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.
Mofrad
Farshid Babapour
FB
Faculty of Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran. farshid.mofrad@yahoo.com
Zoroofi
Reza Aghaeizadeh
RA
Tehrani-Fard
Ali Abbaspour
AA
Akhlaghpoor
Shahram
S
Hori
Masatoshi
M
Chen
Yen-Wei
YW
Sato
Yoshinobu
Y
D000368:Aged; D000465:Algorithms; D044466:Asian People; D006801:Humans; D008099:Liver / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D008953:Models, Anatomic; D015233:Models, Statistical; D019047:Phantoms, Imaging; D011874:Radiometry; D011877:Radionuclide Imaging; D014057:Tomography, X-Ray Computed