Surgically Relevant Morphological Parameters of Proximal Human Femur: A Statistical Analysis Based on 3D...

Recently, more accurate description of the femoral geometry has become of interest to engineers and orthopedic surgeons. However, an appropriate database is lacking. Therefore, the aim of this study is to present morphological parameters and their correlations, which are relevant for medical issues such as impingement after total hip replacement, as well as for implant design and the etiology of hip fractures.

We investigated 12 well-known morphological parameters of the femur in 169 healthy human subjects through evaluation of 3D-reconstructed CT scans. Pearson's coefficients of correlations were calculated using a statistical t-test method for each pair of parameters.

The mean, maximum, minimum, median, and standard deviation values are reported for all parameters. Histograms showing the distribution of each morphological parameter are also presented. It is shown that absolute and horizontal offsets, total femur length, and NCVD parameters are normally distributed, but NCDF and NCDS are not. Furthermore, an inter-correlation matrix was reported to reveal statistical correlations between these parameters. The strongest positive correlation existed between absolute offset (OSA) and horizontal offset (OSH), while the least positive correlation was found between NCDF and total femur length (TFL), and also between NCDS and NCDF. Anteversion angle (ATA) and OSA showed the least negative correlation. However, the strongest negative correlation was found between neck-shaft angle (NSA) and greater trochanter height (GTH), as well as between OSA and NCVD.

Comprehending patients' native bone morphology, including the variations and correlations, is essential for orthopedic surgeons to undertake preoperative planning and surgery as well as to appropriately design medical devices. Thus, more population-based detailed databases are necessary. We investigated an extensive set of proximal femoral morphology parameters using a statistically standardized method to expand the existing knowledge. The results of our study can be used for diverse medical and biomechanical purposes.