MSc Medical Physics in Cancer Radiation Therapy / Course details

The unit will provide the students with the following knowledge and practical skills:

• Introduce the students to python: syntax, scripting approaches, debugging, use of Jupyter notebooks, medical image handling and processing, skills for data science and AI.
• Provide best practice guidelines for identifying the relevant literature within the field of medical physics and skills to effectively critically appraise scientific papers.
• Ability to read, understand and interpret medical statistics commonly presented with the field of cancer radiation therapy, including understanding of how clinical trials are presented and common criticisms.
• Gain an understanding of emerging and future statistical techniques being employed within medical physics and cancer radiation therapy. For example, the adoption of casual inference approaches.
• Skills in research dissemination - scientific report writing, scientific presenting and scientific poster design.
• Scientific leadership skills will be showcased by interactive discussion sessions and case studies of successful research project leadership and impactful translational research.

This unit aims to provide students with the research methodologies needed to succeed in the medical physics in cancer radiation therapy masters. The students will be provided with training in using python as a scripting language, with a particular focus on medical image handling and for use in data science or AI applications. Students will be able to confidently search for and identify literature and be able to critically appraise this material. A focus here will be the ability to interpret statistics presented in medical physics and the wider cancer research literature. Skills in different forms of research dissemination will be taught, covering scientific reports, presentation skills, and research poster design. Finally, we will introduce concepts of scientific leadership and project management skills required to be successful as a medical physicist.

The following learning and teaching processes will be utilised: Classroom based teaching, interactive group sessions and tutorials, paired programming, formative assessments, on-line resources, independent study.

Students should/will be able to:

• Apprise the use of python within the medical physics and cancer radiation therapy workflows.
• Ability to identify and critic medical physics scientific literature.
• Select and evaluate different forms of scientific dissemination approaches.

Students should/will be able to:

• Determine the most suitable python approach for tasks in medical physics.
• Evaluate medical physic scientific papers, including an examination of the statistical robustness of the manuscript.
• Contrast different research dissemination strategies.

Students should/will be able to:

• Script simple python scripts using command line and Juypter notebooks.
• Ability to confidently select the most appropriate form of dissemination for scientific research.

Students should/will be able to:

• Apply analytical skills to systematically analyse evidence.
• Technical: Practical experience in python scripting.

Summative 1: 50%

Students will be given a 'toy' problem to solve in python using the skills learned during these tutorials.

Students will work using paired-programming, submission will be in a Juypter notebook.

Summative 2: 50%

Research dissemination of paper critic, students will be given a recent medical physics paper and present a critic of the manuscript and statistical analysis.

Students will be provided with a marking scheme to guide and will be able to choose one of the research dissemination methods to present their work - short report / poster / (recorded) presentation.

Summative 1: The assignment will be marked according to a defined marking scheme, pairs marked together.

Summative 2: Students will be given individual feedback based on the marking scheme.

Study hours:

Lectures; Tutorials; Seminars; Workshops - 25 hours

Independent study - 125 hours