Soft Tissue Radiological Knee (SToRK) Index: An observational cohort study to produce an index that quantifies the magnitude of soft tissue around the knee using standard radiographs

膝关节软组织放射学(SToRK)指数:一项观察性队列研究,旨在利用标准X光片建立一个量化膝关节周围软组织量的指数。

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Abstract

INTRODUCTION: The soft tissue envelope around the knee can have an impact on the ease of performing surgery such as total knee replacement (TKR). BMI is often used in planning theatre time but may be a poor indicator of the soft tissue around the knee due to varying distribution of adipose tissue. Radiological images directly show the soft tissue. We therefore aim to develop a method of quantifying the soft tissue envelope around the knee using radiographs. METHOD: Plain weight-bearing radiographs were used to measure the total knee (soft tissue and bony) width at the level of the epicondyles of the knee and the bony epicondylar width of the femur. The ratio of the two widths was defined as the Soft Tissue Radiological Knee (SToRK) Index. The validity of the index as a true measure of soft tissue envelope was assessed using cross sectional areas on axial MRI cuts at the level of the epicondyles. The inter-observer reliability was assessed using the intra-class correlation coefficient. SToRK Index values were correlated with patients' BMI, gender and operative time. RESULTS: The results show there is a close correlation between the ratio of cross sectional area of MRI axial cuts at the level of epicondyles and the ratio of linear widths measured on plain radiographs, validating the SToRK Index as a measure of soft tissue envelope. There was also good to excellent inter-rater reliability of measurements of these widths. There was a close correlation between BMI and SToRK Index with differences between men and women. DISCUSSION: We believe the SToRK Index is a validated method of quantifying soft tissue distribution around the knee and gives surgeons a better descriptor of the knee envelope than BMI. It is easy to use, needs simple investigations and is reproducible.

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