Seglearn: A Python Package for Learning Sequences and Time Series

Seglearn is an open-source python package for machine learning time series or sequences using a sliding window segmentation approach. The implementation provides a flexible pipeline for tackling classification, regression, and forecasting problems with multivariate sequence and contextual data. This package is compatible with scikit-learn and is listed under scikit-learn Related Projects. The package depends on numpy, scipy, and scikit-learn. Seglearn is distributed under the BSD 3-Clause License. Documentation includes a detailed API description, user guide, and examples. Unit tests provide a high degree of code coverage

Automated quantitative microstructural analysis of metastatically involved vertebrae: effects of stereologic model and spatial resolution

Summary of background data: Preclinical models of spinal metastases allow for the application of micro-image based structural assessments, however, large data sets resulting from high resolution scanning motivate a need for robust automated analysis tools. Accurate assessment of changes in vertebral architecture, however, may depend both on the resolution of images acquired and the models used to represent the structural data. Objective: To apply a recently developed automated μCT based analysis tool to quantify the effect of diffuse metastatic disease on rat vertebral architecture at multiple resolutions. It was hypothesized that automated methods could accurately quantify differences in vertebral microstructure and that diffuse metastatic disease could be shown to have significant negative architectural effects on trabecular bone independent of stereologic model and resolution. Methods: μCT images acquired at 14 μm3 of healthy and metastatcially involved whole lumbar rat vertebrae were analyzed at high, medium and low (8.725, 17.45, and 34.9 μm3) resolutions using an automated algorithm to yield micro-structural measures of the trabecular centrum and cortical shell. The images analyzed at different resolutions were obtained via up/downsampling of the acquired image data. Trabecular thickness was evaluated with the Parfitt and Hildebrand models, and anisotropy was evaluated through calculation of mean intercept length. Results: Significant differences in microstructural parameters measured in comparing healthy and metastatically involved vertebrae were affected by resolution, however, relative anisotropy was maintained. The Parfitt and Hilderbrand models yielded similar structural differences between healthy and metastatic vertebrae, however, the Hildebrand model was limited due to segmentation accuracy required for its automated application. Conclusions: Differences in microstructural parameters generated through automated analysis at high resolution suggest that diffuse MT1 osteolytic destruction in whole rat vertebrae results primarily in loss of trabeculae in the metastatic vertebrae, as opposed to trabecular thinning. The sensitivity of the bony architectural parameters to resolution motivates the need for high resolution scanning or post-processing of images

Mesh morphing and response surface analysis: quantifying sensitivity of vertebral mechanical behavior

Vertebrae provide essential biomechanical stability to the skeleton. In this work novel morphing techniques were used to parameterize three aspects of the geometry of a specimen-specific finite element (FE) model of a rat caudal vertebra (process size, neck size, and end-plate offset). Material properties and loading were also parameterized using standard techniques. These parameterizations were then integrated within an RSM framework and used to produce a family of FE models. The mechanical behavior of each model was characterized by predictions of stress and strain. A metamodel was fit to each of the responses to yield the relative influences of the factors and their interactions. The direction of loading, offset, and neck size had the largest influences on the levels of vertebral stress and strain. Material type was influential on the strains, but not the stress. Process size was substantially less influential. A strong interaction was identified between dorsal-ventral offset and dorsal-ventral off-axis loading. The demonstrated approach has several advantages for spinal biomechanical analysis by enabling the examination of the sensitivity of a specimen to multiple variations in shape, and of the interactions between shape, material properties, and loading

High resolution bone material property assignment yields robust subject specific finite element models of complex thin bone structures

Accurate finite element (FE) modeling of complex skeletal anatomy requires high resolution in both meshing and the heterogeneous mapping of material properties onto the generated mesh. This study introduces Node-based elastic Modulus Assignment with Partial-volume correction (NMAP) as a new approach for FE material property assignment to thin bone structures. The NMAP approach incorporates point spread function based deblurring of CT images, partial-volume correction of CT image voxel intensities and anisotropic interpolation and mapping of CT intensity assignment to FE mesh nodes. The NMAP procedure combined with a derived craniomaxillo-facial skeleton (CMFS) specific density-isotropic elastic modulus relationship was applied to produce specimen-specific FE models of 6 cadaveric heads. The NMAP procedure successfully generated models of the complex thin bone structures with surface elastic moduli reflective of cortical bone material properties. The specimen-specific CMFS FE models were able to accurately predict experimental strains measured under in vitro temporalis and masseter muscle loading (r=0.93, slope=1.01, n=5). The strength of this correlation represents a robust validation for CMFS FE modeling that can be used to better understand load transfer in this complex musculoskeletal system. The developed methodology offers a systematic process-flow able to address the complexity of the CMFS that can be further applied to create high-fidelity models of any musculoskeletal anatomy

Perceptions of using lithium in fracture management: a survey of orthopaedic surgeons, fracture patients and the general public

