Tesi di laurea

Crystal-assisted beam extraction for Hadrontherapy synchrotrons

ABSTRACT

Bent crystals are currently used for beam manipulation in synchrotrons for high-energy physics - e.g. for slow beam extraction at the U-70 accelerator at IHEP (Protvino, Russia) or for beam shadowing at the SPS accelerator at CERN (Switzerland) or for beam collimation at the LHC at CERN. In fact, if properly aligned, bent crystals are capable of bending beams by angles currently unreachable by any magnet techology presently available.
Bent crystals can represent a valuable way to extract treatment beams from hadrontherapy synchrotrons, alternative to schemes used by machines currently in operation, since they allow to relax strong contraints on machine optics. In order to propose a crystal-assisted extraction scheme, the performance of bent crystals should be assessed: to date, no data is available in literature. The CREMA collaboration has been set up by INFN in order to overcome the lack of information.

The aim of the activity is to characterise the measurement set up presently available at CNAO for assessing the performance of bent crystals at beam energies of interest for hadrontherapy. The activity will mainly consist of Monte Carlo simulations, to be carried out with the FLUKA code. The activity will be complemented by proposing a possible crystal-assisted extraction scheme for hadrontherapy synchrotrons like that of CNAO.
The activity will be carried out in the framework of the CREMA collaboration.

FURTHER INFO

Expected duration of activity (including thesis write-up): 12 months
Preferred technical skills: knowledge of programming (one among python, MatLab, C/C++, Fortran, etc...)
Most suited curriculum studiorum of the candidate: physics, nuclear engineering
Required soft skills: attitude to problem solving, will to take initiative, eagerness to learn, openness to discussions
References: alessio.mereghetti@cnao.it, marco.pullia@cnao.it

 

HeCheck: Range verification with mixed beams

ABSTRACT

Hadrontherapy exploits the Bragg peak to improve the precision of the dose administration to the patient.
The improved precision of the dose delivery requires that the target (patient) is also "precisely the same" day after day along the therapy course. Since therapy lasts typically a few weeks, means to detect patient variations can be a great help in revealing when a replanning is needed.
He and C ions have a very similar mass over charge ratio and could be accelerated simultaneously in the accelerator. While C is used for the treatment, a small amount of additional He ions (the range of which is 3 times larger than that of C ions) can be used to monitor the repeatability of the patient.
At CNAO a detector is being developed, based on a cubic scintillator and a camera for acquiring the emitted light, to monitor the residual range of the He ions exiting the patient. The proposed thesis work is to develop the software for image analysis and comparison to reveal target variations. Simple targets will be irradiated and known variations will be created to test the algorithms to quantify the integrated stopping power.
 
FURTHER INFO

Expected duration of activity (including thesis write-up): 12 months
Preferred technical skills: basic geometric optics, knowledge of programming, image processing
Most suited curriculum studiorum of the candidate: physics, nuclear engineering
Required soft skills: attitude to problem solving, will to take initiative, eagerness to learn, openness to discussions
References: marco.pullia@cnao.it

 

Characterisation of low-intensity beams in the CNAO Experimental Room

ABSTRACT

The National Center for Oncological Hadrontherapy (CNAO, Pavia) is equipped with an experimental room (XPR) where research activities involving the use of CNAO beams can be carried out without hindering the clinical activity. Irradiations in the XPR can take place not only with the same hadrontherapy beams as those clinically available, but also with beams of much lower intensity. Similarly to the treatment beam lines, the XPR beam line terminates with the monitors of the dose delivery system (DDS), responsible for giving feedback on beam position and intensity. In the case of low intensity beams, the DDS monitors presently installed are blind, because the recorded signals are too low; hence, beam setting up for research activities with low intensity beams is always carried out based on the feedback given by the installed experimental setup.
CNAO has recently developed a low-intensity beam monitor, in order to no longer be blind with the delivery of low-intensity beams. The aim of the activity is hence to use the new monitor for characterising the low-intensity beams in the XPR, optimising and standardising hardware knobs.

FURTHER INFO

Expected duration of activity (including thesis write-up): 12 months
Preferred technical skills: knowledge of programming (one among python, MatLab, C/C++, Fortran, etc...)
Most suited curriculum studiorum of the candidate: physics, nuclear engineering
Required soft skills: attitude to problem solving, will to take initiative, eagerness to learn, openness to discussions
References: alessio.mereghetti@cnao.it, marco.pullia@cnao.it

 

Scattering footprint on beam optics measurements in air

ABSTRACT

Measurements are regularly carried out at CNAO to verify the quality of the accelerated beams. Even though beam profiles acquired at the isocentre (i.e. the reference point where patients are positioned for treatment) allow to verify the suitability of accelerated beams to treatments, they cannot be used to reconstruct the beam phase space and the machine optics correctly. In fact, beam profiles are acquired downstream of the vacuum window and of the monitors of the dose delivery system; therefore, measurements are affected by Multiple Coulomb Scattering (MCS), making their use for beam optics or phase space reconstruction not straightforward.

The aim of the activity is to develop a method to subtract the contribution of MCS from measured beam profiles and hence obtain in-vacuum equivalent profiles, hence allowing to use them for reconstructing the beam phase space and the machine optics. The MCS contribution will be characterised by means of the Monte Carlo simulations using the FLUKA code, and its removal by means of numerical methods. Among the considered numerical methods, deep learning is a promising one; for applying it, a collaboration with the University of Torino is being set up.

