title: Performance evaluation of18F radioluminescence microscopy using computational simulation.
abstract: OBJECTIVE
  Radioluminescence microscopy can visualize the distribution of beta-emitting radiotracers in live single cells with high resolution. Here, we perform a computational simulation of18F positron imaging using this modality to better understand how radioluminescence signals are formed and to assist in optimizing the experimental setup and image processing.
  
  
  METHODS
  First, the transport of charged particles through the cell and scintillator and the resulting scintillation is modeled using the GEANT4 Monte-Carlo simulation. Then, the propagation of the scintillation light through the microscope is modeled by a convolution with a depth-dependent point-spread function, which models the microscope response. Finally, the physical measurement of the scintillation light using an electron-multiplying charge-coupled device (EMCCD) camera is modeled using a stochastic numerical photosensor model, which accounts for various sources of noise. The simulated output of the EMCCD camera is further processed using our ORBIT image reconstruction methodology to evaluate the endpoint images.
  
  
  RESULTS
  The EMCCD camera model was validated against experimentally acquired images and the simulated noise, as measured by the standard deviation of a blank image, was found to be accurate within 2% of the actual detection. Furthermore, point source simulations found that a reconstructed spatial resolution of 18.5 μm can be achieved near the scintillator. As the source is moved away from the scintillator, spatial resolution degrades at a rate of 3.5 μm per μm distance. These results agree well with the experimentally measured spatial resolution of 30-40 μm (live cells). The simulation also shows that the system sensitivity is 26.5%, which is also consistent with our previous experiments. Finally, an image of a simulated sparse set of single cells is visually similar to the measured cell image.
  
  
  CONCLUSIONS
  Our simulation methodology agrees with experimental measurements taken with radioluminescence microscopy. This in silico approach can be used to guide further instrumentation developments and to provide a framework for improving image reconstruction.
authors.affiliation: Department of Radiation Oncology, Stanford University, Stanford, CA, 94304, USA.
authors.forename: Qian
authors.initials: Q
authors.lastname: Wang
authors.affiliation: Department of Radiation Oncology, Stanford University, Stanford, CA, 94304, USA.
authors.forename: Debanti
authors.initials: D
authors.lastname: Sengupta
authors.affiliation: Department of Radiation Oncology, Stanford University, Stanford, CA, 94304, USA.
authors.forename: Tae Jin
authors.initials: TJ
authors.lastname: Kim
authors.affiliation: Department of Radiation Oncology, Stanford University, Stanford, CA, 94304, USA.
authors.forename: Guillem
authors.initials: G
authors.lastname: Pratx
mesh_terms: D003198:Computer Simulation; D004583:Electrons; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008853:Microscopy; D009010:Monte Carlo Method
keywords: computational simulation; imager performance evaluation; positron imaging; radioluminescence microscopy