THE WHOLE SLIDE IMAGING TECHNOLOGY AND ITS APPLICATIONS: CURRENT AND EMERGING PERSPECTIVES - IV

In last part of this blog series we explore challenges caveats and future of WSI.

CAVEATS AND CHALLENGES OF WSI

In order to integrate WSI into routine clinical pathology practice, an infrastructure needs to be developed in the pathology department (37, 60, 66, 75, 111). This infrastructure consists of: (i) hardware for scanning slides, storing the scanned images, transmission of the images to pathologists, and the interfaces necessary to display the images and report interpretations; and (ii) the software to facilitate the workflow of the image movement, display, and reporting of the results. Additionally, for remote teleconsultation, features like security of protected patient information, process validation, as well as regulatory, medicolegal, and billing issues need to be added. However, there are many unresolved issues, as outlined below, which still need to be addressed before WSI finds its place in routine application across the wide specialty of pathology (37, 51).

Cost

The cost of procurement, implementation, and operational costs of WSI may be prohibitive, especially for small pathology laboratories due to huge initial cost of the scanners and additional hidden costs of training of staff and pathologists, technical support, digital slide storage systems, and regulatory or licensing costs (43, 112). Technological support for telepathology further compounds these costs. A recently published cost-benefit analysis at a large-volume academic center with slides in excess of 1.5 million showed a projected $1.3 million savings over a 5-year period (113). However, the same analysis needs to be undertaken for smaller laboratories and low-resource settings.

Technological Issues

Scanning the whole slide/smear is a tedious and time-consuming process at present. Scanning times can vary from 1 to 5 min for a small biopsy to 5–20 min for a surgical specimen and 3–5 min for a liquid-based cytology smear (58). Another limitation with currently available scanners is the requirement of massive data storage capacity. Scanning at × 40 magnification of a 1-mm2 area results in a file size of 48 megabytes. Hence, majority of the WSI systems incorporate image compression algorithms (JPEG, JPEG 2000, LZW) to reduce the file size, however that introduces image artefacts. Some scanners offer the ability of multi-resolution representation (pyramid representation) where the field of view on the screen is inversely proportional to the magnification being viewed (43). Majority of the WSI systems utilize a content management system with specific programming in order to display the virtual slides in a consistent and specific manner (43). Currently, there are vendor-dependent limitations with WSI systems. Some vendors use proprietary modules with limited scope of cross-browser compatibility or seamless execution on multiple devices.

Professional Barriers

Unlike radiology where digital systems obviate the need of making films, WSI in pathology does not reduce the laboratory’s workload since glass slides still need to be prepared to be scanned. However, WSI does allow for streamlined navigation of the slides at various magnifications without the fear of accidentally breaking a slide at the microscope. The current WSI systems allow for batch-wise scanning of slides, thus improving the efficiency of the laboratory (8, 43, 113).

Other issues include available bandwidth of the network at the pathologists’ workplace, security issues related to information technology, and installation of compatible browsers. However, with progress in information technology, the systems shall continue to be upgraded for improved speed and compatibility with browsers (60).

The FDA approval of WSI in primary surgical pathology diagnosis does open up the issue of legal implications for the reporting pathologists. The relevant regulatory agencies (such as CLIA) need to put forth their guidelines in light of the expected changes with adoption of WSI by pathologists.

Regulatory Issues

Though FDA has accorded its approval for use of WSI in surgical pathology practice in 2018, the other subspecialties of pathology still have a long path to tread towards this goal. At the same time, validation of WSI for introduction into the surgical pathology practice is still merely a recommendation of the CAP. Regulations also need to be put in place regarding the archiving, retrieval, and access rights of the virtual slide library so formed (8, 38, 113).

CONCLUSION

WSI is an exciting and promising technology with various advantages and a few challenges. The future of WSI lies in having an ideal vendor-neutral archive wherein a single software-hardware solution allows single viewing, storage, and retrieval with no barriers of the data source. This coupled with the promise of artificial intelligence, pathology is poised for new discoveries and solutions (81, 92)

FUTURE OF WSI

1) Availability of high-resolution 3-dimensional imaging, especially for tumors, would improve the use of this technology with correlation between radiologic imaging and WSI (64).

2) Multispectral imaging, when applied to WSI, would offer the ability to characterize chromatic properties and support color-based classification and multi-labelling studies (58).

