Correlations of typical pain patterns with SPECT/CT findings in unhappy patients after total knee arthroplasty

Abstract

PurposeThe diagnostic process in patients after painful total knee arthroplasty (TKA) is challenging. The more clinical and radiological information about a patient with pain after TKA is included in the assessment, the more reliable and sustainable the advice regarding TKA revision can be. The primary aim was to investigate the position of TKA components and evaluate bone tracer uptake (BTU) using pre-revision SPECT/CT and correlate these findings with previously published pain patterns in painful patients after TKA.MethodsA prospectively collected cohort of 83 painful primary TKA patients was retrospectively evaluated. All patients followed a standardized diagnostic algorithm including 99m-Tc-HDP-SPECT/CT, which led to a diagnosis indicating revision surgery. Pain character, location, dynamics and radiation were systematically assessed as well as TKA component position in 3D-CT. BTU was anatomically localized and quantified using a validated localization scheme. Component positioning and BTU were correlated with pain characteristics using non-parametric Spearman correlations (p < 0.05).ResultsBased on Spearman’s rho, significant correlations were found between pain and patients characteristics and SPECT/CT findings resulting in nine specific patterns. The most outstanding ones include: Pattern 1: More flexion in the femoral component correlated with tender/splitting pain and patella-related pathologies. Pattern 3: More varus in the femoral component correlated with dull/heavy and tingling/stinging pain during descending stairs, unloading and long sitting in patients with high BMI and unresurfaced patella. Pattern 6: More posterior slope in the tibial component correlated with constant pain.ConclusionThe results of this study help to place component positioning in the overall context of the "painful knee arthroplasty" including specific pain patterns. The findings further differentiate the clinical picture of a painful TKA. Knowing these patterns enables a prediction of the cause of the pain to be made as early as possible in the diagnostic process before the state of pain becomes chronic.Level of evidenceLevel III