Relationships between Morphological Changes of Lower Limbs and Gender During Medial Compartment Knee Osteoarthritis

Sex differences in osteoarthritis prevalence, pain perception, physical function and therapeutics

OBJECTIVE

Women have a higher prevalence of osteoarthritis (OA) and worse clinical courses than men. However, the underlying factors and therapeutic outcomes of these sex-specific differences are incompletely researched. This review examines the current state of knowledge regarding sex differences in OA prevalence, risk factors, pain severity, functional outcomes, and use and response to therapeutics.

METHODS

PubMed database was used with the title keyword combinations "{gender OR sex} AND osteoarthritis" plus additional manual search of the included papers for pertinent references, yielding 212 references. Additional references were added and 343 that were reviewed for appropriateness.

RESULTS

Globally, women account for 60% of people with osteoarthritis with a greater difference after age 40. The higher risk for women may be due to differences in joint anatomy, alignment, muscle strength, hormonal influences, obesity, and/or genetics. At the same radiographic severity, women have greater pain severity than men, which may be explained by biologically distinct pain pathways, differential activation of central pain pathways, differences in pain sensitivity, perception, reporting, and coping strategies. Women have greater limitations of physical function and performance than men independent of BMI, OA severity, injury history, amount of weekly exercise. Women also have greater use of analgesic medications than men but less use of arthroplasty and poorer prognosis after surgical interventions.

CONCLUSIONS

The recognition of sex differences in OA manifestations and management could guide tailoring of sex-specific treatment protocols, and analysis of sex as a biological variable in future research would enhance development of precision medicine.

Gender-based differences exist in the functional knee phenotypes classification of the osteoarthritic knee

PURPOSE

To identify gender differences in (1) the coronal alignment of functional knee phenotypes and (2) the JLCA (joint line convergence angle) in relation to the phenotype classification.

METHODS

This study is a retrospective data analysis, including 12,099 osteoarthritic knee computed tomography (5025 male, 7074 female) analysed by Medacta software for hip-knee-ankle angle (HKA), femoral mechanical angle (FMA), tibial mechanical angle (TMA) and JLCA. The data were grouped into genders and combined according to the Functional Knee Phenotypes Classification.

RESULTS

Out of 127 phenotypes for males and 131 for females, 17 common phenotypes were reported. The commonest four were similar for both genders with VARHKA177° NEUFMA93° NEUTMA87° (9.8% males, 9.50% females), followed by VARHKA174° NEUFMA93°VARTMA84° (7.1%) and VARHKA174°VARFMA90° NEUTMA87° (7.0%) for males and VARHKA174° NEUFMA93° NEUTMA87° (6.1%), VARHKA174° NEUFMA93°VARTMA84° (5.1%) for females. The commonest FMA and TMA (91.5° to 94.5° and 85.5° to 88.5°, respectively) were the same for both genders, however, the rest of the male population observed greater femoral varus than the female population (p < 0.001). JLCA values ranged from -28.4° to 8.2° in the overall study population. Males and females had a mean JLCA of -2.96° (±2.6° SD) and -2.66° (±2.8°7 SD), respectively, p < 0.001.

CONCLUSIONS

Gender differences exist within the osteoarthritic knee phenotype. The male varus phenotype is influenced by FMA, while TMA values are similar across genders. JLCA variations show similarities to both TMA and FMA, suggesting JLCA is influenced by bone morphology more than by gender. These differences inform surgical decision-making for the personalised approach to the primary TKA.

LEVEL OF EVIDENCE

Level III.

Gender-specific distribution of knee morphology according to CPAK and functional phenotype classification: analysis of 8739 osteoarthritic knees prior to total knee arthroplasty using artificial intelligence

PURPOSE

Osteoarthritis of the knee is commonly associated with malalignment of the lower limb. Recent classifications, as the Coronal Plane Alignment of the Knee (CPAK) and Functional Phenotype classification, describe the bony knee morphology in addition to the overall limb alignment. Data on distribution of these classifications is not sufficient in large populations. The aim of this study was to analyse the preoperative knee morphology with regard to the aforementioned classifications in long leg radiographs prior to total knee arthroplasty surgery using Artificial Intelligence.

