Automated Tissue Micro Array slide analysis

The era of personalized medicine has brought with it the hope for new, better, and more-targeted cancer treatments. It has also instigated an explosion of immunological and DNA-based staining techniques that have created new challenges and opportunities in the area of pathology.

Advances in molecular testing used in cancer treatment are likely to have an impact on survival rates as great as that accompanying the advent of chemotherapy and radiotherapy. However, as high-tech as they may be, the power of these tests is limited by the ability of highly experienced pathologists to achieve deductive insights in their examination of microscope slides.

Pathologists mainly use two staining methods in molecular pathology, immunohistochemistry (IHC) and fluorescent in situ hybridization (FISH). IHC is employed to measure protein expression by way of antibodies, made visible by chemical stains. This technique has traditionally focused on whether or not a cell or group of cells is expressing a specific protein, typically indicated by the presence or absence of stain. New tests have called for the quantification of protein levels by means of both staining intensity and the pattern and location of staining in each cell.

FISH, on the other hand, is a tool to identify the presence, location, and number of specific sequences of DNA in a cell. It is fast becoming the preferred method for identification of gene amplification. In FISH, fluorescent-dyed DNA probes are hybridized to DNA sequences and located by the fluorescent light produced upon excitation.

Improvements in IHC and FISH techniques for pathology had not until recently been matched by advances in imaging technology. But automation has made that connection, addressing the challenges of establishing and maintaining analytical methods characterized by high reproducibility and accuracy.
This article discusses the challenges pathologists face in analyzing microscope slides and considers how new developments in automated image analysis can help to overcome them, as well as manage the explosion of data generated by the use of Tissue Micro Array (TMA) slides.

Automation Relieves the Human Eye

Pathologists must cope with three main areas of challenge in their field: productivity, accuracy, and objectivity.

Firms are under increasing pressure to improve productivity, i.e., to generate more data and process more slides. Tackling the mountain of work manually places a constant strain on resources, staff, and finances. And for those analyzing TMAs, this burden is likely to worsen rapidly.

In any field of science dependent on observation, accuracy is essential. However, it is well reported that, after prolonged visual study, eye and specific cone fatigue can significantly affect a person’s ability to discern color changes and identify unusual objects. The TMA slide format has compounded this effect hundreds of times over. With densities exceeding 600 samples per individual slide, one can see how quickly fatigue becomes an issue.

Finally, there is the question of objectivity. The nature of the human eye is such that every person sees an object slightly differently from the way others see that same object. Subjectivity in this regard is therefore innate. Also, tints and shades can appear to change from one setting or context to another. Different observers may report seeing different features on the same object, as may a single observer at different times.

Automation can improve the practice of pathology by overcoming the limitations of manual microscopy. Some benefits are immediately evident. Digital analysis is not affected by fatigue. Computers can be programmed to recognize visual patterns accurately, and they are better than the human eye at detecting subtle variations in shading and intensity. Tracking large data sets is trivial for well designed systems and databases. Also, computers are consistent, impartial, and objective in their analytical observations.

A case in point is specific cone fatigue, which is a sort of temporary color blindness. When it afflicts a tired pathologist, it causes that person to be momentarily unable to register a range of colors. An automated instrument is not susceptible to such debility.

Indeed, image analysis computing can manage and process huge quantities of data at a phenomenal speed without suffering from any human limitation.
Applied Imaging Corp. (San Jose) began working in this area in the mid-1990s. Its aim was to automate the spadework of anatomical pathology by combining the capabilities of the pathologist’s eye with the power of digital image analysis. The efforts of a team of computer scientists, pathologists, and imaging engineers have resulted in the Ariol automated image analysis system (see Figure 1).

Fig 1: The Ariol automated imaging system by Applied Imaging Corp. (San Jose).

The Ariol provides a new investigative toolbox for the pathologist. Applied Imaging designed the system to supplement pathologists’ experience and training by presenting an objective, consistent, high-resolution view of specimens amenable to the generation of quantifiable results. The technology has application in a variety of pathology settings, including pharmaceutical and biotechnology laboratories, cancer research institutes, university medical centers, and clinical pathology laboratories. It promises to benefit the healthcare professionals whose work relies on pathology data.

Slide Handling and Imaging

Throughput limitations have been a major bottleneck for microscope slide analysis. Managing today’s growing mountain of slides and tests requires a system that can process a large volume of slides at one time and provides easy slide handling and manipulation. The Ariol system’s slide loader can manage up to 50 slides in robust trays and facilitates the transport of slides to and from the microscope stage (see Figure 2). Slides can be scanned automatically unattended—even overnight—and trays can be continually loaded and unloaded for around-the-clock operation with virtually no system downtime.

