Transversely isotropic and isotropic material considerations in determining the mechanical response of geometrically accurate bovine tibia bone.

In finite element method (FEM) simulations of the mechanical response of bones, proper selection of stiffness versus density (E-ρ) formulae for bone constituents is necessary for obtaining accurate results. A considerable number of such formulae can be found in the biomechanics' literature covering both cortical and cancellous constituents. For determining the first and second modal frequencies (in both cranial-caudal and medial-lateral planes) of bovine tibia bone, this work assembled and numerically tested 22 isotropic and 21 orthotropic stiffness-density formulae combinations (cases). To accurately reproduce bone geometry, anatomical 3D models were generated from computed tomography (CT) scans. By matching the bone's digital mass to its actual mass, cortical and cancellous constituents were faithfully segmented by utilizing suitable values of three variables: (1) critical cutoff Hounsfield unit (HU) values, (2) cutoff density value, and (3) utilized number of sub-materials. Consequently, a balanced distribution of finite elements was generated with stiffness values congruent with their cancellous or cortical demarcations. Of the considered 22 isotropic formulae cases and 21 orthotropic (reduced to transversely isotropic) cases, only few yielded accurate frequency estimates. For verifying the accuracy of the solutions emanating from the various formulae, experimental vibration tests of corresponding mode frequencies and shapes (ProSig©) were conducted. When compared with the measured experimental frequency values, the most accurate isotropic formulae yielded numerical estimates of + 0.95% and + 10.65% for the first and second cranial-caudal (C-C) frequencies, respectively. The formulae yielding most accurate estimates also proved successful in estimating frequencies of a second tibia bone yielding numerical estimates within + 4.75% and + 1.88% of the said mode frequencies. For the transversely isotropic material assignment, the closest case scenario computed numerical estimates with a percentage difference of + 2.05% and + 9.36% for the first and second cranial-caudal (C-C) frequencies, respectively. Graphical abstract Mode shapes (left) 1 and (right) 2 for transversely isotropic case 15 T (Bone A): (a) cranial-caudal and (b) medial-lateral plane.

Intracortical stiffness of mid-diaphysis femur bovine bone: lacunar-canalicular based homogenization numerical solutions and microhardness measurements.

Microscale lacunar-canalicular (L-C) porosity is a major contributor to intracortical bone stiffness variability. In this work, such variability is investigated experimentally using micro hardness indentation tests and numerically using a homogenization scheme. Cross sectional rings of cortical bones are cut from the middle tubular part of bovine femur long bone at mid-diaphysis. A series of light microscopy images are taken along a line emanating from the cross-section center starting from the ring's interior (endosteum) ring surface toward the ring's exterior (periosteum) ring surface. For each image in the line, computer vision analysis of porosity is conducted employing an image segmentation methodology based on pulse coupled neural networks (PCNN) recently developed by the authors. Determined are size and shape of each of the lacunar-canalicular (L-C) cortical micro constituents: lacunae, canaliculi, and Haversian canals. Consequently, it was possible to segment and quantify the geometrical attributes of all individual segmented pores leading to accurate determination of derived geometrical measures such as L-C cortical pores' total porosity (pore volume fraction), (elliptical) aspect ratio, orientation, location, and number of pores in secondary and primary osteons. Porosity was found to be unevenly (but linearly) distributed along the interior and exterior regions of the intracortical bone. The segmented L-C porosity data is passed to a numerical microscale-based homogenization scheme, also recently developed by the authors, that analyses a composite made up of lamella matrix punctuated by multi-inclusions and returns corresponding values for longitudinal and transverse Young's modulus (matrix stiffness) for these micro-sized spatial locations. Hence, intracortical stiffness variability is numerically quantified using a combination of computer vision program and numerical homogenization code. These numerically found stiffness values of the homogenization solution are corroborated experimentally using microhardness indentation measurements taken at the same points that the digital images were taken along a radial distance emanating from the interior (endosteum) surface toward the bone's exterior (periosteum) surface. Good agreement was found between numerically calculated and indentation measured stiffness of Intracortical lamellae. Both indentation measurements and numerical solutions of matrix stiffness showed increasing linear trend of compressive longitudinal modulus (E11) values vs. radial position for both interior and exterior regions. In the interior (exterior) region of cortical bone, stiffness modulus values were found to range from 18.5 to 23.4 GPa (23 to 26.0 GPa) with the aggregate stiffness of the cortical lamella in the exterior region being 12% stiffer than that in the interior region. In order to further validate these findings, experimental and FEM simulation of a mid-diaphysis bone ring under compression is employed. The FEM numerical deflections employed nine concentric regions across the thickness with graded stiffness values based on the digital segmentation and homogenization scheme. Bone ring deflections are found to agree well with measured deformations of the compression bone ring.

Geometric-attributes-based segmentation of cortical bone slides using optimized neural networks.

