This study compares stem fit&
fill and periprosthetic bone between noisy and silent CoC hips.
The annual wear rates were compared and intra-observer variability was calculated as the difference between both measurements (precision). The average time it takes to measure one image (without format conversions) was documented and practicality of daily clinical use was evaluated.
The precision was (mean +/− SD): Martell = 1.74+/−1.53, Hyperview = 0.36 +/−0.92, Pro-X = 0.10+/−0.11 Roman = 0.08 +/−0.08. The average measuring time per image was: Martell = 94s, Hyperview = 94s, Pro-X = 92s Roman = 158s.
We have compared four computer-assisted methods to measure penetration of the femoral head into the acetabular component in total hip replacement. These were the Martell Hip Analysis suite 7.14, Rogan HyperOrtho, Rogan View Pro-X and Roman v1.70. The images used for the investigation comprised 24 anteroposterior digital radiographs and 24 conventional acetate radiographs which were scanned to provide digital images. These radiographs were acquired from 24 patients with an uncemented total hip replacement with a follow-up of approximately eight years (mean 8.1; 6.3 to 9.1). Each image was measured twice by two blinded observers. The mean annual rates of penetration of the femoral head measured in the eight-year single image analysis were: Martell, 0.24 (SD 0.19); HyperOrtho, 0.12 (SD 0.08); View Pro-X, 0.12 (SD 0.06); Roman, 0.12 (SD 0.07). In paired analysis of the six-month and eight-year radiographs: Martell, 0.35 (SD 0.22); HyperOrtho, 0.15 (SD 0.13); View Pro-X, 0.11 (SD 0.06); Roman, 0.11 (SD 0.07). The intra- and inter-observer variability for the paired analysis was best for View Pro-X and Roman software, with intraclass correlations of 0.97, 0.87 and 0.96, 0.87, respectively, and worst for HyperOrtho and Martell, with intraclass correlations of 0.46, 0.13 and 0.33, 0.39, respectively. The Roman method proved the most precise and the most easy to use in clinical practice and the software is available free of charge. The Martell method showed the lowest precision, indicating a problem with its edge detection algorithm on digital images.