1
|
Alvarez P, El Mouss M, Calka M, Belme A, Berillon G, Brige P, Payan Y, Perrier P, Vialet A. Predicting primate tongue morphology based on geometrical skull matching. A first step towards an application on fossil hominins. PLoS Comput Biol 2024; 20:e1011808. [PMID: 38252664 PMCID: PMC10833839 DOI: 10.1371/journal.pcbi.1011808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Revised: 02/01/2024] [Accepted: 01/08/2024] [Indexed: 01/24/2024] Open
Abstract
As part of a long-term research project aiming at generating a biomechanical model of a fossil human tongue from a carefully designed 3D Finite Element mesh of a living human tongue, we present a computer-based method that optimally registers 3D CT images of the head and neck of the living human into similar images of another primate. We quantitatively evaluate the method on a baboon. The method generates a geometric deformation field which is used to build up a 3D Finite Element mesh of the baboon tongue. In order to assess the method's ability to generate a realistic tongue from bony structure information alone, as would be the case for fossil humans, its performance is evaluated and compared under two conditions in which different anatomical information is available: (1) combined information from soft-tissue and bony structures; (2) information from bony structures alone. An Uncertainty Quantification method is used to evaluate the sensitivity of the transformation to two crucial parameters, namely the resolution of the transformation grid and the weight of a smoothness constraint applied to the transformation, and to determine the best possible meshes. In both conditions the baboon tongue morphology is realistically predicted, evidencing that bony structures alone provide enough relevant information to generate soft tissue.
Collapse
Affiliation(s)
- Pablo Alvarez
- Sorbonne Université, Institut des Sciences du Calcul et des Données, Paris, France
- Univ. Grenoble Alpes, CNRS, Grenoble INP, TIMC, Grenoble, France
| | - Marouane El Mouss
- Sorbonne Université, Institut des Sciences du Calcul et des Données, Paris, France
| | - Maxime Calka
- Sorbonne Université, Institut des Sciences du Calcul et des Données, Paris, France
| | - Anca Belme
- Sorbonne Université, Institut des Sciences du Calcul et des Données, Paris, France
- Sorbonne Université, Institute Jean Le Rond d’Alembert, UMR 7190, Paris, France
| | - Gilles Berillon
- Muséum national d’Histoire naturelle, UMR 7194 - Histoire naturelle de l’Homme préhistorique, Paris, France
| | - Pauline Brige
- Laboratoire d’Imagerie Interventionnelle Expérimentale, CERIMED, Marseille, France
| | - Yohan Payan
- Univ. Grenoble Alpes, CNRS, Grenoble INP, TIMC, Grenoble, France
| | - Pascal Perrier
- Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-lab, Grenoble, France
| | - Amélie Vialet
- Sorbonne Université, Institut des Sciences du Calcul et des Données, Paris, France
- Muséum national d’Histoire naturelle, UMR 7194 - Histoire naturelle de l’Homme préhistorique, Paris, France
| |
Collapse
|
2
|
A computational framework for canonical holistic morphometric analysis of trabecular bone. Sci Rep 2022; 12:5187. [PMID: 35338187 PMCID: PMC8956643 DOI: 10.1038/s41598-022-09063-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 03/14/2022] [Indexed: 11/22/2022] Open
Abstract
Bone is a remarkable, living tissue that functionally adapts to external loading. Therefore, bone shape and internal structure carry information relevant to many disciplines, including medicine, forensic science, and anthropology. However, morphometric comparisons of homologous regions across different individuals or groups are still challenging. In this study, two methods were combined to quantify such differences: (1) Holistic morphometric analysis (HMA) was used to quantify morphometric values in each bone, (2) which could then be mapped to a volumetric mesh of a canonical bone created by a statistical free-form deformation model (SDM). Required parameters for this canonical holistic morphometric analysis (cHMA) method were identified and the robustness of the method was evaluated. The robustness studies showed that the SDM converged after one to two iterations, had only a marginal bias towards the chosen starting image, and could handle large shape differences seen in bones of different species. Case studies were performed on metacarpal bones and proximal femora of different primate species to confirm prior study results. The differences between species could be visualised and statistically analysed in both case studies. cHMA provides a framework for performing quantitative comparisons of different morphometric quantities across individuals or groups. These comparisons facilitate investigation of the relationship between spatial morphometric variations and function or pathology, or both.
