The most important issue in the assessment of fracture healing is to acquire information about the restoration of the mechanical integrity of bone. Many researchers have attempted to monitor stiffness either directly or indirectly for the purpose of assessing strength, as strength has been impossible to assess directly in clinical practice. The purpose of this study was thus to determine the relationship between bending stiffness and strength using mechanical testing at different times during the healing process. Unilateral, transverse, mid-tibial osteotomies with a 2-mm gap were performed in 28 rabbits. The osteotomy site was stabilized using a double-bar external fixator. The animals were divided into four groups (n=7/group/time point; 4, 6, 8 and 12 weeks). A series of images from micro-computed tomography of the gap was evaluated to detect the stage of fracture healing and a 4-point bending test was performed to measure stiffness and strength. Formation of cortex and medullary canal at the gap was seen in the 12-week group and would represent the remodeling stage. In addition, the relationship between stiffness and strength remained almost linear until at least 12 weeks. However, stiffness recovered much more rapidly than strength. Strength was not fully restored until the later stages of fracture healing. However, the current study demonstrated that stiffness could be monitored as a surrogate marker of strength until at least the remodeling stage.

The most important issue in the assessment of fracture healing is to acquire information about the restoration of the mechanical integrity of bone. Echo tracking (ET) can noninvasively measure the displacement of a certain point on the bone surface under a load. Echo tracking has been used to assess the bone deformation angle of the fracture healing site. Although this method can be used to evaluate bending stiffness, previous studies have not validated the accuracy of bending stiffness. The purpose of the present study is to ensure the accuracy of bending stiffness as measured by ET. A four-point bending test of the gap-healing model in rabbit tibiae was performed to measure bending stiffness. Echo tracking probes were used to measure stiffness, and the results were compared with results of stiffness measurements performed using laser displacement gauges. The relationship between the stiffness measured by these two devices was completely linear, indicating that the ET method could precisely measure bone stiffness.

Introduction

Spinal aBMD only explains 50–80% of vertebral strength, and the application of aBMD measurements in isolation cannot accurately identify individuals who are likely to eventually experience bone fracture, due to the low sensitivity of the test. For appropriate treatment intervention, a more sensitive test of bone strength is needed. Such a test should include not only bone mineral density, but also bone quality. Quantitative computed tomography-based finite element methods (QCT/FEM) may allow structural analyses taking these factors into consideration to accurately predict bone strength (PBS). To date, however, basic data have not been reported regarding the prediction of bone strength by QCT/FEM with reference to age in a normal population. The purpose of this study was thus to create a database on PBS in a normal population as a preliminary trial. With these data, parameters that affect PBS were also analyzed.

Introduction: Low-intensity pulsed ultrasound stimulation (LIPUS) can enhance bone regeneration and callus healing during fracture repair. However, whether a certain phase of the healing process in fracture repair in particular is infiuenced by LIPUS treatment remains unclear. In this investigation, the effect of LIPUS on callus remodeling in a gap healing model was evaluated by bone morphometric analyses using 3-dimensional (3D) quantitative micro computed tomography (μCT) at the healing site, providing information on the temporal sequence of mineralized remodeling events that characterize the gap healing.

Materials and Methods: The rabbit osteotomy model with 2-mm gap for the right tibia was immobilized with four pins fixed to an external fixator with double side bars. LIPUS was continued for both the treatment group (n=7/group/time point) and the control group (n=7/group/time point), for 20 min, six times/week, for 4, 6, or 8 weeks. The control group also received a sham inactive transducer under exactly the same condition as the LIPUS group. After the harvested tibia was scanned by μCT, region of interest was set at the callus healing area. It defined as a center of the osteotomy gap with a width of 1 mm. Morphometric parameters used for evaluation were mineralized callus volume (BV, cm³) and volumetric bone mineral density of mineralized tissue comprising the callus (mBMD, mBMD = BMC/ BV, mgHA/cm³). The whole ROI was measured and was subdivided into three zones. The periosteal callus zone (External), the medullary callus zone (Endosteal) and the remaining zone was the cortical gap zone (Intercortical). For each zone, BV and mBMD were measured. Data of the μCT evaluations were analyzed using a one-way ANOVA test. Statistically significant difference was set at p < 0.05.

Results: In the LIPUS groups, BV for the Endosteal zone was significantly lower for the 8-week group than for the 4-week group. Comparing results at the same time point, the LIPUS group at 8 weeks was significantly higher than that of the control group in the Intercortical zone. As for mBMD, in the LIPUS group, the 8-week group was significantly higher than the 4-week group for Total, External, Internal, and Endosteal zones, respectively. Comparing results at the same time point, mBMD was significantly higher for the LIPUS group at 8 weeks than for the control group in both External and Intercortical zones.

