Assessment of Quantitative Methodology for Evaluation of Retrieved Metallic Femoral Components From Total Knee Replacements Available to Purchase

The metallic surfaces of total joint replacement components are subject to surface damage and roughening that can severely limit the service lifetime of the bearing system. To date, there are no standards by which to characterize the severity and modes of this critical surface damage, and therefore it remains difficult to accurately assess how femoral damage influences total joint replacement longevity. This study introduces a novel femoral component damage scoring methodology that combines a semi-quantitative visual damage scoring assessment and a fully quantitative non-contact characterization of the articular surface profile. The femoral surface was divided into 6 pre-determined zones, with 5 possible modes of damage and 4 (0–3) levels of damage severity, to produce a maximum possible damage score of 90. The 5 modes of metallic surface damage were; number of scratches, scratch depth, third body wear, abrasion and pitting. Three independent examiners were trained and then evaluated 33 retrieved TKRs systems (n = 11 Oxinium and n = 23 CoCr) with in-situ times of 3.6 ± 4.2 yrs (range of 0.1–20 yrs). The average damage score was 19.9 ± 30.8 with an inter-observer variability of only 1.5% Articular damage mode frequency was calculated and found to be 61% for scratching, 15% for pitting and 52% for abrasion. The quantitative characterization of the articular surface profile of the femoral component using non-contact profilometry (n = 150/retrieved component) illustrated a positive correlation between damage score and the average surface roughness for implants with an Ra greater than 65 nm (R² of 0.865). This methodology identified a critical Ra threshold above the standard manufacturing tolerance (∼50nm) wherein visual damage scoring was predictive of increases in quantitative surface roughness. This study validates the use of this novel methodology across most TKR material pairings. Future work will correlate damage scores and measured surface roughness with patient demographic and functional information.