Implementation Of Digital Pathology Research Articles

Understanding the financial aspects of digital pathology: A dynamic customizable return on investment calculator for informed decision-making

BackgroundThe adoption of digital pathology has transformed the field of pathology, however, the economic impact and cost analysis of implementing digital pathology solutions remain a critical consideration for institutions to justify. Digital pathology implementation requires a thorough evaluation of associated costs and should identify and optimize resource allocation to facilitate informed decision-making. A dynamic cost calculator to estimate the financial implications of deploying digital pathology systems was needed to estimate the financial effects on transitioning to a digital workflow. MethodsA systematic approach was used to comprehensively assess the various components involved in implementing and maintaining a digital pathology system. This consisted of: (1) identification of key cost categories associated with digital pathology implementation; (2) data collection and analysis of cost estimation; (3) cost categorization and quantification of direct and indirect costs associated with different use cases, allowing customization of each factor based on specific intended uses and market rates, industry standards, and regional variations; (4) opportunities for savings realized by digitization of glass slides and (5) integration of the cost calculator into a unified framework for a holistic view of the financial implications associated with digital pathology implementation. The online tool enables the user to test various scenarios specific to their institution and provides adjustable parameters to assure organization specific relatability. ResultsThe Digital Pathology Association has developed a web-based calculator as a companion tool to provide an exhaustive list of the necessary concepts needed when assessing the financial implications of transitioning to a digital pathology system. The dynamic return on investment (ROI) calculator successfully integrated relevant cost and cost-saving components associated with digital pathology implementation and maintenance. Considerations include factors such as digital pathology infrastructure, clinical operations, staffing, hardware and software, information technology, archive and retrieval, medical–legal, and potential reimbursements. The ROI calculator developed for digital pathology workflows offers a comprehensive, customizable tool for institutions to assess their anticipated upfront and ongoing annual costs as they start or expand their digital pathology journey. It also offers cost-savings analysis based on specific user case volume, institutional geographic considerations, and actual costs. In addition, the calculator also serves as a tool to estimate number of required whole slide scanners, scanner throughput, and data storage (TB). This tool is intended to estimate the potential costs and cost savings resulting from the transition to digital pathology for business plan justifications and return on investment calculations. ConclusionsThe digital pathology online cost calculator provides a comprehensive and reliable means of estimating the financial implications associated with implementing and maintaining a digital pathology system. By considering various cost factors and allowing customization based on institution-specific variables, the calculator empowers pathology laboratories, healthcare institutions, and administrators to make informed decisions and optimize resource allocation when adopting or expanding digital pathology technologies. The ROI calculator will enable healthcare institutions to assess the financial feasibility and potential return on investment on adopting digital pathology, facilitating informed decision-making and resource allocation.

Expectations and Experiences Among Clinical Staff Regarding Implementation of Digital Pathology: A Qualitative Study at Two Departments of Pathology.

The aim of this study was to assess and evaluate the individual expectations and experiences regarding the implementation of digital pathology (DIPA) among clinical staff in two of the pathology departments in the Region of Southern Denmark before and during the implementation in their department. Seventeen semi-structured interviews based upon McKinsey 7-S framework were held both prior to and during implementation with both managers and employees at the two pathology departments. The interviewees were pathologists, medical doctors in internship in pathology (interns), biomedical laboratory scientists (BLS), secretaries, and a project lead. Using deductive and inductive coding resulted in five overall themes and appertaining sub-themes. The findings pointed to an overall positive attitude towards DIPA from the beginning. The clinical staff perceived being rewarded already during implementation with benefits such as improved collaboration both inter- and intra-departmentally promoting better acceptance of DIPA. The clinical staff also experienced some challenges, e.g., increase in turnaround times, which affected and concerned staff on a personal level. Especially BLS expressed experiencing a demanding and stressful transition due to unexpected increase in workload as well as some barriers for a potentially better implementation process. The key findings of this study were a need for better preparation of staff through transparent communication of the upcoming challenges of the transition to DIPA, more system-specific training beforehand, more allocation of time and resources in the implementation process, and more focus on BLS' work tasks in the requirement specifications.

Transforming diagnostics: The implementation of digital pathology in clinical laboratories.

