Binomial distribution - killing cells with x-rays

In summary, Wendy says that the bionomial distribution may approximate the chance of a cell being damaged/hit with radiation, but that there may be a more sophisticated model that is more accurate.

Does the question make sense, and are there any other medical physicists out there?

  • It makes sense

    Votes: 2 100.0%
  • I don't understand the problem

    Votes: 0 0.0%
  • Yes, I'm a medical Physicist

    Votes: 0 0.0%
  • no, I'm not

    Votes: 1 50.0%

  • Total voters
    2
  • Poll closed .
  • #1
wendy-medicalphysics
1
0
Dear Fellow mathematicians and Physicists,I am doing some MC modelling on tumour growth and radiotherapy treatment modelling and would like to know:

Who out there would agree (or suggest alternatives) to the theroy that the chance of a cell being damaged/hit with radiation (and therefore perhaps dying depending on other parameters) may be described by the bionomial distribution?

Background:
1. Let's say that we have 1000 cells, and k photons will be fired at them
2. Let's also say that a cell will dye if hit 2 or more times (simplistic for now!)
3. I need the number of cells that are hit only 0 or 1 times to be 46% of the total

Can I use the bionomial distribution to work out how may photons that would take (integrating to find the area under the curve to obtain the number of phtotons necessary to achieve point 2.?)

I believe we can think about it as a dice with 1000 number sides.
If we roll the dice k times and take the histogram of the number of times each side came up, then the system is the same as the cell/photon set up...WHAT DO YOU THINK?

Thanks, and write back if you don't understand what I am trying to say

Wendy:rolleyes:
 
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  • #2
Assuming that all photons, with certainty, are absorbed by one of the cells, the above approach seems to me like a reasonable approximation, given the difficulty of incorporating knowledge of the cellular geometry and the radiation source into a model.

I wouldn't call the result a binomial distribution though - perhaps a millenomial distribution ?
 
  • #3
wendy-medicalphysics said:
I believe we can think about it as a dice with 1000 number sides.
If we roll the dice k times and take the histogram of the number of times each side came up, then the system is the same as the cell/photon set up...WHAT DO YOU THINK?

Thanks, and write back if you don't understand what I am trying to say

Wendy:rolleyes:

That would be interesting. And you look at P(X1>=2, X2>=2, X3...)? A very simple and elegant model but I have a feeling it's been superceded. I would look at graphs, random fields, anything with that sort of mapped network type of thingie. Haven't really looked at that kind of stuff in a while so I probably can't help you yet (and I have this ***** of an essay to write.) I suspect what you're looking for is a discrete array of continuous arrays of random numbers. Thus you could model with continuity the cell surface and then model discretely n numbers of cells.
 
Last edited:
  • #4
Are we supposed to use a quantum wavefunction for this?
 

Related to Binomial distribution - killing cells with x-rays

What is the binomial distribution?

The binomial distribution is a probability distribution that describes the likelihood of a certain number of successes in a fixed number of independent trials, where each trial has a binary outcome (success or failure).

How does the binomial distribution relate to killing cells with x-rays?

The binomial distribution can be used to model the probability of a certain number of cells being killed by x-rays in a given sample, where each cell has a binary outcome of being killed or not killed.

What factors can affect the binomial distribution in killing cells with x-rays?

The probability of killing a cell with x-rays can be affected by various factors, such as the intensity and duration of the x-ray exposure, the type of cells being targeted, and the sensitivity of the cells to x-rays.

How can the binomial distribution be used in practical applications?

The binomial distribution can be used to calculate the likelihood of a certain number of cells being killed by x-rays in a given sample, which can be useful in medical treatments such as radiation therapy for cancer.

What are the limitations of using the binomial distribution in killing cells with x-rays?

The binomial distribution assumes that each trial is independent and has a fixed probability of success, which may not always hold true in real-life situations. Additionally, the binomial distribution may not be suitable for cases where the number of trials is very large or the probability of success is very small.

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