Real Time Ultrasound Technology: Current Status and Potential


James R. Stouffer and Yujun Liu
Animal Ultrasound Services, Inc.
Ithaca, NY

INTRODUCTION

The use of ultrasound for measuring fat and muscling in swine and other livestock was first introduced in the 1950's. This involved the use of an A mode ultrasonic unit with a transducer housing a single crystal for depth readings at one point. Initially ultrasonic equipment was used to measure fat thickness as a noninvasive substitute for the ruler probe. Subsequently A-mode readings were made in which muscle depth was observed in addition to the fat depth.

The next major development in which I was involved was the introduction of the Scanogram in 1969. The Scanogram produced B-scans by moving a single transducer over the animal while coordinating the exposure of a continuous series of intensity modulated A-mode signals on film with time exposure. Although the images were reasonably accurate, the technique was too slow and labor intensive to be practical. The animal had to remain motionless for 10 seconds for a complete clear scan of a loin eye to be produced.

The introduction of real time ultrasonic equipment in 1984 was a major development of accurate and practical equipment for use in live animal evaluation. A linear array transducer had a large number of elements (100) lined up in a row which were electronically fired sequentially 30 times per second. A complete cross sectional image was produced faster than the eye could detect. Therefore, this technology become known as "real time ultrasound."


CURRENT USE OF REAL TIME ULTRASOUND

The primary application of real time ultrasound for swine at the present time is for the measurement of fat thickness and loin eye area at the 10th rib. Depending on the characteristics of the ultrasonic unit, the operator may make the measurements on the frozen image at the scanning site or capture the image on a VCR or digitally on a computer. The captured images are usually evaluated with computer software and printed for presentation to breeders or producers. The interpretation of the cross sectional image requires as much time as it does to scan animals. There has been a lot of interest in developing technologies for automatic image interpretation in order to speed up the process and minimize the subjectivity or human judgment. Attempts have been made to automate the measurement of loin eye area but that has not been accomplished as yet.

Another approach is to do a longitudinal scan rather than a cross sectional scan. Animal Ultrasound Services, Inc. (AUS) has been involved in this activity for evaluating live hogs and pork carcasses for several years. Our studies have demonstrated that a longitudinal scan 5 cm off the midline between the 10th and last rib provides an accurate and highly repeatable indication of carcass composition. Another requirement for this scan to be accurate is for the ultrasonic beam from the linear array transducer to be perpendicular to the inside or bottom of the intercostal muscle on the inside of the rib cage. This requires the technician to have the transducer properly placed and oriented at the time the image is captured.

An automated and computerized image analysis system was developed for making multiple measurements of fat and muscle depth from the longitudinal scan. Results from our participation in the Canadian 1992 hog carcass project demonstrated the accuracy of this technique. Details of this study were reported in Jones et al. (1994a, b) and Liu and Stouffer (1995).

The objectives of this study were to develop an automated carcass value technology (CVT) system using real time ultrasound and computer technology to remove human judgment from ultrasonic image interpretation, to establish the accuracy and relationship of longitudinal scans to traditional cross-sectional scans in predicting carcass leanness, and to demonstrate the feasibility of using CVT system in modern slaughter plants.

A total of 325 market barrows and gilts were selected on the rail in a commercial slaughter plant in Canada. The right side of each carcass was scanned on the rail longitudinally between the 10th rib and last rib, five cm lateral to the midline of the carcass, and cross- sectionally at the 3 / 4 last rib.

The ultrasonic equipment consisted of an ultrasonic unit (Aloka Model 500V), a 17 cm long, 3.5 MHz linear array transducer, and a positioning device (U.S. patent 5,316,003, 1994). The computer hardware and software included a 486/33 MHz IBM-compatible computer with a Intel 487 math coprocessor, an image analyzer (AUSKey, Animal Ultrasound Services), an image grabber board (Data Translation DT2851), and a video monitor (Panasonic TR-930B). A portable video cassette recorder (Panasonic AG-2400) was used to record ultrasonic images for later review and manual measurements.

Descriptions of all dependent and independent variables used in this study were given as footnotes in Table 1. All data were analyzed using SAS (1988).