Digital pathology (DP) has emerged as a cutting-edge technology that promises to revolutionise diagnostics in clinical laboratories. This perspective article explores the implementation planning and considerations of DP in a single multicentre institution in Canada, the University Health Network, discussing benefits, challenges, potential implications and considerations for future adopters. We examine the transition from traditional microscopy to digital slide scanning and its impact on pathology practice, patient care and medical research. Furthermore, we address the regulatory, infrastructure and change management considerations for successful integration into clinical laboratories. By highlighting the advantages and addressing concerns, we aim to shed light on the transformative potential of DP and its role in shaping the future of diagnostics.

Biomedical laboratory scientists and technicians in digital pathology - Is there a need for professional development?

Digital pathology (DP) is moving into Danish pathology departments at high pace. Conventionally, biomedical laboratory scientists (BLS) and technicians have prepared tissue sections for light microscopy, but workflow alterations are required for the new digital era with whole slide imaging (WSI); digitally assisted image analysis (DAIA) and artificial intelligence (AI). We aim to explore the role of BLS in DP and assess a potential need for professional development. We investigated the roles of BLS in the new digital era through qualitative interviews at Danish Pathology Departments in 2019/2020 before DP implementation (supported by a questionnaire); and in 2022 after DP implementation. Additionally, senior lecturers from three Danish University Colleges reported on how DP was integrated into the 2023 bachelor's degree educational curricula for BLS students. At some Danish pathology departments, BLS were involved in the implementation process of DP and their greatest concerns were lack of physical laboratory requirements (69%) and implementation strategies (63%). BLS were generally positive towards working with DP, however, some expressed concern about extended working hours for scanning. Work-task transfers from pathologists were generally greeted positively from both management and pathologists; however, at follow-up interviews after DP implementation, job transfers had not been effectuated. At Danish university colleges, DP had been integrated systematically in the curricula for BLS students, especially WSI. Involving BLS in DP implementation and development may benefit the process, as BLS have a hands-on workflow perspective with a focus on quality assurance. Several new work opportunities for BLS may occur with DP including WSI, DAIA and AI, and therefore new qualifications are warranted, which must be considered in future undergraduate programmes for BLS students or postgraduate programmes for BLS.

Real-World Implementation of Digital Pathology: Results From an Intercontinental Survey

The past 70 years have been characterized by rapid advancements in computer technology, and the health care system has not been immune to this trend. However, anatomical pathology has remained largely an analog discipline. In recent years, this has been changing with the growing adoption of digital pathology, partly driven by the potential of computer-aided diagnosis. As part of an international collaboration, we conducted a comprehensive survey to gain a deeper understanding of the status of digital pathology implementation in Europe and Asia. A total of 127 anatomical pathology laboratories participated in the survey, including 75 from Europe and 52 from Asia, with 72 laboratories having established digital pathology workflow and 55 without digital pathology. Laboratories using digital pathology for diagnostic (n = 29) and nondiagnostic (n = 43) purposes were thoroughly questioned about their implementation strategies and institutional experiences, including details on equipment, storage, integration with laboratory information system, computer-aided diagnosis, and the costs of going digital. The impact of the digital pathology workflow was also evaluated, focusing on turnaround time, specimen traceability, quality control, and overall satisfaction. Laboratories without access to digital pathology were asked to provide insights into their perceptions of the technology, expectations, barriers to adoption, and potential facilitators. Our findings indicate that although digital pathology is still the future for many, it is already the present for some. This decade may be a time when anatomical pathology finally embraces digital revolution on a larger scale.

Impact of digital pathology implementation in Reunion Island

In recent decades, the major scientific advances in oncology have complexified anatomic pathology practice. Collaboration with local and national pathologists is essential for ensuring a high-quality diagnosis. Anatomic pathology is undergoing a digital revolution that implements whole slide imaging in routine pathologic diagnosis. Digital pathology improves diagnostic efficiency, allows remote peer review and consultations (telepathology), and enables the use of artificial intelligence. The implementation of digital pathology is of particular interest in isolated territories, facilitating access to expertise and therefore to specialized diagnosis. This review discusses the impact of digital pathology implementation in French overseas territories, particularly in Reunion Island.

