The correlation between femoral trochlear dysplasia and meniscal tear in young individuals: a finite element analysis based on MRI

Introduction

Meniscal tear is a common factor leading to knee disability in clinical work. Reports have estimated that the incidence of meniscal tear is approximately 60 per 100,000, and there is a higher prevalence of meniscal tear in the physically active population (1). Meanwhile, it is well established that meniscal tear can lead to early degenerative osteoarthritis via the increased axial and sheer stress to the adjacent articular cartilage (2), and after meniscal tear, arthroscopic surgery is usually considered the main treatment, but previous studies have shown that surgical treatment of meniscal tear is associated with the long term risk of knee osteoarthritis (3,4). Therefore, meniscal tear poses significant challenges to patients, affecting their quality of life.

Femoral trochlear dysplasia (FTD), characterized by shallow trochlear depth, refers to an anatomical abnormality of the trochlear groove. Due to the unstable contact of the patella and femoral trochlear, patients with FTD encounter clinical symptoms such as patella instability and joint pain (5). Therefore, FTD is possibly a high-risk factor of knee disorders. A previous study by Erden et al. showed a significant correlation between FTD and global joint hypermobility (GJH) (6), which was a risk factor of meniscal tears (7), and Stumetz et al. retrospectively analyzed the strong association of increased tibial tubercle-trochlear groove distance (TT-TG) with both meniscal and cruciate internal knee derangements (8). Their studies have shown the indirect links between FTD and meniscal tear through GJH and increased TT-TG, but currently, there is little research on the direct relation between meniscal tear and FTD. To our knowledge, only Atay et al. (9) have reported that meniscal tear was detected in 30.1% of patients with FTD, compared to 19% in patients aged between 50 and 59 years in another study (10). However, the incidence of FTD in young people with atraumatic meniscal tears has not been reported in the literature.

Finite element analysis (FEA) has been widely applied in knee biomechanics, allowing simulations based on patient-specific three-dimensional (3D) anatomy to assess how joint morphology and loading conditions influence stress distribution and contact patterns. Kedgley et al. found that both the type of meniscal tear and its location within the meniscus influenced the stress on the tear surfaces using FEA (11). Kaiser et al. confirmed the therapeutic effect of trochleoplasty in the trochleodysplastic knees of patients with symptomatic patellofemoral instability using a FEA model (12) and then used the validated models to investigate the quantitative effect of vastus medialis obliquus strengthening, medial patellofemoral ligament reconstruction, and the combination of medial patellofemoral ligament reconstruction and trochleoplasty on lateral patellofemoral stability in different flexion angles (13). Moreover, recent advances have combined FEA with musculoskeletal modeling to simulate gait-related loading conditions (14,15), and these studies highlight the potential for high-fidelity evaluation of meniscal biomechanics. However, FEA has not been reported in exploring the abnormal mechanical changes in the knee caused by FTD. By contrast, the present study used FEA primarily as a mechanistic validation tool to support the epidemiological findings related to meniscus tear based on magnetic resonance imaging (MRI). In this study, we hypothesized that FTD is a risk factor of meniscal tear. First, we investigated the prevalence of FTD in young patients with meniscal tear. Second, the meniscus tear locations in patients with and without FTD were observed, respectively. Last, FEA was used to explore the abnormal mechanical distribution resulting from FTD. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1162/rc).

Methods

This retrospective study was approved by the Ethics Committee of Shanghai Sixth People’s Hospital (No. 2024-164) and was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The requirement to obtain the informed consent of participants was waived due to the retrospective design.

Participants

There were 422 patients with meniscal tears confirmed by the arthroscopy in the meniscal tears group, and they underwent MR scans before the arthroscopy in our institution from July 2020 to April 2023. A total of 412 patients with a history of knee joint pain but no evidence of meniscal tears on MRI served as the comparison group. Patients with excessive accumulation of fluid in the joint, a history of tumor, trauma or knee fracture, inflammation, knee surgery, cruciate ligament injury or tear, osteoarthritis, lower-extremity force line abnormality, or discoid meniscus observed on MRI, and those older than 35 years or younger than 18 years were excluded in two groups. Figure 1 shows the participants screening workflow in the meniscal tears group and the comparison group.

Figure 1 Participant screening workflow in the meniscal tears group and the comparison group. CT, computed tomography; FEA, finite element analysis; MR, magnetic resonance; MRI, magnetic resonance imaging.

