Statistical construction of a Japanese male liver phantom for internal radionuclide dosimetry.

A computational framework is presented, based on statistical shape modelling, for construction of race-specific organ models for internal radionuclide dosimetry and other nuclear-medicine applications. This approach was applied to the construction of a Japanese liver phantom, using the liver of the digital Zubal phantom as the template and 35 liver computed tomography (CT) scans of male Japanese individuals as a training set. The first step was the automated object-space registration (to align all the liver surfaces in one orientation), using a coherent-point-drift maximum-likelihood alignment algorithm, of each CT scan-derived manually contoured liver surface and the template Zubal liver phantom. Six landmark points, corresponding to the intersection of the contours of the maximum-area sagittal, transaxial and coronal liver sections were employed to perform the above task. To find correspondence points in livers (i.e. 2000 points for each liver), each liver surface was transformed into a mesh, was mapped for the parameter space of a sphere (parameterisation), yielding spherical harmonics (SPHARMs) shape descriptors. The resulting spherical transforms were then registered by minimising the root-mean-square distance among the SPHARMs coefficients. A mean shape (i.e. liver) and its dispersion (i.e. covariance matrix) were next calculated and analysed by principal components. Leave-one-out-tests using 5-35 principal components (or modes) demonstrated the fidelity of the foregoing statistical analysis. Finally, a voxelisation algorithm and a point-based registration is utilised to convert the SPHARM surfaces into its corresponding voxelised and adjusted the Zubal phantom data, respectively. The proposed technique used to create the race-specific statistical phantom maintains anatomic realism and provides the statistical parameters for application to radionuclide dosimetry.

[1]  W. S. Snyder,et al.  Estimates of absorbed fractions for monoenergetic photon sources uniformly distributed in various organs of a heterogeneous phantom. , 1974, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[2]  N Petoussi-Henss,et al.  ADULT FEMALE VOXEL MODELS OF DIFFERENT STATURE AND PHOTON CONVERSION COEFFICIENTS FOR RADIATION PROTECTION , 2004, Health physics.

[3]  K. F. Eckerman,et al.  Specific absorbed fractions of energy at various ages from internal photon sources: 6, Newborn , 1987 .

[4]  Guido Gerig,et al.  Parametrization of Closed Surfaces for 3-D Shape Description , 1995, Comput. Vis. Image Underst..

[5]  P. Dimbylow,et al.  Fine resolution calculations of SAR in the human body for frequencies up to 3 GHz. , 2002, Physics in medicine and biology.

[6]  Miguel Á. Carreira-Perpiñán,et al.  Non-rigid point set registration: Coherent Point Drift , 2006, NIPS.

[7]  M Zankl,et al.  Construction of a computed tomographic phantom for a Japanese male adult and dose calculation system , 2001, Radiation and environmental biophysics.

[8]  P B Hoffer,et al.  Computerized three-dimensional segmented human anatomy. , 1994, Medical physics.

[9]  Yen-Wei Chen,et al.  Evaluation of Liver Shape Approximation and Characterization , 2009, 2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing.

[10]  Daniel Lodwick,et al.  NURBS-based 3-D anthropomorphic computational phantoms for radiation dosimetry applications. , 2007, Radiation protection dosimetry.

[11]  S. Koga,et al.  Japanese adult male voxel phantom constructed on the basis of CT images. , 2007, Radiation protection dosimetry.

[12]  N Petoussi-Henss,et al.  Organ dose conversion coefficients for external photon irradiation of male and female voxel models , 2002, Physics in medicine and biology.

[13]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[14]  Deanna Hasenauer,et al.  Hybrid computational phantoms of the male and female newborn patient: NURBS-based whole-body models , 2007, Physics in medicine and biology.

[15]  M. Wernick,et al.  Emission Tomography: The Fundamentals of PET and SPECT , 2004 .

[16]  Martin Caon,et al.  Voxel-based computational models of real human anatomy: a review , 2004, Radiation and Environmental Biophysics.

[17]  Reza Aghaeizadeh Zoroofi,et al.  Volumetric Non-rigid Registration via Thin-plate Spline Model , 2008 .

[18]  D. G. Jones A Realistic Anthropomorphic Phantom for Calculating Organ Doses Arising from External Photon Irradiation , 1997 .

[19]  Daniel P. Huttenlocher,et al.  Computing the minimum Hausdorff distance for point sets under translation , 1990, SCG '90.

[20]  Paolo Cignoni,et al.  A comparison of mesh simplification algorithms , 1998, Comput. Graph..

[21]  Martin Styner,et al.  Statistical shape analysis of neuroanatomical structures based on medial models , 2003, Medical Image Anal..

[22]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  J. K. Lee,et al.  Development of a Korean adult male computational phantom for internal dosimetry calculation. , 2006, Radiation protection dosimetry.

[24]  M. McPeek,et al.  Modeling Three-Dimensional Morphological Structures Using Spherical Harmonics , 2009, Evolution; international journal of organic evolution.

[25]  M G Stabin,et al.  Monte Carlo MCNP-4B-based absorbed dose distribution estimates for patient-specific dosimetry. , 2001, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[26]  Anand Rangarajan,et al.  A new point matching algorithm for non-rigid registration , 2003, Comput. Vis. Image Underst..