Vol. 20 Issue 18
Automated urinalysis morphology images prove useful in analysis and training.
Ask lab experts to name the benefits of automated urine microscopy, and they will probably cite improved turnaround times (TAT) first. To be sure, the automation technology that debuted in the mid-1990s substantially improves TAT in any lab adopting it.
According to many using a system also photographing and storing sample images, another important advantage has become clear. This latest addition to automated microscopy technology provides an invaluable training tool for technologists and medical students.
Unique technology from Iris Diagnostics, Chatsworth, CA, uses a digital camera to take 500 photos of each specimen, which is equivalent to viewing 320 fields. Because they are digital files, the images are electronically stored and recalled at any time. This is a dramatic contrast with conventional manual urine microscopy, where only 10 fields are viewed. Much of the iQ Series of automated microscopy system's value comes from its digital attributes. Through its patented neural network Auto-Particle Recognition, the system enables careful specimen morphology (organisms' form and structure) study, unlike other available microscopy technology. This quality, too, makes an important contribution, as the system serves a dual functionroutine urinalysis and a training system using the stored images for teaching urinalysis sediment identification.
In short, adding photographing and storing sample images to proven automated microscopy has not just provided a more accurate way to assess specimens, but also advanced the field of urinalysis by enabling the people who train in it to become much better at what they do.
To understand the difference automated microscopy imaging makes as a training tool, it helps to understand how current urine microscopy is used for training. Urine samples are inherently unstable. The various elements laboratorians analyze and categorize break down quickly. In fact, once a wet-mount slide is made from a drop of urine, the sample remains stable for only about 10 to 15 minutes, according to Jann Rappe, hematology manager, Providence St. Peter Hospital, Olympia, WA. That's not much time for a senior technologist to demonstrate something to a trainee, or check the accuracy of her work. Nor is there any way for the trainer to preserve an unusual specimen for teaching purposes.
Image-saving automated microcopy addresses all of those issues. The digital images are taken before the elements in the urine break down, and are as static as pictures in a book. So educators can select a variety of images trainees are likely to encounter in the lab, and teach with those. They can also add into the stored library rare but important images with which trainees, and even experienced technologists, should familiarize themselves.
"Recently, we did a routine urine on an inpatient, and I found tumor cells in the urine," Rappe said. "It was totally unexpected and very rare to find. Now, I have photos I can show all 24 people who work all shifts in this lab, so they can be looking out for it. There is no way I could have done that with wet-mount slides."
When Rappe teaches technologists to do urinalysis these days, she has them practice on 10 to 20 saved images, of both typical and atypical specimens. Because the images are saved files, they can be shown to any technologist on any shift at any time.
Three different interviewed lab managers, including Rappe, described training as an added advantage of automated microscopy imaging to the laboratory over and above productivity and automation. Kelly Terry, laboratory director, Methodist Le Bonheur Healthcare, Germantown, TN, noted having archived digital images to teach from and the automated system also simplifies the training process tremendously.
"With manual microscopy, you have a dip stick to do, you've got a microscopic to do, you've got potentially three-to-four confirmatory tests to do," she said. "You have to train how to do the testing, the quality control and the interpretation."
With the Iris system, training essentially means merely teaching technologists how to operate the instrument, including the quality control and troubleshooting, Terry said. Because the instrument is a walkaway system, technologists simply need to be shown how to load it and press the start button. The instrument will automatically run urine chemistry first, determine which samples need to be microscoped, and then perform the microscopy with no human intervention. Many labs do 100 percent microscopy because it can be performed quickly and automatically, and will catch abnormalities chemistry analysis alone will miss.
If the lab sets the criteria on the instrument as such, normal samples will be autoverified and sent directly to the laboratory's LIS. No confirmatory tests are needed because of the type of chemical strip used in the process.
The system also classifies urine particles into 12 categories and 26 subcategories, based on size, shape and texture. When used for training or with a pathological sample, the technologist verifies the classification and makes any necessary revisions, so trainees must learn how to classify particles as well.
