TY - JOUR
T1 - A segmentation framework towards automatic generation of boost subvolumes for FDG-PET tumors
T2 - A digital phantom study
AU - Yang, Fei
AU - Grigsby, Perry W.
N1 - Funding Information:
The authors would like to thank Dr. Michalis Aristophanous for his assistance on PET image simulations. This work was supported in part by the National Cancer Institute Grant R01 CA136931 .
PY - 2012/12
Y1 - 2012/12
N2 - Potential benefits of administering nonuniform radiation dose to heterogeneous tumors imaged with FDG-PET have been widely demonstrated; whereas the number of discrete dose levels to be utilized and corresponding locations for prescription inside tumors vary significantly with current existing methods. In this paper, an automated and unsupervised segmentation framework constituted mainly by an image restoration mechanism based on variational decomposition and a voxel clustering scheme based on spectral clustering was presented towards partitioning FDG-PET imaged tumors into subvolumes characterized with the total intra-subvolume activity similarity and the total inter-subvolume activity dissimilarity being simultaneously maximized. Experiments to evaluate the proposed system were carried out with using FDG-PET data generated from a digital phantom that employed SimSET (Simulation System for Emission Tomography) to simulate PET acquisition of tumors. The obtained results show the feasibility of the proposed system in dividing FDG-PET imaged tumor volumes into subvolumes with intratumoral heterogeneity being properly characterized, irrespective of variation in tumor morphology as well as diversity in intratumoral heterogeneity pattern.
AB - Potential benefits of administering nonuniform radiation dose to heterogeneous tumors imaged with FDG-PET have been widely demonstrated; whereas the number of discrete dose levels to be utilized and corresponding locations for prescription inside tumors vary significantly with current existing methods. In this paper, an automated and unsupervised segmentation framework constituted mainly by an image restoration mechanism based on variational decomposition and a voxel clustering scheme based on spectral clustering was presented towards partitioning FDG-PET imaged tumors into subvolumes characterized with the total intra-subvolume activity similarity and the total inter-subvolume activity dissimilarity being simultaneously maximized. Experiments to evaluate the proposed system were carried out with using FDG-PET data generated from a digital phantom that employed SimSET (Simulation System for Emission Tomography) to simulate PET acquisition of tumors. The obtained results show the feasibility of the proposed system in dividing FDG-PET imaged tumor volumes into subvolumes with intratumoral heterogeneity being properly characterized, irrespective of variation in tumor morphology as well as diversity in intratumoral heterogeneity pattern.
KW - FDG-PET
KW - Intratumoral heterogeneity
KW - Spectral clustering
KW - Variational decomposition
UR - http://www.scopus.com/inward/record.url?scp=84869861879&partnerID=8YFLogxK
U2 - 10.1016/j.ejrad.2012.03.031
DO - 10.1016/j.ejrad.2012.03.031
M3 - Article
C2 - 22840849
AN - SCOPUS:84869861879
SN - 0720-048X
VL - 81
SP - 4123
EP - 4130
JO - European Journal of Radiology
JF - European Journal of Radiology
IS - 12
ER -