title: Investigation of realistic PET simulations incorporating tumor patient's specificity using anthropomorphic models: creation of an oncology database.
abstract: OBJECTIVE
  The GATE Monte Carlo simulation toolkit is used for the implementation of realistic PET simulations incorporating tumor heterogeneous activity distributions. The reconstructed patient images include noise from the acquisition process, imaging system's performance restrictions and have limited spatial resolution. For those reasons, the measured intensity cannot be simply introduced in GATE simulations, to reproduce clinical data. Investigation of the heterogeneity distribution within tumors applying partial volume correction (PVC) algorithms was assessed. The purpose of the present study was to create a simulated oncology database based on clinical data with realistic intratumor uptake heterogeneity properties.
  
  
  METHODS
  PET/CT data of seven oncology patients were used in order to create a realistic tumor database investigating the heterogeneity activity distribution of the simulated tumors. The anthropomorphic models (NURBS based cardiac torso and Zubal phantoms) were adapted to the CT data of each patient, and the activity distribution was extracted from the respective PET data. The patient-specific models were simulated with the Monte Carlo Geant4 application for tomography emission (GATE) in three different levels for each case: (a) using homogeneous activity within the tumor, (b) using heterogeneous activity distribution in every voxel within the tumor as it was extracted from the PET image, and (c) using heterogeneous activity distribution corresponding to the clinical image following PVC. The three different types of simulated data in each case were reconstructed with two iterations and filtered with a 3D Gaussian postfilter, in order to simulate the intratumor heterogeneous uptake. Heterogeneity in all generated images was quantified using textural feature derived parameters in 3D according to the ground truth of the simulation, and compared to clinical measurements. Finally, profiles were plotted in central slices of the tumors, across lines with heterogeneous activity distribution for visual assessment.
  
  
  RESULTS
  The accuracy of the simulated database was assessed against the original clinical images. The PVC simulated images matched the clinical ones best. Local, regional, and global features extracted from the PVC simulated images were closest to the clinical measurements, with the exception of the size zone variability and the mean intensity values, where heterogeneous tumors showed better reproducibility. The profiles on PVC simulated tumors after postfiltering seemed to represent the more realistic heterogeneous regions with respect to the clinical reference.
  
  
  CONCLUSIONS
  In this study, the authors investigated the input activity map heterogeneity in the GATE simulations of tumors with heterogeneous activity distribution. The most realistic heterogeneous tumors were obtained by inserting PVC activity distributions from the clinical image into the activity map of the simulation. Partial volume effect (PVE) can play a crucial role in the quantification of heterogeneity within tumors and have an important impact on applications such as patient follow-up during treatment and assessment of tumor response to therapy. The development of such a database incorporating patient anatomical and functional variability can be used to evaluate new image processing or analysis algorithms, while providing control of the ground truth, which is not available when dealing with clinical datasets. The database includes all images used and generated in this study, as well as the sinograms and the attenuation phantoms for further investigation. It is freely available to the interested reader of the journal at http://www.med.upatras.gr/oncobase/.
authors: Department of Medical Physics, School of Medicine, University of Patras, Rion, GR 265 04, Greece.
authors: Panagiotis
authors: P
authors: Papadimitroulas
authors: George
authors: G
authors: Loudos
authors: Amandine
authors: A
authors: Le Maitre
authors: Mathieu
authors: M
authors: Hatt
authors: Florent
authors: F
authors: Tixier
authors: Nikos
authors: N
authors: Efthimiou
authors: George C
authors: GC
authors: Nikiforidis
authors: Dimitris
authors: D
authors: Visvikis
authors: George C
authors: GC
authors: Kagadis
mesh_terms: D000465:Algorithms; D000886:Anthropometry; D003198:Computer Simulation; D016208:Databases, Factual; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008495:Medical Oncology / Q000592:standards*; D009010:Monte Carlo Method; D009369:Neoplasms / Q000175:diagnosis / Q000000981:diagnostic imaging*; D016011:Normal Distribution; D049268:Positron-Emission Tomography; D015203:Reproducibility of Results; D014018:Tissue Distribution; D014057:Tomography, X-Ray Computed