A statistical geometrical description of the human liver for probabilistic occupant models.

Realistic numerical assessments of liver injury risk for the entire occupant population require incorporating inter-subject variations into numerical models. Statistical shape models of the abdominal organs have been shown to be useful tools for the investigation of the organ variations and could be applied to the development of statistical computational models. The main objective of this study was to establish a standard procedure to quantify the shape variations of a human liver in a seated posture, and construct three-dimensional (3D) statistical shape boundary models. Statistical shape analysis was applied to construct shape models of 15 adult human livers. Principal component analysis (PCA) was then utilized to obtain the modes of variation, the mean model, and a set of statistical boundary shape models, which were constructed using the q-hyper-ellipsoid approach. The first five modes of a human liver accounted for the major anatomical variations. The modes were highly correlated to the height, thickness, width, and curvature of the liver, and the concavity of the right lobe. The mean model and the principal components were utilized to construct four boundary models of human liver. The statistical boundary model approach presented in this study could be used to develop probabilistic finite element (FE) models. In the future, the probabilistic liver models could be used in FE simulations to better understand the variability in biomechanical responses and abdominal injuries under impact loading.

[1]  Yen-Wei Chen,et al.  Automated Segmentation of the Liver from 3D CT Images Using Probabilistic Atlas and Multi-level Statistical Shape Model , 2007, MICCAI.

[2]  Won-Sook Lee,et al.  Analysis of segmented human body scans , 2007, GI '07.

[3]  Nicholas Ayache,et al.  Medical Image Computing and Computer-Assisted Intervention - MICCAI 2007, 10th International Conference, Brisbane, Australia, October 29 - November 2, 2007, Proceedings, Part I , 2007, MICCAI.

[4]  Qing He,et al.  Detecting 3D Corpus Callosum abnormalities in phenylketonuria , 2009, Int. J. Comput. Biol. Drug Des..

[5]  Y. Duan,et al.  Detecting corpus callosum abnormalities in autism based on anatomical landmarks , 2010, Psychiatry Research: Neuroimaging.

[6]  Jeffrey Richard Crandall,et al.  A study of the pedestrian impact kinematics using finite element dummy models: the corridors and dimensional analysis scaling of upper-body trajectories , 2008 .

[7]  Costin D. Untaroiu,et al.  A Finite Element Model of the Foot and Ankle for Automotive Impact Applications , 2012, Annals of Biomedical Engineering.

[8]  Joel D. Stitzel,et al.  Comparison of Organ Location, Morphology, and Rib Coverage of a Midsized Male in the Supine and Seated Positions , 2013, Comput. Math. Methods Medicine.

[9]  Ronald M. Summers,et al.  Hierarchical patch generation for multilevel statistical shape analysis by principal factor analysis decomposition , 2010, Medical Imaging.

[10]  Dipan Bose,et al.  Experimental and computational investigation of human clavicle response in anterior-posterior bending loading - biomed 2009. , 2009, Biomedical sciences instrumentation.

[11]  Dipan Bose,et al.  Effect of seat belt pretensioners on human abdomen and thorax: Biomechanical response and risk of injuries , 2012, The journal of trauma and acute care surgery.

[12]  Thomas Lange,et al.  A Statistical Shape Model for the Liver , 2002, MICCAI.

[13]  Andrew W. Fitzgibbon.  Robust registration of 2D and 3D point sets , 2003, Image Vis. Comput..

[14]  Linda G. Shapiro,et al.  3D Point Correspondence by Minimum Description Length in Feature Space , 2010, ECCV.

[15]  A. Kemper,et al.  Modeling the biomechanical and injury response of human liver parenchyma under tensile loading. , 2015, Journal of the mechanical behavior of biomedical materials.

[16]  Costin D. Untaroiu,et al.  Statistical shape analysis of clavicular cortical bone with applications to the development of mean and boundary shape models , 2013, Comput. Methods Programs Biomed..

[17]  Marc Rioux,et al.  Characterizing human shape variation using 3D anthropometric data , 2006, The Visual Computer.

[18]  Costin D. Untaroiu,et al.  A numerical investigation of mid-femoral injury tolerance in axial compression and bending loading , 2010 .

[19]  Alfred O. Hero,et al.  Least Biased Target Selection in Probabilistic Atlas Construction , 2005, MICCAI.

[20]  Yifei Dai,et al.  Incorporating population-level variability in orthopedic biomechanical analysis: a review. , 2014, Journal of biomechanical engineering.

[21]  Costin D. Untaroiu,et al.  A Finite Element Model of the Lower Limb for Simulating Automotive Impacts , 2012, Annals of Biomedical Engineering.

[22]  Jitendra Malik,et al.  Shape matching and object recognition using shape contexts , 2010, 2010 3rd International Conference on Computer Science and Information Technology.

[23]  Timothy F. Cootes,et al.  Building 3-D Statistical Shape Models by Direct Optimization , 2010, IEEE Transactions on Medical Imaging.

[24]  Roland Materne,et al.  Body surface area and body weight predict total liver volume in Western adults , 2002, Liver transplantation : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society.

[25]  Cristian Lorenz,et al.  3D statistical shape models for medical image segmentation , 1999, Second International Conference on 3-D Digital Imaging and Modeling (Cat. No.PR00062).

