@inproceedings{nokey,
title = {A Radiation detector simulation toolkit for calculating the Arterial Input Function during Dynamic Positron Emission Tomography},
author = {Youstina Daoud and Liam Carroll and Shirin A. Enger},
year = {2022},
date = {2022-04-10},
booktitle = {International Conference on Monte Carlo Techniques for Medical Applications},
abstract = {"Introduction
Dynamic Positron Emission Tomography (dPET) is a functional imaging modality that provides an accurate assessment of patients’ physiological activities and response to treatments such as cancer, cardiac diseases and Alzheimer’s disease. It requires the measurement of the time-course activity concentration of the positron emitting PET radioisotopes in the patient’s arterial plasma, called the Arterial Input Function (AIF). The gold standard measurement of the AIF requires blood samples from the patient during the dPET. In our group, we are developing a non-invasive radiation detector that, placed on a patient’s wrist during the dPET scan, measures the number of positrons and photons escaping the radial artery and calculates the AIF. We have also developed a Modular Radiation Simulation Software for detector simulations called MaRSS that allows the user to run a Geant4-based Monte Carlo simulation, to calculate the AIF. Using the Monte Carlo method, MaRSS simulates a radioactive source decay in the radial artery and scores the amount of radiation escaping the radial artery and reaching the detector placed on the simulated patient’s wrist phantom. The wrist phantom is designed as a cylinder containing 2 holes that simulates the radial artery and vein. The shape and the depth of the radial artery vary between patients and proper knowledge of the distance between the radial artery and the skin, as well as its surface area, is important to accurately design the wrist phantom. Therefore, our aim was to develop a graphical user interface (GUI) allowing the user to import 2D ultrasound scans of a patient’s wrist, provide tools to measure the distance between the radial artery and the skin as well as the radial artery’s surface area and to create the necessary input file to MaRSS. The GUI provides MaRSS with a patient specific and more accurate wrist phantom, providing a patient-specific and more accurate calculation of the AIF without knowledge of C++ or Geant4.
Materials & Methods
The GUI elements were implemented using the multi-platform application and widget toolkit Qt 5 [1]. The C++ library, VTK 8.2.0 [2] was integrated in the GUI, which enables the user to import and manipulate the 2D ultrasound images. The toolkit comprises a measurement tool, a visualization window, a detector tab, a radiation source tab and MaRSS which is its simulation tool. To create an accurate wrist phantom, three 2D – cross secctional ultrasound scans of the patient’s wrist at 2 cm, 4 cm and 6 cm from the wrist crease and 1 longitudinal scan along the radial artery may be acquired and saved in DICOM format. In our case the BK3000 ultrasound system is used. These scans are imported into the GUI by selecting the folder that contains the images. Using the measurement functionalities shown in the top left corner of Figure 1, the surface of the radial artery is measured by drawing an ellipse on the artery’s boundary, then the toolkit measures the surface of the drawn ellipse and displays it in the Measurement window. The artery’s depth is also measured and displayed by drawing a straight line between the artery’s boundary and the skin. Using the left and right arrows, the user can navigate through the selected folder and measure the artery’s surface and depth on the other scans. The top right corner of the GUI shown in Figure 1, illustrates a Detector tab and a Source tab. The Detector tab allows the user to import a detector in STL format and place it on the ultrasound scan to simulate different setups of the detector, this functionality is still under development and
International Conference on Monte Carlo Techniques for Medical Applications, 2022
is optional. The Source tab allows the user to add the radioactive source used during the dPET by entering its mass number and its atomic number. After completing the 3 mandatory steps : import of the scan, measurement of different parameters extracted from the scan and choice of the radioactive source, the user can run the simulation by clicking on Run Simulation in the Simulation menu. The toolkit runs the MaRSS and creates the wrist phantom using the artery’s surface and depth measured by the user, then starts the decay of the chosen source placed randomly inside the artery.
Results
This toolkit allows the user to import 2D ultrasound scans and measure the radial artery’s surface and depth along the wrist, choose the radioactive source from the Source drop-down menu and specify the detector position. An input file to the MaRSS is thus created providing the required information to simulate the wrist phantom, the source and the detector’s position in MaRSS. The Run Simulation tab displays the output of the simulation in the GUI making it the only used tool for setting up the simulation and viewing the results.
Discussion & Conclusions
This toolkit enables the user to run a Geant4 Monte Carlo based simulation for detector development applications in 3 easy steps, not requiring any programming knowledge.
References
[1] Blanchette J, Summerfield M. C++ GUI programming with Qt 4: Prentice Hall Professional; 2006.
[2] Schroeder WJ, Avila LS, Hoffman W. Visualizing with VTK: a tutorial. IEEE Computer graphics and applications. 2000;20(5):20-7.
Acknowledgements This research was undertaken,in part, thanks to funding from the Canada Research Chairs Program (grant # 252135) as well as CHRP (NSERC+CIHR grant 170620).
"},
keywords = {},
pubstate = {published},
tppubtype = {inproceedings}
}