Collapse
|
3
|
Li X. Subject-Specific Head Model Generation by Mesh Morphing: A Personalization Framework and Its Applications. Front Bioeng Biotechnol 2021; 9:706566. [PMID: 34733827 PMCID: PMC8558307 DOI: 10.3389/fbioe.2021.706566] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Accepted: 09/03/2021] [Indexed: 11/30/2022] Open
Abstract
Finite element (FE) head models have become powerful tools in many fields within neuroscience, especially for studying the biomechanics of traumatic brain injury (TBI). Subject-specific head models accounting for geometric variations among subjects are needed for more reliable predictions. However, the generation of such models suitable for studying TBIs remains a significant challenge and has been a bottleneck hindering personalized simulations. This study presents a personalization framework for generating subject-specific models across the lifespan and for pathological brains with significant anatomical changes by morphing a baseline model. The framework consists of hierarchical multiple feature and multimodality imaging registrations, mesh morphing, and mesh grouping, which is shown to be efficient with a heterogeneous dataset including a newborn, 1-year-old (1Y), 2Y, adult, 92Y, and a hydrocephalus brain. The generated models of the six subjects show competitive personalization accuracy, demonstrating the capacity of the framework for generating subject-specific models with significant anatomical differences. The family of the generated head models allows studying age-dependent and groupwise brain injury mechanisms. The framework for efficient generation of subject-specific FE head models helps to facilitate personalized simulations in many fields of neuroscience.
Collapse
Affiliation(s)
- Xiaogai Li
- Division of Neuronic Engineering, Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, Stockholm, Sweden
| |
Collapse
|
4
|
Li X, Zhou Z, Kleiven S. An anatomically detailed and personalizable head injury model: Significance of brain and white matter tract morphological variability on strain. Biomech Model Mechanobiol 2021. [PMID: 33037509 DOI: 10.1101/2020.05.20.105635] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
Finite element head (FE) models are important numerical tools to study head injuries and develop protection systems. The generation of anatomically accurate and subject-specific head models with conforming hexahedral meshes remains a significant challenge. The focus of this study is to present two developmental works: first, an anatomically detailed FE head model with conforming hexahedral meshes that has smooth interfaces between the brain and the cerebrospinal fluid, embedded with white matter (WM) fiber tracts; second, a morphing approach for subject-specific head model generation via a new hierarchical image registration pipeline integrating Demons and Dramms deformable registration algorithms. The performance of the head model is evaluated by comparing model predictions with experimental data of brain-skull relative motion, brain strain, and intracranial pressure. To demonstrate the applicability of the head model and the pipeline, six subject-specific head models of largely varying intracranial volume and shape are generated, incorporated with subject-specific WM fiber tracts. DICE similarity coefficients for cranial, brain mask, local brain regions, and lateral ventricles are calculated to evaluate personalization accuracy, demonstrating the efficiency of the pipeline in generating detailed subject-specific head models achieving satisfactory element quality without further mesh repairing. The six head models are then subjected to the same concussive loading to study the sensitivity of brain strain to inter-subject variability of the brain and WM fiber morphology. The simulation results show significant differences in maximum principal strain and axonal strain in local brain regions (one-way ANOVA test, p < 0.001), as well as their locations also vary among the subjects, demonstrating the need to further investigate the significance of subject-specific models. The techniques developed in this study may contribute to better evaluation of individual brain injury and the development of individualized head protection systems in the future. This study also contains general aspects the research community may find useful: on the use of experimental brain strain close to or at injury level for head model validation; the hierarchical image registration pipeline can be used to morph other head models, such as smoothed-voxel models.