This is a relatively straightforward, objective process because teacher and trainee are looking at the same digital image that, unlike a urine slide, does not degrade over time or look different to different people through a microscope.
James Peele, PhD, director of clinical chemistry, Baptist Medical Center, Jacksonville, FL, finds the objectivity of results turned out by the system gratifying both in a teaching context and in general lab work. It is especially useful, he noted, in mitigating the difference in experience levels often existing between work shifts. The training aspect also lessens the work variability potentially caused by those different levels.
"If you take on a person entirely trained in urinalysis, they get used to seeing certain images on the slide, and they can become very proficient with it," he said. "But as you change shifts and go from person to person, and people leave and new people come on board, you don't have the same level of proficiency as you do in one highly trained individual. In other words, you introduce variability because what one person sees and interprets one way, another person may interpret another way.
"The advantage the Iris iQ system has is that everybody can see the same image and everybody can learn from it the same way. You help to minimize that variability in interpretation," Dr. Peele said.
Rappe appreciates how the technology has dramatically reduced the time she needs to spend in the teaching process. Before microscopy was automated and digitized in her lab, she had to train technologists one on one. She would prepare a wet-mount slide, and then she and her trainee would take turns viewing it, so Rappe could be sure the trainee was seeing what she wanted her to see.
The individual training sessions placed large demands on Rappe's time. What's more, because the samples were always drying out and degrading during training, it took more of those individual sessions to train someone than it would have with stable specimens.
With stored images, Rappe spends a little upfront time showing trainees how to verify the particle classifications performed by the instrument.
Once they have that knowledge under their belts, she can give a whole group of trainees an array of, say, 20 samplesthat is, the digital images of those samplesand have them sort them on their own. When they're finished, she checks their work, which is relatively easy to do because the images don't change. Just as importantly, while they're doing their sorting, she's able to attend to her regular, non-training duties.
In addition to the far more efficient use of her time, Rappe feels more confident about the proficiency of her trainees with the automation technology. "It was very difficult to get a good grasp of the state of someone's training with manual microscopy," she said.
"There was no true way of knowing what they were seeing, because we couldn't reproduce it. So, you really didn't know if you were having issues with someone. You could only guess. With the stored images, I know when they need more training and when they don't."
There is another way in which automated microscopy technology stands out and helps in training, and therefore, analysis. The technology does a superior job of morphology compared to other approaches. In this case, morphology refers to the way the automated microscopy provides precise counts of particles along with images and particle classification. The images allow technologists to actually view the size, shape and texture of the specimen's particles, and verify the results if needed.
Dr. Peele said the morphology features give the lab more detailed, accurate and efficient results. Particle counts are not possible with manual microscopy or other instruments. With no images to check, technologists can't be confident the scattergrams are accurate. If the results on the scattergram fall within a certain range of concern, the only way to confirm them is look at the sample on the microscope, a time-consuming process.
Automated, one-step urine chemistry and microscopy is transforming urinalysis and removing its stigma as one of the most problematic processes in the lab. In labs without an automated urinalysis workcell, a significant number of samples will need to be examined manually under a microscope, one of the most labor-intensive and time-consuming processes in any medical lab. Manual microscopy and automated microscopy not integrated with the chemistry analysis inevitably create workflow bottlenecks by tying up technologists' time.
Once automation is implemented, the bottlenecks disappear and turnaround times plummet. At Terry's lab, the technology taking sample through chemistry and microscopic analysis has cut urinalysis TAT by 75 percent. "That's had a significant impact on our workflow," she said
Moreover, people can be trained more thoroughly, and with more confidence about their proficiency, than with microscopy without images. The training does not demand as much personal involvement from the trainera major boon to workflow, as well.
"We love the technology," Terry said. "It's very reliable. It removes the subjectivity from microscopic urinalysis. It truly standardizes the process."
Alan Reder is a freelance journalist based in Ashland, OR.