122,436 research outputs found

    Combining shape and intensity dxa-based statistical approaches for osteoporotic HIP fracture risk assessment

    Get PDF
    5noAiming to improve osteoporotic hip fracture risk detection, factors other than the largely adopted Bone Mineral Density (BMD) have been investigated as potential risk predictors. In particular Hip Structural Analysis (HSA)-derived parameters accounting for femur geometry, extracted from Dual-energy X-ray Absorptiometry (DXA) images, have been largely considered as geometric risk factors. However, HSA-derived parameters represent discrete and cross-correlated quantities, unable to describe proximal femur geometry as a whole and tightly related to BMD. Focusing on a post-menopausal cohort (N = 28), in this study statistical models of bone shape and BMD distribution have been developed to investigate their possible role in fracture risk. Due to unavailable retrospective patient-specific fracture risk information, here a surrogate fracture risk based on 3D computer simulations has been employed for the statistical framework construction. When considered separately, BMD distribution performed better than shape in explaining the surrogate fracture risk variability for the analysed cohort. However, the combination of BMD and femur shape quantities in a unique statistical model yielded better results. In detail, the first shape-intensity combined mode identified using a Partial Least Square (PLS) algorithm was able to explain 70% of the surrogate fracture risk variability, thus suggesting that a more effective patients stratification can be obtained applying a shape-intensity combination approach, compared to T-score. The findings of this study strongly advocate future research on the role of a combined shape-BMD statistical framework in fracture risk determination.partially_openembargoed_20211027Aldieri A.; Terzini M.; Audenino A.L.; Bignardi C.; Morbiducci U.Aldieri, A.; Terzini, M.; Audenino, A. L.; Bignardi, C.; Morbiducci, U

    Integration of cortical thickness data in a statistical shape model of the scapula

    Get PDF
    Knowledge about bone morphology and bone quality of the scapula throughout the population is fundamental in the design of shoulder implants. In particular, regions with the best bone stock (cortical bone) are taken into account when planning the supporting screws, aiming for an optimal fixation. As an alternative to manual measurements, statistical shape models (SSMs) have been commonly used to describe shape variability within a population. However, explicitly including cortical thickness information in an SSM of the scapula still remains a challenge. Therefore, the goal of this study is to combine scapular bone shape and cortex morphology in an SSM. First, a method to estimate cortical thickness, based on HU (Hounsfield Unit) profile analysis, was developed and validated. Then, based on the manual segmentations of 32 healthy scapulae, a statistical shape model including cortical information was created and evaluated. Generalization, specificity and compactness were calculated in order to assess the quality of the SSM. The average cortical thickness of the SSM was 2.0¿±¿0.63¿mm. Generalization, specificity and compactness performances confirmed that the combined SSM was able to capture the bone quality changes in the population. In this work we integrated information on the cortical thickness in an SSM for the scapula. From the results we conclude that this methodology is a valuable tool for automatically generating a large population of scapulae and deducing statistics on the cortex. Hence, this SSM can be useful to automate implant design and screw placement in shoulder arthroplasty

    Generation of a statistical model of the anatomy of human pelvises

    Get PDF
    Osteoarthritis and osteoporosis are two medical conditions involving the hip which affect the life quality of many people worldwide. These two diseases are diagnosed with 2D imaging by analysis of radiological measures, bone mineral density and joint space. Computed Tomography (CT) can provide 3D images of the hip, but has higher cost and imposes a higher radiation dose to the patient. Another option (which the Biomechanics group in Lund is working on) is to utilize statistical models to construct a 3D model from a 2D image. The Biomechanics group has developed a statistical model of the anatomical variability of the human femur. Adding an equivalent model for the pelvis would then allow to fully represent the hip joint. In this study, CT scans from 26 male and 21 female patients scheduled for hip replacement surgery were used to create a Statistical Shape Model (SSM) to describe the shape of pelvis. To be able to generate the SSM, the shapes of all bones were defined by identical meshes. A template mesh was created based on one of the available anatomies and it was then registered to each hip bone. The registered bones were then used to create the SSM. The registration method was evaluated by a point-to-surface distance difference. For the SSM, the shape variation and the reconstruction of the hip bones were evaluated for the whole group and for the male and female patient cohorts within the group. The SSM created during the study was able to represent the shape variation of both male and female bones. Visually, the gender variance was associated to the width and thickness of the bone, corresponding with the known differences of the pelvic bone between the genders. The results indicate that the model can represent the shape of the bone accurately, independent of gender. Combined with a statistical model for the femur, the SSM created in this study can be used to provide a 2D to 3D reconstruction of the hip from clinical diagnostic images.3D-modell av höftbenet kan hjÀlpa till att förutspÄ artros Det Àr viktigt att förebygga sjukdomar innan de bryter ut. Vanliga 2D-röntgenbilder Àr inte alltid tillrÀckligt noggranna men med 3D-modeller kan tidiga tecken pÄ artros lÀttare identifieras. Vi strÀvar för att fÄ fram 3D-bilder av höften frÄn vanliga röntgenbilder

    Analysis of the three-dimensional anatomical variance of the distal radius using 3D shape models