Abstract Background Lithium, an established psychiatric medication, has recently been shown to enhance new bone formation in preclinical fracture models. Current research is focused on evaluating the efficacy of low-dose, short-term lithium treatment to improve long bone fracture healing through a Phase II randomized clinical trial (LiFT NCT02999022). In working towards future applications of lithium for fracture management, this study aimed to understand the current perceptions of lithium as a psychiatric drug and the potential barriers to its orthopaedic adoption. Methods Three questionnaires, evaluating knowledge about lithium and willingness to embrace its use in fracture healing were disseminated among the general population, fracture patients eligible for the LiFT (Lithium for Fracture Treatment) trial and orthopaedic surgeons across Canada. Results Of the 768 public respondents, 84% were willing to take a medication that would aid fracture healing but only 62.6% if the medication was lithium. Willingness dropped to 44.6% among the 168 respondents who knew about the psychiatric use of lithium. Lack of sufficient knowledge (n = 50) and concerns about side effects including effects on the brain (n = 74) were the main reasons cited by those who were unwilling to use lithium. Of the 29 fracture patients, only 20 patients had previously heard of lithium. Of these, 40% were willing to take lithium for fracture healing with an additional 10% if the dose was low or if the intake duration was short. Only 50% knew that lithium has side effects. Of the 43 orthopaedic surgeons, 38 surgeons knew about clinical use of lithium. Of these, 68% knew that lithium has side effects and 29% knew that it interacts with other drugs. While most agreed that new strategies are needed to improve fracture management, only 68% were willing to prescribe lithium for fractures with an additional 16% if there is scientific evidence and/or a standard dosing protocol. Conclusions This study identified a lack of knowledge about uses and side effects of lithium among all three cohorts. A robust educational framework for orthopaedic surgeons, their patients and the members of their clinical care teams will be essential to widespread repurposing of lithium for fracture care

Mesh-morphing algorithms for specimen-specific finite element modeling

Despite recent advances in software for meshing specimen-specific geometries, considerable effort is still often required to produce and analyze specimen-specific models suitable for biomechanical analysis through finite element modeling. We hypothesize that it is possible to obtain accurate models by adapting a pre-existing geometry to represent a target specimen using morphing techniques. Here we present two algorithms for morphing, automated wrapping (AW) and manual landmarks (ML), and demonstrate their use to prepare specimen-specific models of caudal rat vertebrae. We evaluate the algorithms by measuring the distance between target and morphed geometries and by comparing response to axial loading simulated with finite element (FE) methods. First a traditional reconstruction process based on microCT was used to obtain two natural specimen-specific FE models. Next, the two morphing algorithms were used to compute mappings from the surface of one model, the source, to the other, the target, and to use this mapping to morph the source mesh to produce a target mesh. The microCT images were then used to assign element-specific material properties. In AW the mappings were obtained by wrapping the source and target surfaces with an auxiliary triangulated surface. In ML, landmarks were manually placed on corresponding locations on the surfaces of both source and target. Both morphing algorithms were successful in reproducing the shape of the target vertebra with a median distance between natural and morphed models of 18.8 and 32.2 microm, respectively, for AW and ML. Whereas AW-morphing produced a surface more closely resembling that of the target, ML guaranteed correspondence of the landmark locations between source and target. Morphing preserved the quality of the mesh producing models suitable for FE simulation. Moreover, there were only minor differences between natural and morphed models in predictions of deformation, strain and stress. We therefore conclude that it is possible to use mesh-morphing techniques to produce accurate specimen-specific FE models of caudal rat vertebrae. Mesh morphing techniques provide advantages over conventional specimen-specific finite element modeling by reducing the effort required to generate multiple target specimen models, facilitating intermodel comparisons through correspondence of nodes and maintenance of connectivity, and lends itself to parametric evaluation of "artificial" geometries with a focus on optimizing reconstruction

Structural biomechanics of the craniomaxillofacial skeleton under maximal masticatory loading: Inferences and critical analysis based on a validated computational model

The trend towards optimizing stabilization of the craniomaxillofacial skeleton (CMFS) with the minimum amount of fixation required to achieve union, and away from maximizing rigidity, requires a quantitative understanding of craniomaxillofacial biomechanics. This study uses computational modeling to quantify the structural biomechanics of the CMFS under maximal physiologic masticatory loading.Financial support for this work was provided by the Natural Sciences and Engineering Research Council of Canada (NSERC #RGPIN239206-11), and the Ontario Graduate Scholarship Program

Biomechanical Properties of Metastatically Involved Osteolytic Bone

Skeletal metastasis involves the uncoupling of physiologic bone remodeling resulting in abnormal bone turnover and radical changes in bony architecture, density, and quality. Bone strength assessment and fracture risk prediction are critical in clinical treatment decision-making. This review focuses on bone tissue and structural mechanisms altered by osteolytic metastasis and the resulting changes to its material and mechanical behavior

μFE models can represent microdamaged regions of healthy and metastatically involved whole vertebrae identified through histology and contrast enhanced μCT imaging

Micro-damage formation within the skeleton is an important stimulant for bone remodeling, however abnormal build-up of micro-damage can lead to skeletal fragility. In this study, µCT imaging based micro finite element (μFE) models were used to evaluate tissue level damage criteria in whole healthy and metastatically-involved vertebrae. T13-L2 spinal segments were excised from osteolytic (n=3) and healthy (n=3) female athymic rnu/rnu rats. Osteolytic metastasis was generated by intercardiac injection of HeLa cancer cells. Micro-mechanical axial loading was applied to the spinal motion segments under μCT imaging. Vertebral samples underwent BaSO4 staining and sequential calcein/fuchsin staining to identify load induced micro-damage. μCT imaging was used generate specimen specific μFE models of the healthy and osteolytic whole rat vertebrae. Model boundary conditions were generated through deformable image registration of loaded and unloaded scans. Elevated stresses and strains were detected in regions of micro-damage identified through histological and BaSO4 staining within healthy and osteolytic vertebral models, as compared to undamaged regions. Additionally, damaged regions of metastatic vertebrae experienced significantly higher local stresses and strains than those in the damaged regions of healthy specimens. Areas identified by BaSO4 staining, however, yielded lower levels of stress and strain in damaged and undamaged regions of healthy and metastatic vertebrae as compared to fuschin staining. The multimodal (experimental, image-based and computational) techniques used in this study demonstrated the ability of local stresses and strains computed through µFE analysis to identify trabecular micro-damage, that can be applied to biomechanical analyses of healthy and diseased whole bones