By Gary Tufel

Because of reductions in laboratory budgets and a shortage of trained lab personnel, hematology analyzers must perform more functions, operate more efficiently, and incorporate even more automation of what are presently manual processes, according to Richard Kendall, Hematology Scientific Affairs, Abbott Diagnostics Division (Abbott Park, Ill).

“The average age of lab workers is increasing,” Kendall says, and the number of younger replacements is lagging, creating what he calls a potential crisis of staffing. This in turn has driven laboratory managers to look for new efficiencies. For example, multidiscipline laboratories use multiskilled but less specialized technologists, and automation of hematology analyzers extends beyond the simple CBC, he says.

Kathy Turner, Abbott’s hematology worldwide marketing director, adds that increased automation of analyzers will also be a benefit to smaller labs—as well as to lab workers, who are generalists and not fully trained in the more complex manual functions of hematology analysis.

Another key for the next generation of analyzers: the need for only one pass of the blood sample through the analyzer. Currently, it’s often necessary to repass samples to obtain results. Abbott’s goal is to develop analyzers that minimize the number of repeats and reflexed tests. Recovering and repeating samples for extra tests such as optical platelet counts and nucleated red blood cell counts is a time-consuming process. “Our aim is to get as much information from the blood count as we can the first time, every time,” says Kendall. To that end, Abbott is introducing a new high-end analyzer in early 2005 and another within about a year.

“Every manufacturer is searching for that kind of efficiency,” says Turner. Others may add aftermarket features to existing analyzers, but that adds cost and complexity. “Our goal is to use a hematology analyzer designed to multi-task,” she says. “We now have a very high level of first-pass efficiency, but it is very difficult to be specific about manual review rates because it varies from hospital to hospital and depends on the patient population as well as the laboratory’s own rules.”

Turner says the Abbott instruments, including the current Cell-Dyn 4000 and 3200, are designed so that the bulk of the work is automated and the need for manual intervention is eliminated. She adds that Abbott also offers a number of different analyzers for the needs of different-sized labs, hospitals, and doctors’ offices, from the high-end, highly sophisticated Cell-Dyn 4000 down to the smaller Cell-Dyn 1700 and 1800.

McDonald Horne, MD, Department of Laboratory Medicine, Clinical Center, National Institutes of Health (NIH) in Bethesda, Md, uses the Cell-Dyn 4000 because, “It does a better job with white cell differentials than others that NIH has tried. That analyzer is unique because it performs fully automated CD3, CD4, and CD8 counts—the cell count for monitoring patients with HIV,” he says.

But Horne says the analyzer has had mechanical problems, and that next spring Abbott will introduce an analyzer that is better mechanically. (Abbott is constrained by FDA regulations from discussing the product specifically.)

All the analyzers perform similar tasks with slightly different features, Horne says, but the Cell-Dyn 4000 is best for white blood cell analysis, and better for NIH because of the types of diseases its patients have, which could be less important in commercial clinics. The instrument also analyzes young red blood cells (reticulocytes), mostly measuring RNA in 1- or 2-day-old red blood cells. Reticulocyte analysis measures how rapidly immature red blood cells are made by the bone marrow and then released into the bloodstream. Horne says this fairly new capability is a significant advance because manual methods were imprecise and labor-intensive. “Counting thousands of cells improves the quality of the measurement substantially,” he says.

“All analyzers measure the MCV (mean cell volume) of red cells, but the Bayer Advia measures reticulocyte function as well as cell size,” says Horne. He adds that the Bayer Advia is very sensitive to iron deficiency, a valuable feature to have in a general hospital with children as patients.

But Horne would like to see more features. “In large community hospitals, there are robotics and other ways of handling samples. It would be helpful for us to have instruments that could handle other bodily fluids, such as bone marrow fluids in larger quantities, and spinal and other fluids. Today, it has to be done manually with a microscope,” he says.

Abbott has also developed an automated method for T lymphocyte population analysis, which commonly has to be done as a “send out” in commercial labs. Horne says an analyzer that will measure white blood counts and platelets as well as T cell counts will be beneficial for places with many AIDS patients. “It will be good to be able to do those measurements in a routine lab.” Although the Cell-Dyns already have this feature, NIH did not find it satisfactory and so has not implemented it, Horne says.

In certain anemias, analyzers mistake cells for platelets, Horne says, and there have also been chronic problems with platelets clumping so the instrument sees them as something large and gives a lower platelet count. “Technicians can miss that,” he says.