3) Refinement of AI and machine learning algorithms would allow the pathologists contribute in a larger role in improving patient management and outcomes (51).

Virtual microscopy using whole slide scanning is an area of profound and rapid technologic development with numerous applications in the field of pathology. Despite its several advantages and claims of it being equivalent to conventional microscopy, the adoption of this technique has been rather slow even in the developed nations. The barriers referred to in this paper currently preclude the wide application of whole slide scanning in the resource constrained medical institutions of the developing world. Apart from the technical and cost-related issues, regulatory and validation requirements also need to be adequately addressed, especially for the developing nations. Nevertheless, WSI does provide a golden opportunity for pathologists to guide its evolution, standardization, and implementation by playing a key role in defining/ refining guidelines, designing the resource specific digital pathology laboratories, and propagating standardized educational modules to train the next generation of virtual pathologists.

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Blog Author

Sambit K Mohanty, MD

THE WHOLE SLIDE IMAGING TECHNOLOGY AND ITS APPLICATIONS: CURRENT AND EMERGING PERSPECTIVES - IV

Here's a continuation of our enlightening blog series, in this section we are delving into the intriguing synergy between two technological frontiers - Whole Slide Imaging (WSI) and Artificial Intelligence (AI). In this exploration, we embark on a journey that unveils the transformative potential of their integration, transcending the boundaries of medical diagnostics, research, education and beyond.

Education

Equipped with whole-slide imaging, artificial intelligence (AI) tools can help further training of the next generation of pathologists by providing on demand, standardized, and interactive digital slides that can be shared with multiple users anywhere, at any time (92,93). Additionally, AI tools can provide automated annotations in the form of quizzes for trainees. With the help of these interactive tools trainees can view, pan, and zoom enhanced digital slides, which can provide tutoring in real-time and in a dynamic teaching environment. For the purpose of generating synthetic images, researchers extracted individual and clustered nuclei that were both positively and negatively stained from real whole-slide imaging images, and systematically placed the extracted nuclei clumps on an image canvas - cut-and-paste approach. These images were evaluated by trained pathologists in the task of estimating the ratio of positive to total number of nuclei. The resulting concordance correlation coefficients between the pathologist and the true ratio range from 0.86 to 0.95 (94). The main idea is to force the generator to learn the underlying distribution of the images from the training data. Generation of numerous synthetic histopathology images could be useful because it will give pathology trainees the opportunity to test their skills, besides being useful for quality control and understanding the perceptual and cognitive challenges that pathologists face (75,94).

Quality Assurance

The development of automated, high-speed, and high resolution WSI has a substantial effect on QA. Digitized slides that are readily available to pathologists in the LIS or on the intranet can be used for several QA tasks, including teleconsultation, gauging inter-observer and intra-observer variance, proficiency testing, and archiving of slides (8,39,95,96). For example, CAP optionally sends Whole slide (WS) images in addition to glass slides for certain proficiency testing cases. AI can have an important role in QA. By providing feedback manually or with intelligent deep learning and AI tools, a pathologist has the potential to keep improving on his or her performance. AI can be used as a supplement to these manual digital reviews in routine diagnostic workflow or as a complement to the more formal quality reviews that are part of a pathology laboratory’s quality management process. AI can also provide a quality check on the diagnosis rendered by a pathologist by applying automated diagnostic algorithms. These methods can continue to serve as patient safety mechanisms to improve the quality of diagnosis and to prevent error (75).

Pathological Diagnosis

WSI and AI have been increasingly used for routine pathological diagnosis. Several studies have shown a concordance of 89% to 99% when comparing diagnostic interpretation using digital slides to diagnoses rendered using glass slides and a conventional light microscope (19,32,43,70,92,97). The quality of images produced by WSI scanners has a direct influence on the readers’ performance and their reliability of diagnosis. Most modern scanners come equipped with autofocus optics system to select focal planes to accurately capture the three-dimensional tissue morphology similar to a two-dimensional digital image (43). To account for varying thickness of tissue sections, these systems determine a set of focus points at different focal planes from which scanners capture images to produce sharp tissue representation. However, still digital images with out-of-focus areas may be produced if the autofocus optics system erroneously selects focus points that lie in a different plane than the proper height of the tissue (19,43). To overcome this, AI automatically identifies out-of-focus regions allowing WSI scanners to add a few extra focal points to those regions by either feature engineering or via a representation learning approach. Another approach called Deep Focus, based on representation learning, automatically discovers features from the images to identify blurry regions. Because the Deep Focus program automatically learns features at different levels of abstraction, it can generalize to different types of tissues and even to color variations due to different types of staining, H&E and IHC (10). Standardization of the color displayed by digital slides is important for the accuracy of AI. Color variations in digital slides are often produced because of different lots or manufacturers of staining reagents, variations in thickness of tissue sections, difference in staining protocols, and disparity in scanning characteristics. For this reason, the absence of color normalization in an AI pipeline could negatively affect the performance of machine learning algorithms. For a long time, collecting color statistics to perform color matching across images has remained the main source of color normalization. However, progresses in the generative models have presented novel ways of color normalization (98).

