Generating Fluence Maps from DICOM RTPlan Files in Python

[Bianka Mandac]

Hi! I'm trying to generate fluence maps from DICOM RTPlan files. I have used the equation function from Craft et al (2018) (https://arxiv.org/abs/1608.02842) to generate the exposure function. But I am confused on how to proceed in incorporating the MU in order to generate the fluence maps for sliding window IMRT. 

Is there any document/paper that can help explain the computation of Sliding Window IMRT Fluence Map generation?

Thanks!

[Simon Biggs]

Hi Bianca,

If you just want to calculate an "MU Density" there is the following tool within pymedphys:

https://github.com/pymedphys/pymedphys/issues/434#issue-472618095

To use it, install pymedphys with:

pip install pymedphys[user]

Then within python:

```

import pymedphys

filepath = 'path/to/dicom/plan.dcm'

delivery = pymedphys.Delivery.from_dicom(file path)

mu = delivery.mu

mlc = delivery.mlc

jaw = delivery.jaw

```

Then use pymedphys.mudensity.calculate as described within the following API doc:

https://docs.pymedphys.com/ref/lib/mudensity.html

If you have some success and are interested in writing a little how-to I'd be quite keen to include what you write over at https://docs.pymedphys.com/howto/index.html. There is a noticeable lack of how-to guides at the moment.

Cheers,

Simon

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[Bianka Mandac]

Hi Simon!

I've tried using:

pymedphys.Delivery.from_dicom(imrt_plan_ds, fraction_number=1) 

However I keep encountering errors regarding the jaw:

VisibleDeprecationWarning: Creating an ndarray from ragged nested sequences (which is a list-or-tuple of lists-or-tuples-or ndarrays with different lengths or shapes) is deprecated. If you meant to do this, you must specify 'dtype=object' when creating the ndarray

  jaw = np.array(dicom_jaw)

and 

  File "C:\Users\USER\PycharmProjects\venv\lib\site-packages\pymedphys\_dicom\delivery\core.py", line 172, in _from_dicom_beam

    second_col = deepcopy(jaw[:, 1])

IndexError: too many indices for array: array is 1-dimensional, but 2 were indexed

I've yet to try using the mu_density function alone.

I'll update you as soon as I figure it out.

Thanks!

[Simon Biggs]

Hi Bianka,

Would you be able to copy those details onto an issue over at https://github.com/pymedphys/pymedphys/issues that way we can better track it there.

Cheers,

Simon

To view this discussion on the web visit https://groups.google.com/d/msgid/python-medphys/38e284b6-ed30-4666-a14a-4f3d28318619n%40googlegroups.com.

[Bianka Mandac]

Sure!

I'll post the details later.

Thanks!

Sincerely, 

[Simon Biggs]

So that future internet peeps can follow the trail here's the link to Bianka's issue on GitHub:

https://github.com/pymedphys/pymedphys/issues/1047

To view this discussion on the web visit https://groups.google.com/d/msgid/python-medphys/0add47d8-820e-4519-9abe-4dd2c5f7a70fn%40googlegroups.com.