Fig 2: The Ariol slide loader by Applied Imaging Corp.

The image analysis system is also designed to read the slides’ unique bar codes and relate the coded information to a specific set of procedures required to analyze the slide. This mechanism enables the system to analyze slides of more than one type in a single run. As the foundation of the system’s database, the bar codes are keys to a treasure trove of sample history and data.

Rather than acting as a dumbwaiter that simply pushes slides through the system, the slide loader is a delicate and responsive tool that can recall slides to the stage and even relocate the stage itself. Slides are automatically placed within 5 µm of the same position.

Pathological investigations of tissue or cells are based on the meticulous microscopic examination of samples on glass slides. Using manual methods, this process is inherently time consuming and requires diligent concentration from a highly trained operator.

The Ariol system is designed to remove the burden of manual slide scanning by carrying out frame-by-frame image capture of the tissue or cell suspension. This is done by means of a high-resolution charge-coupled device (CCD) camera optimized for low-light-sensitive imaging across the full spectral band, which works with a high-performance fully automated microscope. The resulting images are of very high quality (0.32 microns per pixel at 20x), and their on-screen presentation on high-definition 1600 x 1200-pixel displays becomes the basis for the system’s automated scoring.

Ultra high performance graphic cards used with the system ensure superior image quality that can liberate users from hours of staring down a microscope. However, the importance of direct microscopic examination in this field of science is not forgotten. With just a click of the mouse, the user of the system can recall the slide onto the stage for closer, ocular viewing.

The purpose of an automated image analysis system should not be to remove or diminish human control, but rather to provide the efficiency and high throughput of automation with the option of full manual control as necessary. The Ariol is fitted with its own fully programmable joystick, keyboard, and mouse and a series of interfaces through which the operator can work interactively with high resolution gigapixel images.

Multiple-display operation allows live side-by-side comparison or lets the user run multiple interfaces simultaneously. This dramatically improves the pathologist’s ability to multitask by creating a clean user interface and an uncluttered desktop environment.

Image Analysis and Results Manipulation

In pathology, imaging algorithms are necessarily the core of any system’s analytical capabilities. The Ariol system’s imaging algorithms were designed specifically for the purposes of pathology image analysis. Each module’s imaging algorithm was developed for a specific type of IHC protocol or FISH technique.
To make the system flexible in its imaging capabilities, the analysis algorithms are supported by a so-called trainable classifier, a feature that enables the user to habituate the system to his or her individual biomarkers under investigation.

System flexibility is further evidenced by the variety of applications in routine use in laboratories worldwide. For research use only and not diagnostic procedures, are specified for TMA, cytoplasmic IHC, DNA ploidy, immunofluorescence, microvessel density, sentinel lymph node, and cellular FISH applications. Other modules, the Microsight cellular rare-event detection, Hersight membrane IHC, and ERsight and PRsight nuclear IHC modules are for IVD use and have 510K clearance.

Image analysis is a resource-intensive process. Consequently, this system features dual Xeon processors, server-grade hard drives and memory, and the Windows XP Professional operating system, ensuring fast analysis with no backlog.

Besides analyzing slides, an automated image analysis system should be equipped with features that enhance postanalysis efficiency in the pathology laboratory. Accordingly, Applied Imaging gave Ariol report generation, data archiving, networking, and laboratory information management system (LIMS) integration functionality.

The system generates full-color electronic reports that can include images of significant cells or tissues analyzed, numerical data and scores, diagnostic comments, and space for a signature. Eliminating the time commitment required for paper reports, this feature ensures clarity and consistency in the communication of data, and results in reports that are e-mail and fax ready.

To support tidy, cost-effective archiving, the system offers a full clinical data management server, terabytes of hard-disk space, 10-Gb digital video–random-access memory discs. All of which is completely scalable to satisfy your storage needs today and in the future.
The potential of this digital technology for high-throughput operation is fully realized through system networking. Pathologists need not huddle around the microscope when they can review cases, including crisp, high-quality images, from their office desktop PC. Besides operating as a single stand-alone system, the Ariol can be configured with multiple review stations and laptop data entry stations situated in various places around the laboratory or department (see Figure 3). Review stations enable the pathologist or laboratory director to review ongoing work, review and sign off on cases, and optimize the system of reporting and archiving data. The data entry stations can be positioned to register each microscope slide as it comes into the laboratory.

Fig 3: The Ariol imaging system enables multiple units to be run simultaneously through a centralized server. The network supports the system’s laptop data entry stations and review stations as well

Both images and data generated by the Ariol system can be integrated seamlessly into existing third-party LIMS. This is accomplished through the system’s advanced Web services, which employ platform-independent, non-vendor-specific XML technology.