Collapse
Affiliation(s)
- Xiaogai Li
- Division of Neuronic Engineering, Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, 141 52, Huddinge, Sweden.
| | - Zhou Zhou
- Division of Neuronic Engineering, Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, 141 52, Huddinge, Sweden
| | - Svein Kleiven
- Division of Neuronic Engineering, Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, 141 52, Huddinge, Sweden
| |
Collapse
|
5
|
Kappert KDR, Voskuilen L, Smeele LE, Balm AJM, Jasperse B, Nederveen AJ, van der Heijden F. Personalized biomechanical tongue models based on diffusion-weighted MRI and validated using optical tracking of range of motion. Biomech Model Mechanobiol 2021; 20:1101-1113. [PMID: 33682028 PMCID: PMC8154835 DOI: 10.1007/s10237-021-01435-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Accepted: 02/11/2021] [Indexed: 12/13/2022]
Abstract
For advanced tongue cancer, the choice between surgery and organ-sparing treatment is often dependent on the expected loss of tongue functionality after treatment. Biomechanical models might assist in this choice by simulating the post-treatment function loss. However, this function loss varies between patients and should, therefore, be predicted for each patient individually. In the present study, the goal was to better predict the postoperative range of motion (ROM) of the tongue by personalizing biomechanical models using diffusion-weighted MRI and constrained spherical deconvolution reconstructions of tongue muscle architecture. Diffusion-weighted MRI scans of ten healthy volunteers were obtained to reconstruct their tongue musculature, which were subsequently registered to a previously described population average or atlas. Using the displacement fields obtained from the registration, the segmented muscle fiber tracks from the atlas were morphed back to create personalized muscle fiber tracks. Finite element models were created from the fiber tracks of the atlas and those of the individual tongues. Via inverse simulation of a protruding, downward, left and right movement, the ROM of the tongue was predicted. This prediction was compared to the ROM measured with a 3D camera. It was demonstrated that biomechanical models with personalized muscles bundles are better in approaching the measured ROM than a generic model. However, to achieve this result a correction factor was needed to compensate for the small magnitude of motion of the model. Future versions of these models may have the potential to improve the estimation of function loss after treatment for advanced tongue cancer.
Collapse
Affiliation(s)
- K D R Kappert
- Department of Head and Neck Oncology and Surgery, Netherlands Cancer Institute, Antoni Van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands. .,Department of Robotics and Mechatronics, Faculty of EEMCS, Technical Medical Centre, University of Twente, Enschede, The Netherlands.
| | - L Voskuilen
- Department of Head and Neck Oncology and Surgery, Netherlands Cancer Institute, Antoni Van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.,Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.,Department of Oral and Maxillofacial Surgery, Academic Centre for Dentistry Amsterdam and Amsterdam UMC, University of Amsterdam and VU University Amsterdam, Amsterdam, The Netherlands
| | - L E Smeele
- Department of Head and Neck Oncology and Surgery, Netherlands Cancer Institute, Antoni Van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.,Department of Oral and Maxillofacial Surgery, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - A J M Balm
- Department of Head and Neck Oncology and Surgery, Netherlands Cancer Institute, Antoni Van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.,Department of Robotics and Mechatronics, Faculty of EEMCS, Technical Medical Centre, University of Twente, Enschede, The Netherlands.,Department of Oral and Maxillofacial Surgery, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - B Jasperse
- Department of Head and Neck Oncology and Surgery, Netherlands Cancer Institute, Antoni Van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands
| | - A J Nederveen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - F van der Heijden
- Department of Head and Neck Oncology and Surgery, Netherlands Cancer Institute, Antoni Van Leeuwenhoek Hospital, Plesmanlaan 121, 1066 CX, Amsterdam, The Netherlands.,Department of Robotics and Mechatronics, Faculty of EEMCS, Technical Medical Centre, University of Twente, Enschede, The Netherlands
| |
Collapse
|
6
|
Calka M, Perrier P, Ohayon J, Grivot-Boichon C, Rochette M, Payan Y. Machine-Learning based model order reduction of a biomechanical model of the human tongue. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 198:105786. [PMID: 33059060 DOI: 10.1016/j.cmpb.2020.105786] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Accepted: 09/30/2020] [Indexed: 06/11/2023]
Abstract
BACKGROUND AND OBJECTIVES This paper presents the results of a Machine-Learning based Model Order Reduction (MOR) method applied to a complex 3D Finite Element (FE) biomechanical model of the human tongue, in order to create a Digital Twin Model (DTM) that enables real-time simulations. The DTM is designed for future inclusion in a computer assisted protocol for tongue surgery planning. METHODS The proposed method uses an "a posteriori" MOR that allows, from a limited number of simulations with the FE model, to predict in real time mechanical responses of the human tongue to muscle activations. RESULTS The MOR method is evaluated for simulations associated with separate single tongue muscle activations. It is shown to be able to account with a sub-millimetric spatial accuracy for the non-linear dynamical behavior of the tongue model observed in these simulations. CONCLUSION Further evaluations of the MOR method will include tongue movements induced by multiple muscle activations. At this stage our MOR method offers promising perspectives for the use of the tongue model in a clinical context to predict the impact of tongue surgery on tongue mobility. As a long term application, this DTM of the tongue could be used to predict the functional consequences of the surgery in terms of speech production and swallowing.
