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

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.

Influence of age and position on the CT number of adipose tissues in pigs.

The location of adipose tissue depots is important in determining their significance. Research into the physical and chemical differences between these depots is therefore of interest. Using image analysis, this paper examines the influence of location on the linear attenuation coefficient of adipose tissue for X-rays, in computed tomography (as indicated by CT number) at three time points. Nine pigs were CT scanned on three separate occasions approximately 1 month apart. The mean CT number was -78, -100, and -104 for visceral adipose tissue (VAT) from the first to the final scan, respectively. The corresponding CT numbers for subcutaneous adipose tissue (SAT) were -80, -101, and -106. There was a significant difference between the CT numbers at each location at each scan (P values from 0.025 to <0.001) and between the CT numbers for each location at different times (P < 0.05). In a separate analysis of the final scan session, the mean CT number of adipose tissue at increasing distances from a mathematically defined center of the animal was determined. Regression analysis showed that the CT number of adipose tissue decreases with increasing distance from the animal's center (y = -102.7 - 0.04 x, P < 0.001, where y is the predicted CT number for adipose tissue, from the animal center (x = 0) to the skin (x = 100)). It can thus be expected that the overall mean CT number for adipose tissue can be used as an indicator of the relative quantities of adipose tissue at each location if the mean for each is known.

Hounsfield Unit dynamics of adipose tissue and non-adipose soft tissues in growing pigs.

Changes in the Hounsfield Unit value of adipose tissue and of non-adipose soft tissue during growth are poorly documented. This study examines the HU of these tissues in growing pigs. Computer tomography scans were made in nine growing pigs on three occasions, approximately four weeks apart. Average body weight was 51, 94, and 121 kg for each successive scan. Images from the level of the diaphragm to the hips were analyzed. The mean HU and its standard deviation, for adipose tissue and for non-adipose soft tissues was determined for each pig. The mean adipose tissue HU for all pigs was -90, -98 and -101 on the first, middle and last scans, respectively. Corresponding HU values for non-adipose soft tissues were, 52, 51 and 49. There was a significant difference (p<0.01) between HU at each scan time for each set of tissues.

Plasma concentrations of cortisol and PGF2alpha metabolite in Danish sows during mating, and intrauterine and conventional insemination.

BACKGROUND: The aims of the present work was to study whether there are any relationships between cortisol and PG-metabolite in mated sows or inseminated with the intrauterine technique and compare these to changes occurring in conventionally inseminated sow. METHODS: Thirty three crossbred sows (Danish Landrace x Danish Large White) were fitted with jugular vein catheters through vena auricularis from one of the ears. The sows were randomly divided into three groups (Boar-, IUI- and AI-group) and blood samples were collected before, during and after service. In a final evaluation only 25 sows that became pregnant and farrowed piglets at full term were used. RESULTS: Cortisol concentrations increased in all groups but Boar-group (n = 8) had a significantly higher cortisol during 10 to 20 min after service than sows in AI-group (n = 8). In mated sows cortisol concentrations peaked at 15 minutes after service. The Boar-group (n = 8) showed no ascending PG-metabolite levels during the whole experiment, while both IUI- and AI-groups (n = 9 and n = 8, respectively) had a 2.5-fold increase in PG-metabolite 15 minutes after service. CONCLUSION: In conclusion, mating of sows by a boar results in a greater increase of cortisol than AI and without an elevation of PG-metabolite levels, which was seen in both the inseminated groups. It was also demonstrated that IUI-group had an earlier significant increase of PG-metabolite levels than sows inseminated conventionally. Further investigation using different semen extenders or even different type of insemination catheters might be helpful in understanding the reason for an immediate increase of PG-metabolite after insemination but not after mating.

Changes in the relative thickness of individual subcutaneous adipose tissue layers in growing pigs.

BACKGROUND: The thickness of the subcutaneous fat layer is an important parameter at all stages of pig production. It is used to inform decisions on dietary requirements to optimize growth, in gilts to promote longevity and finally to assist in the calculation of payments to producers that allow for general adiposity. Currently for reasons of tradition and ease, total adipose thickness measurements are made at one or multiple sites although it has been long recognized that up to three well defined layers (outer (L1), middle (L2), and inner (L3)) may be present to make up the total. Various features and properties of these layers have been described. This paper examines the contribution of each layer to total adipose thickness at three time points and describes the change in thickness of each layer per unit change in body weight in normal growing pigs. METHODS: A group of nine pigs was examined using 14 MHz linear array transducer on three separate occasions. The average weight was 51, 94 and 124 kg for each successive scan. The time between scanning was approximately 4 weeks. The proportion of each layer to total thickness was modeled statistically with scan session as a variable and the change in absolute thickness of each layer per unit change in body weight was modeled in a random regression model. RESULTS: There was a significant change in ratios between scans for the middle and inner layers (P < 0.001). The significant changes were seen between the first and second, and between the first and final, scan sessions. The change in thickness per unit change in body weight was greatest for L2, followed by L1 and L3. CONCLUSION: These results demonstrate that subcutaneous adipose layers grow at different rates relative to each other and to change in body weight and indicate that ultrasound can be used to track these differences.

Quality control in boar semen production by use of the FACSCount AF system.

A simple and rapid flow cytometric method has recently been developed for simultaneous determination of sperm concentration and viability in semen from domestic animals. Use of SYBR-14 trade mark in combination with propidium iodide (PI) allows estimation of the proportion of live sperm (viability). An internal standard of fluorescent microspheres (beads) makes it possible to determine the sperm concentration during the same analysis. In the first experiment, the relationship between sperm viability and litter size was investigated. The second experiment explored whether a smaller variation in the number of motile sperm per insemination dose could be obtained using the FACSCount AF flow cytometer than using a spectrophotometer. Results in the first experiment show that sperm viability is closer related to litter size than is the traditionally used motility parameter. Although the flow cytometer is precise and objective, a limited effect on litter size should be anticipated if ejaculates are selected for insemination according to the percentage of viable sperm. However, the present trial used large insemination doses (2.3 x 10(9) motile sperm/dose) which partially compensate for the differences in motility and viability between boars and ejaculates. In the second experiment it was found that variation in the number of motile sperm per insemination dose could be reduced significantly if the FACSCount AF flow cytometer rather than the Corning 254 spectrophotometer was used for determination of sperm concentration in the raw semen. It is concluded that the FACSCount AF flow cytometer is a strong tool for improvement of the quality control in artificial insemination (AI) centres.