Imaging-Based Methods for Non-invasive Assessment of Bone Properties Influenced by Mechanical Loading

Abstract

Purpose: To describe the most common in vivo imaging-based research tools used to assess bone properties that are influenced by mechanical loading associated with exercise, habitual physical activity, or disease states. Bone is a complex metabolically active tissue that adapts to changes in mechanical loading by altering the amount and spatial organization of mineral.

Method: Using a narrative review design, the authors provide an overview of bone biology and biomechanics to emphasize the importance of bone size scale, porosity, and degree of mineralization when interpreting measures acquired using quantitative ultrasound (QUS), dual-energy X-ray absorptiometry (DXA), computed tomography (CT), magnetic resonance imaging (MRI), and finite element analysis (FEA). For each imaging modality, basic imaging principles, typical outcome measures associated with changes in mechanical loading, and salient features for physiotherapists are described.

Main results: While each imaging modality has strengths and limitations, currently CT-based methods are best suited for determining the effects of mechanical loading on bone properties-particularly in the peripheral skeleton.

Conclusions: Regardless of the imaging technology used, the physiotherapist must carefully consider the assumptions of the imaging-based method, the clinical context, the nature of the change in mechanical loading, and the expected time course for change in bone properties.

Purpose: To describe the most common in vivo imaging-based research tools used to assess bone properties that are influenced by mechanical loading associated with exercise, habitual physical activity, or disease states. Bone is a complex metabolically active tissue that adapts to changes in mechanical loading by altering the amount and spatial organization of mineral. Method: Using a narrative review design, the authors provide an overview of bone biology and biomechanics to emphasize the importance of bone size scale, porosity, and degree of mineralization when interpreting measures acquired using quantitative ultrasound (QUS), dual-energy X-ray absorptiometry (DXA), computed tomography (CT), magnetic resonance imaging (MRI), and finite element analysis (FEA). For each imaging modality, basic imaging principles, typical outcome measures associated with changes in mechanical loading, and salient features for physiotherapists are described. Main Results: While each imaging modality has strengths and limitations, currently CT-based methods are best suited for determining the effects of mechanical loading on bone properties—particularly in the peripheral skeleton. Conclusions: Regardless of the imaging technology used, the physiotherapist must carefully consider the assumptions of the imaging-based method, the clinical context, the nature of the change in mechanical loading, and the expected time course for change in bone properties.

Keywords: adaptation physiologique; adaptation, physiological; adult; adulte; bone and bones; charge; diagnostic imaging; imagerie médicale; os; osseux; poids; weight-bearing.

Figure 1

Bone size scale (μm to cm) capable of being imaged by each modality and the corresponding bone properties shown as a function of the effective radiation dose (μSv).

Figure 2

Stress–strain curve for tensile or compressive loading of bone.

Figure 3

Resistance to bending force in two bone shafts with identical cross-sectional areas, elastic modulus, and stress from axial force but differing in the distance of the material from the centre of the “cylinder.” The arrows indicate the magnitude of deformation associated with the same bending force, demonstrating that the shaft on the left cannot resist as much bending force as the one on the right. The midsections of the long bones in the arms and legs gradually become wider and thinner as adults age, becoming more like the bone on the right.

Figure 4

Sample DXA images. Bone density, mass, and area are calculated for each region of interest (defined by semi-automatic line placement) and the total region of interest in scans of the whole body (A), distal forearm (B), lumbar spine (C), and proximal femur (D). Measures of vertebral heights and type and severity of vertebral deformity are derived from semi-automated marker placement on Vertebral Fracture Assessment images of L4 to T4 (E). (All images were acquired using the Hologic Discovery A scanner, except the forearm scan, which was acquired using the Hologic QDR 4500A.)

Figure 5

Examples of distal radius images: Cross-sectional image of radius and ulna using whole-body CT (Aquilion CX, Toshiba) (A); improved resolution using pQCT (XCT 960, Stratec) (B); analysis of (B) using OsteoQ software to facilitate analysis of cortical shell thickness (C) and trabecular connectivity (D); ultradistal radius imaged by HR-pQCT (Xtreme, Scanco) (E); and (E) sectioned for analysis of the trabecular network (F)