Laboratory managers seek technology that can reduce cost and shorten turnaround time while maintaining or increasing quality. With the unprecedented increase in computing power, digital technologies are positioned to potentially transform the practice of laboratory hematology by improving laboratory productivity, better communicating results, and providing new insight into disease. One of these of technologies, digital imaging, is the subject of this article. Digital imaging is a technology by which a camera, combined with appropriate optics and illumination, creates a numerical representation of a physical object. Once in a digital format, the image can be analyzed, displayed, printed, or manipulated in ways that might not otherwise be possible.
In the laboratory the “physical object” may be cells or tissues on a glass microscope slide. For more than 50 years the digital imaging of cells has been performed to quantify cellular features or to measure molecular markers. Currently digital imaging is often used in the context of education or supporting remote diagnosis, particularly in anatomic pathology. But there is a significant history of this technology being utilized for hematology. This is not surprising, since hematology is among the clinical laboratory sciences most dependent on the assessment of cell morphology. For more than 100 years, microscopists have manually viewed blood films stained by Romanovsky methods to count cells, or to assess abnormalities of white or red blood cells. Although this requires little equipment, the manual microscopic review of blood films is tedious and time consuming.
Early applications of digital imaging
Attempts to apply digital imaging systems to hematology began as computers became available. In 1966, the Cydac Scanning Microscope System was described. This was followed by a more widely commercialized system, the Corning Larc, which performed a 5-part WBC differential count on spun smears of blood. During the 1970s there was great enthusiasm for digital imaging of blood smears, leading to commercialization of at least ten other imaging processing instruments.1 These systems, while greatly limited by the technology of the time, could perform morphologic and differential analysis of blood films prepared by wedge smears, or spin technologies. However, since the volume and uniformity of blood deposition onto the slide could not be controlled, total cell counts could not be done.
The laboratory analysis of whole blood dramatically changed in the 1980s with the introduction of flow-based analyzers. These instruments could perform a white blood cell (WBC) differential, count red cells, WBCs and platelets, and measure parameters such as hemoglobin concentration. Because of these great strides, digital imaging platforms were essentially abandoned. During the next 20 years flow-based blood analyzers became highly automated, integrated many new features, and grew in complexity.2 While technical approaches differ according to the type of flow-based analyzer, the analysis is usually accomplished by measuring cell interaction with laser light or electrical impedance to determine cell size and cytoplasmic features.
In all instances the assessment of cells is indirect, and as such, it is subject to ambiguities that can only be resolved by a laboratory professional reviewing a glass microscope slide. So called “flags” are messages generated by automated hematology analyzers that indicate technologist review is needed. Thus, in a wide range of samples processed by the flow-based analyzers (for example, 15% to 50%, depending on the patient population), the preparation and review of a blood smear microscope slide is required. For the laboratory with a high number of manual differential counts this can impose staffing challenges, add cost, disrupt the workflow, and lengthen turnaround time. Fortunately, digital imaging technologies are once again being introduced that can reshape how laboratory hematology is performed and alleviate some of these burdens.
It is an understatement to say that camera and computer technology has changed between the 1970s and today. We have experienced an explosion of digital products for the consumer market, and many digital technologies have been integrated into laboratory instruments. Today, digital imaging can be applied to hematology in several ways, as summarized in Table 1.==
Discussions of some of these technologies, such as the multiple digital products for proficiency testing and education, and whole slide imaging technology, are outside the scope of this article. We will illustrate two approaches that support clinical diagnostics: automating the microscopic review of the WBC differential, and an integrated hematology system based on digital imaging.
Automated review of the WBC differential
The manual WBC differential is widely used and conceptually simple, but it requires technical expertise in locating and identifying cells. This can be a challenge if laboratory professionals are not experienced in the review of difficult cases, which is increasingly common as staff shortages lead to more technologist cross-training. In hospitals with evening or overnight shifts, a backlog of difficult cases may be left for the early morning. Finally, performing many WBC differential counts on a daily basis is time-consuming and fatiguing for technologists.
Digital imaging of Romanovsky-stained blood films can improve the work environment and alleviate some of the burdens associated with performing a WBC differential. With properly prepared and well-stained blood films, imaging technology can locate WBCs, capture images of the cells, perform a preliminary classification of cell type, and then display those images on a monitor (Figure 1). The advantages of this approach are immediately evident, since the technologist is freed from preparing slides and locating cells and can manipulate cells on the monitor to confirm or reclassify the identity of 100 (or more) WBCs. Metaphorically, the technologist becomes the editor, rather than having to author the book.
Understandably there are nuances to successful imaging of whole blood. Of primary importance are the uniform application of blood on the microscope slide and the consistent staining of the cells. Control of these aspects lessens the difficulty of acquiring and analyzing cell images, which in turn affects imaging rate and the accuracy of cell classification. With high-speed computing technology it is possible to derive a microscopic differential count on many more cells than the traditional 100 cell count performed by manual microscopy. This has the potential to raise the precision of the differential count. A study of one automated WBC classification system demonstrated 89.9% accuracy in the classification of cell images when compared to human review of a glass slide.3 Notably, new digital hematology systems that provide automated results do not need to reach 100% classification accuracy, since by design a qualified medical technologist is required to view images on a monitor for definitive classification before the case is released to the laboratory information system (LIS). It is also important to note that this technology is not limited to white cells. Images of red cells, platelets, reticulocytes, and even circulating tumor cells may also be captured and displayed on the monitor.
Digital imaging systems for WBC differential may stand alone or be linked to other instruments in the laboratory, such as the laboratory information system or whole-blood analyzer. With certain systems, the analyzer may be configured so that if certain abnormalities or flags occur upon analysis, the blood tube can be routed to an automated slide maker and stainer so that a glass slide is available for digital imaging. Ideally these instruments all communicate with each other, and preferably they are in a physically integrated format.