Knee joint scanning and measurement

MR scans were performed on two groups in the supine position with a 3.0-T scanner (Magnetom Verio, Siemens Healthcare, Erlangen, Germany). The knees were slightly flexed up to 15–30°. The MR scanning protocol included sagittal T1-weighted and proton density-weighted image (PDWI), axial and coronal PDWI.

• Sagittal T1-weighted: repetition time (TR) =466 ms, echo time (TE) =8 ms, flip angle =140°, matrix =320×240 pixels, field of view (FOV) read =170 mm × 170 mm, FOV phase =100%, slice thickness =3.0 mm, space between slices =0.5 mm, voxel size =0.5 mm × 0.5 mm × 3.0 mm, imaging time (min:s) =00:27.
• Sagittal PDWI: TR =2,320 ms, TE =35 ms, flip angle =140°, matrix =320×240 pixels, FOV read =170 mm × 170 mm, FOV phase =100%, slice thickness =3.0 mm, space between slices =0.5 mm, voxel size =0.4 mm × 0.4 mm × 3.0 mm, imaging time (min:s) =00:51.
• Axial PDWI: TR =2,550 ms, TE =35 ms, flip angle =140°, matrix =320×240 pixels, FOV read =170 mm × 170 mm, FOV phase =100%, slice thickness =3.0 mm, space between slices =0.5 mm, voxel size =0.5 mm × 0.5 mm × 3.0 mm, imaging time (min:s) =01:01.
• Coronal PDWI: TR =2,570 ms, TE =31 ms, flip angle =140°, matrix =320×240 pixels, FOV read =170 mm × 170 mm, FOV phase =100%, slice thickness =3.0 mm, space between slices =0.5 mm, voxel size =0.5 mm × 0.5 mm × 0.3 mm, imaging time (min:s) =01:02.

According to Pfirrmann et al.’s (16) suggestions, the sulcus angle, sulcus width, sulcus depth, sulcus lateral facet width, trochlea epicondylar axial angle, sulcus lateral facet ratio, trochlear facet asymmetry, patella epicondylar axis angle were measured at 3 cm above the tibiofemoral joint, and Insall-Salvati index was measured in the sagittal PDWI of the knee joint MRI (Figure 2). FTD was classified into type A (shallow trochlear sulcus), B (flat or convex trochlea), C (hypoplastic medial facet), and D (cliff-shaped trochlea) according to the Dejour classification (17), and we entitled the knee joint without FTD as type 0, as shown in Figure 3. Two professional radiologists (AA and BB) took the measurement of radiological parameters, and the main meniscal tear locations were separately counted by them. When they were not consistent with the diagnosis, they solved it by consultation.

Figure 2 Measurement of the radiological parameters on the axial and sagittal images. The angle subtended by AB and DE, trochlea epicondylar axial angle; the angle subtended by FG and DE, patella epicondylar axis angle. ∠AOB, sulcus angle; AB, sulcus width; AC, sulcus lateral facet width; AC/AB, sulcus lateral facet ratio; BO/AO, trochlear facet asymmetry; HI/IJ, Insall-Salvati index; OC, sulcus depth.

Figure 3 The MRI showing the different types of FTD: type 0 (knee without FTD), A (shallow trochlear sulcus), B (flat or convex trochlea), C (hypoplastic medial facet), and D (cliff-shaped trochlea). The FEA showed the stress distribution on menisci of knee joints with different types of FTD, and the color changes from red to deep blue represent the stress variation from large to small on the menisci. The left one is medial meniscus, and the right one is lateral meniscus. FEA, finite element analysis; FTD, femoral trochlear dysplasia; MRI, magnetic resonance imaging.

The establishment of finite element model of knee joint

To avoid the changes of force distribution due to meniscus tears and the occurrence of selection bias, we randomly selected the imaging data of patients in each type of FTD (type 0, A, B, C, and D) in the comparison group to establish FEA models. These patients underwent both CT and MRI in our institution. For CT scans, these patients were in the supine position with their knee extended and underwent scanning by a 64-slice multidetector CT scanner (GE, LightSpeed VCT, Chicago, IL, USA) with the tube voltage as 120 kV, tube current as 350 mA, slice thickness as 5 mm, and the reconstructive thickness as 0.625 mm. In MR scans, the protocols included sagittal T1-weighted and PDWI.

