Study-Unit Description

Study-Unit Description


CODE MPH3005

 
TITLE Monte Carlo Methods for Medical Physics and Radiation Protection

 
LEVEL 03 - Years 2, 3, 4 in Modular Undergraduate Course

 
ECTS CREDITS 2

 
DEPARTMENT Medical Physics

 
DESCRIPTION Monte Carlo methods are today the gold standard for development of new techniques, optimization and research in Medical Physics and Radiation Protection particularly in the case of dose estimates. Most of the software used for dosimetry in Medical Physics and Radiation Protection (e.g., treatment planning systems, CT patient dose calculation software) is based on Monte Carlo mathematical and statistical techniques. This study-unit will present the principles of Monte Carlo methods as applied to radiation physics, Medical Physics and Radiation Protection. The unit includes hands-on simulations.

Study-unit Aims:

The aims of the study-unit are to:
- Familiarise students with the mathematical and statistical principles of Monte Carlo methods including probability density functions, random number generation, sampling rules and outcome scoring;
- Review how Monte Carlo techniques are used to simulate radiation transport;
- Introduce the GEANT4 Monte Carlo code;
- Illustrate how Monte Carlo techniques can be used to solve issues in Medical Physics and Radiation Protection;
- Provide opportunities to students for hands-on practice in the use of Monte Carlo techniques in Medical Physics and Radiation Protection.

Learning Outcomes:

1. Knowledge & Understanding
By the end of the study-unit the student will be able to:

- Understand the principles of Monte Carlo methods as applied to simulation of radiation transport in medical physics and radiation protection;
- Describe a physical system in terms of probability density functions;
- Explain the use of a random number generator; the need for a source of random numbers uniformly distributed on the unit interval;
- Explain the use of sampling rules as prescriptions for sampling from the specified parameter of interest;
- Explain the scoring of outcomes accumulated into overall tallies for the quantities of interest;
- Explain methods of statistical uncertainty in terms of variance as a function of the number of trials;
- Explain variance reduction techniques and the need to reduce simulation computational time;
- Explain parallelization and vectorization algorithms to allow Monte Carlo methods to be implemented efficiently on advanced computer architectures; and
- List the main Monte Carlo codes available which have been used for medical applications.

2. Skills
By the end of the study-unit the student will be able to:

- Demonstrate use of the Monte Carlo code GEANT4;
- Apply the GEANT4 code to the simulation of radiation transport;
- Apply the GEANT4 code to solve issues in Medical Physics and Radiation Protection.

Main Text/s and any supplementary readings:

Main
- Vassiliev,, O. N. (2016). Monte Carlo Methods for Radiation Transport: Fundamentals and Advanced Topics. Springer.

Supplementary
- Ljungberg, M., Strand, S. E., & King, M. A. (2012). Monte Carlo Calculations in Nuclear Medicine: Applications in Diagnostic Imaging. CRC.
- Seco, J. & Verhaegen, F. (2016). Monte Carlo Techniques in Radiation Therapy. CRC.

 
STUDY-UNIT TYPE Lecture, Independent Study & Practicum

 
METHOD OF ASSESSMENT
Assessment Component/s Resit Availability Weighting
Practical (1 Hour) 50%
Examination (1 Hour) 50%

 
LECTURER/S

 
The University makes every effort to ensure that the published Courses Plans, Programmes of Study and Study-Unit information are complete and up-to-date at the time of publication. The University reserves the right to make changes in case errors are detected after publication.
The availability of optional units may be subject to timetabling constraints.
Units not attracting a sufficient number of registrations may be withdrawn without notice.
It should be noted that all the information in the study-unit description above applies to the academic year 2019/0, if study-unit is available during this academic year, and may be subject to change in subsequent years.

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