Using Statistical Shape Models to Optimize TKA Implant Design

Subchondral bone expansion in advanced knee osteoarthritis: Relation with radiographic severity and role in surgical decision-making

Background

Joint space width (JSW) is a traditional imaging marker for knee osteoarthritis (OA) severity, but it lacks sensitivity in advanced cases. We propose tibial subchondral bone area (TSBA), a new CT imaging marker to explore its relationship with OA radiographic severity, and to test its performance for classifying surgical decisions between unicompartmental knee arthroplasty (UKA) and total knee arthroplasty (TKA) compared to JSW.

Methods

We collected clinical, radiograph, and CT data from 182 patients who underwent primary knee arthroplasty (73 UKA, 109 TKA). The radiographic severity was scored using Kellgren-Lawrence (KL) grading system. TSBA and JSW were extracted from 3D CT-reconstruction model. We used independent t-test to investigate the relationship between TSBA and KL grade, and binary logistic regression to identify factors associated with TKA risk. The accuracy of TSBA, JSW and established classification model in differentiating between UKA and TKA was assessed using AUC.

Results

All parameters exhibited inter- and intra-class coefficients greater than 0.966. Patients with KL grade 4 had significantly larger TSBA than those with KL grade 3. TSBA (0.708 of AUC) was superior to minimal/average JSW (0.547/0.554 of AUC) associated with the risk of receiving TKA. Medial TSBA, together with gender and Knee Society Knee Score, emerged as independent classification factors in multivariate analysis. The overall AUC of composite model for surgical decision-making was 0.822.

Conclusion

Tibial subchondral bone area is an independent imaging marker for radiographic severity, and is superior to JSW for surgical decision-making between UKA and TKA in advanced OA patients.

Database of segmentations and surface models of bones of the entire lower body created from cadaver CT scans

The range of applications of digital surface models of the bones in science and industry is wide. Three-dimensional reconstructions of bones are used in biomechanics, biomedical engineering, medical image processing, orthopedics, traumatology, radiology, patient education, anatomy, anthropometry, forensic anthropology, ergonomics, usability and human factors engineering, or accident and injury analysis and prevention. No open access database or repository of skeletal surface models of the full lower extremities exists. Therefore, the objective of this publication was to provide access to consistent complete bone models of the pelvis and lower limbs of multiple subjects, including biometric data. Segmentations and surface models of the bones of the lower extremities of more than twenty subjects were created from open access postmortem whole-body computed tomography scans. The database provides a broad range of applications by giving access to the data of the complete process chain, from the raw medical imaging data through the segmentations to the surface models.

Statistical modeling: Assessing the anatomic variability of knee joint space width

Population-based knee joint space width (JSW) assessments are promising for the prevention and early diagnosis of osteoarthritis. This study aimed to establish the statistical shape and alignment model (SSAM) of knee joints for assessing anatomic variation in knee JSW in the healthy Chinese male population. CT scans of asymptomatic knee joints of healthy male participants (n = 107) were collected for manual segmentation to create mesh samples. The as-scanned positional error was reduced by a standard processing flow of deformable mesh registration. Principal component analysis (PCA) was performed to create a tibiofemoral SSAM that was trained on all mesh samples. The anatomic variability of the JSW in the healthy Chinese male population was then assessed using the SSAM with regression analysis and 3D analysis by color-coded mapping. Almost all PCA modes had a linear influence on the anatomic variation of the medial and lateral JSW. The JSW variability within the SSAM was mainly explained by mode 1 (45.1 % of variation), demonstrating that this mode had the greatest influence on JSW variation. 3D assessment of the JSW showed that the minimum medial JSW varied from 2.76 to 3.23 mm, and its site shifted a short distance on the medial tibial plateau. The root-mean-square fitting and generalization errors of the SSAM were below 1 mm. This study will benefit the design and optimization of prosthetic devices, and may be applicable to the prevention and early diagnosis of osteoarthritis.

Designing and in vitro testing of a novel patient-specific total knee prosthesis using the probabilistic approach

In order to prevent failure as well as ensure comfort, patient-specific modelling for prostheses has been gaining interest. However, deterministic analyses have been widely used in the design process without considering any variation/uncertainties related to the design parameters of such prostheses. Therefore, this study aims to compare the performance of patient-specific anatomic Total Knee Arthroplasty (TKA) with off-the-shelf TKA. In the patient-specific model, the femoral condyle curves were considered in the femoral component's inner and outer surface design. The tibial component was designed to completely cover the tibia cutting surface. In vitro experiments were conducted to compare these two models in terms of loosening of the components. A probabilistic approach based on the finite element method was also used to compute the probability of failure of both models. According to the deterministic analysis results, 103.10 and 21.67 MPa von Mises stress values were obtained for the femoral component and cement in the anatomical model, while these values were 175.86 and 25.76 MPa, respectively, for the conventional model. In order to predict loosening damage due to local osteolysis or stress shield, it was determined that the deformation values in the examined cement structures were 15% lower in the anatomical model. According to probabilistic analysis results, it was observed that the probability of encountering an extreme value for the anatomical model is far less than that of the conventional model. This indicates that the anatomical model is safer than the conventional model, considering the failure scenarios in this study.