Plotting a Dose-Volume Histogram from Matrix of Values

In summary, the conversation revolves around using a matrix of size 150x1 with values between 5.321 and 13.226 to create a dose-volume histogram. The individual has sorted the matrix and plotted it, but they want the graph to include values from 0 to 14. They also request assistance with determining the edges of the histogram bins and the release of MATLAB they are using.
  • #1
linger
2
0
Hi, I have a matrix 150x1 with values between 5.321 to 13.226 and I want to use the matrix and plot a dose-volume histogram (https://en.wikipedia.org/wiki/Dose-volume_histogram).
Can someone help me.
 
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  • #2
Sure. Do you have some more information you could share about this?
 
  • #3
no, not really, but have tried to solve it and have come this far

D = sort(D); %D matrix 150x1
x= [150:-1:1]*100/150;
plot(D, x);
xlim([0,14]);

have I done it right so far?
the graph plots only from the smallest x value 5.321 to the highest 13.226 and I want it to draw from 0 to 14.
 
  • #4
Which release of MATLAB are you using?

Also, do you have an idea of what you want the edges of the histogram bins to be?
 
  • #5


Sure, I'd be happy to help you plot a dose-volume histogram from your matrix of values. A dose-volume histogram is a plot that shows the distribution of radiation doses received by a particular organ or tissue in a patient. It is a useful tool for evaluating the effectiveness and potential side effects of radiation therapy.

To plot a dose-volume histogram, you will need to first determine the dose received by each volume in your matrix. This can be done by sorting the values in your matrix from lowest to highest and then dividing them into equal volume bins. For example, if you have 150 values, you could divide them into 10 bins of 15 values each.

Next, you will need to calculate the percentage of volume that received each dose. This can be done by dividing the number of values in each bin by the total number of values in your matrix and multiplying by 100. This will give you a percentage for each dose level.

Once you have calculated the percentage of volume for each dose, you can plot them on a graph with the dose on the x-axis and the percentage of volume on the y-axis. This will give you a visual representation of the dose-volume relationship for your data.

I would also recommend labeling your axes, including a title for your graph, and including a legend to explain the different dose levels. This will make your plot easier to interpret for others.

I hope this helps you plot your dose-volume histogram. If you have any further questions or need additional assistance, please don't hesitate to ask. Good luck with your research!
 

1. What is a dose-volume histogram (DVH)?

A DVH is a graphical representation of the radiation dose received by a specific volume of tissue or organ. It shows the percentage of the volume that received a certain dose, allowing for a more accurate evaluation of the radiation therapy treatment.

2. How is a DVH calculated?

A DVH is calculated by plotting the percentage of the volume versus the corresponding dose received. This is done by using a matrix of values that includes the volume and dose data points for each tissue or organ being analyzed.

3. What information can be obtained from a DVH?

A DVH provides information about the dose distribution within a specific tissue or organ. It can show the amount of radiation that a particular volume of tissue received, as well as the minimum, maximum, and average doses received by that volume.

4. What are the benefits of using a DVH?

A DVH allows for a more accurate evaluation of the radiation therapy treatment by taking into account the volume of tissue that received a particular dose. It also helps in identifying the areas of the tissue that received high doses, which can help in adjusting the treatment plan to minimize potential side effects.

5. How can a DVH be used in clinical practice?

A DVH is a valuable tool in treatment planning and evaluation in clinical practice. It can help in optimizing treatment plans to ensure adequate dose coverage while minimizing the risk of side effects. It can also be used to compare different treatment plans and assess the effectiveness of the treatment. Additionally, it can aid in post-treatment analysis to monitor radiation-induced toxicity in patients.

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