Table 1. Descriptive statistics of carcass and ultrasonic measurements
Variable aN MeanSD MinMax
HCWT32581.29 6.5965.6094.80
AUTOFD32519.68 7.02 5.4040.50
AUTOMD32553.82 5.3637.9068.00
LRFD324 17.05 6.15 5.90 37.40
R10FD32423.92 7.537.2045.90
R34FD13820.91 6.696.9041.70
R34MD13849.45 4.9938.3066.30
R34LMA13837.11 4.6727.1750.48
LEAN132232.00 3.3724.2540.31
GRLEAN32242.42 3.9233.9553.37
LOIN_L3239.20 1.096.4611.98
HAM_L32212.59 1.419.6316.20
SHLDR_L32310.21 1.097.4113.17
LEAN1P31239.37 3.1931.0248.87
GRLEANP31252.17 2.7844.0060.33
LOIN_LP31311.31 1.068.0114.31
HAM_LP31215.50 1.4511.7119.98
SHLDR_LP31312.56 1.049.8215.21
a AUTOFD: Automatic fat depth averaged from five measurements
AUTOMD: Automatic muscle depth averaged from five measurements
GRLEAN: Grade lean (kg), the sum of LEAN1, skinless square-cut belly (brisket bone and cartilage and buttons removed) and side (spare) ribs.
GRLEANP: Grade lean percentage (%) = GRLEAN x 2 x 100 / HCWT
HAM_L: Lean in ham (kg), defatted deboned ham muscle components.
HAM_LP: Lean percentage in Ham (%) = HAM_L x 2 x 100 / HCWT
HCWT: Hot carcass weight, kg
LEAN1: Lean (kg), the sum of the four lean primals of ham, loin, butt, and picnic.
LEAN1P: Lean percentage (%) = LEAN1 x 2 x 100 / HCWT
LOIN_L: Lean in loin (kg), regular loin (boneless, no subcutaneous fat cover) and tenderloin.
LOIN_LP: Lean percentage in Loin (%) = LOIN_L x 2 x 100 / HCWT
LRFD: Last rib fat depth from longitudinal scans, mm
R10FD: 10th rib fat depth from longitudinal scans, mm
R34FD: Fat depth from cross-sectional scans at the 3 / 4 last rib, 5 cm off midline, mm
R34LMA: Loin muscle area from cross-sectional scans at the 3 / 4 last rib, cm²
R34MD: Muscle depth from cross-sectional scans at the 3 / 4 last rib, 5 cm off midline, mm
SHLDR_L: Lean in shoulder (kg)
SHLDR_LP: Lean percentage in Shoulder (%) = SHLDR_L x 2 x 100 / HCWT

Table 2. Regression equations predicting weight (kg) of carcass lean, grade lean, and primal cuts using hot carcass weight and automatic fat depth and muscle depth (n=312)

Dependent Variable
Intercept

HCWT

AUTOFD

AUTOMD

RSD

R² x 100
LEAN1-.2030.3513a -.2836 a.1705 a 1.1987.64
GRLEAN-1.8112 c .5038 a-.2436 a .1491 a1.09 92.29
LOIN_L-1.2368 b .1009 a-.0770 a .0694 a.51 78.63
HAM_L.2672.1263 a -.1131 a.0792 a .6777.45
SHLDR_L.7596.1241 a -.0934 a.0220 a .5277.95
a P<.001
b P<.01
c P<.05

Table 3. Regression equations predicting weight (kg) of carcass lean, grade lean, and primal cuts using hot carcass weight, manual fat depth, muscle depth, and loin muscle area measured between the 3rd and 4th last rib of the carcass right sides (n=131)
Dependent Variable
Intercept

HCWT

R34FD

R34MD

R34LMA

RSD

R² x 100
LEAN1.1953.3814 a -.3426 a.1516 a ---1.3484.95
2.3066.3593 a -.3183 a--- .1800 a1.3185.58
GRLEAN-1.8404.5452 a .2947 a.1145 a ---1.2190.94
-.4943.5229 a .2738 a--- .1536 a1.1591.77
LOIN_L-1.3165 b .1208 a-.0972 a .0545 a--- .5277.98
-.6371.1111 a -.0876 a--- .0705 a.5079.86
HAM_L.0389.1299 a -.1373 a.0941 a ---.7076.06
1.5345.1204 a -.1241 a--- .0986 a.7275.06
SHLDR_L1.4579 b .1308 a-.1081 a .0031---.53 76.76
1.3953 b.1280 a -.1066 a--- .0111.5376.92
a P<.001
b P<.05