Digital pathology implementation in a private laboratory: The CEDAP experience

IntroductionThe transition to digital pathology has been carried out by several laboratories across the globe, with some cases described in Portugal. In this article, we describe the transition to digital pathology in a high-volume private laboratory, considering the main challenges and opportunities. Material and methodsOur process started in 2020, with laboratory workflow adaptation and we are currently using a high-capacity scanner (Aperio GT450DX) to digitize slides at 20×. The visualization system, Aperio eSlide Manager WebViewer, is integrated into the Laboratory System. The validation process followed the Royal College of Pathologists Guidelines. ResultsRegarding validation, the first phase detected an error rate of 6.8%, mostly due to digitization errors. Phase optimization and collaboration with technical services led to improvements in this process. In the second validation phase, most of the slides had the desired quality for evaluation, with only an error rate of 0.6%, corrected with a new scan. The interpathologist correlation had a total agreement rate of 96.87% and 3.13% partial agreement. ConclusionThe implementation and validation of digital pathology was a success, being ready for prime time. The total integration of all laboratory systems and the acquisition of new equipment will maximize their use, especially with the application of artificial intelligence algorithms.

Development of quality assurance program for digital pathology by the Korean Society of Pathologists.

Digital pathology (DP) using whole slide imaging is a recently emerging game changer technology that can fundamentally change the way of working in pathology. The Digital Pathology Study Group (DPSG) of the Korean Society of Pathologists (KSP) published a consensus report on the recommendations for pathologic practice using DP. Accordingly, the need for the development and implementation of a quality assurance program (QAP) for DP has been raised. To provide a standard baseline reference for internal and external QAP for DP, the members of the Committee of Quality Assurance of the KSP developed a checklist for the Redbook and a QAP trial for DP based on the prior DPSG consensus report. Four leading institutes participated in the QAP trial in the first year, and we gathered feedback from these institutes afterwards. The newly developed checklists of QAP for DP contain 39 items (216 score): eight items for quality control of DP systems; three for DP personnel; nine for hardware and software requirements for DP systems; 15 for validation, operation, and management of DP systems; and four for data security and personal information protection. Most participants in the QAP trial replied that continuous education on unfamiliar terminology and more practical experience is demanding. The QAP for DP is essential for the safe implementation of DP in pathologic practice. Each laboratory should prepare an institutional QAP according to this checklist, and consecutive revision of the checklist with feedback from the QAP trial for DP needs to follow.

Current Developments of Artificial Intelligence in Digital Pathology and Its Future Clinical Applications in Gastrointestinal Cancers.

Simple SummaryThe rapid development of technology has enabled numerous applications of artificial intelligence (AI), especially in medical science. Histopathological assessment of tissues remains the gold standard for diagnosis of gastrointestinal (GI) cancers for subsequent management. In a traditional anatomical pathology (AP) laboratory, histopathologists are required to manually assess, quantify and classify diseases under a microscope in a semiquantitative or qualitative manner. The conversion of analogue-to-digital pathology is on the rise, conforming with trends toward digitalization. The rapid adoption of digital pathology (DP) is driven by factors such as the worldwide shortage of pathologists and medical technologists, the increasing incidence of cancer and the critical need to improve laboratory efficiency. In this review, we aim to provide a comprehensive summary of algorithms for AI detection and classification of GI cancer. We will also provide critical insight into the application of algorithms for routine care in clinical practice.The implementation of DP will revolutionize current practice by providing pathologists with additional tools and algorithms to improve workflow. Furthermore, DP will open up opportunities for development of AI-based tools for more precise and reproducible diagnosis through computational pathology. One of the key features of AI is its capability to generate perceptions and recognize patterns beyond the human senses. Thus, the incorporation of AI into DP can reveal additional morphological features and information. At the current rate of AI development and adoption of DP, the interest in computational pathology is expected to rise in tandem. There have already been promising developments related to AI-based solutions in prostate cancer detection; however, in the GI tract, development of more sophisticated algorithms is required to facilitate histological assessment of GI specimens for early and accurate diagnosis. In this review, we aim to provide an overview of the current histological practices in AP laboratories with respect to challenges faced in image preprocessing, present the existing AI-based algorithms, discuss their limitations and present clinical insight with respect to the application of AI in early detection and diagnosis of GI cancer.

Digital Pathology Implementation can Help Alleviate Limited Pathology Services in Developing Countries

This short communication highlights lack of resources in Pathology in developing countries which ultimately affects pathology residency training as well as routine practice of lab medicine. There are a few recommendations to help alleviate pathology manpower in resource limited countries including digitization of teaching resources, integration of pathology education into systems-based curriculum, concept of virtual electives, specialization within pathology practices beyond the academic centers and competency-based certification. Opportunities like digital pathology, virtual trainings and online courses can play an important role in pathology education and for covering all kind of curricula. These changes will also implement a standardized education system of international quality. The digital world has a lot to offer in terms of training and there are extensive learning options if we learn to utilize them properly. More and more remote platforms are becoming available in the form of elective opportunities and online teaching sessions. It is important to promote these platforms as they do not have border restrictions and they are a perfect example of how education should be free and accessible to everyone around the world. Keywords: Digital pathology; Virtual training; Electives; Pathology education; Manpower; Competen

Prior to Implementation of Digital Pathology-Assessment of Expectations among Staff by Means of Normalization Process Theory.

