MIROpt

Open tools

The source code of MIROpt is fully open and can be accessed and donwloaded from the OpenReggui platform.

Monte Carlo based treatment planning (using the fast MC dose engine MCsquare)
Robust (worst-case) optimization (using libraries from the large-scale non linear optimizer IPOPT)
Robustness against setup (systematic and random) and range errors
4D robust optimization
Versatile design through MATLAB interface

Workflow integration with OpenReggui

The plugin developed in OpenReggui offers a graphical interface and a very user-friendly environment for MIROpt.

MIROpt has been used in different research projects that lead to several conference communication and journal articles:

Performance of a hybrid Monte Carlo-Pencil Beam dose algorithm for proton therapy inverse planning, Barragan Montero A. M., Souris K., Sanchez-Parcerisa D., Sterpin E., and Lee J. A., Med Phys 2017, doi: 10.1002/mp.12688
Patient-specific bolus for range shifter air gap reduction in intensity-modulated proton therapy of head-and-neck cancer studied with Monte Carlo based plan optimization, Michiels S., Barragan A. M., Souris K., Poels K., Crijns W., Lee J. A., Sterpin E., Nuyts S., Haustermans K., and Depuydt T., Radiother Oncol. 2017 doi: 10.1016/j.radonc.2017.09.006
EP-1643: Simulate baseline shift uncertainties to improve robustness of proton therapy treatments, Souris K., Barragan A., Di Perri D., Geets X., Sterpin E., and Lee J. A., and Sterpin E., ESTRO 2017 doi: 10.1016/S0167-8140(17)32078-9
SU-H3-GePD-T-2: Simulation of Motion Amplitude Variations to Verify the Robustness of Treatment Plans, Souris K., Barragan Montero A., Janssens G., Di Perri D., Sterpin E., and Lee J. A., and Sterpin E., AAPM 2017 SU-H3-GePD-T-2
OC-0265: Efficient implementation of random errors in robust optimization for proton therapy with Monte Carlo, Barragan Montero A. M., Souris K., Sterpin E., and Lee J. A., ESTRO 2016 doi: 10.1016/S0167-8140(16)31514-6
WE-AB-209-01: A Monte Carlo-Based Method to Include Random Errors in Robust Optimization, Barragan Montero A. M., Souris K., Lee J. A., and Sterpin E., AAPM 2016 doi: 10.1118/1.4957770