METHODS

The cohort comprised 8739 preoperative long leg radiographs of 7456 patients of all total knee arthroplasty surgeries between 2009 and 2021 from our institutional database. The automated measurements were performed with the validated Artificial Intelligence software LAMA (ImageBiopsy Lab, Vienna) and included standardized axes and angles [hip-knee-ankle angle (HKA), mechanical lateral distal femur angle (mLDFA), mechanical medial proximal tibia angle (mMPTA), mechanical axis deviation (MAD), anatomic mechanic axis deviation (AMA) and joint line convergence angle (JLCA)]. CPAK and functional phenotype classifications were performed and all measurements were analysed for gender, age, and body mass index (BMI) within these subgroups.

RESULTS

Varus alignment was more common in men (m: 2008, 68.5%; f: 2953, 50.8%) while neutral (m: 578, 19.7%; f: 1357, 23.4%) and valgus (m: 345, 11.8%; f: 1498, 25.8%) alignment was more common in women. The most common morphotypes according to CPAK classification were CPAK Type I (2454; 28.1%), Type II (2383; 27.3%), and Type III (1830; 20.9%). An apex proximal joint line (CPAK Type VII, VIII and IX) was only found in 1.3% of all cases (n = 121). In men, CPAK Type I (1136; 38.8%) and CPAK Type II (799; 27.3%) were the most common types and women were spread more equally between CPAK Type I (1318; 22.7%), Type II (1584; 27.3%) and Type III (1494; 25.7%) (p < 0.001). The most common combination of femur and tibia types was NEUmLDFA0°,NEUmMPTA0° (m: 514, 17.5%; f: 1004, 17.3%), but men showed femoral varus more often. Patients with a higher BMI showed a significantly lower age at surgery (R2 = 0.09, p < 0.001). There were significant differences between men and women for all radiographic parameters (p < 0.001).

CONCLUSION

Distribution in knee morphology with gender-specific differences highlights the wide range in osteoarthritic knees, characterized by CPAK and phenotype classification and may influence future surgical planning.

LEVEL OF EVIDENCE

Level III.

Comparison of accuracy for hip-knee-ankle (HKA) angle by X-ray and knee motion analysis system and the relationships between HKA and gait posture

BACKGROUND

The lower limb mechanical axis was used to assess the severity of knee osteoarthritis (KOA) with varus/valgus deformity and the accuracy of targeted lower limb alignment correction after operation by conventional X-rays. There are lots of parameters to assess the gait in elder patients such as velocity, stride length, step width and swing/stance ratio by knee joint movement analysis system. However, the correlation between the lower limb mechanical axis and gait parameters is not clear. This study is aimed at obtaining the accuracy of the lower limb mechanical axis by the knee joint movement analysis system and the correlation between the lower limb mechanical axis and gait parameters.

METHODS

We analysed 3D knee kinematics during ground gait of 99 patients with KOA and 80 patients 6 months after the operations with the vivo infrared navigation 3D portable knee joint movement analysis system (Opti-Knee®, Innomotion Inc, Shanghai, China). The HKA (Hip-Knee-Ankle) value was calculated and compared to X-ray findings.

RESULTS

HKA absolute variation after the operation was 0.83 ± 3.76°, which is lower than that before the operation (5.41 ± 6.20°, p = 0.001) and also lower than the entire cohort (3.36 ± 5.72). Throughout the cohort, a significant correlation with low coefficients (r = -0.19, p = 0.01) between HKA value and anterior-posterior displacement was found. In comparing the HKA values measured on the full-length alignment radiographs and 3D knee joint movement analysis system (Opti-Knee), there was a significant correlation with moderate to high coefficients (r = 0.784 to 0.976). The linear correlation analysis showed that there was a significant correlation between the values of HKA measured by X-ray and movement analysis system (R² = 0.90, p < 0.01).

CONCLUSIONS

Data with equivalent results as HKA, the 6DOF of the knee and ground gait data could be provided by infrared navigation based 3D portable knee joint movement analysis system comparing with the conventional X-rays. There is no significant effect of HKA on the kinematics of the partial knee joint.

