrieved from MRI images and six degree‐of‐freedom tibiofemoral kinematics determined during a flexion cycle with minimal medial pressure. The first 13 partial least squares (PLS) components explained 90% of the variation in the kinematics and accounted for 89% of the variation in geometry. The first three PLS components which shared geometric changes to particular surface congruencies of the tibial and femoral condyles explained the most amount of variation in the kinematics, primarily in anterior–posterior translation. Meanwhile, variations in femoral condyle width and the intercondylar space, tibia plateau size and conformity, and tibia eminences heights in PLS 2 and 4 explained the greatest amount of variation in internal–external rotation. PLS 4 exhibiting variation in overall size of the knee accounted for greatest amount of variation in geometry (50%) and had the greatest influence on the abduction–adduction motion and some on internal–external rotation but, overall, explained only a small proportion of the kinematics (10%). Elucidating the complex relationship between tibiofemoral bone geometry and passive kinematics may help personalize treatments for improved functional outcomes in patients.

show abstract

Section: Discussionsupporting

confidence: 59%

Section: Discussionmentioning

confidence: 91%

mentioning

confidence: 99%

mentioning

confidence: 99%

See 2 more Smart Citations

Determining the relationship between tibiofemoral geometry and passive motion with partial least squares regression

O’Rourke

Bucci

Burton

et al. 2023

Journal Orthopaedic Research

View full text Add to dashboard Cite

show abstract

“…They form the patellofemoral joint when they come together the knee is the biggest joint in the human body and is often considered the most strained joint. 1 The arrangement of bones inside the joint serves as a fulcrum for the muscles that flex and extend the knee. The extracapsular, intracapsular, and ligament designs, as well as the cross-joint muscle extensions, provide the joint with the essential stability to withstand the significant biomechanical force exerted on it.…”

Section: Introductionmentioning

confidence: 99%

Association of Knee Pain in Long Standing and Sitting among University Teachers

Tahir¹,

Maqsood²,

Azhar³

et al. 2023

THJ

View full text Add to dashboard Cite

Background: Prolonged sitting and standing raise the load on the knee, thus increasing the risk of knee pain and severity among teachers. Objective: To determine the association of knee pain in long-standing and sitting among school and university teachers. Methods: It was a cross-sectional survey conducted on 185 patients with a history of chronic knee pain. The data was collected from school and university teachers in the private and public sectors. Data were collected from both male and female teachers having knee pain and aged between 27 to 60 years and the patients who have a history of knee osteoarthritis, carcinoma, traumatic injury and wound/infection were excluded from the survey. The categorical variables were evaluated by frequency and percentages, while mean and standard deviation were calculated for continuous variables. The correlation was calculated between knee pain reported by university professors due to long periods of standing or sitting. Results: Out of 185 participants, 111 (60%) were females and 74 (40%) were males, with a mean age of 41.37±11.33. There was a weak positive correlation between knee pain and standing hours, which was statistically significant (r=0.273, n =185, p<0.001). There was a negative correlation between knee pain and sitting hours, (r=-0.160, n=185, p<0.05). Conclusion: This study found that prolonged standing hours may increase knee pain among teachers as compared to prolonged sitting. More standing hours during academic activities tend to increase knee pain while prolonged sitting did not increase that pain. There was a negative correlation between knee pain and sitting hours, and weak positive correlation between knee pain and standing hours, which was statistically significant.

show abstract

Effect of patient specificity on predicting knee cartilage degeneration in obese adults: Musculoskeletal finite‐element modeling of data from the CAROT trial

Orozco,

Stenroth,

Esrafilian

et al. 2024

Journal Orthopaedic Research

View full text Add to dashboard Cite

Obesity is a known risk factor for development of osteoarthritis (OA). Numerical tools like finite‐element (FE) models combined with degenerative algorithms have been developed to understand the interplay between OA and obesity. In this study, we aimed to predict knee cartilage degeneration in a cohort of obese adults to investigate the importance of patient‐specific information on degeneration predictions. We used a validated FE modeling approach and three different age‐dependent functions (step‐wise, exponential, and linear) to simulate cartilage degradation under overloading in the knee joint. Gait motion analysis and magnetic resonance imaging data from 115 obese individuals with knee OA were used for musculoskeletal and FE modeling. Cartilage degeneration predictions were contrasted with Kellgren–Lawrence (KL) and Boston–Leeds Osteoarthritis Knee Score (BLOKS) grades. The findings show that overall, the similarities between numerical predictions and clinical measures were better for the medial (average area under the curve (AUC) = 0.62) compared to the lateral compartment (average AUC = 0.52) of the knee. Classification results for KL grades, full patient‐specific models and patient‐specific geometry with generic gait data showed higher AUC values (AUC = 0.71 and AUC = 0.68, respectively) compared to generic geometry and patient‐specific gait (AUC = 0.48). For BLOKS grades, AUC values for both full patient‐specific models and for patient‐specific geometry with generic gait locomotion were higher (AUC = 0.66 and AUC = 0.64, respectively) compared to when the generic geometry and patient‐specific gait were used (AUC = 0.53). In summary, our study highlights the importance of considering individual information in knee OA prediction. Nevertheless, our findings suggest that personalized gait play a smaller role in the OA prediction and classification capacity than personalized joint geometry.

show abstract

Correlation between knee anatomy and joint laxity using principal component analysis

Cited by 5 publications

References 38 publications

Determining the relationship between tibiofemoral geometry and passive motion with partial least squares regression

Determining the relationship between tibiofemoral geometry and passive motion with partial least squares regression

Association of Knee Pain in Long Standing and Sitting among University Teachers

Effect of patient specificity on predicting knee cartilage degeneration in obese adults: Musculoskeletal finite‐element modeling of data from the CAROT trial

Contact Info

Product

Resources

About