利用X射线计算机断层扫描在小鼠肥胖模型的FAT卷的分割和测量

The overall goal of this procedure is to non-invasively image quantitate and visualize the fat content of living mice. This is accomplished by first performing an X-ray CT scan of the mouse. The second step of the procedure is to segment and quantify the fat volumes within the mouse based on radio density.

The third step is to visualize the CT data in three dimensions with fat volumes highlighted in red. Ultimately, results can enable the quantitation and visualization of fat content during longitudinal in vivo studies using an albia X-ray ct, coupled with PMOD and vol view software packages. One of the key benefits of this technique versus existing methods like X vivo analysis, is that this technique allows for non-invasive and longitudinal assessment of fat in small animal disease models.

Generally, individuals new to this method will struggle because the segmentation and visualization protocol includes several steps that must be completed in succession. Further, the optimal x-ray parameters must be utilized during acquisition. To obtain the best contrast from adipose tissue, Begin by anesthetizing the obese mice of interest using an induction chamber and then transfer to a nose cone.

Maintain the anesthesia during the imaging position the mice in a standard rat bed with the limbs lateral to the torso. This provides a uniform CT acquisition. Set the CT system to scan a bed of 115 millimeters length using 600 projections.

Set the x-ray source to 200 microamps and 45 kilovolt peak and use a 0.5 millimeter aluminum filter to harden the beam. The equivalent radiation deep dose that the mouse will receive for this setting is approximately 220 milli seavers, while the shallow dose equivalent is 357.4 milli seavert on the computer. Select the FBP algorithm using standard parameters for image reconstruction.

Ultimately, the final image is made of 125 micron isotropic, foxholes, and can be used for whole animal image analysis. Image analysis is performed using PMOD analysis software first PMOD segments, images according to tissue density, and then for fat volume. After loading the image, reduce its size to minimize computational demands.

Navigate to the main view tab, select tools followed by reduce. Set the reduction values to two for X, two for Y, and two for z, check, replace and run the process. A message box appears when the process is complete.

To eliminate bed and nose cone elements from the images, mask them before the VOI analysis. Navigate to planes layouts, rotations, mirror 3D markers and select planes and layouts. Select show plane Z.Then scroll to the nose cone in the Z plane.

Next, select the main VOI tab and choose draw vertices. Draw an ROI around the nose, excluding the bed and nose cone and select copy actual ROI to each other. Slice with the nose cone element.

Paste the ROI from the buffer onto the nose as needed. Use the edit group of vertices command to adjust the ROIs. When the nose cones are no longer visible, delete the ROI and generate a VOI to encompass the animal girth.

Navigate to VOI tools, followed by masking and algebra. Enter minus 1000 in the provided dialogue box. Then select the button that reads Mask voxels outside the selected vois.

When the message irreversible data operation do you want to continue is displayed, select yes. Now navigate to planes layouts, rotations, mirror 3D markers, and finally, planes and layouts. Select show all planes.

Examine the integrity of the VOI. When the VOI looks good, save it as an analyze file and change the file name prefix. Proceed with segmenting the image for total animal volume.

Begin with selecting tools and external. Then select the segmentation checkbox. Enter a range of minus 300 to positive 3, 500 and run the segmentation.

Then select VOI statistics, which reports statistics representing the total volume. Take note of this volume. Now segment the image for fat volume by first returning to the nons segmented massed image.

Second, load the saved mass data file and check the analyze box in the load window. Next, select tools and external. Then select the segmentation checkbox.

Enter a range of minus 200 to minus 50 and run the segmentation. After approving the results, select VOI.Statistics. Take note, the reported statistics represent the fat volume.

Save the results in the analyzed format and provide a unique file name prefix. However, if skin or peripheral density remains, use the erosion and dilation protocol to eliminate these regions for VOI analysis. Before saving, navigate to tools external and select the morphological checkbox in the new box.

Select erosion followed by. Okay, return to the morphological checkbox and select dilation and okay, check that the skin or peripheral density issue has been resolved and save the results. Utilize the software package Volvo view version 3.2 to create rendered 3D visual displays of the segmented images.

Begin with opening the CT dataset saved in the analyze format. Use the default settings in the pop-up window, then open the plugins menu and under utility select merge volumes. Uncheck rescale components.

Click assign Second input. Choose the segmented fat data for the second input and use the default settings in the popup window. Then apply the plugin for a larger view of the subject mouse.

Double click the volume view window. Return to the color slash opacity tab. The component dropdown box refers to which dataset is currently being edited.

Two sliders are located at the bottom of the tab. They determine the relative brightness of each component dataset within the overlay using values between zero and one. To change the color to gray scale, for instance, go to the scalor color mapping section.

Double click one of the sliders and drag it out of the box. Add a second slider by clicking anywhere within the slider area. Make the left color slider black and the right color slider white.

Next, go to the scalor opacity mapping box and create a new point by clicking within the box. This will give a total of three points in the window for the middle point. Change the scalar value to about minus 3000 and change the opacity value to zero.

At the right of the window is the third point change its scalor value to about 32, 000 and its opacity to 0.25. The first point can be anywhere to the left just as long as the opacity value is set to zero. With the scalar set switch to component two, which should edit the appearance of the fat, change each of the color sliders to red by double clicking and sliding the hue slider H to the end.

This false colors the fat to red To create a three panel rotation movie displaying the CT fat and overlay first click and drag the subject mouse into an upright position with the back facing U.Second under component weights, set the value of component two to zero so that only the CT scan is displayed. Third click review followed by camera and select a number of frames for the rotation movie. Fourth, change the X rotation value to 360 degrees.

Fifth select create in the popup dialogue box. Create a new folder named CT and save the file in TIF format, which will output a series of rotation images. Repeat these steps for the fat image as well as for the overlaid fat CT image, saving their rotation images to their own folders to generate a rotation movie from the output images, open image J and import the image sequences.

Select the first image in the CT folder and the others will be automatically selected. Repeat this process for the fat and overlay sequences with one of the stacks. Still open.

Open the ROI manager. It is under analyze tools, and then ROI manager draw an ROI around the subject mouse that excludes needless background pixels. When completed, click add in the ROI manager.

Then to every image sequence, apply the same ROI When the ROI is on all the stacks, right click. Within the ROI select, duplicate, and select. Check the duplicate stack.

This separates the ROI from the rest of the image. Now close the larger image stacks and repeat this procedure for all three image sequences. To combine the stacks, use the command combine, which is under stacks, and then tools.

Select the CT stack for stack one and the fat stack for stack two. Then repeat the process. Selecting the newly combined stacks for stack one and the overlay stack for stack two.

This completes the creation of a three panel image rotation stack. Preview the stack by selecting play in the lower left corner of the image window. Then save it as an A VI movie.

Obese B six V LE OB J mice were employed to illustrate the feasibility of the Alber CT system. For CT based fat content measurements, they were compared with C 57 black six wild types. On the left is the total CT volume of an obese mouse.

At center is the fat volume in red, and at the right is the overlay. Similar analysis of wild type animals shows the substantial difference in fat content compared to the obese mouse. Total volume, fat volume and volume ratios were calculated for each animal.

The averaged fat to total volume ratio for the wild type group and the obese group was 0.09 and 0.42 respectively. These values differed significantly with a P value of 0.001. After watching this video, one should have a solid understanding of how to segment the fat volumes within a CT data set of a living mouse once mastered.

This technique should take under 30 minutes to perform. Thanks for watching, and we'll see you again next time.