Limits...
Computer tomographic investigation of subcutaneous adipose tissue as an indicator of body composition.

McEvoy FJ, Madsen MT, Nielsen MB, Svalastoga EL - Acta Vet. Scand. (2009)

Bottom Line: In some circumstances, computer assisted analysis of the resulting image data can identify and measure anatomical features.Image analysis correctly identified the limits of the relevant tissues and automated measurements were successfully generated.The approach to image analysis reported permits the creation of various maps showing adipose thickness or correlation of thickness with other variables by location on the surface of the pig.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Small Animal Clinical Sciences, Faculty of Life Sciences, University of Copenhagen, DK-1870 Frederiksberg C, Denmark. fme@life.ku.dk

ABSTRACT

Background: Modern computer tomography (CT) equipment can be used to acquire whole-body data from large animals such as pigs in minutes or less. In some circumstances, computer assisted analysis of the resulting image data can identify and measure anatomical features. The thickness of subcutaneous adipose tissue at a specific site measured by ultrasound, is used in the pig industry to assess adiposity and inform management decisions that have an impact on reproduction, food conversion performance and sow longevity. The measurement site, called "P2", is used throughout the industry. We propose that CT can be used to measure subcutaneous adipose tissue thickness and identify novel measurement sites that can be used as predictors of general adiposity.

Methods: Growing pigs (N = 12), were each CT scanned on three occasions. From these data the total volume of adipose tissue was determined and expressed as a proportion of total volume (fat-index). A computer algorithm was used to determined 10,201 subcutaneous adipose thickness measurements in each pig for each scan. From these data, sites were selected where correlation with fat-index was optimal.

Results: Image analysis correctly identified the limits of the relevant tissues and automated measurements were successfully generated. Two sites on the animal were identified where there was optimal correlation with fat-index. The first of these was located 4 intercostal spaces cranial to the caudal extremity of the last rib, the other, a further 5 intercostal spaces cranially.

Conclusion: The approach to image analysis reported permits the creation of various maps showing adipose thickness or correlation of thickness with other variables by location on the surface of the pig. The method identified novel adipose thickness measurement positions that are superior (as predictors of adiposity) to the site which is in current use. A similar approach could be used in other situations to quantify potential links between subcutaneous adiposity and disease or production traits.

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Correlation between combined skin and subcutaneous adipose tissue thickness and general adiposity. Level-plot showing the correlation at the last scan (N = 12) between the combined skin and subcutaneous adipose tissue thickness and general adiposity (fat-index), as defined in the text. The x-axis, labelled "Measure point", shows position along the circumference of the pig (zero is dorsal and 101 is ventral). The y-axis, labelled "Slice number" describes distance along the length of the pig (zero is caudal, 101 is cranial). The colour scale indicates the correlation coefficient between skin plus subcutaneous adipose tissue thickness and general adiposity (fat-index). Correlation coefficient values < 0.2 have been truncated to 0.2 for this figure so that the full colour scale can be applied to values between 0.2 and 1.
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Figure 3: Correlation between combined skin and subcutaneous adipose tissue thickness and general adiposity. Level-plot showing the correlation at the last scan (N = 12) between the combined skin and subcutaneous adipose tissue thickness and general adiposity (fat-index), as defined in the text. The x-axis, labelled "Measure point", shows position along the circumference of the pig (zero is dorsal and 101 is ventral). The y-axis, labelled "Slice number" describes distance along the length of the pig (zero is caudal, 101 is cranial). The colour scale indicates the correlation coefficient between skin plus subcutaneous adipose tissue thickness and general adiposity (fat-index). Correlation coefficient values < 0.2 have been truncated to 0.2 for this figure so that the full colour scale can be applied to values between 0.2 and 1.

Mentions: The average thickness measurements from all pigs at the final scan session and the average correlation between thickness at each measure point and total mantle volume for the final scan session is illustrated in Figure 2. This figure demonstrates the strength of the currently used P2 site, which is situated at slice 39 in a region of high correlation with fat mantle volume. Figure 3 shows the average of the correlation coefficient for the association between skin plus SAT thickness and fat-index, at each measure point at the final scan session.