Anatomical Imaging Study on Uneven Settlement of the Proximal Tibia

OBJECTIVE

Uneven settlement of the proximal tibia significantly contributes to the onset and progression of medial compartment knee OA; however, the specific location and variations of proximal tibial deformity remain unclear. Therefore, this study aimed to explore the effects of the anatomic morphology of different tibial regions on proximal tibial vara and proximal tibial microstructural changes with age in both sexes to reveal the pattern of uneven settlement of the proximal tibia.

METHODS

In this retrospective study, we reviewed the radiographs of 414 patients (789 legs) between May and September 2021. The medial proximal tibial angle (MPTA) and four anatomic angles of the tibia (i.e., the tibial plateau-epiphyseal line [PT-EL] angle, epiphyseal line-tibial platform [EL-PF] angle, epiphyseal axis inclination angle [EAIA], and subepiphyseal axis inclination angle [SAIA]) were measured. The effect of each angle on MPTA and their changes with age in both sexes were investigated using Pearson's correlation coefficient and multiple linear regression.

RESULTS

In females, PT-EL angle, EL-PF angle, and SAIA negatively correlated with MPTA (r = -0.325, -0.246, and -0.502; p < 0.05), and EAIA positively correlated with MPTA (r = 0.099, p < 0.05). Regression analysis showed that the correlations between MPTA and PT-EL angle, EL-PF angle, and SAIA were significant (β = -1.003, -0.013, and -0.971; adjusted R²  = 0.979). Furthermore, MPTA negatively correlated with age (r = -0.202, p < 0.05); PT-EL angle and EAIA positively correlated with age (r = 0.237 and 0.142, p < 0.05). Regression analysis showed that only the correlation between PT-EL angle and age was significant (β = 5.635, p < 0.05). In males, PT-EL angle, EL-PF angle, and SAIA negatively correlated with MPTA (r = -0.270, -0.267, and -0.533; p < 0.05), and EAIA positively correlated with MPTA (r = 0.135, p < 0.05). Regression analysis showed that the correlations between MPTA and PT-EL angle, EL-PF angle, and SAIA were significant (β = -0.992, -0.017, and -0.958; adjusted R²  = 0.970). However, there was no significant correlation between age and any of the measured angles (p > 0.05).

CONCLUSIONS

Proximal tibial vara is affected by the anatomic morphology of the epiphyseal and subepiphyseal regions. In females, the uneven settlement of the epiphysis progresses with age and may be responsible for dynamic varus deformity of the proximal tibia.

Automated Artificial Intelligence-Based Assessment of Lower Limb Alignment Validated on Weight-Bearing Pre- and Postoperative Full-Leg Radiographs

The assessment of the knee alignment using standing weight-bearing full-leg radiographs (FLR) is a standardized method. Determining the load-bearing axis of the leg requires time-consuming manual measurements. The aim of this study is to develop and validate a novel algorithm based on artificial intelligence (AI) for the automated assessment of lower limb alignment. In the first stage, a customized mask-RCNN model was trained to automatically detect and segment anatomical structures and implants in FLR. In the second stage, four region-specific neural network models (adaptations of UNet) were trained to automatically place anatomical landmarks. In the final stage, this information was used to automatically determine five key lower limb alignment angles. For the validation dataset, weight-bearing, antero-posterior FLR were captured preoperatively and 3 months postoperatively. Preoperative images were measured by the operating orthopedic surgeon and an independent physician. Postoperative images were measured by the second rater only. The final validation dataset consisted of 95 preoperative and 105 postoperative FLR. The detection rate for the different angles ranged between 92.4% and 98.9%. Human vs. human inter-(ICCs: 0.85−0.99) and intra-rater (ICCs: 0.95−1.0) reliability analysis achieved significant agreement. The ICC-values of human vs. AI inter-rater reliability analysis ranged between 0.8 and 1.0 preoperatively and between 0.83 and 0.99 postoperatively (all p < 0.001). An independent and external validation of the proposed algorithm on pre- and postoperative FLR, with excellent reliability for human measurements, could be demonstrated. Hence, the algorithm might allow for the objective and time saving analysis of large datasets and support physicians in daily routine.