Collapse
Affiliation(s)
- Maxime Calka
- Univ. Grenoble Alpes, CNRS, Grenoble INP, TIMC-IMAG, Grenoble F-38000, France; Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-lab, Grenoble F-38000, France; ANSYS, Villeurbanne F-69100, France.
| | - Pascal Perrier
- Univ. Grenoble Alpes, CNRS, Grenoble INP, GIPSA-lab, Grenoble F-38000, France
| | - Jacques Ohayon
- Univ. Grenoble Alpes, CNRS, Grenoble INP, TIMC-IMAG, Grenoble F-38000, France; Savoie Mont-Blanc University, Polytech Annecy-Chambéry, Le Bourget du Lac 73376, France
| | | | | | - Yohan Payan
- Univ. Grenoble Alpes, CNRS, Grenoble INP, TIMC-IMAG, Grenoble F-38000, France
| |
Collapse
|
7
|
Li X, Zhou Z, Kleiven S. An anatomically detailed and personalizable head injury model: Significance of brain and white matter tract morphological variability on strain. Biomech Model Mechanobiol 2020; 20:403-431. [PMID: 33037509 PMCID: PMC7979680 DOI: 10.1007/s10237-020-01391-8] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2020] [Accepted: 09/20/2020] [Indexed: 12/28/2022]
Abstract
Finite element head (FE) models are important numerical tools to study head injuries and develop protection systems. The generation of anatomically accurate and subject-specific head models with conforming hexahedral meshes remains a significant challenge. The focus of this study is to present two developmental works: first, an anatomically detailed FE head model with conforming hexahedral meshes that has smooth interfaces between the brain and the cerebrospinal fluid, embedded with white matter (WM) fiber tracts; second, a morphing approach for subject-specific head model generation via a new hierarchical image registration pipeline integrating Demons and Dramms deformable registration algorithms. The performance of the head model is evaluated by comparing model predictions with experimental data of brain-skull relative motion, brain strain, and intracranial pressure. To demonstrate the applicability of the head model and the pipeline, six subject-specific head models of largely varying intracranial volume and shape are generated, incorporated with subject-specific WM fiber tracts. DICE similarity coefficients for cranial, brain mask, local brain regions, and lateral ventricles are calculated to evaluate personalization accuracy, demonstrating the efficiency of the pipeline in generating detailed subject-specific head models achieving satisfactory element quality without further mesh repairing. The six head models are then subjected to the same concussive loading to study the sensitivity of brain strain to inter-subject variability of the brain and WM fiber morphology. The simulation results show significant differences in maximum principal strain and axonal strain in local brain regions (one-way ANOVA test, p < 0.001), as well as their locations also vary among the subjects, demonstrating the need to further investigate the significance of subject-specific models. The techniques developed in this study may contribute to better evaluation of individual brain injury and the development of individualized head protection systems in the future. This study also contains general aspects the research community may find useful: on the use of experimental brain strain close to or at injury level for head model validation; the hierarchical image registration pipeline can be used to morph other head models, such as smoothed-voxel models.
