1Carestream Molecular Imaging, 2Department of Chemistry and Biochemistry, University of Notre Dame, 3Freimann Life Science Center, University of Notre Dame, 4Research and Development, Oncovision, GEM-Imaging S.A.
Sasser, T. A., Chapman, S. E., Li, S., Hudson, C., Orton, S. P., Diener, J. M., et al. Segmentation and Measurement of Fat Volumes in Murine Obesity Models Using X-ray Computed Tomography. J. Vis. Exp. (62), e3680, doi:10.3791/3680 (2012).
Obesity is associated with increased morbidity and mortality as well as reduced metrics in quality of life.1 Both environmental and genetic factors are associated with obesity, though the precise underlying mechanisms that contribute to the disease are currently being delineated.2,3 Several small animal models of obesity have been developed and are employed in a variety of studies.4 A critical component to these experiments involves the collection of regional and/or total animal fat content data under varied conditions.
Traditional experimental methods available for measuring fat content in small animal models of obesity include invasive (e.g. ex vivo measurement of fat deposits) and non-invasive (e.g. Dual Energy X-ray Absorptiometry (DEXA), or Magnetic Resonance (MR)) protocols, each of which presents relative trade-offs. Current invasive methods for measuring fat content may provide details for organ and region specific fat distribution, but sacrificing the subjects will preclude longitudinal assessments. Conversely, current non-invasive strategies provide limited details for organ and region specific fat distribution, but enable valuable longitudinal assessment. With the advent of dedicated small animal X-ray computed tomography (CT) systems and customized analytical procedures, both organ and region specific analysis of fat distribution and longitudinal profiling may be possible. Recent reports have validated the use of CT for in vivo longitudinal imaging of adiposity in living mice.5,6 Here we provide a modified method that allows for fat/total volume measurement, analysis and visualization utilizing the Carestream Molecular Imaging Albira CT system in conjunction with PMOD and Volview software packages.
2. Image Acquisition and Reconstruction
3. Image Analysis
Image analysis is performed using the PMOD (PMOD Technologies LTD, Zurich, Switzerland) analysis software. Images are segmented in PMOD according to tissue density-first for total volume and then for fat volume.
3.1 Images may be reduced for analysis to minimize computational demands.
The message: "Bounding box will change" displays once the reduction is complete.
3.2 Images can be masked to eliminate bed and nose-cone elements for subsequent volume-of-interest (VOI) analysis.
The message: "Irreversible data operation. Do you want to continue?" displays.
3.3 First, segment the image for total animal volume:
Reported statistics represent the total volume.
3.4 Next, segment the image for fat volume:
The reported statistics represent the fat volume.
Optional: If skin/peripheral density remains, the "Erosion and Dilation" protocol below may be performed to eliminate these regions for VOI analysis.
4. Visualization of CT Images
4.1 VolView v3.2 (Kitware, Clifton Park, NY, USA) was utilized to create rendered 3D visual displays of segmented images.
4.2 Return to the Color/Opacity tab. The component drop-down box refers to which data set is currently being edited. Two sliders are located at the bottom of the tab and determine the relative brightness of each component data set within the overlay, using values 0 to 1. For component 1, the CT, we prefer to use a grayscale color scheme. To change the color:
4.3 To create a three-panel rotation movie displaying the CT, fat, and overlay:
4.4 ImageJ v 1.43u was used to generate a rotation movie file using the VolView output images.
5. Representative Results
Results for three WT (C57BL/6J) mice and four obese (B6.V-Lepob/J) mice are reported here as a representative example of fat/total volume ratio measurements employing the Albira CT system. Figure 1 below provides a representative display created with VolView v3.2 for the segmentation (i.e. total volume and fat volume) of obese mice CT images.
Figure 1. Representative CT images segmented for fat. (A) Obese mouse (B6.V-Lepob/J) CT total volume in grayscale, (B) fat volume in red, and (C) image fusion. (D) WT mouse (C57BL/6J) CT total volume in grayscale, (E) fat volume in red, and (F) image fusion.
Total volumes, fat volumes, and calculated fat/total volume ratios are reported below in Table 1 for each WT mouse and each obese mouse. The averaged fat/total volume ratio for the WT group and the obese group was 0.09 and 0.42 respectively (Figure 2). The fat/total volume ratios for the WT mice versus the obese mice was found to differ significantly (p = 0.001).
|WT (C57BL/6J)||Total (cm3)||Fat (cm3)||Fat/Total Ratio||Obese (B6.V-Lepob/)||Total (cm3)||Fat (cm3)||Fat/Total Ratio|
|Animal 1||28.79||3.00||0.10||Animal 1||66.25||26.75||0.40|
|Animal 2||33.25||3.05||0.09||Animal 2||61.15||26.31||0.43|
|Animal 3||30.30||2.63||0.09||Animal 3||64.19||25.7||0.40|
Table 1. Total volume, fat volume, and fat/total volume ratios for WT and obese mice. Total and fat volumes were derived from segmented images using PMOD VOI analysis.
Figure 2. Averaged fat/total volume ratios for WT mice versus obese mice. Averaged fat/total volume ratios for WT (C57BL/6J) and obese (B6.V-Lepob/J) found to be 0.09 and 0.42 respectively are displayed. (Error bars = single standard deviation). WT versus obese fat/total volume ratios were found to differ significantly (p-value = 0.001).
Here, utilizing B6.V-Lepob/J mice we have illustrated the feasibility of performing fat content measurements in a small animal model using the Albira CT system. These measurements are consistent with expectations for comparisons of intra-group and inter-group measurements. Firstly, representative results provided here highlight limited intra-group variability in measurements of fat/total volume ratios in both WT and obese mice groups using these procedures. Secondly, fat/total volume ratios for WT versus obese mice differ significantly. Finally, based on comparisons (not shown) with previous values reported for relative total fat mass and percent body fat for WT versus B6.V-Lepob/J mice, our measurements for fat/total volume ratios for WT versus B6.V-Lepob/J mice fall within an expected range,7, 8.
The methods detailed here could be applied or adapted to other models and/or study objectives. Modifications in reconstruction parameters may be required to achieve specific objectives. For example, Judex et al. (2010) reported that 50 μm resolution images were required for some region specific analysis. One cm isotropic volumes of an image may be selected for 35 μm reconstructions in the Albira 5.0 Suite Reconstructor using the "HR" reconstruction option. Once the Albira CT system has been utilized for region and organ specific fat content measurements the full benefits (i.e. simultaneous region and organ specific fat volume measurements and longitudinal measurements) of CT based fat content analysis may be realized for the Albira CT system.
Here we provide a detailed, step by step method for the measurement of fat content in living mice using X-ray CT imaging. We acquired our CT data sets using an Albira image station, and performed subsequent segmentation and analysis using the PMOD software suite. Finally, we provide instructions to enable facile rendering and visualization of the fat tissue distribution within the whole animal.
Todd A. Sasser, Shengting Li, Sean P. Orton, and Seth T. Gammon are employees of Carestream Molecular Imaging. Carlos Correcher is an employee of Oncovision, Gem-Imaging S.A. W. Matthew Leevy is a consultant for Carestream Molecular Imaging.
We warmly thank the Notre Dame Integrated Imaging Facility (NDIIF) and Carestream Health for financial support for this project.