Fifteen percent of the primary total knee arthroplasties (TKA) fails within 20 years. Among the main causes for revision surgery are instability and patellofemoral pain. Currently, the diagnostic pathway requires various diagnostic techniques to reveal the original cause for the failed knee prosthesis and is therefore time consuming and inefficient. Accordingly, there is a growing demand for a diagnostic tool that is able to simultaneously visualize soft tissue structures, bone and TKA. Magnetic resonance imaging (MRI) is capable of visualising all the structures in the knee although a trade- off needs to be made between metal artefact reducing capacities and image quality. Low-field MRI (0.25T) results in less metal artefacts and a lower image quality compared with high-field MRI (1.5T). The aim of this study is to develop a MRI imaging guide to image the problematic TKA and to evaluate this guide by comparing low-field and high-field MRI on a case study. Based on literature and current differential diagnostic pathways a guide to diagnose patellofemoral pain, instability, malposition and signs of infection or fracture with MRI was developed. Therefore, methods as Insall Salvati, patellar tilt angle and visibility of fluid and soft tissues were chosen. Visibility was scored on a VAS scale from 0 to 100mm (0mm zero visibility, 100mm excellent visibility). Subsequently, this guide is used to analyse MRI scans made of a volunteer (female, 61 years, right knee) with primary TKA (Biomet, Zimmer) in sagittal, coronal and transversal direction with a FSE PD metal artefact reducing (MAR) sequence (TE/TR 12/1030ms, slice thickness 4.0mm, FOV 260×260×120mm3, matrix size 224×216) on low-field MRI (Esaote G-scan Brio, 0.25T) and with a FSE T1-weighted high bandwidth MAR sequence (TE/TR 6/500ms, slice thickness 3.0mm, FOV 195×195×100mm3, matrix size 320×224) on high-field MRI (Avanto 1.5T, Siemens). Scans were analysed three times by one observer and the intra observer reliability was calculated with a two-way random effects model intra class correlation coefficient (ICC).Introduction
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