Biology subjects

Bredbenner, T. L.

Publications and source records attributed to Bredbenner, T. L..

3 recordsLinked to original sources

bioRxiv2021

The relationships between structural organization, material properties, and loading conditions and the risk of fracture and fracture location in the femur

Increased risk of skeletal fractures due to bone mass loss is a major public health problem resulting in significant morbidity and mortality, particularly in the case of hip fractures. Current clinical methods based on two-dimensional measures of bone mineral density (areal BMD or aBMD) are often unable to identify individuals at risk of fracture. The underlying hypothesis of this study was that combinations of femur structural traits are different for those femurs that suffer a fragility fracture within the proximal region of the femur and those that sustain a fracture in either the subtrochanteric or midshaft region of the femur, resulting in an "atypical femur fracture". Accordingly, the objective of this study was to determine the effects of varying combinations of structural traits, material properties, and loading conditions on femur stress response and the location of stress response variation using a validated parametric finite element model. Statistical shape and trait modelling of the femur was used to describe variability in the structural organization of a set of femurs in an efficient manner and the resulting description of structural variability was exploited to investigate how different mechanisms of fracture might occur, whether in the proximal region or in the subtrochanteric and midshaft region. In combination with parameters describing loading condition and material property variation, variation in structural organization is associated with regional increases in maximum principal stress and the percentage of bone expected to damage, and these increases are likely associated with increased fracture risk. The results of this study indicate that there are multiple pathways and combinations of descriptor variation that may result in increased fracture risk and that these pathways can lead to fracture in any region of the femur under both overload conditions, such as with sideways fall loading, and stance loading, which due to the repetitive nature may lead to the accumulation of fatigue damage within the bone and further impair bone condition and increased susceptibility to fracture.

bioengineering↗

bioRxiv2021

Deep learning-based segmentation of high-resolution computed tomography image data outperforms commonly used automatic bone segmentation methods

Segmenting bone from background is required to quantify bone architecture in computed tomography (CT) image data. A deep learning approach using convolutional neural networks (CNN) is a promising alternative method for automatic segmentation. The study objectives were to evaluate the performance of CNNs in automatic segmentation of human vertebral body (micro-CT) and femoral neck (nano-CT) data and to investigate the performance of CNNs to segment data across scanners. Scans of human L1 vertebral bodies (microCT [North Star Imaging], n=28, 53m3) and femoral necks (nano-CT [GE], n=28, 27m3) were used for evaluation. Six slices were selected for each scan and then manually segmented to create ground truth masks (Dragonfly 4.0, ORS). Two-dimensional U-Net CNNs were trained in Dragonfly 4.0 with images of the [FN] femoral necks only, [VB] vertebral bodies only, and [F+V] combined CT data. Global (i.e., Otsu and Yen) and local (i.e., Otsu r = 100) thresholding methods were applied to each dataset. Segmentation performance was evaluated using the Dice coefficient, a similarity metric of overlap. Kruskal-Wallis and Tukey-Kramer post-hoc tests were used to test for significant differences in the accuracy of segmentation methods. The FN U-Net had significantly higher Dice coefficients (i.e., better performance) than the global (Otsu: p=0.001; Yen: p=0.001) and local (Otsu [r=100]: p=0.001) thresholding methods and the VB U-Net (p=0.001) but there was no significant difference in model performance compared to the FN + VB U-net (p=0.783) on femoral neck image data. The VB U-net had significantly higher Dice coefficients than the global and local Otsu (p=0.001 for both) and FN U-Net (p=0.001) but not compared to the Yen (p=0.462) threshold or FN + VB U-net (p=0.783) on vertebral body image data. The results demonstrate that the U-net architecture outperforms common thresholding methods. Further, a network trained with bone data from a different system (i.e., different image acquisition parameters and voxel size) and a different anatomical site can perform well on unseen data. Finally, a network trained with combined datasets performed well on both datasets, indicating that a network can feasibly be trained with multiple datasets and perform well on varied image data.

bioengineering↗

bioRxiv2021

Circulating miRNAs associated with bone mineral density in healthy adult baboons.

MicroRNAs (miRNAs) regulate gene expression post-transcriptionally and circulate in the blood, making them attractive biomarkers of disease state for tissues like bone that are challenging to interrogate directly. Here we report on five miRNAs - miR-197-3p, miR-320a, miR-320b, miR-331-5p, and miR-423-5p - that are associated with bone mineral density (BMD) in 147 healthy adult baboons. These baboons range in age from 15 to 25 years (45 to 75 human equivalent years) and were 65% female with a broad range of BMDs including a minority of osteopenic individuals. miRNAs were generated via RNA sequencing from buffy coats collected at necropsy and areal BMD evaluated via DXA of the lumbar vertebrae post-mortem. Differential expression analysis controlled for the underlying pedigree structure of these animals to account for genetic variation which may be driving miRNA abundance and BMD values. While many of these miRNAs have been associated with risk of human osteoporosis, this finding is of interest because the cohort represent a model of normal aging and bone metabolism rather than a disease cohort. The replication of miRNA associations with osteoporosis or other bone metabolic disorders in animals with healthy BMD suggests an overlap in normal variation and disease states. We suggest that these miRNAs are involved in the regulation of cellular proliferation, apoptosis, and protein composition in the extracellular matrix throughout life. However, age-related dysregulation of these systems may lead to disease causing associations of the miRNAs among individuals with clinically defined disease.

genomics↗