• Sagittal T1-weighted: TR =11.7 ms, TE =5.44 ms, flip angle =140°, matrix =320×240 pixels, FOV read =150 mm × 150 mm, FOV phase =100%, slice thickness =0.6 mm, space between slices =0.5 mm, voxel size =0.5 mm × 0.5 mm × 3.0 mm, imaging time (min:s) =05:31.
• Sagittal PDWI: TR =14.1 ms, TE =5 ms, flip angle =140°, matrix =320×240 pixels, FOV read =150 mm × 150 mm, FOV phase =100%, slice thickness =0.6 mm, space between slices =0.5 mm, voxel size =0.4 mm × 0.4 mm × 3.0 mm, imaging time (min:s) =05:57.

In this study, the establishment of all knee joint models was based on the integration of patient CT and MRI data. First, the CT data of patients with different types of FTD were imported into Mimics 19.0 software (Materialise, Leuven, Belgium). By setting specific thresholds (235–1,850 HU), the fibula, tibia, femur, and patella were segmented to reconstruct their surface geometric models, which were then exported in STL format. Simultaneously, MRI data were used to segment the articular cartilage, meniscus, and bones, generating preliminary STL surface models that included soft tissues.

Due to differences in coordinate systems and resolutions between computed tomography (CT) and magnetic resonance (MR) images, registration of the MRI models was necessary. First, anatomical landmarks (such as the femoral intercondylar line, tibial intercondylar eminence, and patellar apex) were used in Mimics to perform rigid registration. The MRI bone models were preliminarily aligned to the CT bone models, and the global positional calibrations of the two datasets were completed. Subsequently, the aligned CT bone models and MRI soft tissue models were imported into Geomagic Studio 2017 (3D Systems, Rock Hill, SC, USA), where global registration algorithms were employed to further adjust the positional relationships of the soft tissue models. Fine registration algorithms were then applied to refine the soft tissue boundaries, ensuring sub-millimeter precision in alignment with the CT bone model boundaries. Local deformation tools were used to correct the complexities of the soft tissue boundaries, ensuring that the geometric morphology of the soft tissues was fully consistent with the CT bone models. The finalized integrated models were exported in STEP format.

The STEP files were subsequently imported into SolidWorks software (Dassault Systèmes, Vélizy-Villacoublay, France), where the 3D knee joint models were assembled within a unified coordinate system to ensure anatomical consistency of the bones, articular cartilage, and menisci. The assembled models were then exported in x_t format. Quadratic tetrahedral elements were used for bone and cartilage, and mixed tetrahedral/hexahedral elements for the meniscus. Local refinement (≈0.8–1.0 mm) was applied in posterior horns and contact regions, with coarser mesh (≈1.5–2.0 mm) elsewhere; overall quality indices met recommended thresholds (18,19). Finally, the models were imported into ANSYS 19.0 (ANSYS, Canonsburg, PA, USA) for the establishment of structural analysis models, as shown in Figure 4A-4C. In this study, bones, articular cartilage, and menisci were defined as isotropic linear elastic materials, and their respective material properties were assigned Young’s modulus (E) and Poisson’s ratio (ν) based on their mechanical characteristics (20-25), as detailed in Table 1. Ligament structures within the knee joint were simplified as spring elements, and then all models were meshed in ANSYS and used for FEA. The mesh convergence analysis verified that the soft tissue mesh size of 0.5 mm adopted in this study satisfied the convergence criterion (relative change below 3%), ensuring the reliability of the computational results. The detailed procedures and findings of mesh convergence analysis are provided in Appendix 1 (Table S1, Figure S1).

Figure 4 The knee joint model development process: (A) the knee joint model reconstructed from CT and MRI; (B) the mesh generation in ANSYS; (C) the boundary condition settings in ANSYS. CT, computed tomography; MRI, magnetic resonance imaging.

Boundary condition settings

Due to the presence of synovial fluid in the knee joint, the contact between femoral cartilage and medial meniscus, lateral meniscus, tibial plateau cartilage, and patellar cartilage was defined as frictionless contact, and the rest as bound contact. The main ligaments (anterior cruciate ligament, posterior cruciate ligament, medial collateral ligament, lateral collateral ligament, patellar ligament) and quad tendon were represented as tension-only spring elements connecting their anatomical insertion sites, and meniscal roots (anterior and posterior horns) were anchored to the tibial plateau using high-stiffness, tension-only spring elements to maintain hoop stress transfer. The material properties for ligaments, tendons, and meniscal roots are provided in Table 2 (26-30). Meanwhile, we defined the degrees of freedom of the femur and femoral cartilage as 0 in the X- and Y-axis directions, and the distal tibia and fibula were set to be fixed to the ground. According to previous research (31), the human knee joint bears a torque of 20–30 Nm during activity, so a moment of 20 Nm was applied to the upper surface of the femur. Finally, stress analysis was performed on the model to observe and analyze the stress distribution on the medial and lateral menisci of the knee joint models with different types of FTD. The FEA reported three primary endpoints: (I) peak von Mises stress to reflect local stress concentration; (II) contact stress; and (III) contact area to characterize load distribution. For clinical comparability, values were summarized at the meniscal subregional level (medial/lateral × anterior/midbody/posterior).