The Food and Drug Administration broadly classifies instruments that automate the WBC differential as automated differential cell counters or cell locating devices. Cell locating devices include the CellaVision systems and the EasyCell assist. The Bloodhound™ Integrated Hematology System, manufactured by Constitution Medical, Inc., is both an automated differential cell counter and a cell locating device. Please note: This device is under development and is not currently cleared by the Food and Drug Administration. It is not available for sale within or outside the United States.
Integrated digital hematology system
The Bloodhound system is an instrument that is designed to print blood onto a microscope slide with a controlled method, automatically stain cells, perform a CBC with WBC differential, and locate WBCs by digital imaging, all in an analyzer with a footprint of 42 inches. If any potential abnormalities are flagged, the technologist then reviews images on an iMac® viewing station. Conceptually the system produces the automated results typical of a modern flow-based whole blood analyzer along with functions of the cell locating device previously described, all from analysis of the glass microscope slide (Figure 2).
Unlike devices that use a wedge or spinning approach to create a blood film, this system uniformly prints a consistent volume of blood on the glass slide in a reproducible format (Figure 3). The printed slide is stained with a proprietary Romanovsky stain, using fresh stain for each sample. A low-magnification imager counts red and white cells and platelets, and records the location of up to 600 randomly selected WBCs to perform a WBC differential. The selected WBCs and surrounding cells in their fields are then analyzed at high magnification to classify the WBC and reticulocytes and measure RBC parameters such as hemoglobin content and mean corpuscular volume. Both the low- and high-powered imaging stations use LED illumination with different wavelengths, also known as multispectral imaging, to enable these determinations. Because the volume of blood printed onto the slide is known and the numbers of cells in the print area are counted, it is possible to calculate the number of cells per microliter. Thus, a complete blood count and the common set of the parameters identified in the annual survey of hematology analyzers by the College of American Pathologists can be determined from a glass microscope slide at an intended processing rate of 60 samples per hour.4
A viewing station displays numerical data and images from the analysis of WBCs, RBCs and platelets. If the automated analysis resulted in any flags for these cells, the technologist can immediately view images on the viewing station to resolve the flag. The system automatically provides a 5-part WBC differential, with nucleated red blood cells (nRBCs) being separately counted and displayed so that they do not distort the WBC count. Any cell not identified in the normal 5-part differential categories of neutrophil, eosinophil, basophil, lymphocyte, or monocyte is placed into an unclassified category. When this occurs, a flag is set and a more detailed message is provided to explain the reason for the flag.
Before the case can be released, the technologist must assign any unclassified cells to a defined subcategory with a mouse click. Unusual morphologic findings, such as blood parasites, RBC inclusions, and giant platelets, can also be viewed and classified by the technologist. With the viewing station, it may not be necessary to handle or examine glass slides with oil-immersion microscopy, as the relevant images are displayed on the monitor. However, since a glass slide is prepared for every case, these are always available for review.
Implications for the future
The opportunities offered by this approach to digital hematology are intriguing. As an example, red cells are displayed in a montage of images that can be sorted by size, shape, or hemoglobin content. Thus, it is possible to assess anisocytosis or poikilocytosis in a quantitative fashion. A reticulocyte count is automatically determined for every sample without the need for special reagents. Coupled with measurements of RBC parameters, this may provide a deeper understanding of anemia. Imaging approaches may also prove to be more accurate in analyzing samples with low numbers of white cells or platelets, because virtually all the cells printed on the slide are counted. This may be useful in monitoring the recovery of bone marrow after chemotherapy, or better determining the need for platelet transfusion.
The digital images of cells on each case may be reviewed remotely away from the analyzer, and can be shared with multiple viewing stations. When necessary, the laboratory supervisor or pathologist can view the case by using an additional station. After cases have been finalized and sent to the LIS, reports with cell images can be sent to workstations in the hospital or to mobile devices. Images on each flagged case are archived for up to two years, which allows retrospective comparisons. Digital images also enable collaboration between laboratories for education, and facilitate the training of students and competency and proficiency testing in clinical laboratory science.
The automatic capture of digital images on every case may streamline laboratory workflow, especially when abnormalities are encountered.5 When the analysis of the sample triggers a flag, indicating a potential morphologic or numeric abnormality, images of cells are immediately available without the need to retrieve a blood tube, prepare a slide, stain the slide, and then find those abnormalities on a slide under oil-immersion microscopy.
Digital technologies impact virtually all aspects of life in the twenty-first century. As digital imaging is introduced to laboratory hematology, it has the potential to improve the work environment and laboratory productivity, to enable education, and to enhance communication with clinicians.
James Linder, MD, is Professor of Pathology and Microbiology at the University of Nebraska Medical Center and Chief Medical Officer at Constitution Medical Inc.
David Zahniser, PhD, is Chief Scientific Officer at Constitution Medical Inc.
- Tatsumi N, Pierre RV. Automated image processing. Past, present, and future of blood cell morphology identification. Clin Lab Med. 2002;22(1):299-315.
- Buttarello M, Plebani M. Automated blood cell counts: state of the art. Am J Clin Pathol. 2008;130(1):104-116.
- Briggs C, et al. Can automated blood film analysis replace the manual differential? An evaluation of the CellaVision DM96 automated image analysis system. Int J Lab Hematol. 2009;31(1):48-60.
- CAP Today, Laboratory Information Product Guide: Hematology Analyzers. December 2011;4-39.
- Ceelie H. Examination of peripheral blood films using automated microscopy; evaluation of Diffmaster Octavia and Cellavision DM96. J Clin Pathol. 2007;60(1):72-79.