Welcome to our multipart blog series on "The Whole Slide Imaging Technology and Its Applications: Current and Emerging Perspectives." In this comprehensive series, we delve into the world of whole slide imaging (WSI) and explore its wide-ranging applications in various fields. From healthcare to research, WSI has revolutionized the way we examine and analyze tissue samples, offering unprecedented opportunities for diagnosis, education, and scientific advancements. Join us as we unravel the intricacies of WSI, examine its current state, and explore the exciting emerging perspectives that promise to shape the future of this remarkable technology. Get ready to embark on a journey through the digitalization of microscopy, where virtual slides become windows into a world of endless possibilities.
Digital pathology (DP) is a subspecialty of Pathology that utilizes Whole Slide Imaging (WSI) wherein glass slides are converted into digital slides and are viewed by pathologists through automated image analysis (1,2). It started in the 1960s with telepathology research and subsequent introduction of virtual microscopy and commercial WSI scanners in the 1990s (3). However, technical requirements (scanner, storage, and network), high cost and slow speed of scanning were major limiting factors for its broad dissemination. Over the last decade, the concept of DP has revolutionized as new, potent, affordable scanners and assisted technological advancement and mass- or cloud-based storage technologies have developed bringing a paradigm shift in the field of Pathology (4). This has shown significant impact in dissemination of educational material, expansion of diagnostic services to underprivileged areas, real-time digital consultation services, virtual tumor board, and intra- and inter-institutional academic and research collaborations (4,5).
WSI aids in the integration of electronic workflows and health records, and generation of diagnostic support based on computational tools like artificial intelligence (AI) (6). Although WSI has tremendous lucrative benefits in pathology, involving diagnostic and academic/research services, the complexities involved in the implementation as well as technical and logistic hindrances remain an impediment to its widespread and global adoption (7). For example, current scanning technology does not satisfactorily accommodate thick smears and three-dimensional cell groups in cytopathology (8-11). With suboptimal tissue sections, scanners are currently not providing good results, when encountering tissue folds, air bubbles, and poor staining (8). Unless significant modifications to the workflow are made centered around DP (e.g. automation, continuous flow processes, and quality of the histology presented to the WSI devices), placing WSI systems in the clinical pathology laboratory has been shown to stress the system in terms of reliability, reproducibility, turn-around time, and throughput (9).
Some important milestones in digital and computational pathology are as follows:
1950 Alan Turing conceived the idea of using computers to mimic intelligent behavior and critical thinking.
1956 John McCarthy coined the term artificial intelligence (AI).
1959 Arthur Samuel coined the term machine learning (ML) as “the ability to learn without being explicitly programmed”.
1965 Computerized image analysis of microscopy images of cells and chromosomes by Judith Prewitt and Mortimer Mendelsohn.
1986 Term deep learning (DL) coined by Rina Dechter.
1988 Convolutional neural network (CNN) invented by Yann LeCun.
1990 Whole slide scanners introduced.
1998 Tripath becomes the first company with an automated PAP smear screening product to receive FDA approval.
2003 Cytyc received FDA approval for their ThinPrep Imaging System.
2013 Development of photoacoustic microscopy imaging technique.
2014 Ian Goodfellow introduced generative adversarial network.
2016 MUSE microscopy technique invented to enable high resolution imaging without tissue consumption.
2017 Philips receives approval for a digital pathology whole-slide scanning solution (IntelliSite).
2018 FDA permits first medical device using AI to detect diabetic retinopathy in adults (IDx DR).
2021 FDA authorizes the first AI-based software to detect prostate cancer (Paige Prostate).
Stay tuned for the next part of our blog series, where we delve into the technology aspect of WSI
1. Aeffner F, Zarella MD, Buchbinder N, Bui MM, Goodman MR, Hartman DJ, et al. Introduction to digital image analysis in whole-slide imaging: a white paper from the digital pathology association. Journal of pathology informatics. 2019;10.
2. Hamilton PW, Wang Y, McCullough SJ. Virtual microscopy and digital pathology in training and education. Apmis. 2012 Apr;120(4):305-15.
3. Ferreira R, Moon J, Humphries J, Sussman A, Saltz J, Miller R, et al. "The virtual microscope". Romanian Journal of Morphology and Embryology. 1997;45: 449–453.
4. Ho J, Parwani AV, Jukic DM, Yagi Y, Anthony L, Gilbertson JR. Use of whole slide imaging in surgical pathology quality assurance: design and pilot validation studies. Human pathology. 2006 Mar 1;37(3):322-31.
5. Pantanowitz L. Digital images and the future of digital pathology. Journal of pathology informatics. 2010;1.
6. Pantanowitz L, Sharma A, Carter AB, Kurc T, Sussman A, Saltz J. Twenty years of digital pathology: an overview of the road travelled, what is on the horizon, and the emergence of vendor-neutral archives. Journal of pathology informatics. 2018;9.
7. Saco A, Bombi JA, Garcia A, Ramírez J, Ordi J. Current status of whole-slide imaging in education. Pathobiology. 2016;83(2-3):79-88.
8. Abels E, Pantanowitz L. Current state of the regulatory trajectory for whole slide imaging devices in the USA. Journal of pathology informatics. 2017;8.
9. Wilbur DC. Digital cytology: current state of the art and prospects for the future. Acta cytologica. 2011;55(3):227-38.
10. Cucoranu IC, Parwani AV, Pantanowitz L. Digital whole slide imaging in cytology. Archives of Pathology and Laboratory Medicine. 2014 Mar;138(3):300.
11. Farris AB, Cohen C, Rogers TE, Smith GH. Whole slide imaging for analytical anatomic pathology and telepathology: practical applications today, promises, and perils. Archives of pathology & laboratory medicine. 2017 Apr;141(4):542-50.
Sambit K Mohanty, MD