Digital Pathology
Implementation in Clinical Practice with AI applications
- 1st Edition - November 27, 2024
- Imprint: Academic Press
- Authors: Meera Hameed, Matthew G Hanna
- Language: English
- Paperback ISBN:9 7 8 - 0 - 4 4 3 - 1 3 8 0 9 - 6
- eBook ISBN:9 7 8 - 0 - 4 4 3 - 1 3 8 1 0 - 2
Digital Pathology: Implementation in Clinical Practice with AI Applications covers digital pathology applications in a clinical pathology laboratory setting, providing guidance… Read more
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Request a sales quoteDigital Pathology: Implementation in Clinical Practice with AI Applications covers digital pathology applications in a clinical pathology laboratory setting, providing guidance and various tools for practical implementation. This comprehensive and detailed description of nuts and bolts of digital pathology implementation is unique and comes from the experience of high throughput scanning from a large surgical pathology laboratory. This is a valuable reference to prepare the end users not only about thoughtful launch of digital pathology but also to prepare for the future use of AI mediated decision support tools as the field advances.
This book covers the entire range of this topic and can be used as a practical reference for individuals that wish to be part of the evolution of diagnostic pathology. Sections include pre-analytic, analytic, and post-analytic processes, encompassing hardware, software, space, staffing, quality control, laboratory information system applications, clinical validation, use cases and future applications, including computer assisted diagnosis and decision support tools.
- Provides detailed aspects of the implementation of digital pathology in the clinical laboratory, including machine learning/artificial intelligence tools
- Presents examples of how digital imaging and AI are drivers in research and development in radiology, with parallels to situations in pathology
- Includes best practices and guidelines that can be practically applied by pathologists and data scientists
Pathologists, Machine Learning Scientists, Trainees Industry professionals related to Digital and Computational Pathology
- Title of Book
- Cover image
- Title page
- Table of Contents
- Copyright
- List of contributors
- Preface
- Acknowledgment
- Chapter 1. Basics of digital pathology
- Abstract
- Introduction
- Digital imaging basics
- Digital pathology timeline
- Digital pathology ecosystem
- Digital photomicroscopy
- Gross imaging
- Video streaming
- Whole slide scanning
- Monitors/display devices
- Input devices for digital pathology
- Interoperability and standards in digital pathology
- Applications
- Challenges/limitations
- References
- Chapter 2. The seven S’s for success
- Abstract
- Introduction
- Technology adoption
- Sponsorship from leadership
- Space allocation
- Assessment of current space utilization
- Ergonomics and user experience
- Staffing resources
- Scanner considerations
- Imaging mode
- Slide throughput/continuous load
- Scan speeds
- Slide size/format
- Magnification/resolution
- Flexibility in scan area
- Live viewing needs
- Multi z-plane support
- Rescan rates
- Whole slide image file format
- Lab space/countertop weight load
- User experience
- Storage
- Software
- Service and maintenance
- Honorable mention
- Conclusion
- References
- Chapter 3. Building a business case for digital pathology
- Abstract
- Introduction
- Understanding the costs associated with digital pathology
- Financial benefits of digital pathology
- Creating a business plan
- Discussion
- References
- Chapter 4. Preanalytic factors in digital pathology implementation
- Abstract
- Introduction
- Basic histology workflow
- Digital pathology in histology laboratory
- Logistical challenges
- Adoption of whole slide imaging workflow
- References
- Chapter 5. Quality management in digital pathology: analytic and postanalytic phases
- Abstract
- Introduction
- Analytic step
- Postanalytic step quality factors
- Image quality and computational pathology tools
- Published quality error rates
- Digital pathology quality management systems
- The cost of quality
- Conclusions
- References
- Chapter 6. Use cases in surgical pathology
- Abstract
- Introduction
- Telepathology
- Tumor detection and classification
- Metastases detection in lymph nodes
- Quantitative biomarker detection
- Prediction of genetic mutation on hematoxylin and eosin whole slide images
- Image-based prognosis and outcome prediction
- Summary
- References
- Chapter 7. Use cases in cytology
- Abstract
- Introduction
- Whole slide imaging in cytopathology
- Telecytology
- Rapid onsite evaluation
- References
- Chapter 8. Regulatory aspects of digital pathology
- Abstract
- Introduction
- Food and Drug Administration regulations in digital pathology whole slide imaging devices
- History of whole slide imaging and Food and Drug Administration regulation
- Food and Drug Administration perspective on whole slide imaging components
- Background and history of Clinical Laboratory Improvement Amendment and remote whole slide imaging sign-out
- Accreditation
- Additional considerations around remote primary sign-out through digital pathology
- Billing
- Legislation potentially affecting digital pathology regulation
- References
- Chapter 9. Standards in digital pathology
- Abstract
- Standards and interoperability in digital pathology
- What is a standard and why is it important?