Discussion: The most striking finding in our study was that LIPUS accelerated bone formation in the Intercortical zone and callus resorption in the Endosteal zone. This suggests that LIPUS could shorten the time required for remodeling. However, the results of this study do not clarify whether an early phase in callus formation in particular is infiuenced by LIPUS.

Introduction: Low-intensity pulsed ultrasound stimulation (LIPUS) reportedly enhances restoration of strength at fracture healing sites. However, evaluation of strength by mechanical testing was limited to only one direction, with either bending or torsion. Quantitative micro computed tomography (μCT) scans allow us to calculate strength-related parameters such as cross-sectional moment (CSM) and cross-sectional moment of inertia (CSMI). Previous studies have performed 2-dimensional (2D) analyses, and 3-dimensional (3D) evaluations have not been described. The purpose of this study was thus to investigate the effects of LIPUS on osteotomy healing using 3D analyses of CSM and CSMI.

Materials and Methods: Bilateral, transverse, mid-tibial osteotomies with a 2-mm gap were performed in 42 rabbits. LIPUS was continued for both the treatment group (n=7/group/time point) and the control group (n=7/ group/time point), for 20 min, six times/week, for 4, 6, or 8 weeks. The control group also received a sham inactive transducer under the same condition as the LIPUS group. After the tibia was scanned by μCT, region of interest (ROI) was set at the center of the osteotomy gap with a width of 1 mm. Center of gravity for the ROI and the XYZ coordinate was calculated. An optional line (I) can be drawn in this coordinate. The angle of the Z axis (𝛉) was measured, and also the degree of angle of the X axis (φ) was measured. The 3D CSM [I (φ, 𝛉)] around this line was calculated using the following equation: I (φ, 𝛉) = ∫ r²dV (mm5), where r is the distance of a voxel to the center of gravity (mm) and dV is the area of a voxel (mm3). The axial CSM was defined as CSMx: I (0, 90), CSMy: I (90, 90), whereas the polar CSM was also defined as CSMp: I (any, 0). 3D CSMI weighted by density distribution was calculated using the following equation: I’ (φ, 𝛉) = ∫ r²dm = ∫ ρr²dV (mg.mm²), ρ is the measured volumetric callus mineral density. Likewise CSMIx, CSMIy and CSMIp were calculated. These data of the μCT evaluations were analyzed using a one-way ANOVA test (p< 0.05).

Results: When 3D CSMs at the same time point were compared, values for the LIPUS groups were significantly higher than those for control groups for CSMx at 6 weeks and CSMp at 8 weeks. As for comparison of 3D CSMIs at the same time point, values for the LIPUS groups were significantly higher than those of the control groups for CSMIx, CSMIy, and CSMIp at 6 and 8 weeks.

Discussion: Bone healing by 3D CSM and CSMI has not been described before. Our results demonstrate that these bone strength parameters improved with LIPUS during the early phases. However, whether the late phase of callus formation is infiuenced remains unclear.

Introduction: There is a clear need for the development of more sensitive risk assessment tools for clinical predictors of fractures. Bone densitometries are limited in the ability to account for complex geometry, architecture, and heterogeneity of bone. Quantitative computed tomography (QCT)-based finite element (FE) Methods: (QCT/FEM) are able to perform structural analyses taking these factors into consideration to accurately predict bone strength. However, no basic data have been available regarding predicted strength (PS) of the proximal femur by QCT/FEM with reference to age in a normal population. The purpose of this study was thus to create a database on PS in a normal population as a preliminary trial. With these data, parameters that affect PS were also analyzed.

Methods: Participants in this study comprised individuals who participated in a health checkup program with computed tomography (CT) at our hospital in 2008. Participants included 487 men and 237 women (age range, 40–87 years). Exclusion criteria were provided. Scan data of the proximal femur were isolated and taken from overall data from CT of each participant with simultaneous scans of a calibration phantom containing hydroxyapatite rods. A FE model was constructed from the isolated data using Mechanical Finder software. For each of the FE models, loading and boundary conditions as well as the definition of PS were exactly the same as described by Bessho et al. (Bone 2009). For each participant, height, weight, and abdominal circumference (AC) were measured. The analyses included linear regression analysis relating age and PS, one-way analysis of variance to compare average PS among the groups of participants who were divided into 5-year age brackets, and multiple regression analysis to determine how PS was affected by age, height, weight, and AC. Differences were considered significant for values of p< 0.05.

Result: The following results were obtained. First, average PS was lower in women than in men for all age ranges. Second, PS in men under stance configuration, and those in women under stance and fall configurations significantly decreased with age. Third, weight positively affected PS in both men and women.

Discussion: This was the first study to investigate changes in PS with age in a normal population. Whether PS by QCT/FEM correlates more closely with fracture risk for osteoporotic patients in comparison to other bone densitometries remains unclear, but the our results did not contradict any existing concept of risk factors for fragility fracture. More baseline data for PS in normal populations need to be accumulated by increasing the number of participants in studies like this.