Master Thesis: Prediction of radiation necrosis for brain metastases treatments

  • Intern
  • Department: R&D Engineering

Company Description

Founded in Munich, Germany in 1989, Brainlab develops, manufactures and markets software-driven medical technology, enabling access to improved, more efficient, less-invasive patient treatments. Our key to success is our creative, talented and hard-working team, which consists of around 2000 dedicated and inspiring individuals in 25 locations worldwide. To succeed in reaching our targets, we are seeking committed colleagues who can stand behind our core values curious, authentic and useful:

Job Description

Project description:

Research question: Can equivalent uniform dose predict radiation necrosis for stereotactic radiosurgery of brain metastases? 

Brain metastases can be effectively treated using stereotactic radiosurgery (SRS). However, high dose is inevitably delivered to healthy brain tissue as well, which is known to be related to radiation necrosis. The steadily increasing number of treated and re-treated patients potentially allows for radiobiological modelling of such complications. Such models could be utilized to further reduce the toxicity of SRS. 

In this work, equivalent uniform dose (EUD) shall be utilized to model the normal tissue complication probability (NTCP) of radiation necrosis locally. A version of EUD which accounts for multiple lesions shall be implemented in an existing framework for treatment plan evaluation. The software shall subsequently be utilized to define model parameters and validate the model on clinical data from the University Hospital, LMU Munich.  

Project logistics: 

The thesis will be carried out at Brainlab AG in the RT Planning R&D department in close collaboration with the LMU Munich University Hospital, and will be supervised at the Physics Faculty of LMU Munich. 

Qualifications

  • Bachelor in physics / computer science / other engineering 
  • Ideally specialization in medical physics 
  • Project experience with Python (for analysis and validation) 
  • First experience in C++ (for extension of EUD model and data export) 
  • Ideal duration is 9-12 months: 3-6 months practical phase (internship or working student) and up to 6 months Master thesis 

Additional Information

  • A mutually-supportive, international team
  • Meaningful work with a lasting impact on medical technology
  • Award-winning subsidized company restaurant and in-house cafes
  • Variety-rich fitness program in our ultra-modern 360m2 company gym
  • Regular after work, team, and company events

Ready to apply? We look forward to receiving your online application including your first available start date and desired salary. 

Contact person: Daniel Sypli

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