Image Analysis

Image analysis tools can automate and quantify with greater consistency and accuracy than light microscopy (81, 99). Computer-aided diagnosis is widely used for Estrogen receptor (ER), Progesterone receptor (PR), and HER2/neu assessments in breast cancer (100, 101), Ki67 assessment in neuroendocrine neoplasms (102, 103), PD-L1 as immune checkpoint molecules in various solid organ malignancies, as well as multiple other clinical and research stains. The reliability of these methods requires the standardization of the image acquisition step. AI methods aid in enabling the regions of interest selection (104, 105). Nuclear segmentation in WSI enables extraction of high-quality features for nuclear morphometrics and other analysis in computational pathology (94). For this reason, automatic nuclei segmentation is among the most studied problems in AI. In general, these algorithms estimate a probability map of the nuclear and non-nuclear (two-class) regions on the basis of learned nuclear appearances and rely on complex methods after processing to obtain the final nuclear shapes and separation between touching nuclei (106). Kumar and colleagues (107) have created a well-annotated database consisting of 30 whole-slide images of digitized tissue samples from several organs. The slides were taken from the publically available database The Cancer Genome Atlas. The images were generated at 18 different hospitals, which adds to the diversity of this dataset in terms of variation in slide preparation protocols among laboratories. Over 21,000 nuclei were manually annotated to train a deep learning algorithm. Unlike former methods, a nuclei segmentation as a three-class problem was created. They considered the nuclei edges as a third class when generating the tertiary probability map. This map was subjected to region growing to segment the individual nuclei.

During most pathological analysis, pathologists are interested in identifying a subset of nuclei in a particular anatomical region. For example, in T1 bladder cancer (108), pathologists are interested in identifying the tumor nuclei within lamina propria. Similarly, in breast and neuroendocrine tumors, the pathologists are interested in the ratio of Ki67 tumor positive nuclei to total tumour nuclei within the hotspots. In follicular lymphoma, the analysis is limited to only the presence of centroblasts within the neoplastic follicles. For these reasons, there is an increasing interest in developing AI algorithms that can identify a subset of cells within a certain anatomical region. Also, whole slide is partitioned into superpixels on the basis of similarity at some magnification. Superpixels are grouped into anatomical regions (specifically epithelium) on the basis of graph clustering. Finally, each cluster is classified as ductal carcinoma in situ or benign or normal on the basis of features extracted by deep learning (104,109, 110).

In the dynamic convergence of Whole Slide Imaging (WSI) and Artificial Intelligence (AI), we witness the epitome of transformative innovation. This amalgamation not only underscores the potential to revolutionize medical diagnostics and research but also exemplifies the harmonious partnership between human expertise and computational prowess. As WSI continues to empower pathologists with unprecedented levels of data-rich insights, AI augments their capabilities by swiftly identifying patterns, anomalies, and predictive trends. The synergy between these realms holds the promise of accelerated diagnoses, enhanced treatment decisions, and novel scientific breakthroughs. As we conclude this blog series, we stand on the cusp of a new era in healthcare, one where WSI and AI harmonize to unravel the mysteries of the microcosmic world, inspiring optimism for a healthier and more informed future.

References

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Blog Author

Sambit K Mohanty, MD

Whole Slide imaging technology and its applications: Current and emerging perspectives -III

Lets dive into applications of Digital pathology in part-III of this blog series.

APPLICATIONS OF WHOLE SLIDE IMAGING

Health care facilities are witnessing extensive digitization with inclusion of digital imaging connected to hospital information systems, LIS, picture archiving, and communication systems. Pathology laboratories equipped with WSI facility would fall into place well in such a setting with varied applications in diagnosis, education, and research (11, 34,37, 42,43).