Collapse
Affiliation(s)
- Xiaogai Li
- Division of Neuronic Engineering, Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, 141 52, Huddinge, Sweden.
| | - Zhou Zhou
- Division of Neuronic Engineering, Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, 141 52, Huddinge, Sweden
| | - Svein Kleiven
- Division of Neuronic Engineering, Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, 141 52, Huddinge, Sweden
| |
Collapse
|
8
|
Zhou Y, Yoo P, Feng Y, Sankar A, Sadr A, Seibel EJ. Towards AR-assisted visualisation and guidance for imaging of dental decay. Healthc Technol Lett 2019; 6:243-248. [PMID: 32038865 PMCID: PMC6952244 DOI: 10.1049/htl.2019.0082] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Accepted: 10/02/2019] [Indexed: 12/27/2022] Open
Abstract
Untreated dental decay is the most prevalent dental problem in the world, affecting up to 2.4 billion people and leading to a significant economic and social burden. Early detection can greatly mitigate irreversible effects of dental decay, avoiding the need for expensive restorative treatment that forever disrupts the enamel protective layer of teeth. However, two key challenges exist that make early decay management difficult: unreliable detection and lack of quantitative monitoring during treatment. New optically based imaging through the enamel provides the dentist a safe means to detect, locate, and monitor the healing process. This work explores the use of an augmented reality (AR) headset to improve the workflow of early decay therapy and monitoring. The proposed workflow includes two novel AR-enabled features: (i) in situ visualisation of pre-operative optically based dental images and (ii) augmented guidance for repetitive imaging during therapy monitoring. The workflow is designed to minimise distraction, mitigate hand-eye coordination problems, and help guide monitoring of early decay during therapy in both clinical and mobile environments. The results from quantitative evaluations as well as a formative qualitative user study uncover the potentials of the proposed system and indicate that AR can serve as a promising tool in tooth decay management.
Collapse
Affiliation(s)
- Yaxuan Zhou
- Department of Electrical and Computer Engineering, University of Washington, Seattle, WA 98195, USA
- Human Photonics Lab, Department of Mechanical Engineering, University of Washington, Seattle, WA 98195, USA
| | - Paul Yoo
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA 98195, USA
| | - Yingru Feng
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA 98195, USA
| | - Aditya Sankar
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA 98195, USA
| | - Alireza Sadr
- School of Dentistry, University of Washington, Seattle, WA 98195, USA
| | - Eric J. Seibel
- Human Photonics Lab, Department of Mechanical Engineering, University of Washington, Seattle, WA 98195, USA
| |
Collapse
|
9
|
Miller K, Joldes GR, Bourantas G, Warfield S, Hyde DE, Kikinis R, Wittek A. Biomechanical modeling and computer simulation of the brain during neurosurgery. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2019; 35:e3250. [PMID: 31400252 PMCID: PMC6785376 DOI: 10.1002/cnm.3250] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2019] [Revised: 06/28/2019] [Accepted: 08/08/2019] [Indexed: 06/10/2023]
Abstract
Computational biomechanics of the brain for neurosurgery is an emerging area of research recently gaining in importance and practical applications. This review paper presents the contributions of the Intelligent Systems for Medicine Laboratory and its collaborators to this field, discussing the modeling approaches adopted and the methods developed for obtaining the numerical solutions. We adopt a physics-based modeling approach and describe the brain deformation in mechanical terms (such as displacements, strains, and stresses), which can be computed using a biomechanical model, by solving a continuum mechanics problem. We present our modeling approaches related to geometry creation, boundary conditions, loading, and material properties. From the point of view of solution methods, we advocate the use of fully nonlinear modeling approaches, capable of capturing very large deformations and nonlinear material behavior. We discuss finite element and meshless domain discretization, the use of the total Lagrangian formulation of continuum mechanics, and explicit time integration for solving both time-accurate and steady-state problems. We present the methods developed for handling contacts and for warping 3D medical images using the results of our simulations. We present two examples to showcase these methods: brain shift estimation for image registration and brain deformation computation for neuronavigation in epilepsy treatment.
