A marker-free registration method for standing X-ray panorama reconstruction for hip-knee-ankle axis deformity assessment

Radiologists should use the hip-knee-ankle angle rather than the mechanical axis deviation to describe knee alignment

OBJECTIVE

Preoperative and postoperative coronal knee alignment is an important predictor of total knee arthroplasty (TKA) failure. Radiologists often report the mechanical axis deviation (MAD) rather than hip-knee-ankle angle (HKAA) to describe coronal knee alignment. The aim of this study is to evaluate (i) how well the MAD predicts the HKAA; (ii) if patient height and sex affect the performance of the MAD; and (iii) if the MAD could be measured faster than the HKAA.

MATERIALS AND METHODS

Two hundred patients undergoing hip-to-ankle radiographs for TKA planning were retrospectively reviewed. The MAD and HKAA were measured using previously published methods by the Visage picture archiving and communication systems (PACS) tools. Receiver operator characteristic (ROC) curves were used to evaluate the performance of the MAD to predict HKAA by gender and height. The performance of a linear model was used to predict HKAA from MAD in a prospectively collected cohort of 40 patients. Paired t tests were used for the comparison of time measurement in MAD and HKAA in this cohort.

RESULTS

MAD strongly correlated with HKAA (r = 0.99, p < 0.001); however, the performance of MAD differed by height (p = 0.005) and sex (p < 0.001). There was no significant difference in the time taken to measure HKAA versus MAD (p > 0.05).

CONCLUSION

HKAA should be used instead of the MAD because it is more clinically relevant and takes the same amount of time to be measured.

A new automatic stitching method for full-length lower limb radiography

Full-length lower limb x-rays are used to diagnose and plan surgical procedures, such as Total Knee Arthroplasty (TKA) and High Tibial Osteotomy (HTO). Due to the size limitation of digital radiography (DR), panoramic x-ray images cannot be obtained in a single exposure, necessitating multiple exposures and image stitching. In favor of manually constructing full-length x-ray images, we propose a new feature-based automated method for stitching together x-ray images. This new method is based on Canny algorithm, which detects and aligns bone edges before fusing them using a Wavelet form domain. Twenty-eight sets of lower limb x-ray images obtained from our hospital have been stitched and evaluated. The hip, knee, and ankle (HKA) angle was computed in two different ways then compared to manually stitched x-ray images by an expert. The stitching time was only three seconds, and the P-value was P = 0.974, and an accuracy rate of 100% was found. This method demonstrated greater precision and speed than both manually stitched x-ray images and previously published methods.