Quantitative Strain Mapping of an Abdominal Aortic Aneurysm

1. 4D Ultrasound Set-up

1. When using the imaging software, use a laptop capable of running mathematical computing software to automate the 4D acquisition process. Connect the laptop with this custom code to the ultrasound system via the USB port. Note that the imaging software has a 4D ultrasound feature integrated into the software.
2. After turning on the ultrasound system, set up the physiological monitoring unit while also ensuring that the heart rate and temperature buttons are on. Initialize the 3D motor stage attached to the transducer holder.
3. Use the appropriate stage and ultrasound transducer for image acquisition. Ensure that all proper connections are made.
4. Proceed with anesthetizing and preparing the animal for imaging. Add ophthalmic ointment to the eyes to prevent corneal desiccation, secure the paws to the stage electrodes, and insert a lubricated rectal temperature probe. Remove fur in the area of interest using a depilatory cream.
5. Make sure depilatory cream is completed removed. Then, apply a generous amount of the warmed ultrasonic transducing gel to the animal. This is especially important to create a good connection over the entire region of interest for 4D imaging.

2. 4D Ultrasound Acquisition

1. Begin a new study on the ultrasound system and open the imaging window in B-Mode (brightness mode). Lower the transducer onto the animal and locate the region of interest using the x- and y-axis knobs on the stage, making sure the respiratory rate does not decrease substantially. Monitor this at the bottom of the screen.
2. Position the transducer within the middle of the region of interest. From there, approximate the distance needed for the transducer to move up and down such that the entire region of interest is included.
3. Enter the approximate dimensions into the computing software code, including a step size which is typically ~0.08 mm for abdominal aortic aneurysm imaging. Begin running the code after ensuring the animal's heart and respiratory rates are stable. This is important for reducing errors when reconstructing images.
4. After completing the image acquisition, export the data as raw XML files.

3. 4D Ultrasound Data Conversion

1. Input the raw XML files into software that can convert the data into the proper format for the 3D stain analysis. Here we use Matlab to convert XML files into MAT files. The full Matlab script is available here.
2. For proper conversion, the number of frames, step size, and desired output resolution will also need to be input.
3. After resampling the matrix in through plane, import the new MAT file into the 3D strain analysis code.

4. 3D Strain Code Analysis

1. Begin analysis by properly adjusting the imported MAT file. For example, the image volume may need to be rescaled to reduce computation time.
2. Input the region to be analyzed and determine the appropriate mesh template to segment the image data as either simple boxes or manually chosen polygons. The box size of the regions and spacing between the center points may need to be altered for each data set. The optimal numbers chosen for box size will be around the order of pixels of the feature being tracked, which can be approximated by looking at the number of pixels in two dimensions in one slice. The spacing of the boxes will determine the resolution of the strain fields. More boxes will increase the resolution but may also substantially increase computation time.
3. Begin computing the Jacobians and gradients iteratively within each of these regions. After the precomputation is complete, apply the warping function.
4. Calculate the deformation gradient tensor. First calculate strain, and then calculate the eigenvalues and eigenvectors using the direct deformation estimation method.
5. Plot these results in the desired planes using a technique such as color mapping of a cut plane to represent the strain field over your region of interest.