Advancing Osteoporosis Evaluation Procedures: Detailed Computational Analysis of Regional Structural Vulnerabilities in Osteoporotic Bone

Abstract

Osteoporotic fractures of the femur are associated with poor healing, disability, reduced quality of life, and high mortality rates within 1 year. Moreover, osteoporotic fractures of the femur are still considered to be an unsolved problem in orthopedic surgery. In order to more effectively identify osteoporosis-related fracture risk and develop advanced treatment approaches for femur fractures, it is necessary to acquire a greater understanding of how osteoporosis alters the diaphyseal structure and biomechanical characteristics. The current investigation uses computational analyses to comprehensively examine how femur structure and its associated properties differ between healthy and osteoporotic bones. The results indicate statistically significant differences in multiple geometric properties between healthy femurs and osteoporotic femurs. Additionally, localized disparities in the geometric properties are evident. Overall, this approach will be beneficial in the development of new diagnostic procedures for highly detailed patient-specific detection of fracture risk, for establishing novel injury prevention treatments, and for informing advanced surgical solutions.

Keywords: biomechanics; computational analysis; diagnostic methods; fracture prevention; patient-specific; personalized medicine.

Figure 1

Three-dimensional models exhibiting disparities of morphological data between healthy and osteoporotic femurs. Heat maps show scaled bone thickness data corresponding with each location on the femur. (High thickness depicted in blue, ranging to low thickness shown in red). (A) Healthy femur. (B–D) Three examples of femurs with osteoporosis. Anterior view (above) and posterior view (below) are shown.

Figure 2

Perimeter data from the healthy and osteoporosis experimental groups. (A) Periosteal perimeter data. (B) Endosteal perimeter data. (C) Periosteal and endosteal perimeters at 80% biomechanical length (BL). (D) Periosteal and endosteal perimeters at 60% BL. (E) Periosteal and endosteal perimeters at 40% BL. (F) Periosteal and endosteal perimeters at 20% BL. Cross-section perimeter examples from a healthy femur.

Figure 3

Plots of area moment of inertia data from the healthy and osteoporosis experimental groups. (A) Area moment of inertia around the x axis $\left(I_x\right)$. (B) Area moment of inertia around the y axis $\left(I_y\right)$. (C) Minimum area moment of inertia $\left(I_{min}\right)$. (D) Maximum area moment of inertia $\left(I_{max}\right)$. Sampling location = percentage of biomechanical length.

Figure 4

Plots of section modulus data from the healthy and osteoporosis experimental groups. (A) Section modulus about the x axis $\left(Z_x\right)$. (B) Section modulus about the y axis $\left(Z_y\right)$. (C) Minimum section modulus $\left(Z_{min}\right)$. (D) Maximum section modulus $\left(Z_{max}\right)$. Sampling location = percentage of biomechanical length.

Figure 5

Biomechanical data of the healthy and osteoporosis experimental groups at four sampling locations along the biomechanical length (BL) of the femur. (A) Polar section modulus $\left(Z_{pol}\right)$ at 80% BL. (B) $Z_{pol}$ at 60% BL. (C) $Z_{pol}$ at 40% BL. (D) $Z_{pol}$ at 20% BL. (E) Polar moment of inertia (J) at 80% BL. (F) J at 60% BL. (G) J at 40% BL. (H) J at 20% BL. (I) Femur 3D model showing sampling locations (blue).

Figure 6

Cortical area (CA) data of healthy and osteoporosis experimental groups. (A) CA data from 80% biomechanical length (BL). (B) CA from 60% BL. (C) CA from 40% BL. (D) CA from 20% BL. (E) Healthy femur CA (shown in white) at 80% BL. (F) Healthy femur CA at 60% BL. (G) Healthy femur CA at 40% BL. (H) Healthy femur CA at 20% BL. (I) Osteoporotic femur CA at 80% BL. (J) Osteoporotic femur CA at 60% BL. (K) Osteoporotic femur CA at 40% BL. (L) Osteoporotic femur CA at 20% BL.

Figure 7

Conceptualization of how CT scans could be used to obtain comprehensive, patient-specific information about osteoporosis risk. Left femur with heat map showing regional bone thickness, a sampling location showing a cross-section of osteoporotic bone, and an example of regional quantitative data that can be calculated at a given sampling location. Cortical area (CA), endosteal perimeter (EndostPer), area moment of inertia around the x axis $\left(I_x\right)$, area moment of inertia around the y axis $\left(I_y\right)$, polar moment of inertia (J), and polar section modulus $\left(Z_{pol}\right)$.