tutorial mri-coupled fluorescence tomography of small …nir/nirfast/tutorials/tutorial...
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Tutorial: Imaging a mouse brain tumor in an MRI-‐coupled fluorescence molecular tomography system This tutorial will use sample files found here. Background/context for tutorial: An MRI-‐coupled fluorescence tomography system was used to examine the receptor expression profile (EGFR in this case) of a glioblastoma model in a mouse. The system geometry is shown in Fig. 1, and consists of 8 optical fibers which couple light between the head of the mouse, the laser source, and the spectrograph detectors.
An EGFR-‐targeted fluorophore was injected into the mouse two days prior to imaging to allow it to accumulate in the tumor and clear from the surrounding tissue. On imaging day, MRI (T1-‐weight with Gadolinum, stored as DICOM images) and optical data (both excitation and fluorescence emission, stored in a .paa file) were acquired concurrently. We need to merge these data sets to recover images of the fluorescence activity in the mouse head, illustrated here:
MRI Data
Optical Data
MRI-‐fluorescence overlay
Fig. 1. MRI-‐fluorescence tomography system geometry for mouse head imaging.
Now let’s walk through the steps of creating a mesh from the MRI images, calibrating the optical data, and reconstructing multi-‐modal FMT images.
1. Open NIRFAST
2. Load DICOMS: In the modules list open the “DICOM” module. Select Import and browse to the MRI directory with the DICOM images and import them. The folder would normally contain several MRI sequences, but there should only be one sequence here – click Load.
NIRFASTSlicer will create a “Volume” which is just your 3D image data upon which you can do various operations. As you work with and process this volume (such as cropping or segmenting), NIRFASTSlicer may create new volumes with modified names.
3. View and render loaded DICOMS: Open the “Volume Rendering” module.
You will need to select your volume and enable 3D visualization. The 3-‐D volume will show in the purple window – you can rotate, zoom, etc. You can also try different presets and experiment with advanced visualization settings:
4. Crop the image volume to the tissue region: Select the “Crop Volume” module and click on the eye to enable ROI visibility. Use the crop box to select an ROI encompassing only the tissue. Select Crop! This will create a new volume of the cropped ROI with an appended “…-‐subvolume-‐scale_1”
5. Change the number format: Now we need to do a format change (due to the vagaries of segmenting in Slicer). Select the “Cast Scalar Volume” module. Make sure to select your cropped subvolume for the input and output volumes, as shown below. Select Short and Apply.
6. Saving: (at any point, you may want to save your work. File > Save and select “Change Directory for Selected Files”. Choose a directory and save. If you Save again, we recommend following the same procedure and replacing your files).
7. Segment the tissue into regions: Now we want to segment the tissue into 4 regions: The background, the brain, the tumor, and all other tissues. This will let us perform spatially-‐guided image reconstructions when we come to that. Select the “Editor (segment tissue)” module to view the segmentation tools (choose “Generic Colors” from the dropdown the first time you select the Editor). There are several approaches to segmenting tissue (see 3DSlicer Editor documentation), and the most efficient methods are often case-‐specific. For this case we recommend:
a. Make sure the proper subvolume is selected as “Master Volume” b. Select the threshold tool and move the lower threshold range to label as much of the
head as possible, leaving few “holes” inside and few “islands” outside the tissue. A minimum of about 445 works for this case. Select Apply.
c. You can change the opacity of the label by selecting the pin and then double arrows to reveal the viewing details. Note that two volumes are shown – the master subvolume-‐scale1 and the “label”. You can select the rings to apply your changes to all 3 views.
d. To remove remaining holes, use the dilate tool, and then erode by the same amount. Make sure there are no holes or islands in the volume.
e. Additional tissue types: For each new region, select a new label (brown, 3, is selected below). We typically segment the brain and tumor manually using the Draw or Paint (which allows multi-‐slice painting) tools, slice-‐by-‐slice. You can also try the Wand Effect, Level Tracing Effect, and other built-‐in tools. The bottom image below shows a slice segmented into brain, tumor, and head regions.
f. (Good idea to Save once you’re done segmenting! If you save, you can load everything back up just as you left it!).
8. Positioning optical sources/detectors: Now, we need to place markers, or fiducials, where the 8 optical fibers touch the tissue. This needs to be done in a specific order to correspond to the order of the actual fibers, as shown here:
Select the Markup/Fiducial tool at the top of NIRVIEW to place “fiducial” markers. Select “persistent” in this tool so you can place all 8 without re-‐selecting the tool. Note that these will show up in the Volume rendering as well. (Save your work)
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9. Create the finite element mesh for optical reconstruction: Now it’s time to create the mesh (aka, numerical model geometry) by selecting the “Create Mesh” module. Choose your Input Label Map, and the markup variable in “Sources/Detectors” (usually this is just called “F”). You might want to change the output directory and output mesh name. Under Mesh Parameters, change the mesh “type” to “fluorescence”, and reduce cell radius and facet distance to about 0.8. Do not “optimize mesh” – this is good to do, but will take a long time. Your inputs should look like the below. Select Apply.
