A method for assessment of the shape of the proximal femur and its relationship to osteoporotic hip fracture

Abstract

The shape of the proximal femur has been demonstrated to be important in the occurrence of fractures of the femoral neck. Unfortunately, multiple geometric measurements frequently used to describe this shape are highly correlated. A new method, active shape modeling (ASM) has been developed to quantify the morphology of the femur. This describes the shape in terms of orthogonal modes of variation that, consequently, are all independent. To test this method, digitized standard pelvic radiographs were obtained from 26 women who had suffered a hip fracture and compared with images from 24 age-matched controls with no fracture. All subjects also had their bone mineral density (BMD) measured at five sites using dual-energy X-ray absorptiometry. An ASM was developed and principal components analysis used to identify the modes which best described the shape. Discriminant analysis was used to determine which variable, or combination of variables, was best able to discriminate between the groups. ASM alone correctly identified 74% of the individuals and placed them in the appropriate group. Only one of the BMD values (Ward's triangle) achieved a higher value (82%). A combination of Ward's triangle BMD and ASM improved the accuracy to 90%. Geometric variables used in this study were weaker, correctly classifying less than 60% of the study group. Logistic regression showed that after adjustment for age, body mass index, and BMD, the ASM data was still independently associated with hip fracture (odds ratio (OR)=1.83, 95% confidence interval 1.08 to 3.11). The odds ratio was calculated relative to a 10% increase in the probability of belonging to the fracture group. Though these initial results were obtained from a limited data set, this study shows that ASM may be a powerful method to help identify individuals at risk of a hip fracture in the future.

Shape Modeling and Analysis with Entropy-Based Particle Systems

“…In orthopedics, for example, researchers have applied shape models to the study of bone shapes and pathologies. In [48], Gregory, et al use a point-based modeling approach called Active Shape Modeling to study the correlation between proximal femur shapes and the rate of hip fracture in women. As with many other clinical shape studies, the goal of the hip fracture study is to develop an image-based assessment of the risk of the occurrence of the pathology.…”

Expected frequency of biomechanically adverse values of proximal femur geometric variables for fracture risk in the East Slovak female population (epidemiological study)

“…Several scientists measured independently geometric variables as HAL, u, a angle in clinical studies and they concluded that the geometric variation of proximal femur significantly contributes to the large variation in hip fracture risk [13][14][15][16][17][18][19][20][21][22][23][24][25] main topic inertia in minimum cross section of neck) and higher BR (buckling ratio) than controls without fractures [17], 4. u angle can be used to determine of the fracture risk independently of BMD [18], 5. patient with osteopenia measured in the total hip area may sustain a femoral neck fracture by fall, when she has adverse values of geometric variables of proximal femur (biomechanically unfavourable proximal femur configuration) [25], 6. there is a direct relationship between the predictor variable values BMI (body mass index), alpha angle, theta angle, and HAL and an categorical variable FNS value of <1, in that an increase of one relevant unit of measurement in these variables significantly increases the odds of fall-related fracture [12]. The contribution of our study lies in the finding of the 95% CI, within we can expect with 95% probability the mean values (m) of proximal femur geometric variables HAL, u angle, and a angle in the East Slovak female population.…”

Computational Analysis of Bone Fracture

“…Further, measures of proximal femur morphology from conventional radiographs predict hip fractures as well as BMD measurements [38] and improved correlation results when used in combination with BMD measures [31]. A two dimensional description of the proximal femur derived from an active shape model in combination with BMD measured at Ward's triangle prospectively classified 90 % of patients who had suffered a hip fracture [39]. Correlation models that combine BMD measurements with maximum principal strain predictions computed from two-dimensional finite element analysis (FEA) models and subject's height and neck shaft angle were able to correctly identify 82 % of subjects who previously reported a femoral fracture [40].…”