Modeling Lung Architecture in the XCAT Series of Phantoms: Physiologically Based Airways, Arteries and Veins

The purpose of this paper was to extend the extended cardiac-torso (XCAT) series of computational phantoms to include a detailed lung architecture including airways and pulmonary vasculature. Eleven XCAT phantoms of varying anatomy were used in this paper. The lung lobes and initial branches of the airways, pulmonary arteries, and veins were previously defined in each XCAT model. These models were extended from the initial branches of the airways and vessels to the level of terminal branches using an anatomically-based volume-filling branching algorithm. This algorithm grew the airway and vasculature branches separately and iteratively without intersecting each other using cylindrical models with diameters estimated by order-based anatomical measurements. Geometrical features of the extended branches were compared with the literature anatomy values to quantitatively evaluate the models. These features include branching angle, length to diameter ratio, daughter to parent diameter ratio, asymmetrical branching pattern, diameter, and length ratios. The XCAT phantoms were then used to simulate CT images to qualitatively compare them with the original phantom images. The proposed growth model produced 46369 ± 12521 airways, 44737 ± 11773 arteries, and 39819 ± 9988 veins to the XCAT phantoms. Furthermore, the growth model was shown to produce asymmetrical airway, artery, and vein networks with geometrical attributes close to morphometry and model based studies. The simulated CT images of the phantoms were judged to be more realistic, including more airways and pulmonary vessels compared with the original phantoms. Future work will seek to add a heterogeneous parenchymal background into the XCAT lungs to make the phantoms even more representative of human anatomy, paving the way towards the use of XCAT models as a tool to virtually evaluate the current and emerging medical imaging technologies.

[1]  Michael Sandborg,et al.  CTmod - A toolkit for Monte Carlo simulation of projections including scatter in computed tomography , 2008, Comput. Methods Programs Biomed..

[2]  H Kitaoka,et al.  A three-dimensional model of the human airway tree. , 1999, Journal of applied physiology.

[3]  Christoph Bandt,et al.  Fractal exponents for the upper airways of mammalian lungs , 1995 .

[4]  Ewald R. Weibel,et al.  Geometry and Dimensions of Airways of Conductive and Transitory Zones , 1963 .

[5]  Bruno De Man,et al.  CatSim: a new computer assisted tomography simulation environment , 2007, SPIE Medical Imaging.

[6]  Bruno Golosio,et al.  The xraylib library for X-ray-matter interactions. Recent developments , 2011 .

[7]  Ching-Long Lin,et al.  Image‐based modeling of lung structure and function , 2010, Journal of magnetic resonance imaging : JMRI.

[8]  Salman Siddiqui,et al.  Development and Analysis of Patient-Based Complete Conducting Airways Models , 2015, PloS one.

[9]  F. Laurent,et al.  Assessment of bronchial wall thickness and lumen diameter in human adults using multi‐detector computed tomography: comparison with theoretical models , 2007, Journal of anatomy.

[10]  Ehsan Samei,et al.  The Effect of Contrast Material on Radiation Dose at CT: Part II. A Systematic Evaluation across 58 Patient Models. , 2017, Radiology.

[11]  Benjamin M. W. Tsui,et al.  MCAT to XCAT: The Evolution of 4-D Computerized Phantoms for Imaging Research , 2009, Proceedings of the IEEE.

[12]  W. Paul Segars,et al.  Organ doses, effective doses, and risk indices in adult CT: comparison of four types of reference phantoms across different examination protocols. , 2012, Medical physics.

[13]  W P Segars,et al.  Population of anatomically variable 4D XCAT adult phantoms for imaging research and optimization. , 2013, Medical physics.

[14]  M. Moseley,et al.  Efficient simulation of magnetic resonance imaging with Bloch-Torrey equations using intra-voxel magnetization gradients. , 2006, Journal of magnetic resonance.

[15]  H Zaidi,et al.  Relevance of accurate Monte Carlo modeling in nuclear medical imaging. , 1999, Medical physics.

[16]  J. Maina,et al.  Morphometric characterization of the airway and vascular systems of the lung of the domestic pig, Sus scrofa: comparison of the airway, arterial and venous systems. , 2001, Comparative biochemistry and physiology. Part A, Molecular & integrative physiology.

[17]  Geoffrey McLennan,et al.  CT-based geometry analysis and finite element models of the human and ovine bronchial tree. , 2004, Journal of applied physiology.

[18]  K. Horsfield,et al.  Volume of the conducting airways calculated from morphometric parameters. , 1981, Bulletin of mathematical biology.

[19]  K. Horsfield,et al.  Morphology of the bronchial tree in man. , 1968, Journal of applied physiology.

[20]  Valery Naranjo,et al.  Comparing algorithms for automated vessel segmentation in computed tomography scans of the lung: the VESSEL12 study , 2014, Medical Image Anal..

[21]  E R Weibel,et al.  Morphometry of the human pulmonary acinus , 1988, The Anatomical record.

[22]  K. Horsfield,et al.  Morphometry of pulmonary veins in man , 2007, Lung.

[23]  Philip Kollmannsberger,et al.  Architecture of the osteocyte network correlates with bone material quality , 2013, Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research.

