METHODS: A total of 15 femora were examined with four parameters i.e. maximum length of femur (FeMl), diameter of femoral head (FeHd), transverse diameter of midshaft (FeMd) and condylar breadth (FeCb). Osteometric board and vernier calipers were employed for the conventional method, while CT reconstructed images and Osirix MD software was utilised for the virtual method.
RESULTS: Results exhibited that there were no significant differences in the measurements by conventional and virtual methods. There were also no significant differences in the measurements by the intra or inter-observer error analyses. The intraclass correlation coefficients (ICC) were more than 0.95 by both intra and inter-observer error analyses. Technical error of measurement had displayed values within the acceptable ranges (rTEM <0.08 for intra-observer, <2.25 for inter-observer), and coefficient of reliability (R) indicated small measurement errors (R > 0.95 for intra-observer, R > 0.92 for inter-observer). By parameters, FeMl showed the highest R value (0.99) with the least error in different methods and observers (rTEM = 0.02-0.41%). Bland and Altman plots revealed points scattered close to zero indicating perfect agreement by both virtual and conventional methods. The mean differences for FeMl, FeHd, FeMd and FeCb measurements were 0.01 cm, -0.01 cm, 0.02 cm and 0.01 cm, respectively.
CONCLUSION: This brought to suggest that bone measurement by virtual method was highly accurate and reliable as in the conventional method. It is recommended for implementation in the future anthropological studies especially in countries with limited skeletal collection.
MATERIALS AND METHODS: 52 healthy volunteers were scanned in a 16-slice MDCT, and the volume of 104 sets of carpal bones was measured using a Syngo workstation (Both CT and workstation-Siemens Healthcare, Erlangen, Germany).
RESULTS: Male carpal bones were of higher volume compared to the female carpal bones (p<0.001). Area under the curve (AUC) assessment of responder-operator characteristics curves showed that the trapezium bone was best able to predict sex with an AUC of 0.986. At a trapezium bone volume of ⩾1.94cm(3), there was a 93.5% probability that the subject was male. Binary logistic regression analysis found that the highest accuracy was derived using the pisiform, trapezium and capitate bones. There was a strong relationship between sex prediction and grouping of the carpal bone volumes (Nagelkerke R(2)=0.923) with an overall prediction accuracy of 97%.
CONCLUSION: All 8 carpal bones exhibit sexual dimorphism to varying degrees. A binary regression analysis combining the 5 carpal bones with the highest predictive values for sex produces an accurate predictive model.