10. Complete mesh creation: NIRFAST will create a mesh and launch Matlab. Once created, a program which allows the user to refine source-‐detector locations will open. If you do
nothing, NIRFAST will automatically attempt to place sources and detector positions an appropriate distance inside the surface of the mesh. This will work for this tutorial, but for more accurate positioning, a drop-‐down menu provides system-‐specific scripts which move the sources and detectors in a pre-‐defined way (more on this at www.nirfast.org). You can write and add your own script for your specific geometry (look in Nirfast/toolbox/fiducials for examples on how to write these – adding your script to this folder will automatically make it available in the GUI). For this tutorial, do not select from the drop down list and simply select Done. You have now created an FEM mesh!
11. Using the interface for the Matlab component of NIRFAST: The NIRFASTMatlab main GUI window will be opened automatically. While it is possible to use this, currently, we recommend starting a new instance of Matlab and typing “nirfast” to run the program and browse to the directory you saved your mesh (this step is necessary because the automatically-‐started instance currently does not open the Matlab workspace window, which is very handy when using NIRFASTMatlab. A fix is coming).
12. Calibrate the optical data to the diffusion light propagation model: From the NIRFASTMatlab GUi, select Data > Calibrate > Fluorescence and fill in the fields as below. This program will calibrate the data to the model and generate a homogeneous initial guess mesh which will become an input to the reconstruction program. Input mesh: (browse to the mesh you created) Data: (browse to the Optical data provided in your tutorial files) Save Data To: Browse to a folder to save the calibrated data and name it something like “Calib_data_tutorial” Save Mesh To: This is the homogeneous initial guess mesh which will become an input to the reconstruction program. We like to name these “initial guess” meshes with an “IG” prefix. Other fields: Leave as default
13. Reconstruct optical images: Now it’s time to reconstruct an image. From the Main GUI, select Reconstruct > Reconstruct > Fluorescence.
First, we will run a reconstruction with no spatial priors. Fill in the fields as shown below: Input mesh: Browse to the mesh you initial guess mesh Input Data: Browse to the your calibrated data file Save Solution To: Enter the name of your solution files – e.g. “recon_mouse_tutorial” Reconstruction Basis: In this example, we will not use priors. You will need to change the pixel (reconstruction) basis to define 3 dimensions. Try [20 20 20] for now. Uncheck View Solution Other fields: Leave as default
14. Spatial priors option: You can now repeat the reconstruction using hard priors (remember, this is a 3-‐region volume) if you like. You can compare results from both approaches.
15. Visualizing reconstructed optical images and image overlay: Go back to the NIRFASTSlicer window. If you have closed the Scene for this animal, reopen it now.
a. Loading and displaying optical data: Select the “Import Optical Properties” module
Select the browse symbol next to “VTK Mesh” and browse to “solmesh_recon_mouse_tutorial.vtk”. For the Bounding Volume, select the subvolume_scale_1 volume. This is the MRI volume you created when you cropped the original volume. Select Resample Mesh.
You will now see a list of optical parameters from the mesh. In this case, the only one we are interested in ends with “etamuaf”, since this is the parameter we reconstructed.
By default, etamuaf should load and be displayed, looking something like the below:
b. Adjusting the image display, transparency: There are many parameters that you can adjust to change the look of this display. Start by expanding the options in a slice window. Select the double ring icon to ensure your adjustments change all slice views. Select the double arrow to see more options. Notice there are 3 volumes shown, the label map (you do not want to visualize this), the MRI subvolume-‐scale_1 as the background and the _etamuaf volume as the foreground. Adjust the number box next to the etamuaf volume to change the transparency of the solution over the MRI background. You can also use the interpolate icon to smooth the image values, as shown in the two examples below.
c. Adjusting the image display, thresholding values: Now select the “Volumes” module and select the “etamuaf” volume as the Active Volume.
Use the Threshold sliders to adjust the image overlays. Feel free to play with other presets and mappings.
Another tip: To view colorbars for the optical parameters, select the “Quantification > Data Probe” module, Enable ScalarBar and select Foreground
d. 3-‐D rendering of optical images: Finally, you can go back to the “Volume Rendering” module and select the etamuaf volume to show in 3-‐D. Ultimately, you might have a window that looks like the below. You can open the Advanced menu and continue adjusting the look of the rendering.
At any point, you can save your data, and all info in the scene will be available for future viewing.
16. Finally, if you ran a hard priors reconstruction, go ahead and load those images by again using “Import Optical Properties” and browsing to the hard prior vtk files.
For more tutorials and documentation on NIRFAST, or to join our mailing list, please visit http://www.nirfast.org/. See Davis, et al., Academic Radiology, 2010 and Davis et al., JBO, 2010 for details on MR-‐guided FMT for diagnosing brain tumors over-‐expressing epidermal growth factor receptor. Data used for this tutorial were originally published in these papers.