Other Undergraduate thesis topic ideas in medical physics

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A junior applied physics major is seeking guidance on selecting a thesis topic, initially proposing a project on bipolar junction transistors for dosimetry but feeling uncertain due to existing studies. The discussion highlights that undergraduate projects in medical physics often rely on available equipment and data, with an emphasis on collaboration rather than novelty. Key topics in medical physics include dosiomics and outcome prediction, which explore higher-order metrics in radiotherapy; radiomics for improved cancer detection using advanced imaging techniques; flash radiation therapy (Flash RT), which investigates high-dose radiation delivery to minimize toxicities; and linac-MRI hybrid machines that combine radiation therapy with MRI for better treatment precision. Resources for further reading on Flash RT are also shared, indicating ongoing research interest in this area.
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I am a junior applied physics major. I am supposed to write my thesis topic proposal but honestly have no idea what to do. I wrote a proposal about using bipolar junction transistors to create a dosimeter but there are already studies on it and honestly, I am not sure about it so I am trying to find a new topic.
 
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A lot of projects in medical physics depend on what equipment, software, and/or data is available to you. As an undergraduate you won't be expected to develop something novel, though you might be able to get involved with a collaboration and take on a sub-project of something larger. This is a question you should speak with your professors about.

Here are some hot topics in medical physics right now:
  1. Dosiomics and outcome prediction
    Historically we prescribe and constrain radiotherapy treatment plans using first order scoring metrics: mean dose to a volume, max dose, etc., but there's some evidence that higher order metrics that allow us to grade things like texture or other patterns in the dose maps (dosiomics) may influence treatment outcomes as well.
  2. Radiomics and disease detection
    Similarly, higher order patterns in CT, MRI and PET images can improve our ability to detect cancers. Or, there is a lot of open source data on COVID-19, and lot of people have been developing machine-learning tools to help identify the presence of COVID-19 on CT scans. You could, even take that further to outcome prediction, attempting to identify those patients likely to progress to severe stages of the disease and who would benefit from some of the newer anti-viral interventions.
  3. Flash RT
    There's some evidence that when radiation is delivered at very high dose dates (above about 40 Gy/s), toxicities that are induced at more conventional dose rates can be avoided. There's a big question right now about why this is, and lots of interest in modifying conventional machines and devices to deliver and measure radiation at high dose rates.
  4. Linac-MRI Hybrid Machines
    There are now a number of commercially available machines that combine therapeutic linear accelerators (or Co-60 sources) and MRI units so that the soft-tissue contrast of MRI can be used to guide radiation delivery. But these introduce magnetic fields into the mechanics of radiation transport, and this can lead to a lot of interesting questions about magnetic fields can influence detectors, dose distributions, etc.
 
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Choppy said:
A lot of projects in medical physics depend on what equipment, software, and/or data is available to you. As an undergraduate you won't be expected to develop something novel, though you might be able to get involved with a collaboration and take on a sub-project of something larger. This is a question you should speak with your professors about.

Here are some hot topics in medical physics right now:
  1. Dosiomics and outcome prediction
    Historically we prescribe and constrain radiotherapy treatment plans using first order scoring metrics: mean dose to a volume, max dose, etc., but there's some evidence that higher order metrics that allow us to grade things like texture or other patterns in the dose maps (dosiomics) may influence treatment outcomes as well.
  2. Radiomics and disease detection
    Similarly, higher order patterns in CT, MRI and PET images can improve our ability to detect cancers. Or, there is a lot of open source data on COVID-19, and lot of people have been developing machine-learning tools to help identify the presence of COVID-19 on CT scans. You could, even take that further to outcome prediction, attempting to identify those patients likely to progress to severe stages of the disease and who would benefit from some of the newer anti-viral interventions.
  3. Flash RT
    There's some evidence that when radiation is delivered at very high dose dates (above about 40 Gy/s), toxicities that are induced at more conventional dose rates can be avoided. There's a big question right now about why this is, and lots of interest in modifying conventional machines and devices to deliver and measure radiation at high dose rates.
  4. Linac-MRI Hybrid Machines
    There are now a number of commercially available machines that combine therapeutic linear accelerators (or Co-60 sources) and MRI units so that the soft-tissue contrast of MRI can be used to guide radiation delivery. But these introduce magnetic fields into the mechanics of radiation transport, and this can lead to a lot of interesting questions about magnetic fields can influence detectors, dose distributions, etc.
Thank you! I'll check these out.
 
Choppy said:
Flash RT
There's some evidence that when radiation is delivered at very high dose dates (above about 40 Gy/s), toxicities that are induced at more conventional dose rates can be avoided. There's a big question right now about why this is, and lots of interest in modifying conventional machines and devices to deliver and measure radiation at high dose rates.
Interesting! Can you give a link or two for further reading? Thanks.
 
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