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BREAST CANCER RESEARCH MAY LEAD TO BETTER BEEF QUALITY

by: Sharla Ishmael

Who would have thought that breast cancer research would have anything to do with beef quality grading? What links the two together is ultrasound, or rather a new technology developed from ultrasound called elastography.

Elastography, which is the imaging of elastic properties of soft tissues using ultrasound, was invented more than a decade ago by Dr. Jonathan Ophir, director of the ultrasonics laboratory at the University of Texas-Houston Health Science Center. He and other health professionals across the globe are perfecting elastography as a diagnostic tool used, for example, to detect cancerous tumors of the breast or prostate more effectively than palpation by a doctor's fingertips.

At the same time Ophir was developing elastography, meat scientists in the United States and Australia were vigorously researching the use of ultrasound as a tool to predict carcass grade parameters, explains Dr. Rhonda Miller, an animal science professor in the meat science section at Texas A&M University. �We were real interested in ultrasound because it's noninvasive,� she says. �It doesn't destroy the carcass so you don't have any product loss.�     

     

The Introduction

About that time, Miller and her colleagues got a visit from an Australian who was doing similar research into ultrasound and beef carcass grading. On his way out the door, he happened to mention that he was on his way to see an ultrasound engineer in Houston who had invented a new way to apply ultrasound to human tissue to better understand some disease states. He said, �Would you mind if I told him about you guys�.�

The fellow in Houston turned out to be Dr. Ophir, and that was the beginning of what Miller calls �the ideal collaboration between animal agriculture and the medical field.� They share information with each other, Ophir's lab measures samples for Miller free of charge and, in the big picture, society benefits not only from the advance in scientific knowledge and application but the leverage of increasingly scarce research dollars as well.

Miller explains, �We had funding through the checkoff program in the early '90s, but we haven't gone back for a lot of funding. We've been using state funding (for advanced technology research) and also trying to use our collaboration with Jonathan (funded at least in part by the National Institute of Health) to keep working.�

So, over the last several years Miller, along with fellow meat scientist Dan Hale, ag engineer Dale Whitaker and a number of graduate students, have conducted a series of studies using elastography. Their success, so far, has been moderate.

It turns out that working with beef tissues is a little more complicated than what researchers are doing with human tissue. Even so, Miller believes using elastography for evaluating beef � and pork � carcass quality holds promise.

How elastography works

Basically, whether you're talking about beef or breast, the technology works the same way. A technician applies an ultrasound transducer (similar to what would be used to scan a steer's rib eye or do a sonogram on a pregnant woman) to the tissue.      

It takes a two-dimensional image to get a �before� picture of the tissue. Then pressure is applied to the tissue as a series of �light taps� says Miller. At the end of the compression, an �after� ultrasound picture is taken. The difference between the before-and-after pictures is analyzed with a software program.

�This software looks to see what tissues are collapsing or changing and what tissues aren't,� Miller explains. �It takes that information and forms an image called an elastogram. An elastogram is a picture of what areas are soft and hard in a tissue. (Ophir) has been working with this technology to look at breast cancer, because one of the problems of using ultrasound and mammography is that the tissue itself is distorted.

�So the actual size, dimension, location of the cancerous tumor you may not really be able to detect. Also with the other technologies, you don't learn anything about the tumor. You just know that there's a change in the tissue. Because as cancerous tissues evolve, they develop necrotic centers, which are hollow, or fluid-filled, which are very soft,� Miller adds.

�With elastography, because you don't distort the tissue...so you can see the hard areas and you can see if it's soft in the middle. That helps them grade the level of the tumor.�

Elastography and beef

So, how do you apply that to beef? Miller says it makes sense from a theoretical standpoint because when a carcass is warm, the fat is softer than the lean, and when a carcass is chilled, the fat is harder than the lean. Remember, an elastogram gives you a map of soft and hard areas in the tissue.

�We might be able to do not only marbling, but also be able to gather more information,� says Miller. �Our quality grading system is supposed to segment carcasses into categories based on palatability or eating characteristics. So Choice is supposed to eat better than Select. And that is true part of the time, but not all of the time.

More than just marbling

�The philosophy that I have is marbling has information,� she explains. �Marbling not only has a slight relationship to tenderness, it has an even stronger relationship to flavor and juiciness. Marbling is important in its relationship to palatability. But there's a lot of missing information there.

�We don't really have the ability to use marbling to predict eating quality as well as we would like. So if we could use this elastography where we could estimate marbling and gather additional information about the structural components or the tenderness of the meat, that would be great,� Miller adds.

For example, elastography could reveal information about muscle fiber components and connective tissue, both of which might help predict how tender meat from a given carcass will be � or how tough.

�Certainly there is Select meat that is tender,� Miller says. �It doesn't quite have the flavor and juiciness of Choice, but it's tender. And that meat may have more value than Select meat with the same amount of marbling that is tough. So this would give us much more information where we could decide as an industry how we wanted to grade our carcasses and put them into better classes for palatability."

She also points out that since they started working with elastography, other video imaging technologies have been commercialized that do a good job of predicting marbling. An example is the CAM system, which takes an image of a rib eye with a camera as the carcass is going down the line and distinguishes the marbling from the lean.

�What we would ideally like is (to develop) a system similar to the CAM system where you go and put the thing over the rib eye to take the image, then a little tiny 1 cm plate comes down in the middle of that rib eye and in a fraction of a second takes the information for an elastogram,� Miller says. �That is very realistic to be able to get to that point. But we have to know that the information we're getting is correctly related to something.�

Challenges and questions

For example, how does the information they get from raw beef relate to a cooked, final product on somebody's dinner plate? They also need a better understanding of how meat responds to compression, because muscle tissues contain a high percentage of water, which complicates the picture, literally.

�It's like a cake,� Miller explains. �When you test a cake out of the oven, you apply pressure to see if it's done. If it is, the structure collapses pretty uniformly and then springs back. We call that a stress relaxation curve. They are a very important part of the elastogram.

�Those curves are great as long as they are linear, but meat does it so that it's curvilinear. It will hold up to pressure, then all of a sudden it collapses,� she says. �So what we think is happening is that the connective tissues are linear and the meat part is curvilinear, which just throws everything out the window. We're trying to understand why the curves on some meat collapse very quickly and others don't.�

For example, an initial study at Texas A&M showed that 88 percent of the variability in Warner-Bratzler shear force tests (used to evaluate tenderness) was accounted for by the elastogram information. However, a second study that actually utilized improved image processing capability only accounted for 47 percent of the variation.

      She believes imaging software that is similar to those satellite pictures you see of terrain might help them solve these problems. And, Ophir is still fine-tuning the elastography process in order to get a clearer picture, Miller says. He once reminded her that it took 40 years to develop ultrasound to the point where it could really be used as a diagnostic tool.

      �We're still in the data analysis stage. Hopefully by the end of the summer or fall we'll have some answers as to whether we have good information. We might need to do additional samples,� Miller says.

      And even once they're confident the information is good, there lies another potential hurdle in the commercialization of the process: can elastography equipment hold up in the real-world environment of cold, wet packing plant facilities?

      In the meantime, somewhere there may be another scientist working on the answer to any of these questions, even though he or she might not know it yet. After all, a decade ago who would have thought to look at beef quality and breast cancer through the same viewfinder?

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