Collapse
Affiliation(s)
- K. Miller
- Intelligent Systems for Medicine Laboratory, Department of Mechanical Engineering, The University of Western Australia, 35 Stirling Highway, Perth, WA 6009, Australia
| | - G. R. Joldes
- Intelligent Systems for Medicine Laboratory, Department of Mechanical Engineering, The University of Western Australia, 35 Stirling Highway, Perth, WA 6009, Australia
| | - G. Bourantas
- Intelligent Systems for Medicine Laboratory, Department of Mechanical Engineering, The University of Western Australia, 35 Stirling Highway, Perth, WA 6009, Australia
| | - S.K. Warfield
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital and Harvard Medical School, 300 Longwood Avenue, Boston MA 02115
| | - D. E. Hyde
- Computational Radiology Laboratory, Department of Radiology, Boston Children’s Hospital and Harvard Medical School, 300 Longwood Avenue, Boston MA 02115
| | - R. Kikinis
- Surgical Planning Laboratory, Brigham and Women’s Hospital and Harvard Medical School, 45 Francis St, Boston, MA 02115
- Medical Image Computing, University of Bremen, Germany
- Fraunhofer MEVIS, Bremen, Germany
| | - A. Wittek
- Intelligent Systems for Medicine Laboratory, Department of Mechanical Engineering, The University of Western Australia, 35 Stirling Highway, Perth, WA 6009, Australia
| |
Collapse
|
10
|
Hewer A, Wuhrer S, Steiner I, Richmond K. A multilinear tongue model derived from speech related MRI data of the human vocal tract. COMPUT SPEECH LANG 2018. [DOI: 10.1016/j.csl.2018.02.001] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
|
11
|
Fougeron N, Rohan PY, Macron A, Travert C, Pillet H, Skalli W. Subject specific finite element mesh generation of the pelvis from biplanar x-ray images: application to 120 clinical cases. Comput Methods Biomech Biomed Engin 2018; 21:408-412. [PMID: 29969279 DOI: 10.1080/10255842.2018.1469624] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
Abstract
Several Finite Element (FE) models of the pelvis have been developed to comprehensively assess the onset of pathologies and for clinical and industrial applications. However, because of the difficulties associated with the creation of subject-specific FE mesh from CT scan and MR images, most of the existing models rely on the data of one given individual. Moreover, although several fast and robust methods have been developed for automatically generating tetrahedral meshes of arbitrary geometries, hexahedral meshes are still preferred today because of their distinct advantages but their generation remains an open challenge. Recently, approaches have been proposed for fast 3D reconstruction of bones based on X-ray imaging. In this study, we adapted such an approach for the fast and automatic generation of all-hexahedral subject-specific FE models of the pelvis based on the elastic registration of a generic mesh to the subject-specific target in conjunction with element regularity and quality correction. The technique was successfully tested on a database of 120 3D reconstructions of pelvises from biplanar X-ray images. For each patient, a full hexahedral subject-specific FE mesh was generated with an accurate surface representation.
Collapse
Affiliation(s)
- Nolwenn Fougeron
- a Institut de Biomécanique Humaine Georges Charpak, Arts et Métiers , Paris , France
| | - Pierre-Yves Rohan
- a Institut de Biomécanique Humaine Georges Charpak, Arts et Métiers , Paris , France
| | - Aurélien Macron
- a Institut de Biomécanique Humaine Georges Charpak, Arts et Métiers , Paris , France.,b CEA, LETI, CLINATEC, MINATEC Campus , Grenoble , France
| | - Christophe Travert
- a Institut de Biomécanique Humaine Georges Charpak, Arts et Métiers , Paris , France
| | - Hélène Pillet
- a Institut de Biomécanique Humaine Georges Charpak, Arts et Métiers , Paris , France
| | - Wafa Skalli
- a Institut de Biomécanique Humaine Georges Charpak, Arts et Métiers , Paris , France
| |
Collapse
|
12
|
Wang H, Sun X, Wu T, Li C, Chen Z, Liao M, Li M, Yan W, Huang H, Yang J, Tan Z, Hui L, Liu Y, Pan H, Qu Y, Chen Z, Tan L, Yu L, Shi H, Huo L, Zhang Y, Tang X, Zhang S, Liu C. Deformable torso phantoms of Chinese adults for personalized anatomy modelling. J Anat 2018; 233:121-134. [PMID: 29663370 PMCID: PMC5987821 DOI: 10.1111/joa.12815] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/19/2018] [Indexed: 11/26/2022] Open
Abstract