These problems commonly occur with impedance counts. Abbott has made advances using specific antibodies that will measure platelets, only increasing the accuracy of the count, Horne says. Kendall says the next generation of Abbott analyzers will encompass fluorescent analysis, and the capability will be expanded in the future, with applications in such fields as anemia diagnostics and infection. These new capabilities in future generations of analyzers, expanding on CBCs, will eliminate the need to send samples out to more advanced labs or perform the tests by hand, which could take hours, Turner adds.

Horne discusses another need: identifying young platelets, which can’t be done reliably by blood smears. “This is important because when platelet counts are low, we need to know whether they’re not being produced or are being destroyed. The youngest ones can be detected by the RNA present; in reticulocytes, the amount of RNA decreases as cells age over a day or two. When lots of red cells are destroyed and production goes up, more young cells enter the bloodstream. Some analyzers can tell how many have RNA, but it is important to know whether it’s an excessive amount so we can tell if it’s leaving the marrow early. That’s a sign that bone marrow is regenerating. Some instruments have been able to do this,” Horne says.

Cost Issues
Features to address these needs cost money, and the analyzers aren’t cheap. “Most instruments are purchased at costs of around $80,000 to $130,000,” says Turner.

“NIH rents its Cell-Dyn 4000s,” says Horne. “It’s better to rent than to get new models.”

Still, because of capital budgeting procedures, most hospitals purchase their analyzers, says Turner. Hospitals generally keep these analyzers for about 5 to 7 years. Turner estimates that about 60% of hospitals worldwide purchase analyzers, and about 90% in the United States purchase them.

Automation is key. Turner says that less money and fewer skilled technicians create more reliance on analyzers, so it makes sense to automate the instruments as much as possible. For example, Abbott will soon launch software that will examine hematology results, approve the ones that meet the laboratory’s own criteria, and release them to doctors, a practice that is now done manually. In effect, says Kendall, the software will act as a filter, differentiating those results that require human intervention from those that do not.

“This will help to eliminate human error, and it is in keeping with our goal of making this process efficient and easy to use,” says Turner.

This software can be viewed as a virtual lab manager, which can organize a number of lab functions. Abbott wants to make these available to a variety of hospitals in an affordable manner, particularly to smaller hospitals with smaller budgets.

Turner says this will speed up the process and get results to clinicians faster. “It is automated, more efficient, and will improve patient care,” she says. “This will make things quicker and provide more accurate results,” Kendall agrees. “Customers have told us this, and it is incumbent on us and other manufacturers to provide these efficiency improvements.”

Abbott also offers Cell-Dyn® eQC™, Abbott Diagnostics Division’s entry into World Wide Web-based QC Peer Review. This electronic peer review program adds value for Cell-Dyn users with rapid QC data submission and emailed electronic reports. Turner says it allows labs to assess the quality control of their analyzers by comparing their results with those of the same analyzers across the country, enabling labs to determine if their analyzers are getting consistent results and are calibrated correctly. This is yet another way to improve the efficiency of the hematology laboratory.

The Next Generation of Analyzers?
Amnis Corp is developing a system designed to advance the technology and automation of cell analysis. Although it is currently being used in research and it is too early for it to go into clinics, the system is moving toward clinical lab use, says Amnis Vice President of Research and Development William E. Ortyn.

Ortyn says that the ImageStream® System measures more features per cell than any other available technology. It combines, in a single platform, the population statistics of a flow cytometer, the detailed visual analysis of a microscope, and the analytical capabilities of advanced image processing software. It works like a flow cytometer, analyzing hundreds of cells per second and generating detailed population statistics. But it also visualizes like a microscope. Every dot in the scatter plot is associated with up to six images of the corresponding cell. These images reveal fine structure details of cell morphology, while the population analysis allows statistical rigor and detection of rare events.

“We developed an architecture that rapidly and effectively measures 300 parameters on an individual cell,” says Ortyn. In its current form, the instrument is used by researchers in biotech and pharmaceutical development, evaluation, and quality control of cell lines, and by those doing basic research in the study of disease. The ability to see high-quality cell images within a sample, combined with the statistical rigor imparted by large sample sizes and a broad feature set, is very appealing to the researcher. These same characteristics will play an increasingly important role in clinical diagnostics to expand automation, eliminate repeat tests, and provide pathologists with the confidence instilled by examining imagery, if desired.

When can labs expect to use the instrument? Ortyn says it is already being used to some extent for hematology analysis, and that some large manufacturers are interested in it because they see it as a way to automate further. “Our system offers the ability to replicate exactly what a human technician would do,” he says.

Gary Tufel is a contributing writer for Clinical Lab Products.