[26]  Frans Vos,et al.  A statistical description of the articulating ulna surface for prosthesis design , 2009, 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro.

[27]  Xiangrong Zhou,et al.  3D open-surface shape correspondence for statistical shape modeling: Identifying topologically consistent landmarks , 2009, 2009 IEEE 12th International Conference on Computer Vision.

[28]  Song Wang,et al.  Evaluating Shape Correspondence for Statistical Shape Analysis: A Benchmark Study , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[29]  Rhodri H. Davies,et al.  Learning Shape: Optimal Models for Analysing Natural Variability , 2004 .

[30]  Costin D. Untaroiu,et al.  Identification of occupant posture using a Bayesian classification methodology to reduce the risk of injury in a collision , 2011 .

[31]  Matthew P Reed,et al.  Anthropometric specification of child crash dummy pelves through statistical analysis of skeletal geometry. , 2009, Journal of biomechanics.

[32]  Hans-Peter Meinzer,et al.  Statistical shape models for 3D medical image segmentation: A review , 2009, Medical Image Anal..

[33]  Jacob B Putnam,et al.  Development, Calibration, and Validation of a Head–Neck Complex of THOR Mod Kit Finite Element Model , 2014, Traffic injury prevention.

[34]  Stephen A Ridella,et al.  Modifications to Improve the Durability, Usability and Biofidelity of the THOR-NT Dummy , 2011 .

[35]  David J. Hawkes,et al.  Instantiation and registration of statistical shape models of the femur and pelvis using 3D ultrasound imaging , 2008, Medical Image Anal..

[36]  Christopher J. Taylor,et al.  A Method of Automated Landmark Generation for Automated 3D PDM Construction , 2000, BMVC.

[37]  Linda G. Shapiro,et al.  3D point correspondence by minimum description length with 2DPCA , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[38]  K Püschel,et al.  Standard liver volume in the Caucasian population. , 1999, Liver transplantation and surgery : official publication of the American Association for the Study of Liver Diseases and the International Liver Transplantation Society.

[39]  Guido Gerig,et al.  Unbiased diffeomorphic atlas construction for computational anatomy , 2004, NeuroImage.

[40]  A. Kemper,et al.  Effect of storage on tensile material properties of bovine liver. , 2014, Journal of the mechanical behavior of biomedical materials.

[41]  Martin Styner,et al.  Evaluation of 3D Correspondence Methods for Model Building , 2003, IPMI.

[42]  Yen-Wei Chen,et al.  Automated segmentation of the liver from 3D CT images using probabilistic atlas and multilevel statistical shape model. , 2008, Academic radiology.

[43]  Stuart Crozier,et al.  3D Statistical Shape Models to Embed Spatial Relationship Information , 2005, CVBIA.

[44]  Fred L. Bookstein,et al.  Principal Warps: Thin-Plate Splines and the Decomposition of Deformations , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[45]  L. V. van Vliet,et al.  Statistical descriptions of scaphoid and lunate bone shapes. , 2010, Journal of biomechanics.

[46]  Philippe Vezin,et al.  Development of a Set of Numerical Human Models for Safety , 2005 .

[47]  Travis D. Eliason,et al.  Statistical shape modeling describes variation in tibia and femur surface geometry between Control and Incidence groups from the osteoarthritis initiative database. , 2010, Journal of biomechanics.

[48]  Chang Shu,et al.  Landmark-free posture invariant human shape correspondence , 2011, The Visual Computer.

[49]  Philippe Beillas,et al.  The effects of posture and subject-to-subject variations on the position, shape and volume of abdominal and thoracic organs. , 2009, Stapp car crash journal.

[50]  Stephen A Ridella,et al.  Thoracic Biofidelity Assessment of the THOR Mod Kit ATD , 2013 .

[51]  Christopher J. Taylor,et al.  Statistical models of shape - optimisation and evaluation , 2008 .

[52]  Philippe Beillas,et al.  Statistical modeling of human liver incorporating the variations in shape, size, and material properties. , 2013, Stapp car crash journal.

[53]  Xiangrong Zhou,et al.  A Fast 3D Correspondence Method for Statistical Shape Modeling , 2007, 2007 IEEE Conference on Computer Vision and Pattern Recognition.

[54]  Yen-Wei Chen,et al.  Application of statistical shape model to diagnosis of liver disease , 2010, The 2nd International Conference on Software Engineering and Data Mining.

[55]  Costin D. Untaroiu,et al.  Performance-Based Classification of Occupant Posture to Reduce the Risk of Injury in a Collision , 2013, IEEE Transactions on Intelligent Transportation Systems.

[56]  P J Laz,et al.  A review of probabilistic analysis in orthopaedic biomechanics , 2010, Proceedings of the Institution of Mechanical Engineers. Part H, Journal of engineering in medicine.

[57]  Costin D Untaroiu,et al.  A Numerical Investigation on the Variation in Hip Injury Tolerance With Occupant Posture During Frontal Collisions , 2014, Traffic injury prevention.

[58]  F. S. Gayzik,et al.  Development of a Full Body CAD Dataset for Computational Modeling: A Multi-modality Approach , 2011, Annals of Biomedical Engineering.