Automated-System Applications

The Ariol system has application in the quantification of a number of biomarkers that aid pathologists in cancer cell analysis as well as toxicology studies. Most compelling is its use in screening thousands of TMA cores unattended in a single run. In the case of toxicology, deleterious compounds can be detected in a fraction of the time compared to using conventional manual microscopy methods. Ultimately, insight gleaned from large studies can further the development and improvement of personalized medicine.

Genetic approaches toward improving the treatment of breast cancer are already proving beneficial, and indicating the brightness of the future of personalized medicine. One of the best-established examples involves the overexpression of the HER-2/neu gene that occurs in about 30% of metastatic breast cancer patients. The HER-2/neu protein, a member of the epidermal growth factor receptor family, resides in the membrane of expressing cells. The challenge has been to identify the 30% of patients at risk by finding a way to measure overexpression of HER-2/neu dependably.

The market-leading IHC test for HER-2/neu is the HercepTest from DakoCytomation a/s (Glostrup, Denmark). Analysis of this test calls for measurements of staining intensity, pattern continuity, and stained-cell frequency to be made on the region of the invasive tumor. The method has proved to be a considerable challenge for the pathology community, having been demonstrated to show poor reproducibility in scoring by manual methods.1 In a recent comparison of local and centralized testing of HER-2/neu status, the concordance between results was measured at only 74%.2 Digital image analysis has been shown to improve accuracy and reproducibility in scoring this test.3
In the experiment, the Ariol was used to provide high-throughput analysis for HER-2/neu IHC-stained slides. The slides were transferred automatically by the system’s slide loader, and then scanned at low magnification to produce a satellite view of the entire tissue section. Automatic or user-defined target regions were then scanned frame by frame at higher magnification, with three bright-field-filter images being collected per frame. The use of bright-field filters and a monochrome CCD camera—as opposed to a color camera—is unique to the Ariol system and is recognized as producing very accurate high-resolution images without the need for the artificial distortion of colors or shapes.

The captured images were brought together seamlessly by the system to produce a high-resolution image of the whole slide into and out of which the analyst could zoom while maintaining excellent image quality.

Analysis of defined tissue regions was then conducted using the system’s cell-masking template to quantify the number of cells and to analyze stain intensity and pattern continuity specifically within the cell membrane (see Figure 4). This membrane specificity makes for truly objective analysis.

Fig 4 : Analysis of HER-2/neu IHC images using membrane masking enables visualization of membrane-specific staining patterns

The work-flow improvement contributed by the slide loader and the system’s intuitive interface enhances analysis considerably. With the additional benefits of high accuracy and objectivity, imaging automation makes the daunting task of TMA capture and analysis a good example of how the technology may advance cancer research.

The value of the technology is being demonstrated quantifiably by the Sanger Institute. “Combined with the use of TMA arrays this provides us with the ability to rapidly gather large volumes of image data for many tissue samples. Image analysis allows us to produce more objective measures of staining, and moves quantitation away from subjective category based human assessment.” The Ariol system is now used routinely in their facility with the capacity to analyze ~25,000 images/day.

Perhaps the potential of automated image analysis is most impressive with respect to routine IHC markers. Used in immunohistochemistry since the beginning, nuclear and cytoplasmic IHC markers have been the bread and butter of many laboratory investigations. Despite this fact, however, this area of pathology still exhibits considerable diversity in terms of scoring methods and analysis patterns. Some slides may require only a quick glance down a microscope by an experienced pathologist to yield a report of positive or negative, while other slides may call for the counting of more than a thousand cells.

To accommodate these practices, the Ariol was designed for work-flow flexibility. For rapid examination, the system provides clear, easy-to-view tissue images and full cataloging and quick porting. For more expansive quantification, it offers a choice of nuclear, cytoplasmic, and membrane-masking methods for high-specificity object analysis or convenient area analysis. Both system configurations engage in pixel-by-pixel analysis for highly objective results and are integrated with a review interface for ease of use.

Conclusion

Automated image analysis does not replace pathologists; rather, it aids them in their work. Designed never to fade in concentration or accuracy, automated image analysis systems perform slide analysis at levels previously unachievable by manual means.

The positive implications of automation for this field of laboratory endeavor are several. First, staff are released from long hours at the microscope. The time savings resulting from improved work flow can benefit areas of pathology, toxicology, and biomarker discovery, where maximizing productivity and data analysis is an issue. Where high density TMA analysis is required, automated tracking, imaging, and quantitative analysis is essential. Also, technologists, pathologists, and other researchers can be networked to instantly and easily compare data. Ariol augments the role of the pathologist by providing a tool that allows more-comprehensive analysis and generates greater confidence in results. Finally, advantages can be realized in the areas of operational costs and returns on investments.