- Who develops standards?
- Types of standards in healthcare that support digital pathology
- Standards for digital pathology in more detail
- Enhancing interoperability
- Closing remarks
- References
- Chapter 10. The basics of machine learning and artificial intelligence
- Abstract
- Introduction
- “Shallow” learning
- Deep learning
- Convolutional neural networks
- Recurrent neural networks
- Generative models: autoencoders and generative adversarial networks
- Reinforcement learning
- ChatGPT: everything, everywhere, all at once
- Things to come
- Summary and overview
- References for further reading
- Chapter 11. Academic industry partnerships
- Abstract
- Introduction
- Digital pathology clinical trials
- Academic industry partnership benefits
- Risks associated with academic industry partnership
- Academia versus industry priorities
- Contracts
- Innovation cycle
- The pathologist’s role
- Disclosure and conflict of interest
- Intellectual property
- Conclusion
- Disclosures
- References
- Chapter 12. Ethical aspects of using artificial intelligence in digital and computational pathology
- Abstract
- Introduction
- The shift from pathology to digital and computational pathology
- Ethical concerns in leveraging artificial intelligence in digital pathology and computational pathology
- Regulation of artificial intelligence and machine learning and oversight
- Successful artificial intelligence case studies in digital pathology and computational biology
- Achieving ethical use of artificial intelligence in digital pathology
- Conclusions
- Disclosures
- Funding
- References
- Chapter 13. Next-generation imaging in pathology
- Abstract
- Why next-gen imaging matters
- Looking beyond whole slide imaging
- What makes a new imaging tech relevant to pathology?
- What is the new tech and how does it work?
- Optical coherence tomography/optical coherence microscopy
- A framework for validation is evolving
- Making sense of it all
- References
- Index
- Edition: 1
- Published: November 27, 2024
- Imprint: Academic Press
- No. of pages: 400
- Language: English
- Paperback ISBN: 9780443138096
- eBook ISBN: 9780443138102
MH
Meera Hameed
Dr. Hameed is the Chief of Surgical Pathology overseeing a large surgical pathology laboratory with over 80,000 cases and generating over a million slides per year. In the last several years her division has undertaken the task of digitizing slides (retrospective and prospective) using multiple platforms with a vision is to incorporate the use of digital information and digital information systems into all aspects of Pathology. She is also the Co-Director for the Warren Alpert Center for Digital and Computational Pathology at her institution. Through the Center an infrastructure has been established for deep learning which includes a high-performance computing cluster with a solid foundation to foster collaborations among experimental and diagnostic pathologists, computer and imaging scientists and experts in deep learning and artificial intelligence.
Affiliations and expertise
Memorial Sloan Kettering Cancer Center, USAMH
Matthew G Hanna
Dr. Hanna is the Director of Digital Pathology Informatics at Memorial Sloan Kettering Cancer Center. He leads the digital transformation of the pathology department as it related to clinical implementation and translation of digital pathology. Dr Hanna speaks regularly at international and domestic conferences on the successful deployment of digital pathology at his institution. The large pathology department has demonstrated a high volume of prospective clinical scanning, and retrospective archival digitization of over 5 million slides to date. Dr Hanna has also collaborated with computational pathology researchers to develop and integrate clinical decision support tools in the Department. Through the early adopter status and developed infrastructure at the institution, practical implementation steps and lessons learned can be used as a blueprint for other institutions to enable success
Affiliations and expertise
Memorial Sloan Kettering Cancer Center, USARead Digital Pathology on ScienceDirect