In recent years, there has been increasing demand for personalized anatomy modelling for medical and industrial applications, such as ergonomics device development, clinical radiological exposure simulation, biomechanics analysis, and 3D animation character design. In this study, we constructed deformable torso phantoms that can be deformed to match the personal anatomy of Chinese male and female adults. The phantoms were created based on a training set of 79 trunk computed tomography (CT) images (41 males and 38 females) from normal Chinese subjects. Major torso organs were segmented from the CT images, and the statistical shape model (SSM) approach was used to learn the inter-subject anatomical variations. To match the personal anatomy, the phantoms were registered to individual body surface scans or medical images using the active shape model method. The constructed SSM demonstrated anatomical variations in body height, fat quantity, respiratory status, organ geometry, male muscle size, and female breast size. The masses of the deformed phantom organs were consistent with Chinese population organ mass ranges. To validate the performance of personal anatomy modelling, the phantoms were registered to the body surface scan and CT images. The registration accuracy measured from 22 test CT images showed a median Dice coefficient over 0.85, a median volume recovery coefficient (RCvlm ) between 0.85 and 1.1, and a median averaged surface distance (ASD) < 1.5 mm. We hope these phantoms can serve as computational tools for personalized anatomy modelling for the research community.
Collapse
Affiliation(s)
- Hongkai Wang
- Department of Biomedical EngineeringFaculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalianLiaoningChina
| | - Xiaobang Sun
- Department of Biomedical EngineeringFaculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalianLiaoningChina
- Department of Information TechnologyUniversity of JyväskyläJyväskyläFinland
| | - Tongning Wu
- China Academy of Industry and Communications TechnologyBeijingChina
| | - Congsheng Li
- China Academy of Industry and Communications TechnologyBeijingChina
| | - Zhonghua Chen
- Department of Biomedical EngineeringFaculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalianLiaoningChina
| | - Meiying Liao
- Department of Biomedical EngineeringFaculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalianLiaoningChina
| | - Mengci Li
- Department of Biomedical EngineeringFaculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalianLiaoningChina
| | - Wen Yan
- Department of Biomedical EngineeringFaculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalianLiaoningChina
| | - Hui Huang
- Department of Biomedical EngineeringFaculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalianLiaoningChina
| | - Jia Yang
- Department of Biomedical EngineeringFaculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalianLiaoningChina
| | - Ziyu Tan
- Department of Biomedical EngineeringFaculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalianLiaoningChina
| | - Libo Hui
- Department of Biomedical EngineeringFaculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalianLiaoningChina
| | - Yue Liu
- Department of Biomedical EngineeringFaculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalianLiaoningChina
| | - Hang Pan
- Department of Biomedical EngineeringFaculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalianLiaoningChina
| | - Yue Qu
- Department of Biomedical EngineeringFaculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalianLiaoningChina
| | - Zhaofeng Chen
- Department of Biomedical EngineeringFaculty of Electronic Information and Electrical EngineeringDalian University of TechnologyDalianLiaoningChina
| | - Liwen Tan
- Institute of Digital MedicineThird Military Medical UniversityChongqingChina
| | - Lijuan Yu
- The Affiliated Cancer Hospital of Hainan Medical CollegeHaikouHainanChina
| | - Hongcheng Shi
- Department of Nuclear MedicineZhongshan HospitalFudan UniversityShanghaiChina
| | - Li Huo
- Department of Nuclear MedicinePeking Union Medical College HospitalBeijingChina
| | - Yanjun Zhang
- Department of Nuclear Medicinethe First Affiliated Hospital of Dalian Medical UniversityDalianLiaoningChina
| | - Xin Tang
- Trauma Department of Orthopaedicsthe First Affiliated Hospital of Dalian Medical UniversityDalianLiaoningChina
| | - Shaoxiang Zhang
- Institute of Digital MedicineThird Military Medical UniversityChongqingChina
| | - Changjian Liu
- Trauma Department of Orthopaedicsthe First Affiliated Hospital of Dalian Medical UniversityDalianLiaoningChina
| |
Collapse
|