KAHIBARO
27.5. Adding a PET Source
Table of Contents
Point source
In a PET scanner simulation you usually start source modeling with the simplest possible case: a small activity concentrated in one position. In GATE this is called a point source, even though numerically it has a small finite size. For building and testing a PET scanner geometry, a point source on the axis of the scanner is very useful, because it gives clean, symmetric data that clearly show whether your ring and digitizer work as expected.
In the PET context this point source almost always represents a positron emitting radionuclide, typically F‑18. You already configure the particle type and decay physics in other parts of your simulation, so here the focus is on placing and shaping the source in space.
Within a PET ring you usually place the point source at the center of the scanner, that is at the origin of the world coordinate system, or slightly shifted to investigate spatial response. In an OpenGATE style Python script, you define the spatial distribution of the source as a very small sphere or box. The radius or half size should be small compared with the detector spacing and crystal dimensions, so that you can treat it as a single point when interpreting results, but not so tiny that you run into numerical precision issues. A practical radius of a few millimeters is typically sufficient for PET performance checks.
The position of the point source is usually specified directly in world coordinates, for example $(0, 0, 0)$ for the center, or $(x_0, y_0, z_0)$ to move it off axis. In a cylindrical PET ring, moving the point radially or axially lets you study spatial dependence of sensitivity and resolution. Keep in mind that any translations of the scanner geometry relative to the world will change the apparent relationship between the point source and the crystals, so it is good practice to define the scanner symmetrically around the origin if you plan to use central point sources.
Activity and time configuration are shared with other source types, but for a point source they have a simple interpretation. The total activity is concentrated in one small region, so the local count rate can be high. This makes the point source useful for quick simulations with many coincidences in a small number of events. When you compare PET performance metrics such as radial blurring or energy spectra, a central point source is often your first test case before moving to more realistic, extended sources.
In a PET simulation framework like GATE, the same radioactive source definition that you use for a more complex activity distribution can also be used for the point source. The PET specific difference is mostly geometric: the number of detection angles and LORs generated by a central point is small compared with a large phantom. This simplicity helps you to debug detector IDs, coincidence sorting, and energy windows for the PET scanner you built in the previous sections.
For PET performance checks, keep the point source small compared to detector spacing, place it at a well defined position, usually the scanner center, and use it to validate that hits, singles, coincidences, and detector IDs behave as expected before moving to complex phantoms.
Phantom source
Once a PET scanner has been checked with a point source, you typically switch to a phantom source to approximate clinical or experimental situations. A phantom source means that activity is distributed over a finite volume instead of being concentrated at a single point. In PET work this often corresponds to an anthropomorphic phantom, a uniform cylinder, or a region with “hot” and “cold” areas.
In GATE you represent a phantom geometrically, for example as a cylinder or a more complex volume created earlier in your geometry chapter, and then you define the source so that the spatial distribution of positron emitters follows the shape and composition of that phantom. For a simple uniform cylinder phantom, you choose the same dimensions as the physical phantom and set the spatial distribution type so that positron emission is uniform inside that volume. This lets you study scanner sensitivity, uniformity, and effects like attenuation and scatter in a way that is much closer to realistic PET imaging.
For PET in particular, phantom sources are essential when you want to simulate standard test setups, such as a uniform cylinder or a phantom with line or sphere inserts. In a GATE script, you typically attach the activity distribution to an existing volume that is already defined as a phantom in your geometry, rather than creating a separate geometric volume just for the source. The same radionuclide configuration as for the point source, for example F‑18 with a positron emission spectrum, is used, but now the positions of the decays are sampled across the phantom volume.
The shape of the phantom source strongly influences the resulting coincidence data. A large uniform cylinder will generate coincidences across many lines of response, producing sinograms that resemble clinical PET data. Hot spheres embedded in a lower activity background allow you to study contrast recovery, partial volume effects, and the impact of reconstruction algorithms that you might apply later outside GATE. Because the phantom extends over the whole field of view, scatter and attenuation become important, and therefore the physics list and material definitions you selected earlier become more critical than in the simple point source case.
From a configuration point of view, the phantom source needs a correct mapping between physical geometry and activity distribution. For simple uniform activity, this is straightforward: all points in the phantom volume have the same probability of containing a decay. For more realistic PET simulations you can later replace this uniform distribution by an image based activity map, but that belongs to separate chapters on voxelized geometry and internal dosimetry. In the context of building a PET scanner, it is enough to understand that a phantom source means sampling decay positions inside an extended volume that matches a phantom geometry.
The acquisition settings for a phantom source are usually different from those for a point source. Because the activity is spread out, you may need a higher total number of decays or longer simulated acquisition time to obtain adequate statistics per voxel or per region of interest. At the same time, global count rates per detector may be similar to or lower than those with a compact point source, which can help you explore realistic dead time and random coincidence conditions if you add those effects later.
In practical PET scanner development, you often use a sequence of sources: a central point source to validate geometry and timing, then a uniform phantom source to check sensitivity and uniformity, and finally more complex phantoms or patient like activity distributions. For this chapter, the important distinction is geometric: a point source samples one localized position, while a phantom source samples positions across an extended object that you already created in the scanner geometry. Both sources rely on the same PET specific radionuclides and physics configuration that are set elsewhere in your simulation.
A PET phantom source distributes positron emitting activity throughout a phantom volume, typically matching an existing geometric object, and is essential to test scanner performance, sensitivity, and image quality under realistic attenuation and scatter conditions.
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