Statistical analysis

Statistical analysis was performed using the software SPSS 26.0 (IBM Corp., Armonk, NY, USA). The distributions of quantitative variables were tested by the Shapiro-Wilk test. The independent samples t-test was used to analyze the continuous variables with a normal distribution. The Mann-Whitney U test was used for the variables with a non-normal distribution. The chi-square test was used to analyze the prevalence of trochlear dysplasia in two groups. To enhance the reliability of the regression model, a multicollinearity assessment was conducted on the predictor variables utilizing the variance inflation factor (VIF). Variables with a VIF value less than 10 were retained in the subsequent logistic regression analysis. A P value <0.05 was accepted as statistically significant.

Results

The demographic characteristics of two groups

There were 422 patients in the meniscal tears group; 208 of these patients had medial meniscal tears, 207 patients had lateral meniscal tears, and 7 patients had both. There were 412 patients in the comparison group. Table 3 shows the demographic characteristics in the meniscal tears group and comparison group, and there were no statistical differences in the age, sex, and side of knee in the two groups (P=0.280, P=0.396, and P=0.492, respectively).

Meanwhile, 89 of 259 male patients (34.36%) and 63 of 163 female patients (38.65%) had FTD in the meniscal tears group, and 49 of 241 male patients (20.33%) and 30 of 171 female patients (17.54%) had FTD in the comparison group. There was no statistical difference in the incidence rate of FTD between males and females in the same group (P=0.405 for the meniscal tears group and P=0.526 for the comparison group).

The influence of FTD to meniscal tear

Table 4 shows the number of different types of FTD in the two groups, and the prevalence of FTD was significantly higher in the meniscal tears group than in the comparison group (36.02% vs. 19.17%, P<0.001). With a total of 231 patients having FTD in the two groups, the proportion of individuals with meniscal tears was also higher than that of people without meniscal tears (65.8% vs. 34.2%, P<0.001).

The anatomical parameters of two groups

As shown in Table 5, the sulcus angle, sulcus width, and sulcus lateral facet width were significantly higher, whereas sulcus depth and trochlea epicondylar axial angle were significantly lower in the meniscal tears group than in the comparison group (P<0.001). There were no significant differences in the sulcus lateral facet ratio, trochlear facet asymmetry, patella epicondylar axis angle, and Insall–Salvati index between the two groups (P>0.05).

Whether FTD was an independent risk factor of meniscal tear

According to previous reports (17,32,33), FTD was divided into low-grade (type A) and high-grade (type B, C, and D), and this two-grade classification has greater significance in clinical work. The results of multicollinearity testing indicated that the high VIF of sulcus width, sulcus lateral facet width, and sulcus lateral facet ratio was due to the ratio of sulcus lateral facet width and sulcus width being sulcus lateral facet ratio, so we chose sulcus width instead of sulcus lateral facet width and sulcus lateral facet ratio to build logistic regression model. In sum, age, gender, FTD grades, sulcus angle, sulcus width, sulcus depth, trochlea epicondylar axial angle, trochlear facet asymmetry, patella epicondylar axis angle, and Insall-Salvati index were retained in the model. Table 6 presents the results of logistic regression analysis, which showed that age [odds ratio (OR) =1.034, P=0.043] and gender (OR =2.376, P<0.001) were associated with meniscal tear. The low-grade FTD (OR =0.877, P=0.681) was not associated with meniscal tear, whereas the high-grade FTD (OR =0.278, P=0.043) was closely associated with meniscal tear. Sulcus angle (OR =1.092, P=0.002), sulcus width (OR =1.192, P<0.001), and trochlea epicondylar axial angle (OR =0.909, P<0.001) were associated with meniscal tear, whereas sulcus depth (OR =0.904, P=0.325), trochlear facet asymmetry (OR =0.375, P=0.150), patella epicondylar axis angle (OR =1.020, P=0.456), and Insall-Salvati index (OR =0.401, P=0.051) were not.