    Get PDF
    BACKGROUND: Various medical fields rely on detailed anatomical knowledge of the distal radius. Current studies are limited to two-dimensional analysis and biased by varying measurement locations. The aims were to 1) generate 3D shape models of the distal radius and investigate variations in the 3D shape, 2) generate and assess morphometrics in standardized cut planes, and 3) test the model's classification accuracy. METHODS: The local radiographic database was screened for CT-scans of intact radii. 1) The data sets were segmented and 3D surface models generated. Statistical 3D shape models were computed (overall, gender and side separate) and the 3D shape variation assessed by evaluating the number of modes. 2) Anatomical landmarks were assigned and used to define three standardized cross-sectional cut planes perpendicular to the main axis. Cut planes were generated for the mean shape models and each individual radius. For each cut plane, the following morphometric parameters were calculated and compared: maximum width and depth, perimeter and area. 3) The overall shape model was utilized to evaluate the predictive value (leave one out cross validation) for gender and side identification within the study population. RESULTS: Eighty-six radii (45 left, 44% female, 40 +/- 18 years) were included. 1) Overall, side and gender specific statistical 3D models were successfully generated. The first mode explained 37% of the overall variance. Left radii had a higher shape variance (number of modes: 20 female / 23 male) compared to right radii (number of modes: 6 female / 6 male). 2) Standardized cut planes could be defined using anatomical landmarks. All morphometric parameters decreased from distal to proximal. Male radii were larger than female radii with no significant side difference. 3) The overall shape model had a combined median classification probability for side and gender of 80%. CONCLUSIONS: Statistical 3D shape models of the distal radius can be generated using clinical CT-data sets. These models can be used to assess overall bone variance, define and analyze standardized cut-planes, and identify the gender of an unknown sample. These data highlight the potential of shape models to assess the 3D anatomy and anatomical variance of human bones

    Computational Biomechanical Modeling of the Human Knee During Kneeling

    Get PDF
    Total knee replacement benefits patients who suffer from severe knee pain or joint stiffness and other joint related illnesses that limit everyday activities. There has been an increase in the number of procedures performed each year and a need to evaluate the performance of these implants during specialized activities such as kneeling. Most computational studies lack insight into inter-patient variability and the results do not apply to large population. This study developed: (1) three-dimensional explicit finite element (FE) models to investigate natural and implanted knee joint kinematics and bone strain and (2) a platform to enable population-based evaluation by combining statistical model and joint function. Verification of a finite element model confirmed a strong agreement between model predicted and in-vitro kinematics of specimen-specific patellofemoral (PF) joints of four cadaveric knees in simulated kneeling. Three different commonly used PF implants were employed in an additional broader patellar bone strain study to assess the relative performance of these implants during highly demanding activities. This study predicted that the medialized dome design achieves the optimal balance of sufficient congruency between PF articular surfaces while still facilitating sagittal plane tilt to reduce isolated loading of the distal nose of the patella. A combined statistical shape model and FE method were utilized to successfully identify the most important shape characteristics affecting joint performance during kneeling. Scaling in the knee joint has minimal effect on PF joint kinematics but greatly affects joint contact mechanics. Knee soft tissue dimensions alter the kinematics. The patellar bone strain model described here provides a novel platform for further implant performance analyses. The statistical shape-function model is a tool for population based studies to help predict the clinical outcome of joint replacement

    The Interaction of Genetic Background and Mutational Effects in Regulation of Mouse Craniofacial Shape.

    Get PDF
    Inbred genetic background significantly influences the expression of phenotypes associated with known genetic perturbations and can underlie variation in disease severity between individuals with the same mutation. However, the effect of epistatic interactions on the development of complex traits, such as craniofacial morphology, is poorly understood. Here, we investigated the effect of three inbred backgrounds (129X1/SvJ, C57BL/6J, and FVB/NJ) on the expression of craniofacial dysmorphology in mice (Mus musculus) with loss of function in three members of the Sprouty family of growth factor negative regulators (Spry1, Spry2, or Spry4) in order to explore the impact of epistatic interactions on skull morphology. We found that the interaction of inbred background and the Sprouty genotype explains as much craniofacial shape variation as the Sprouty genotype alone. The most severely affected genotypes display a relatively short and wide skull, a rounded cranial vault, and a more highly angled inferior profile. Our results suggest that the FVB background is more resilient to Sprouty loss of function than either C57 or 129, and that Spry4 loss is generally less severe than loss of Spry1 or Spry2 While the specific modifier genes responsible for these significant background effects remain unknown, our results highlight the value of intercrossing mice of multiple inbred backgrounds to identify the genes and developmental interactions that modulate the severity of craniofacial dysmorphology. Our quantitative results represent an important first step toward elucidating genetic interactions underlying variation in robustness to known genetic perturbations in mice

    Estimation of Human Body Shape and Posture Under Clothing

    Full text link
    Estimating the body shape and posture of a dressed human subject in motion represented as a sequence of (possibly incomplete) 3D meshes is important for virtual change rooms and security. To solve this problem, statistical shape spaces encoding human body shape and posture variations are commonly used to constrain the search space for the shape estimate. In this work, we propose a novel method that uses a posture-invariant shape space to model body shape variation combined with a skeleton-based deformation to model posture variation. Our method can estimate the body shape and posture of both static scans and motion sequences of dressed human body scans. In case of motion sequences, our method takes advantage of motion cues to solve for a single body shape estimate along with a sequence of posture estimates. We apply our approach to both static scans and motion sequences and demonstrate that using our method, higher fitting accuracy is achieved than when using a variant of the popular SCAPE model as statistical model.Comment: 23 pages, 11 figure
    • 

    corecore