Table 4. Regression equations predicting percentage (%) of carcass lean, grade lean, and primal cuts using hot carcass weight and automatic fat and muscle depth measurements (n=312)
Dependent Variable
Intercept

AUTOFD

AUTOMD

RSD

R² x 100
LEAN1P36.6616 a -.3640 a.1829 a 1.5078.24
GRLEANP48.9019 a -.3065 a.1723 a 1.3576.43
LOIN_LP9.0095 a -.0986 a.0788 a .6364.52
HAM_LP14.1802 a -.1495 a.0789 a .8565.49
SHLDR_LP13.4752 a -.1159 a-.0252 a .6363.82
a P<.001

Table 5. Regression equations predicting percentage (%) of carcass lean, grade lean, and primal cuts using manual fat depth, muscle depth, and loin muscle area measured at the 3rd AND 4th last rib of the carcass right sides (n=131)
Dependent Variable
Intercept

R34FD

R34MD

R34LMA

RSD

R² x 100
LEAN1P38.6268 a -.4241 a.1835 a ---1.6276.46
39.9075 a-.4031 a ---.1981 a 1.6176.93
GRLEANP51.3618 a -.3539 a.1559 a ---1.4773.37
51.5657 a-.3346 a ---.1915 a 1.4076.05
LOIN_LP10.1547 a -.1167 a.0723 a ---.6562.56
10.3596 a-.1079 a ---.0859 a .6265.79
HAM_LP13.8101 a -.1762 a.1035 a ---.8866.78
15.1122 a-.1653 a ---.0966 a .9164.56
SHLDR_LP14.6654 a -.1314 a-.0077 ---.6565.01
14.4400 a-.1301 a ---.0156.64 65.34
a P<.001

The results of this study indicate that a computer based real time ultrasound system can be used to accurately evaluate multiple fat and lean measurements on a longitudinal scan between the tenth and last ribs. These measurements can accurately predict the composition of pork carcasses and major cuts.

Similar results have been accomplished on live hogs (Cisneros et al., 1996). The same technology can be used for selecting breeding stock. This technology has been used at major barrow shows to produce carcass evaluation on live hogs in lieu of carcass measurements in a packing plant because of the increasing difficulty to collect the latter.

POTENTIAL APPLICATION

Real time ultrasound technology will continue to be improved and this will provide for advancement in current applications. Improved image quality should result in greater accuracy in the measurement of fat and muscling. There will be expanded opportunities for automation and computerization and real time ultrasound for live animal and carcass evaluation.

Another application of real time ultrasound is to evaluate primal cuts to decide how they could best be utilized. External fat and amount of seam fat are important in deciding which hams should be processed for specialty markets. Belly thickness and ratio of fat to lean would be desirable information in sorting for different markets. Techniques for determining these characteristics could be developed for scanning live animals as well as carcasses and primal cuts.

The role of quality in value based marketing is becoming more important in the distribution of pork both domestically and for export. Measurements of intramuscular fat in live hogs and pork carcasses with real time ultrasound is very likely. The detection of soft and exudative muscle in pork carcasses and major boneless cuts is another area that real time ultrasound may be utilized with computer and software development.

The universal adoption of electronic identification in the swine and meat packing industry should be a driving force for the adoption of further automated and computerized real time ultrasonic systems. This could lead to pork carcass evaluation prior to splitting which is more accurate and easier to automate.

REFERENCES

Cisneros, F., M. Ellis, K. D. Miller, J. Novakofski, E. R. Wilson, and F. K. McKeith. 1996. Comparison of transverse and longitudinal real-time ultrasound scans for prediction of lean cut yields and fat-free lean content in live pigs. J. Anim. Sci. 74:2566-2576.

Jones, S. D. M., A. K. W. Tong, W. M. Robertson, and P. Skoczylas. 1994a. National Pork Carcass Cutout Project (1992) Part 1: A comparison of the 1978 and 1992 cut outs. Canadian Pork Council. 75 Albert Street, Suite 1101, Ottawa, Canada.

Jones, S. D. M., A. K. W. Tong, A. F. Fortin, C. Campbell, and W. M. Robertson. 1994b. National Pork Carcass Cutout Project (1992) Part 3: Evaluation of new technology for grading pork carcasses. Canadian Pork Council. 75 Albert Street, Suite 1101, Ottawa, Canada.

Liu, Y and J. R. Stouffer, 1995. Pork carcass evaluation with an automated and computerized ultrasonic system. J. Anim. Sci. 73:29-38.