• GDCM > 2
  • Please refer to GDCM v2 installation guide
  • You can also install GDCM v3 using package manager
• CUDA

• The code has been tested with GDCM v2 and CUDA v10.2 on Ubuntu 20.04
• The code has been tested with GDCM v3 and CUDA v11.8 on Ubuntu 22.04

$ git clone https://github.com/mghro/moquimc.git

$ cd moquimc/tests/mc/phantom
$ cmake .
$ make

• You may need to modify the CUDA configuration on the CMakeList.txt
• The default is to use CUDA compute capability 7.5

$ python create_phantom.py # create water phantom
$ ./phantom_env --lxyz 100 100 350 --pxyz 0.0 0.0 -175 --nxyz 200 200 350 --spot_energy 200.0 0.0 --spot_position 0 0 0.5 --spot_size 30.0 30.0 --histories 100000 --phantom_path ./water_phantom.raw --output_prefix ./ --gpu_id 0 > ./log.out

• There have been large updates in moqui and we added new features
  • Statistical uncertainty based stopping criteria (Please refer to the example input parameter Statistical stopping criteria)
  • Robust options (setup errors and density scaling, Please refer to the example input parameter Robust options)
  • Aperture handling
  • Support multiple calibration curves (You can override machine selection and define multiple calibration curves for a machine)
  • Unit weights per spot for Dij calculation (This only works for Dij scorer. The UnitWeight will be the absolute number of particles simulated)

• moqui uses fitted functions for calibration curves
• You need to obtain stopping power ratio to water and radiation length per density and define compute_rsp_ and compute_rl_ functions in patient_material_t
• To obtain the curves:
  1. Obtain material information using TOPAS
  2. Calculate correction factors for desired SPR curve
  3. Calculate fitting curves and implement them in moqui
  4. You can refer to the fit_rsp.py for the curve fitting
• You can find the TOPAS extensions and example parameter file under treatment_machines/TOPAS
• These are updated version of the HU extension in TOPAS (https://github.com/topasmc/extensions/tree/master/HU)

Hoyeon Lee ([email protected])
Jungwook Shin
Joost M. Verburg
Mislav Bobić
Brian Winey
Jan Schuemann
Harald Paganetti

This work is supported by NIH/NCI R01 234210 "Fast Individualized Delivery Adaptation in Proton Therapy"