WSI IN EDUCATION, TUMOR BOARDS, PRESENTATIONS, QUALITY ASSURANCE, AND RESEARCH

WSI has gained wide acceptance for education, at the tumor boards, and for presentations, research, and quality assurance (QA) (4,43-46). Digitized slides are more interactive compared to glass slides, can be easily shared anywhere at any time, and can help standardize training and research material. Many authors have highlighted its use in undergraduate medical education, pathology residents and fellow training (45-48). Unlike glass slide teaching sets, digital slides do not fade, break, or disappear. Digital slides also offer the ability to standardize images, permit annotation, and can provide a wide case range for trainees (48,49). Digital teaching sets can be accessed on a server over a network, are available to multiple users, and can be developed to contain test modules for trainees. WSI can also facilitate preparation and conduct of tumor boards through obviating the need of a multi-headed microscope or microscope with projection attachment or acquisition of multiple static images of a case (50,51). This is because WSI offers higher quality images with annotation, greater educational value for clinicians, involves less preparation time than photographing cases, and permits real-time flexibility (e.g. easy to add on cases, perform side-by-side viewing, and gives access to the entire slide which allows one to answer “on-the-spot” questions) (52). It is also useful in E-education, virtual workshops, and for proficiency testing (53). The use of this technology in Quality Assurance (QA) programs in Surgical pathology and Cytopathology can help in cost cutting and overcoming transportation difficulties, as also minimizing the potential second-reviewer bias by hiding the initial diagnosis (10, 30, 54). Online WSI resources such as College of American Pathologists (CAP) Virtual Slide Box, Digital Pathology Association hosted repository, and the Cancer Digital Slide Archive offer virtual slide sets for training and learning purposes. Virtual slides are also being used in pathology conferences and meetings to promote interactive learning and provide ease of visualization of multiple images of different stains in conjunction with relevant clinical material (30). Electronic publication of text books and articles in scientific journals has also opened new panoramas of scientific communication (55). Utilization of WSI-generated high-quality virtual images has proven to be the single most upgrade for pathology journals, thus empowering the readers to be involved in a scientifically based diagnostic approach to the lesion described (56).

WSI IN PRIMARY FROZEN SECTION/INTRAOPERATIVE CONSULTATION/DIAGNOSIS

Over the last few years, WSI has been utilized in primary frozen section diagnosis and secondary/tertiary teleconsultation (43,51, 57-59). The advantages include access to an entire digitized slide or even an entire case (set of slides), automated scanning, the high resolution of images available for review, rapid interpretation time, and the ability of teleconferencing.

A high concordance rate between WSI-based frozen section and permanent section diagnosis or on-site interpretation has been demonstrated in several studies (11,37, 60). However, further studies on a range of different pathologies are required to validate the utility and limitations of WSI. Successful implementation requires: effective planning and communication, a willingness to adjust old routines without compromising quality, and histo-technologists who are able to provide consistently high-quality frozen section slides (41,61,62).

WSI IN ROUTINE PATHOLOGICAL DIAGNOSIS

WSI is increasingly being used in the daily practice of surgical pathology, particularly for teleconsultation and certain quality assurance practices, such as obtaining second opinions (31,63,64). However, it raises a question whether WSI will be utilized for making routine pathologic diagnoses, ushering in the era of the “slideless” laboratory, especially after the COVID-19 pandemic (60,65,66). The adoption of digital pathology has been slower than in radiology partly due to the fact that in pathology, digital data is acquired in a slightly different manner from that in radiology (31,67,68). Although both fields require an imaging modality to collect primary data, in radiology, images begin as digital data whereas pathology images have to be converted from an analog substrate into a digital format (67-69).

Rendering routine pathologic diagnoses using WSI is feasible if the images truly represent an accurate digital reproduction of the scanned glass slide which can be saved, archived, reviewed, and later retrieved without any degradation (70). Moreover, apart from integration with the LIS, the routine use of WSI requires seamless connectivity over broadband networks, efficient workstations, cost-effective storage solutions, and standards-based informatics transactions for integrating information (63,71). Discrepancies between digital and glass slide diagnoses may be attributed to inadequate clinical data, missed tissue on the digital slide, and the pathologists’ lack of experience using a WSI system (72). One study demonstrated that using a virtual slide system, correct diagnosis was made in 66% of cases without clinical data provided compared to a correct diagnosis of 76% when clinical data was provided (72). Therefore, in order for WSI to become an accepted diagnostic modality, the provision of adequate medical information (e.g. gross pathology description, prior pathology reports, clinical history, imaging and other relevant laboratory parameters etc.) will need to be weaved into the imaging system (63,73,74).