FURTHER INFO

Expected duration of activity (including thesis write-up): 12 months
Preferred technical skills: knowledge of programming (one among python, MatLab, C/C++, Fortran, etc...)
Most suited curriculum studiorum of the candidate: physics, nuclear engineering
Required soft skills: attitude to problem solving, will to take initiative, eagerness to learn, openness to discussions
References: alessio.mereghetti@cnao.it, marco.pullia@cnao.it

 

Scattering footprint on beam phase space introduced by the PEPITEs monitor in CNAO accelerator beam lines

ABSTRACT

The PEPITEs monitor is a beam profile monitor developed by IN2P3 to measure in-vacuum beam profiles. It is characterised by a very low material budget, minimising the beam Multiple Coulomb Scattering (MCS) and allowing the deployment of the monitor in beam lines for hadrontherapy, like those of CNAO.

The aim of the activity is to characterise the beam MCS due to the PEPITEs monitor and the distortion thus introduced on the beam phase space at various positions along the CNAO accelerator beam lines. The activity will be carried out by means of the Monte Carlo simulations using the FLUKA code.

FURTHER INFO

Expected duration of activity (including thesis write-up): 12 months
Preferred technical skills: knowledge of programming (one among python, MatLab, C/C++, Fortran, etc...)
Most suited curriculum studiorum of the candidate: physics, nuclear engineering
Required soft skills: attitude to problem solving, will to take initiative, eagerness to learn, openness to discussions
References: alessio.mereghetti@cnao.it, marco.pullia@cnao.it

 

Magnetic design of a novel scanning magnet for hadron therapy

ABSTRACT

The European Superconducting Ion Gantry (EuroSIG) project, a collaborative effort between CNAO, CERN, INFN, and MedAustron, is dedicated to the design and construction of a novel gantry for hadron therapy. A key component of this project is the downstream scanning system, which incorporates the innovative Rake magnet concept, recently patented by CNAO.
While a baseline design of a first Rake demonstrator is now under construction at CERN, several features of this new concept could be further explored and optimized.
In this thesis, the student will learn the basics of accelerator magnet design and how to use FEM electromagnetic software (e.g. OPERA) to perform simulations. He/she will use Python codes to optimize the magnet and explore novel and exotic configurations. Finally, it is asked to provide support during the prototyping phase.
We are looking for a fresh, curious, and motivated mind to explore the boundaries and push the limits of the Rake concept!

FURTHER INFO

Expected duration of activity (including thesis write-up): 9-12 months;
Preferred technical skills: basic knowledge of coding (Python and/or Matlab), fundamentals of electromagnetism, particle accelerators, and electrical machines;
References: enrico.felcini@cnao.it, marco.pullia@cnao.it

 

Master's Thesis Proposal
Simulation and Benchmarking of Multicellular Tumor Spheroid Growth with Extensions to Model Ionizing Radiation Effects

INTRODUCTION

The modeling of 3D multicellular tumor spheroids (MCTS) is increasingly important as it better represents real cell-cell interactions compared to traditional 2D models. This thesis proposes to replicate and modernize an existing agent-based Monte Carlo model for MCTS growth, initially implemented with FORTRAN [1, 2], using Python and modern programming practices. Following this, the model will be extended to include the effects of ionizing radiation. Collaboration with CNAO and supervision by a medical physicist with coding expertise will be integral to the project.

OBJECTIVES

1.    Replication and Renewal: Recreate the FORTRAN-based model using Python, focusing on modularity, maintainability, and documentation.
2.    Benchmarking: Validate the renewed model by comparing it with published data and replicating the original results.
3.    Model Extension: Extend the model to incorporate the effects of different types of ionizing radiation, including photons, protons, and carbon ions.
4.    Analysis: Evaluate how various radiation types influence tumor growth and assess the robustness of the extended model.

METHODOLOGY

•    Model Replication: Implement the existing model using modern programming practices, ensuring the code is modular and maintainable. This process will involve learning new coding techniques and adapting to contemporary programming standards.
•    Collaboration: Integrate experimental data from CNAO to benchmark and validate the model, working closely with the radiobiological unit.
•    Extension for Radiation Effects: Modify the model to simulate the impact of photon, proton, and carbon ion irradiation on tumor growth.
•    Simulation and Analysis: Conduct simulations to assess the effects of different radiation types and perform sensitivity analyses to refine the model.

LEARNING CURVE

Building the code from scratch will involve a significant learning curve for both the student and the supervisor. The student will gain experience in modern coding practices and model development, while the supervisor will provide guidance to navigate this learning process. Emphasis will be placed on best practices in coding, including modular design and thorough documentation, to ensure a robust and maintainable model.

TIMELINE (APPROX. 1 YEAR)

Literature review - 1 month
Model replication and renewal - 3-5 months
Benchmarking and validation - 2 months
Model extension for radiation effects (*) - 3 months
Simulation and data analysis (*) - 1-2 months
(* )additional goals that will be pursued if time permits.

CONCLUSION

This thesis will modernize an important 3D tumor growth model and extend it to include radiation effects, providing new insights into cancer treatment optimization. The project will involve close collaboration with CNAO and supervision from a Medical Physicist with expertise in Python, offering valuable learning opportunities for the student in coding and model development.

REQUIREMENTS

Knowledge of a programming language is required (knowledge of Python is a plus).

REFERENCES

1.    Ruiz-Arrebola, S. "An on-lattice agent-based Monte Carlo model simulating the growth kinetics of multicellular tumor spheroids." Journal of Computational Physics, 2017. DOI: 10.1016/j.jcp.2017.07.036.
2.    Ruiz-Arrebola, S., Álvarez-Sánchez, J., & García-Sánchez, F. "Evaluation of Classical Mathematical Models of Tumor Growth Using an On-Lattice Agent-Based Monte Carlo Model." Journal of Computational Physics, 2020. DOI: 10.1016/j.jcp.2020.109035.

CONTACTS: matteo.bagnalasta@cnao.it giuseppe.magro@cnao.it fisicimedici@cnao.it