Tibial cutting guide (resector) holding pins position and subsequent risks of periprosthetic fracture in unicompartmental knee arthroplasty: a finite element analysis study

Periprosthetic tibial fracture as a complication of unicompartmental knee arthroplasty: Current insights

Periprosthetic fracture following knee arthroplasty is a rare but devastating complication associated with significant morbidity. With unicompartmental knee arthroplasty being performed far less frequently than total knee arthroplasty, periprosthetic fracture following unicompartmental knee arthroplasty presents a particular challenge to orthopaedic surgeons, due to clinical unfamiliarity and sparsity of literature. An up-to-date review of the epidemiology, risk factors, and management strategies for PPF after UKA is presented.

Tibial Lateral Condyle Fracture After Cementless Oxford Unicompartmental Knee Arthroplasty (UKA): A Report of Four Cases

Cementless unicompartmental knee arthroplasty (UKA) has a lower rate of radiolucency in postoperative follow-up than cemented UKA. However, the rate of tibial plateau fracture, one of the complications, has been reported to be higher in cementless UKA than in cemented UKA. We report four cases of postoperative tibial lateral condyle fractures after cementless Oxford UKA. Four patients underwent cementless Oxford UKA. Immediate postoperative radiography and CT showed no fracture lines. At five to six weeks postoperatively, MRI showed a fracture line from the intersection of the longitudinal and transverse tibial osteotomies through the lateral pinhole to the end of the lateral tibial diaphysis. At three months, bone union was observed without surgical treatments. Lateral tibial fracture after cementless Oxford UKA has a good clinical course without the need for surgical intervention. Medial fractures should thus be more actively prevented. MRI is useful for less symptomatic tibial lateral condyle fractures.

A novel image-based machine learning model with superior accuracy and predictability for knee arthroplasty loosening detection and clinical decision making

Background

Loosening is the leading cause of total knee arthroplasty (TKA) revision. This is a heavy burden toward the healthcare system owing to the difficulty in diagnosis and complications occurring from the delay management. Based on automatic analytical model building, machine learning, may potentially help to automatically recognize the risk of loosening based on radiographs alone. The aim of this study was to build an image-based machine-learning model for detecting TKA loosening.

Methods

Image-based machine-learning model was developed based on ImageNet, Xception model and a TKA patient X-ray image dataset. Based on a dataset with TKA patient clinical parameters, another system was then created for developing the clinical-information-based machine learning model with random forest classifier. In addition, the Xception Model was pre-trained on the ImageNet database with python and TensorFlow deep learning library for the prediction of loosening. Class activation maps were also used to interpret the prediction decision made by model. Two senior orthopaedic specialists were invited to assess loosening from X-ray images for 3 attempts in setting up comparison benchmark.

Result

In the image-based machine learning loosening model, the precision rate and recall rate were 0.92 and 0.96, respectively. While for the accuracy rate, 96.3% for visualization classification was observed. However, the addition of clinical-information-based model, with precision rate of 0.71 and recall rate of 0.20, did not further showed improvement on the accuracy. Moreover, as class activation maps showed corresponding signals over bone-implant interface that is loosened radiographically, this confirms that the current model utilized a similar image recognition pattern as that of inspection by clinical specialists.

Conclusion

The image-based machine learning model developed demonstrated high accuracy and predictability of knee arthroplasty loosening. And the class activation heatmap matched well with the radiographic features used clinically to detect loosening, which highlighting its potential role in assisting clinicians in their daily practice. However, addition of clinical-information-based machine-learning model did not offer further improvement in detection. As far as we know, this is the first report of pure image-based machine learning model with high detection accuracy. Importantly, this is also the first model to show relevant class activation heatmap corresponding to loosening location.

Translational potential

The finding in this study indicated image-based machine learning model can detect knee arthroplasty loosening with high accuracy and predictability, which the class activation heatmap can potentially assist surgeons to identify the sites of loosening.

Augmented reality-aided unicompartmental knee arthroplasty

Purpose

To illustrate a surgical technique for augmented reality (AR)-assisted unicompartmental knee arthroplasty (UKA) and report preliminary data.

Methods

We developed an AR-based navigation system that enables the surgeon to see the tibial mechanical axis superimposed on the patient’s leg in addition to the tibial cutting angle. We measured the tibial resection angle in 11 UKAs using postoperative radiographs and calculated the absolute difference between preoperative target angle and postoperative measured angle. The target angle was determined for each patient: mean values were 0.7° ± 1.0° varus in coronal alignment and 5.3° ± 1.4° posterior slope in sagittal alignment.

Results

The angles measured on postoperative radiographs were 2.6° ± 1.2° varus in the coronal plane and 4.8° ± 2.5° posterior slope in the sagittal plane. The absolute differences between the target and measured angles were 1.9° ± 1.5° in coronal alignment and 2.6° ± 1.2° in sagittal alignment. No patients experienced complications, including surgical site infection and periprosthetic fracture.

Conclusion

The AR-based portable navigation system may provide passable accuracy in terms of proximal tibial resection during UKA.

Level of Evidence

IV

Avulsion Fracture of Bicruciate Ligament and Patellar Tendon in Bicruciate-Retaining Total Knee Arthroplasty

Tibial intercondylar fracture with anterior cruciate ligament avulsion is a unique but rare complication of bicruciate-retaining total knee arthroplasty. Here, we describe an even rarer condition that the tibial intercondylar fracture involved bicruciate ligament and partial patellar tendon avulsion fracture resulting in significant clinical instability in a 70-year-old woman, a combination not yet reported in the literature. Dual-energy computed tomography helped characterize the fracture. During revision surgery, the bicruciate retaining total knee arthroplasty was revised to posterior-stabilized total knee arthroplasty and the patellar tendon was repaired with a suture anchor. She recovered well progressively, and at 6 months, she could walk with the use of an assisted walking device.