Computer-aided Design of Distal Femoral Osteotomy for the Valgus Knee and Effect of Correction Angle on Joint Loading by Finite Element Analysis

Objective

Lateral open‐wedge distal femoral osteotomy (DFO) has been used to treat valgus deformity of the knee, with good clinical outcomes. However, there is a lack of biomechanical studies regarding the angle of correction. The objective of this study was to apply computer‐aided design (CAD) for osteotomy planning in a three‐dimensional (3D) anatomical model and to assess the biomechanical differences among the varying correction angles on joint loading by finite element analysis (FEA).

Methods

To model different angles of lateral open‐wedge DFO correction, the CAD software package Mimics 21.0 was used to accurately simulate the operated knee. The femur was cut to 0°, 2°, 4°, 6°, 8°, and 10° of varus (equivalent to hip‐knee‐ankle angles of 180°, 178°, 176°, 174°, 172°, and 170°, respectively). The original knee model and the corrected models were processed by FE software. Then, the FE models were subjected to an axial force to obtain the von Mises stress (VMS) and shear stress distributions within the femoral cartilages and menisci.

Results

Under a compressive load of 740 N, the highest VMS in lateral and medial compartments of the intact knee model was 3.418 and 3.303 MPa. The maximum value of both the VMS and the shear stress in the lateral compartment decreased as the varus angle increased, but the corresponding values in the medial compartment increased. When the hip‐knee‐ankle (HKA) angle was 180°, the VMS in the lateral and medial compartments was balanced (3.418 and 3.303 MPa, respectively). Meanwhile, when the HKA angle was 178° (3.488 and 3.625 MPa, respectively), the shear stress in the lateral and medial compartments was balanced. In addition, the magnitude of change in the stress was significantly higher in the medial compartment (90.9%) than in the lateral compartment (19.3%).

Conclusion

The optimal correction angle of the valgus knee is close to neutral alignment or slightly varus (0° ‐ 2°). Overcorrection is not recommended, as it can result in a steep increase of the stress within the medial compartment and may accelerate the process of medial compartment OA.

Variation in the patellar tendon moment arm identified with an improved measurement framework

The mechanical advantage of the knee extensor mechanism depends heavily on the patellar tendon moment arm (PTMA). Understanding which factors contribute to its variation may help improve functional outcomes following arthroplasty. This study optimized PTMA measurement, allowing us to quantify the contribution of different variables. The PTMA was calculated about the instantaneous helical axis of tibiofemoral rotation from optical tracked kinematics. A fabricated knee model facilitated calculation optimization, comparing four data smoothing techniques (raw, Butterworth filtering, generalized cross-validated cubic spline-interpolation and combined filtering/interpolation). The PTMA was then measured for 24 fresh-frozen cadaveric knees, under physiologically based loading and extension rates. Combined filtering/interpolation enabled sub-mm PTMA calculation accuracy throughout the range of motion (root-mean-squared error 0.2 mm, max error 0.4 mm), whereas large errors were measured for raw, filtered-only and interpolated-only techniques at terminal flexion/extension. Before scaling, the mean PTMA was 46 mm; PTMA magnitude was consistently larger in males (mean differences: 5 to 10 mm, p < .05) and was strongly related to knee size: larger knees have a larger PTMA. However, while scaling eliminated sex differences in PTMA magnitude, the peak PTMA occurred closer to terminal extension in females (female 15°, male 29°, p = .01). Knee size accounted for two-thirds of the variation in PTMA magnitude, but not the flexion angle where peak PTMA occurred. This substantial variation in angle of peak PTMA has implications for the design of musculoskeletal models and morphotype-specific arthroplasty. The developed calculation framework is applicable both in vivo and vitro for accurate PTMA measurement.