[24]  Rangasami L. Kashyap,et al.  Building Skeleton Models via 3-D Medial Surface/Axis Thinning Algorithms , 1994, CVGIP Graph. Model. Image Process..

[25]  J S Fleming,et al.  Study of the three‐dimensional geometry of the central conducting airways in man using computed tomographic (CT) images , 2002, Journal of anatomy.

[26]  Irène Buvat,et al.  Monte Carlo simulations in emission tomography and GATE: An overview , 2006 .

[27]  Ramin Bozorgmehry Boozarjomehry,et al.  Developmental model of an automatic production of the human bronchial tree based on L-system , 2016, Comput. Methods Programs Biomed..

[28]  Raúl San José Estépar,et al.  Automatic Synthesis of Anthropomorphic Pulmonary CT Phantoms , 2015, bioRxiv.

[29]  Peter J Hunter,et al.  Investigation of the relative effects of vascular branching structure and gravity on pulmonary arterial blood flow heterogeneity via an image-based computational model. , 2005, Academic radiology.

[30]  Ehsan Samei,et al.  Quantum noise properties of CT images with anatomical textured backgrounds across reconstruction algorithms: FBP and SAFIRE. , 2014, Medical physics.

[31]  H Benoit-Cattin,et al.  The SIMRI project: a versatile and interactive MRI simulator. , 2005, Journal of magnetic resonance.

[32]  Bram van Ginneken,et al.  Automated segmentation of pulmonary structures in thoracic computed tomography scans: a review , 2013 .

[33]  Mary I Townsley,et al.  Structure and composition of pulmonary arteries, capillaries, and veins. , 2012, Comprehensive Physiology.

[34]  Ehsan Samei,et al.  Patient-based estimation of organ dose for a population of 58 adult patients across 13 protocol categories. , 2014, Medical physics.

[35]  A Bush,et al.  The role of inflammation in airway disease: remodeling. , 2000, American journal of respiratory and critical care medicine.

[36]  W P Segars,et al.  The development of a population of 4D pediatric XCAT phantoms for imaging research and optimization. , 2015, Medical physics.

[37]  K. P. Van de Woestijne,et al.  Anatomy of membranous bronchioles in normal, senile and emphysematous human lungs. , 1994, Journal of applied physiology.

[38]  Claudia C Brunner,et al.  Material-specific transfer function model and SNR in CT , 2013, Physics in medicine and biology.

[39]  Peter J Hunter,et al.  Anatomically based finite element models of the human pulmonary arterial and venous trees including supernumerary vessels. , 2005, Journal of applied physiology.

[40]  B.M.W. Tsui,et al.  Development of a dynamic model for the lung lobes and airway tree in the NCAT phantom , 2002 .

[41]  W P Segars,et al.  Realistic CT simulation using the 4D XCAT phantom. , 2008, Medical physics.

[42]  K. Horsfield,et al.  Morphometry of the Small Pulmonary Arteries in Man , 1978, Circulation research.

[43]  Matthias Ochs,et al.  Quantitative microscopy of the lung: a problem-based approach. Part 1: basic principles of lung stereology. , 2013, American journal of physiology. Lung cellular and molecular physiology.

[44]  G Cumming,et al.  Angles of branching and diameters of branches in the human bronchial tree. , 1967, The Bulletin of mathematical biophysics.

[45]  Eric A Hoffman,et al.  The lung physiome: merging imaging‐based measures with predictive computational models , 2009, Wiley interdisciplinary reviews. Systems biology and medicine.

[46]  R. Yen,et al.  Morphometry of the human pulmonary vasculature. , 1996, Journal of applied physiology.

[47]  Ehsan Samei,et al.  Patient-specific radiation dose and cancer risk estimation in CT: part I. development and validation of a Monte Carlo program. , 2010, Medical physics.

[48]  E. Weibel,et al.  American Thoracic Society Documents An Official Research Policy Statement of the American Thoracic Society/European Respiratory Society: Standards for Quantitative Assessment of Lung Structure , 2010 .

[49]  Cynthia B Paschal,et al.  MRI simulator with object-specific field map calculations. , 2004, Magnetic resonance imaging.

[50]  Merryn H. Tawhai,et al.  Multiscale Modeling for the Lung Physiome , 2004 .

[51]  J. Solomon,et al.  Characteristic image quality of a third generation dual-source MDCT scanner: Noise, resolution, and detectability. , 2015, Medical physics.

[52]  Nooshin Kiarashi,et al.  Finite-element modeling of compression and gravity on a population of breast phantoms for multimodality imaging simulation. , 2016, Medical physics.

[53]  Yunlong Huo,et al.  Intraspecific scaling laws of vascular trees , 2012, Journal of The Royal Society Interface.

[54]  W. Segars,et al.  4D XCAT phantom for multimodality imaging research. , 2010, Medical physics.

[55]  Katsuyuki Taguchi,et al.  XCAT/DRASIM: a realistic CT/human-model simulation package , 2011, Medical Imaging.

[56]  P. J. Hunter,et al.  Generation of an Anatomically Based Three-Dimensional Model of the Conducting Airways , 2000, Annals of Biomedical Engineering.

[57]  K. Burrowes,et al.  Towards a virtual lung: multi-scale, multi-physics modelling of the pulmonary system , 2008, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.