In cortical bone, solid (lamellar and interstitial) matrix occupies space left over by porous microfeatures such as Haversian canals, lacunae, and canaliculi-containing clusters. In this work, pulse-coupled neural networks (PCNN) were used to automatically distinguish the microfeatures present in histology slides of cortical bone. The networks' parameters were optimized using particle swarm optimization (PSO). When forming the fitness functions for the PSO, we considered the microfeatures' geometric attributes-namely, their size (based on measures of elliptical perimeter or area), shape (based on measures of compactness or the ratio of minor axis length to major axis length), and a two-way combination of these two geometric attributes. This hybrid PCNN-PSO method was further enhanced for pulse evaluation by combination with yet another method, adaptive threshold (AT), where the PCNN algorithm is repeated until the best threshold is found corresponding to the maximum variance between two segmented regions. Together, this framework of using PCNN-PSO-AT constitutes, we believe, a novel framework in biomedical imaging. Using this framework and extracting microfeatures from only one training image, we successfully extracted microfeatures from other test images. The high fidelity of all resultant segments was established using quantitative metrics such as precision, specificity, and Dice indices.

Segmentation of histology slides of cortical bone using pulse coupled neural networks optimized by particle-swarm optimization.

The aim of this study is to automatically discern the micro-features in histology slides of cortical bone using pulse coupled neural networks (PCNN). To the best knowledge of the authors, utilizing PCNN in such an application has not been reported in the literature and, as such, constitutes a novel application. The network parameters are optimized using particle swarm optimization (PSO) where the PSO fitness function was introduced as the entropy and energy of the bone micro-constituents extracted from a training image. Another novel contribution is combining the above with the method of adaptive threshold (T) where the PCNN algorithm is repeated until the best threshold T is found corresponding to the maximum variance between two segmented regions. To illustrate the quality of resulting segmentation according to this methodology, a comparison of the entropy/energy obtained of each pulse is reported. Suitable quality metrics (precision rate, sensitivity, specificity, accuracy, and dice) were used to benchmark the resulting segments against those found by a more traditional method namely K-means. The quality of the segments revealed by this methodology was found to be of much superior quality. Another testament to the quality of this methodology was that the images resulting from testing pulses were found to be of similarly good quality to those of the training images.

On the relevance of uniaxial tensile testing of urogynecological prostheses: the effect of displacement rate.

INTRODUCTION AND HYPOTHESIS: Uniaxial tensile testing is commonly used to calculate values of mechanical properties of urogynecological prostheses used in stress urinary incontinence and pelvic organ prolapse surgery in women. Clinical behavior of these products has been linked to their mechanical properties, hence influencing the clinician's preference for one brand or another. The objective of this study is to assess the effect of displacement rate used in uniaxial tensile testing on peak load, extension at peak load, and initial stiffness of Prolene® mesh, used as a proxy for urogynecological prostheses. METHODS: Strips of Prolene® mesh measuring 10 × 30 mm were submitted to uniaxial tensile testing at the following rates: 1, 10, 50, 100, and 500 mm/min. Peak load, elongation at peak load, and initial stiffness were computed from load vs displacement curves at all displacement rates. The effect of displacement rate on these parameters was estimated by fitting linear trend lines through the data. RESULTS: The displacement rate at which uniaxial tensile testing is performed has significant effects on the values of extension at peak load and initial stiffness, but not on the peak load. CONCLUSIONS: When urogynecological prostheses are submitted to uniaxial tensile testing, studies at more than one displacement rate should be performed. More importantly, these displacement rates should be within the range of applicability.

Polypropylene midurethral tapes do not have similar biologic and biomechanical performance in the rat.

OBJECTIVES: To evaluate the biomechanical properties and histologic changes of different commercially available polypropylene midurethral tapes (MUTs) after implantation in the rat. METHODS: Pieces of Advantage, intravaginal slingplasty (IVS), suprapubic arch sling (SPARC), and tension-free vaginal tape (TVT) were implanted over the rectus fascia of rats, with six rats serving as controls. On retrieval 24 wk later, the degree of adherence and sample measurements were recorded. Biomechanical testing of the retrieved samples was performed using the uniaxial loading method. Histologic evaluation of the samples under light microscopy included the following parameters: inflammatory infiltrate, fibrosis, mast cell presence, muscular infiltration, and collagen filling of the mesh. RESULTS: No mesh extrusion or infection was encountered. The biomechanical and histologic results were consistent within each group. TVT displayed peculiar adherence characteristics not found among the other brands. No statistically significant difference were found in mean peak load and extension at peak load among the four tested brands. Stiffness of TVT was significantly lower than that of each of the other three brands. Stiffness of Advantage was significantly higher than that of SPARC. The histologic findings differed from one MUT brand to another. By grading certain histologic parameters, an untested model to assign a score for biocompatibility potential in the rat, to different MUTs, was developed. CONCLUSIONS: Commercially available polypropylene MUTs display different biologic and biomechanical properties in the rat.