Digital slides offer several advantages in terms of fidelity of the diagnostic material, portability, ease of sharing, retrieval of archival images, and ability to make use of computer-aided diagnostic tools (e.g. image algorithms) (37, 62, 75, 76). WSI has also permitted new business models of care in pathology (78). For example, virtual IHC service provided by large national laboratories. After the remote reference laboratory performs staining and slide scanning services, the referring pathologist is provided with full access to these IHC slides for interpretation or referral to a teleconsultant (43). In the near future, the adoption of standards, validation guidelines, automation of workflow, creation of new revenue streams, and nuances of clinical digital practice will likely dictate a new standard of care for primary pathologic interpretations (11, 77-80).

WSI AND IMMUNOHISTOCHEMISTRY AND ELECTRON MICROSCOPY

WSI offers advantages in enhancing objectivity in the interpretation of IHC used in tumor diagnosis, prognosis, and evaluation of biomarkers for targeted therapy (1,81,82). A study reported a concordance of 90% between WSI and glass slides of HER2/neu expression in breast cancer (81). Application of automated image analysis with algorithm-based scoring for the prognostic markers can assist in improving the scoring protocols and thereby enhance the efficacy of targeted therapies (82). Also in electron microscopy, a virtual ultrathin slide allows the pathologists to navigate the slide in their office while noting the exact location of the specific features. Apart from this, WSI technology can be valuable for obtaining consultation on ultrathin sections from experts located in higher centres (83).

WSI and CYTOPATHOLOGY

The role of WSI in Cytopathology has been increasing but there are certain obstacles such as the inherent complexity of scanning, higher scanning time, and storage costs (10,84-87). The scanning of cytology smear is difficult as well as complex because of its three dimensional character (85). Consequently, it is essential to integrate z-stacking or multiplane scanning feature into the systems intended for use in cytopathology (87). Alternative approach includes the conversion of z-stacks of images into video frames and storing the stack as a high-efficiency video coding file(s). Subsequent video compression has demonstrated to exceed the JPEG compression with comparable image quality (88). A comparison of conventional glass slides and WSI in 10 cervical and 20 non-gynecologic cytology cases showed similar diagnostic concordance between the two modalities among the reviewing cytopathologists (89). Another recent study comparing WSI with glass slides of thin-layer cervical specimens demonstrated 95.3% concordance rates, paving the way for WSI use in routine cytologic diagnosis (86). A study by Wright et al evaluated the efficiency of WSI in cervico-vaginal cytology highlighting issues such as a lack of familiarity with the technology, difficulty in detecting few abnormal cells in the smears, problems with hyperchromatic nuclei, dark and crowded groups of cells, and massive image file size leading to increased duration of scanning (90). Certain problems encountered while using WSI in cytology smears compared to the histology sections, include (a) presence of dense overlapping tissue fragments making it difficult for scanners to focus on the cells, (b) red cell contamination of the smear and/or background acellular material(s) leading the scanner to focus on red cells and/or the background material rather than the cells of interest, (c) smears with scant cellularity making z-stacking difficult, and (d) need to remove the screening marks/dots before scanning (for which keeping a photographic record of the diagnostic screening marks is recommended) (91). Papanicolaou- and H&E-stained smears often have cells in multiple planes due to wet fixation, and thus require z-scanning to obtain a crisp, high quality image. On the other hand, air-dried Romanowsky-stained smears can be scanned with only x and y-axes, as air drying flattens the cells thus minimizing the requirement of z-stacking (91,92).

Given the ongoing need for a cytologic diagnosis, the trend of using WSI in Cytopathology may possibly increase in future as minimally invasive procedures to obtain material for genetic/ molecular analysis are used. The possibility to scan whole slides and to organize them in structured databases accessible via the Internet would represent a powerful educational resource. The examples of rare cases can be shared without the risk of stain fading or loss or breakage of slide(s).

In next part of this series we will explore WSI in Artificial intelligence.

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Blog Author

Sambit K Mohanty, MD