The probability of locations in meniscal tears

In the meniscal tears group, there were 429 meniscal tears in the 422 patients (208 had medial meniscal tears, 207 had lateral meniscal tears, and 7 had both). There were 157 meniscal tears in the total of 152 FTD patients in the meniscal tears group (78 had medial meniscal tears, 69 had lateral meniscal tears, and 5 had both). Table 7 presents the number and incidence rate of different meniscal tear locations in the meniscal tears group and the meniscal tear patients with or without FTD. It shows that tears commonly occurred in the posterior horn of the medial meniscus, followed by the anterior horn and midbody of the lateral meniscus.

The abnormal biomechanical distribution in FTD

The results of FEA showed that the stress on the medial and lateral menisci of the knees with type 0 was uniformly distributed in the anterior horn and midbody. In patients with FTD types from A to D, the stress was more focused on the posterior horn in the medial meniscus, and the strength of stress was abnormally increased. For the lateral meniscus, the stress distribution was more concentrated on the anterior horn or midbody. These stress changes were in correspondence with the high probability of tear in these locations, which provided the biomechanical evidence for the reason why they were most vulnerable to tear (Figure 3).

Discussion

In our research, the most significant finding was that the incidence of FTD in the young patients with meniscal tears was higher than that in the comparison group. FEA was first used in patients with FTD, and it confirmed that patients with FTD showed abnormal biomechanical distribution on menisci. With the extent of FTD exacerbated, from type A to D, the abnormal stress on menisci gradually increased. The posterior horn of the medial meniscus received the strongest stress, followed by the anterior horn and midbody of the lateral meniscus, and this was in correspondence with the rate of tear locations. Therefore, FTD was a potential risk factor of meniscal tear.

A previous report showed that high-grade FTD was associated with anterior knee pain, patellar maltracking, instability, and the development of osteoarthritis (34). Meanwhile, Peeters et al. showed that in the tibial plateau and patella of FTD individuals, a narrower medial compartment led to a smaller overall mediolateral width (35), indicating that FTD had negative effects on the movement and stability of knee. Thus, we speculate that FTD changes the biomechanics of knee joint, which leads to increased stress on the meniscus and makes it more likely to be injured. In addition, one meniscal tear may aggravate the instability of the knee joint and increase the risk of the other meniscus tearing, which needs further research.

The present study showed that the prevalence of FTD in patients with meniscal tears was 36.02%, whereas the prevalence of FTD in the general population was 14.45% in a study with a sample size of 1,992 cases that reviewed MR images (36). In our study, the prevalence of FTD in patients without meniscal tears was 19.17%, so the prevalence of FTD in patients with meniscal tears in our study was obviously increased. However, another study that focused on the prevalence of FTD by evaluating human skeletally mature femoral specimens on photographs reported that the prevalence of FTD was around 39.24% (37). This difference might be due to the different positions of the knees and the different observing methods.

Previous reports have indicated that the two-grade classification showed better intra- and inter-observer agreements compared to the four-grade classification (38). Individuals with the high-grade FTD were more likely to benefit from surgery compared to the low-grade FTD (17,32,33). It indicated that the two-grade classification had greater clinical significance, so it was used in our logistic regression analysis. The results showed that the low-grade FTD was not, whereas the high-grade FTD was, the independent predictor of meniscal tear, probably because the force on the meniscus in the low-grade FTD group is not large enough, whereas in the high-grade FTD group, the higher stress on the meniscus makes it more likely to result in tears. Therefore, for patients with high-grade FTD, preventing meniscal tear is of vital importance, and for those who have already experienced meniscus tear, a more aggressive treatment plan is necessary to promote recovery. A previous report (7) showed that age and gender were the risk factors of meniscal tear, and male sex was associated with a higher risk of degenerative meniscal tear. However, in our research, females were more prone to meniscus tear than males. This may be attributed to the difference in the research groups, and our participants were aged from 18 to 35 years. In this age range, meniscus tears associated with FTD may be more likely to be sports-related injuries rather than degenerative ones. Moreover, our study identified sulcus angle, sulcus width, and trochlea epicondylar axial angle as the risk factors of meniscal tear, whereas sulcus depth, trochlear facet asymmetry patella epicondylar axis angle, and Insall-Salvati index were not found to be significant risk factors, and the potential mechanism underlying these findings requires further investigation.

