Radiomics analysis of patellofemoral joint improves knee replacement risk prediction: Data from the Multicenter Osteoarthritis Study (MOST)

Objective

Knee replacement (KR) is the last-resort treatment for knee osteoarthritis. Although radiographic evidence of tibiofemoral joint has been widely adopted for prognostication, patellofemoral joint has gained little attention and may hold additional value for further improvements. We aimed to quantitatively analyse patellofemoral joint through radiomics analysis of lateral view radiographs for improved KR risk prediction.

Design

From the Multicenter Osteoarthritis Study dataset, we retrospectively retrieved the initial-visit lateral left knee radiographs of 2943 patients aged 50 to 79. They were split into training and test cohorts at a 2:1 ratio. A comprehensive set of radiomic features were extracted within the best-performing subregion of patellofemoral joint and combined into a radiomics score (RadScore). A KR risk score, derived from Kellgren-Lawrence grade (KLG) of tibiofemoral joint and RadScore of patellofemoral joint, was developed by multivariate Cox regression and assessed using time-dependent area under receiver operating characteristic curve (AUC).

Results

While patellofemoral osteoarthritis (PFOA) was insignificant during multivariate analysis, RadScore was identified as an independent risk factor (multivariate Cox p-value < 0.001) for KR. The subgroup analysis revealed that RadScore was particularly effective in predicting rapid progressor (KR occurrence before 30 months) among early- (KLG < 2) and mid-stage (KLG ​= ​2) patients. Combining two joints radiographic information, the AUC reached 0.89/0.87 for predicting 60-month KR occurrence.

Conclusions

The RadScore of the patellofemoral joint on lateral radiographs emerges as an independent prognostic factor for improving KR prognosis prediction. The KR risk score could be instrumental in managing progressive knee osteoarthritis interventions.

Effect of anterior tibial bowing on measurement of posterior tibial slope on conventional X-rays

PURPOSE

The posterior tibial slope (PTS) has different biomechanical effects on the knee. Especially in revision ACL reconstruction, a precise analysis is essential. Therefore, we investigate the influence of the anterior tibial bowing angle on the posterior slope measurement. Our hypothesis of the present study is that the short tibial X-rays underestimate the PTS in cases with increased anterior bowing of the tibia.

METHODS

The PTS was measured on 162 true longitudinal radiographs of the complete tibia (lateral mechanic axis). The average age of the patients was 35.7 years (range 19-59 years) and the most common diagnosis was failed anterior cruciate ligament reconstruction. Using this X-ray, the slope on the short axis and the slope on the entire axis were measured. In addition, the angle of the anterior bowing was determined.

RESULTS

The mean PTS for the lateral mechanic axis of the tibia was 10.6° (± 3.5) in contrast to 11.6° (± 3.5) for the short tibial axis. These two measurements differ significantly. (p  < 0.001). The mean anterior tibial bowing angle on the lateral X-rays of the whole tibia was 2.3° (± 2.0). There is a significant positive, relationship between tibial bowing angle and PTS as referenced by the lateral mechanic axis (Spearman's correlation, r = 0.273 and p < 0.001).

CONCLUSION

With increasing anterior tibial bowing, the posterior tibial slope on the short knee radiograph is underestimated compared to the slope measurement on the lateral mechanic axis.

Can the measured angle ABC on the lateral projection of the knee be used to determine the tube angulation for an optimum skyline projection?

INTRODUCTION

The current technique of angulating for a skyline knee projection relies heavily on the radiographer's estimation of the patella tilt, rendering it subjective and prone to errors. This study therefore aims to (i) examine the correlation between angle ABC measured on the lateral X-ray image and skyline angulation (measured in degrees) and (ii) determine the inter-rater reliability of angle ABC measurements.

METHODS

145 sets of lateral and skyline X-ray images from patients aged 40-70 years old were retrospectively analysed. Angle ABC was measured using prominent landmarks such as the trochlear sulcus, tibial tuberosity and the anterior border of the patella on the lateral knee radiograph. It was then retrospectively compared with the skyline tube angulations to identify any correlation between the two. An inter-rater reliability test was also conducted using the intraclass correlation coefficient (ICC) to determine the reproducibility of the measurement method.

RESULTS

A weak correlation was found between angle ABC and skyline angulation (r = 0.1, p = 0.25). The proposed method of measurement shows good inter-rater reliability (ICC = 0.81, 95% CI: 0.77 to 0.84).

CONCLUSION

There is insufficient evidence to indicate a correlation between angle ABC and skyline angulation. However, angle ABC can be reliably measured, implying the replicability of the measurement method for other purposes.

IMPLICATIONS FOR PRACTICE

The proposed measurement method of angle ABC on the lateral view could have future applications in other areas such as in the measurement of patellofemoral alignment and trochlear morphology.

Development of retake support system for lateral knee radiographs by using deep convolutional neural network

INTRODUCTION

Lateral radiography of the knee joint is frequently performed; however, the retake rate is high owing to positioning errors. Therefore, in this study, to reduce the required number and time of image retakes, we developed a system that can classify the tilting directions of lateral knee radiographs and evaluated the accuracy of the proposed method.

METHODS

Using our system, the tilting directions of a lateral knee radiographs were classified into four direction categories. The system was developed by training the DCNN based on 50 cases of Raysum images and tested on three types test dataset; ten more cases of Raysum images, one case of flexed knee joint phantom images and 14 rejected knee joint radiographs. To train a deep convolutional neural network (DCNN), we employed Raysum images created via three-dimensional (3D) X-ray computed tomography (CT); 11 520 Raysum images were created from 60 cases of 3D CT data by changing the projection angles. Thereby, we obtained pseudo images attached with correct labels that are essential for training.

RESULTS

The overall accuracy on each test dataset was 88.5 ± 7.0% (mean ± standard deviation), 81.4 ± 11.2%, and 73.3 ± 9.2%. The larger the tilting degree of the knee joint, the higher the classification accuracy.

CONCLUSION

DCNN could classify the tilting directions of a knee joint from lateral knee radiographs. Using Raysum images made it possible to facilitate creating dataset for training DCNN. The possibility was indicated for using support system of lateral knee radiographs.

IMPLICATIONS FOR PRACTICE

The system may also reduce the burden on patients and increase the work efficiency of radiological technologists.