Gender-Related Aspects in Osteoarthritis Development and Progression: A Review

Osteoarthritis (OA) is a common degenerative joint disease treated mostly symptomatically before approaching its definitive treatment, joint arthroplasty. The rapidly growing prevalence of OA highlights the urgent need for a more efficient treatment strategy and boosts research into the mechanisms of OA incidence and progression. As a multifactorial disease, many aspects have been investigated as contributors to OA onset and progression. Differences in gender appear to play a role in the natural history of the disease, since female sex is known to increase the susceptibility to its development. The aim of the present review is to investigate the cues associated with gender by analyzing various hormonal, anatomical, molecular, and biomechanical parameters, as well as their differences between sexes. Our findings reveal the possible implications of gender in OA onset and progression and provide evidence for gaps in the current state of art, thus suggesting future research directions.

Patients with varus knee osteoarthritis undergoing high tibial osteotomy exhibit more femoral varus but similar tibial morphology compared to non-arthritic varus knees

PURPOSE

The aim of this study was to compare alignment parameters between patients undergoing high tibial osteotomy (HTO) for knee osteoarthritis (OA) and non-arthritic controls.

METHODS

Pre-operative computed tomography images from 194 patients undergoing HTO for medial knee OA and 118 non-arthritic controls were utilized. All patients had varus knee alignment (mean age: 57 ± 11 years; 45% female). The hip-knee-ankle (HKA) angle, mechanical lateral distal femoral angle (mLDFA), medial proximal tibial angle (MPTA) and non-weight-bearing joint line convergence angle (nwJLCA) were compared between "control group" and "HTO group". Femoral and tibial phenotypes were also assessed and compared between groups. Variables found on univariate analysis to be different between the groups were entered into a binary logistic regression model.

RESULTS

The mean age was lower (Δ = 4 ± 6 years, p = 0.024), body mass index (BMI) was higher (Δ = 1.1 ± 2.8 kg/m², p = 0.032) and there were more females (Δ = 14%, p = 0.020) in the HTO group. The HTO group had more overall varus (7° ± 4.7° vs 4.8° ± 1.3°, p < 0.001). There was a significant difference in the mean mLDFA between the two groups with the HTO group having more femoral varus (88.7 ± 3.2° vs 87.3 ± 1.8°, p < 0.001). MPTA was similar between the groups (p = 0.881). Age was found to be a strong determinant for femoral varus (p = 0.03).

CONCLUSION

Patients undergoing HTO for medial knee OA have more femoral varus compared to non-arthritic controls while tibial morphology was similar. This will be an important consideration in pre-operating planning for realignment osteotomy in patients presenting with medial knee OA and warrants further investigation.

LEVEL OF EVIDENCE

III, retrospective comparative study.

Metabolic syndrome and the incidence of knee osteoarthritis: A meta-analysis of prospective cohort studies

Background

Cross-sectional studies suggest an association between metabolic syndrome (MetS) and knee osteoarthritis (KOA). We performed a meta-analysis to evaluate whether MetS is an independent risk factor for KOA.

Methods

Prospective cohort studies evaluating the association between MetS and KOA in general population were retrieved from PubMed and Embase. Only studies with multivariate analyses were included. Data were pooled with a random-effect model, which is considered to incorporate heterogeneity among the included studies.

Results

Five studies including 94,965 participants were included, with 18,990 people with MetS (20.0%). With a mean follow-up duration of 14.5 years, 2,447 KOA cases occurred. Pooled results showed that MetS was not significant associated with an increased risk of KOA after controlling of factors including body mass index (adjusted risk ratio [RR]: 1.06, 95% CI: 0.92~1.23, p = 0.40; I² = 33%). Subgroup analysis showed that MetS was independently associated with an increased risk of severe KOA that needed total knee arthroplasty (RR = 1.16, 95% CI: 1.03~1.30, p = 0.02), but not total symptomatic KOA (RR = 0.84, 95% CI: 0.65~1.08, p = 0.18). Stratified analyses suggested that MetS was independently associated with an increased risk of KOA in women (RR = 1.23, 95% CI: 1.03~1.47, p = 0.02), but not in men (RR = 0.90, 95% CI: 0.70~1.14, p = 0.37).

Conclusions

Current evidence from prospective cohort studies did not support MetS was an independent risk factor of overall KOA in general population. However, MetS may be associated with an increased risk of severe KOA in general population, or overall KOA risk in women.