FEA has great potential to study the pathogenesis of degenerative or traumatic joint diseases. The location of meniscus tear was consistent with this abnormal biomechanical redistribution. We found that the posterior horn of the medial meniscus had the highest rate of tear compared to other parts of meniscus, which was in correspondence with a previous report (39), and approximately 74% of medial meniscal tears were in the posterior horn in our research, compared to the reported 75% of medial meniscal tears being in the posterior horn (40). In our study, the FTD patients without meniscus tear were used to build an FEA model, because it was reported that the location and type of meniscus tear influenced the stress distribution on the meniscus. To avoid this disturbance, we did not build an FEA model from FTD patients with meniscus tear.

Previous research using FEA confirmed that the stress on the medial meniscus was higher than that on the lateral meniscus, explaining why the medial meniscus was more prone to tear (41), and this was consistent with our results. Lateral meniscus has less attachment to peripheral structure, allowing it more flexibility and less tendency to tear when compared to medial meniscus (42,43). However, in our research, there were slightly more lateral meniscal tears than medial meniscal tears in the meniscal tears group. This was mainly for the reason that we took arthroscopy as the gold standard for the diagnosis of meniscal tear. However, in our clinical work, some patients with meniscal tears diagnosed by MRI underwent conservative treatment instead of arthroscopic surgery. Meanwhile, a considerable amount of meniscal tears in the elderly patients were due to degeneration, and they were excluded in our study. Their tears were mainly located in the posterior horn of the medial meniscus (44), thus causing the inconsistency between our research and the results in the general population.

It is reported that FTD has a higher incidence in females than in males (45), yet there was a slightly higher proportion of FTD patients in the meniscal tears group and a little lower proportion of FTD patients in the comparison group in females than that in males in our research. This was mainly because the incidence of meniscus tear in men was higher than that in women, especially in the physically active population (7,46). In addition, not all the meniscal tear patients were associated with pain (47), and these patients are less likely to seek medical care, which made the gender distribution of FTD patients in the two groups different from that in the general population.

Children were more likely to have discoid meniscus, and their meniscus tears had better healing outcomes than that in adults (48), so some children with tears chose conservative treatment instead of arthroscopic surgery in our clinical work. Meanwhile, MRI provided lower sensitivity and specificity in evaluating the meniscal tears of children than that of adults (49). Additionally, degenerative meniscus lesions mainly occurred in the middle-aged or elderly individuals, which is closely related to tissue aging, and probably follows the osteoarthritis (50). In order to avoid the above risk factors that affected the results, individuals younger than 18 years or older than 35 years were excluded in this study.

There are some limitations in our study. First, we only focused on meniscal tears and did not observe the injuries of cartilage, ligaments, and so on. Although there were concomitant injuries in FTD, we wanted to reduce interference factors and ascertain the more accurate relationship between meniscal tear and FTD. Second, our FEA was designed primarily as a mechanistic validation tool to support MRI-based clinical findings rather than to provide absolute stress predictions. Accordingly, several methodological simplifications were adopted, including representing bone as a homogeneous high-modulus elastic material rather than real heterogeneous bone, while retaining elasticity instead of assuming a purely rigid body to help maintain contact stability and improve future applicability (51,52), simplifying ligaments and meniscal roots as tension-only springs (18,53), assuming frictionless cartilage–cartilage contact (19), and applying a simplified moment load. Third, we adopted a simplified quasi-static loading scheme rather than a full musculoskeletal-FEA integration. Nevertheless, recent musculoskeletal-FEA frameworks (14,15,54,55) have demonstrated the potential of dynamic loading integration, and future work will incorporate such approaches together with cadaveric or in-vivo validation to enhance generalizability. Finally, our research just focused on the young group, and further research is needed in other age groups.

Conclusions

Conclusively speaking, the incidence of FTD was significantly higher in the patients with meniscal tears, indicating that FTD might be a potential risk factor of meniscal tear. The reason for this might be that FTD changed the biomechanics and increased the stress on the meniscus.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1162/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1162/dss

Funding: This work was supported by the National Natural Science Foundation of China (No. 81503595) and the Shanghai Health Care Commission Project (No. 202040194).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1162/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This retrospective study was approved by the Ethics Committee of Shanghai Sixth People’s Hospital (No. 2024-164), and informed consent from participants was waived due to the retrospective design.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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