Nutrient radiography and computed tomography are uniquely positioned to measure biological samples due to the sensitivity of nutrients to hydrogen atoms. The main advantage of these techniques is to provide non-destructive and non-invasive three-dimensional maps of hydrogen content in tissue samples or water content in plant roots and soil. Nutrient imaging is applicable to many different areas of research, such as energy materials, material science, engineering, plants, soil, water movements, et cetera.
This technique cannot be used for therapy or institute diagnostic due to the risks of radiation exposure. However, it can be used to determine tumor margins in small resected intact tumors, for example. I recommend an individual interested in this technique to contact us and discuss their research questions.
Our information is available on our website, neutrons.ornl.gov. Demonstrating the procedure will be Yuxuan Zang, a Neutron Scattering Scientist, Jean Bilheux, Computer Instrument Scientist, and Erik Stringfellow, a Scientific Associate from our Imaging team. To begin, open a terminal window on the Beamline computer.
Type CSS and press Enter to launch the user interface. If not opened by default, choose the User Home option in the Menu tab to open the APEX Imaging interface. In the first tab of the interface, ProposalCameraSE Device, select the Beamline optics by clicking on the Optics button next to Camera/Detectors.
Click on the Slits button to set the pinhole aperture size and opening of the slit system. Bolt the rotation stage onto the XY stages where the sample is to be placed. If using Detector other than CCD, select a lens as per desired spatial resolution and focal length.
After focusing the camera, focus the image at the location of the neutron scintillator. Then, place a neutron-absorbing resolution mask against the detector scintillator to fine-tune the lens focus with neutrons. Next, using APEX, automate moving the detector motor and collect excessive radiographs using different detector positions from the mirror.
Compare the radiographs by evaluating line pairs in an image software tool such as Fiji or ImageJ. Then, secure the sample in a suitable aluminum container or heavy-duty aluminum foil, and place the sample on the rotation stage as close as possible to the detector. Measure the sample-to-detector distance and remove the sample.
Replace it with the resolution mask to evaluate the pixel size at sample position in this Beamline configuration. Using a known feature dimension, evaluate the number of pixels across the feature to determine the pixel size. Reposition the sample on the rotation stage.
Next, using the Align Sample tab in the APEX interface, align the sample with the neutron beam by taking successive, fast radiographs while the sample is moving until it is in full view of the detector. Save the sample alignment file. Before starting the CT scan, click the Align Sample tab and use the Automated Sample Rotation check option to verify that the sample remains in the field of view at different angles by assessing radiographs as they are generated at different sample orientations with the beam.
Select the first APEX tab named ProposalCameraSE Device. Click on the Switch Proposal or Sample button. Select the project number and sample ID to be measured in the sample list on the right and list of proposals on the left.
Use the back arrow to come back to the main APEX interface. In the Camera Detector option list, select the detector from four available detectors and/or CCD, and/or sCMOS, SBIG CCD, or MCP. In the Sample Environment Device section, click on Rotation Stage, CT Scan.
Then, select one of the rotation stages that corresponds to the sample to be scanned. At the bottom of the tab, select Data Acquisition Mode and select the White Beam. Then, select the second APEX tab named Align Sample.
Type a sample file name and press Enter. Repeat for the sub-folder name. Assume that the sample is aligned and ready for CT.Select a desired acquisition time and click on the Take Quick Images button to collect a series of radiographs with different acquisition times.
To evaluate signal-to-noise ratio, open the collected radiographs in ImageJ or Fiji and plot a profile going from the sample to an open area. If multiple samples are set on the XY stage on multiple rotation stages, record each sample position after alignment and click on the Save in a File button to save the data as CSV file. Next, select the third APEX tab titled Collect Data to set up the CT scan parameters.
Type a file name on the first writeable line and press Enter. Repeat for the sub-folder name. In the Align Sample Using the Saved File section, select the file that previously recorded the sample motor positions.
Click on Align Using File to make the sample go back in position in the neutron beam. To calculate the number of projections based on Nyquist's theorem, first, calculate the number of pixels across the sample horizontal dimension and multiply by 1.5 to obtain the number of needed projections to fulfill Nyquist's sampling. Enter the rotation start angle, rotation end angle, rotation step size, the number of images per step, and the exposure time for each image.
Start the CT scan by clicking on the Collect Data button. On the Linux Analysis server, access the Imaris 3D Notebook by clicking the top menu shortcut, Applications, then Analysis-Imaging and CT reconstruction. Run the first few lines of the code, which will load the tools necessary to run Imaris 3D.
Load the data flat and dark-field. Verify that all three data sets are properly loaded. Crop the data by selecting the region of interest in the image.
Perform filtering as necessary by running the code in the filtering section. Proceed with normalization, followed by beam fluctuation correction. Select the background region from the image, followed by transmission to attenuation.
Then, perform automated sample tilt correction by calculating the tilt using the code and applying the tilt correction. Next, perform strike removal and rotation center calculation. Then, perform volumetric reconstruction and view the data.
Save the data in the project number folder named Shared. Then, turn on Amira software on the Facility Analysis server, load the reconstructed slices in the software, and proceed with visualization, further filtering, and analysis. A custom-designed interface was developed to guide this experimental protocol and minimize human error.
The interface logically moves through the necessary steps prior to measuring a sample. Neutron computed tomography, or NCT, of a rat's femur with a titanium implant is shown here. The false color attenuation based NCT of the femur and a diagonal cut through the bone to reveal the implant were obtained.
The implant does not interact with neutrons as much as the bone material, so its attenuation is minimal and it appears darker than the surrounding bone. The trabecular bone, which is present within the medullary space of the femur, is clearly visible at the proximal end of the sample. The ability of neutrons to detect soft tissue specimens was demonstrated on an ethanol-fixed mouse lung.
The reconstructed volume of the lung was obtained from NCT. A cut through the right lobe of the lung is illustrated here. The false color volumetric rendering of a plant root and soil system in a rectangular aluminum container was obtained, as well.
Despite a poor signal-to-noise ratio, the root system in the soil is clearly visible in vertical cuts of the sample. It is crucial to evaluate the pixel size, so the recorded images can be relayed to the physical dimensions. The quality of 3D volume reconstruction relies on good sampling following the Nyquist theorem.
More advanced neutron imaging techniques, such as neutron grading interferometry, can be performed following a similar procedure. These novel methods would answer questions, such as the three dimensional nanoporosity distribution in porous materials. Neutron radiography and computed tomography have the broad scientific impact.
These techniques are of application and the understanding of batteries and their failure mechanism. Advanced materials behavior such as 3D printed ones, archeology, biology, and better localization of tumors.