Computer tomographic investigation of subcutaneous adipose tissue as an indicator of body composition.

McEvoy FJ, Madsen MT, Nielsen MB, Svalastoga EL - Acta Vet. Scand. (2009)

Correlation between combined skin and subcutaneous adipose tissue thickness and general adiposity. Level-plot showing the correlation at the last scan (N = 12) between the combined skin and subcutaneous adipose tissue thickness and general adiposity (fat-index), as defined in the text. The x-axis, labelled "Measure point", shows position along the circumference of the pig (zero is dorsal and 101 is ventral). The y-axis, labelled "Slice number" describes distance along the length of the pig (zero is caudal, 101 is cranial). The colour scale indicates the correlation coefficient between skin plus subcutaneous adipose tissue thickness and general adiposity (fat-index). Correlation coefficient values < 0.2 have been truncated to 0.2 for this figure so that the full colour scale can be applied to values between 0.2 and 1.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2710334&req=5

Figure 3: Correlation between combined skin and subcutaneous adipose tissue thickness and general adiposity. Level-plot showing the correlation at the last scan (N = 12) between the combined skin and subcutaneous adipose tissue thickness and general adiposity (fat-index), as defined in the text. The x-axis, labelled "Measure point", shows position along the circumference of the pig (zero is dorsal and 101 is ventral). The y-axis, labelled "Slice number" describes distance along the length of the pig (zero is caudal, 101 is cranial). The colour scale indicates the correlation coefficient between skin plus subcutaneous adipose tissue thickness and general adiposity (fat-index). Correlation coefficient values < 0.2 have been truncated to 0.2 for this figure so that the full colour scale can be applied to values between 0.2 and 1.
Mentions: The average thickness measurements from all pigs at the final scan session and the average correlation between thickness at each measure point and total mantle volume for the final scan session is illustrated in Figure 2. This figure demonstrates the strength of the currently used P2 site, which is situated at slice 39 in a region of high correlation with fat mantle volume. Figure 3 shows the average of the correlation coefficient for the association between skin plus SAT thickness and fat-index, at each measure point at the final scan session.

Bottom Line: In some circumstances, computer assisted analysis of the resulting image data can identify and measure anatomical features.Image analysis correctly identified the limits of the relevant tissues and automated measurements were successfully generated.The approach to image analysis reported permits the creation of various maps showing adipose thickness or correlation of thickness with other variables by location on the surface of the pig.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Small Animal Clinical Sciences, Faculty of Life Sciences, University of Copenhagen, DK-1870 Frederiksberg C, Denmark. fme@life.ku.dk

ABSTRACT

Background: Modern computer tomography (CT) equipment can be used to acquire whole-body data from large animals such as pigs in minutes or less. In some circumstances, computer assisted analysis of the resulting image data can identify and measure anatomical features. The thickness of subcutaneous adipose tissue at a specific site measured by ultrasound, is used in the pig industry to assess adiposity and inform management decisions that have an impact on reproduction, food conversion performance and sow longevity. The measurement site, called "P2", is used throughout the industry. We propose that CT can be used to measure subcutaneous adipose tissue thickness and identify novel measurement sites that can be used as predictors of general adiposity.

Methods: Growing pigs (N = 12), were each CT scanned on three occasions. From these data the total volume of adipose tissue was determined and expressed as a proportion of total volume (fat-index). A computer algorithm was used to determined 10,201 subcutaneous adipose thickness measurements in each pig for each scan. From these data, sites were selected where correlation with fat-index was optimal.

Results: Image analysis correctly identified the limits of the relevant tissues and automated measurements were successfully generated. Two sites on the animal were identified where there was optimal correlation with fat-index. The first of these was located 4 intercostal spaces cranial to the caudal extremity of the last rib, the other, a further 5 intercostal spaces cranially.

Conclusion: The approach to image analysis reported permits the creation of various maps showing adipose thickness or correlation of thickness with other variables by location on the surface of the pig. The method identified novel adipose thickness measurement positions that are superior (as predictors of adiposity) to the site which is in current use. A similar approach could be used in other situations to quantify potential links between subcutaneous adiposity and disease or production traits.

Show MeSH
Related in: MedlinePlus