The Region of Southern Denmark is the first in Denmark to implement digital pathology (DIPA), starting at the end of 2020. The DIPA process involves changes in workflow, and the pathologist will have to diagnose based on digital whole slide imaging instead of through the traditional use of the conventional light microscope and glass slides. In addition, in the laboratory, the employees will have to implement one more step to their workflow—scanning of tissue. The aim of our study was to assess the expectations and readiness among employees and management towards the implementation of DIPA, including their thoughts and motivations for starting to use DIPA. We used a mixed-method approach. Based on the findings derived from 18 semi-structured interviews with employees from the region’s departments of pathology, we designed a questionnaire, including questions from the normalization measure development tool. The questionnaires were e-mailed to 181 employees. Of these employees, 131 responded to the survey. Overall, they reported feeling sufficiently tech-savvy to be able to use DIPA, and they had high expectations as well as motivation and readiness for the upcoming changes. However, the employees were skeptical regarding the allocation of resources, and few were aware of reports about the effects of DIPA. Based on the findings, it seems to be important to provide not only a thorough introduction to the new intervention and the changes it will entail, but also to continue to ensure that the staff know how it works and why it is necessary to implement.

Digital Pathology Implementation in Private Practice: Specific Challenges and Opportunities.

Digital pathology (DP) is being deployed in many pathology laboratories, but most reported experiences refer to public health facilities. In this paper, we report our experience in DP transition at a high-volume private laboratory, addressing the main challenges in DP implementation in a private practice setting and how to overcome these issues. We started our implementation in 2020 and we are currently scanning 100% of our histology cases. Pre-existing sample tracking infrastructure facilitated this process. We are currently using two high-capacity scanners (Aperio GT450DX) to digitize all histology slides at 40×. Aperio eSlide Manager WebViewer viewing software is bidirectionally linked with the laboratory information system. Scanning error rate, during the test phase, was 2.1% (errors detected by the scanners) and 3.5% (manual quality control). Pre-scanning phase optimizations and vendor feedback and collaboration were crucial to improve WSI quality and are ongoing processes. Regarding pathologists’ validation, we followed the Royal College of Pathologists recommendations for DP implementation (adapted to our practice). Although private sector implementation of DP is not without its challenges, it will ultimately benefit from DP safety and quality-associated features. Furthermore, DP deployment lays the foundation for artificial intelligence tools integration, which will ultimately contribute to improving patient care.

Digital Pathology Using Primary Case Sign-Out


 The applicability of the identified findings and the potential impact on patient outcomes for any individual diagnostic setting was unclear.
 In the majority of the identified studies, the authors reported diagnostic accuracy and clinical utility outcomes that supported digital pathology systems as a valuable diagnostic modality, comparable to conventional microscopy. These studies lacked statistical power calculations, making the accuracy of these statements unclear.
 One systematic review and 1 diagnostic study reported clinical utility outcomes of digital pathology. This evidence supported digital pathology using primary case sign-out for accurate prognosis of patient outcomes; however, the clinical utility compared to conventional microscopy was unclear in the identified evidence.
 One systematic review and 13 diagnostic cohort studies reported on the diagnostic accuracy of whole slide image (WSI). The identified outcomes indicated that WSI is a valuable diagnostic modality; however, a large range of diagnostic accuracy in different settings, and a lack of clear statistical power in all studies make comparator conclusions to conventional microscopy unclear.
 One systematic review and 4 diagnostic cohort studies reported diagnostic areas that can present challenges for a digital pathology implementation, the most common being the interpretation and grading of dysplasia.
 One identified systematic review stressed the importance of whole-system validation to identify strengths and weaknesses of specific digital pathology implementations. The range of diagnostic accuracy across studies also indicated that implementation of digital pathology primary case sign-out systems is associated with unclear diagnostic accuracy until appropriately validated.
 No relevant cost-effectiveness evidence for digital pathology using primary case sign-out was identified.

L’intelligence artificielle pourrait-elle intervenir dans l’aide au diagnostic des cancers du sein ? – L’exemple de HER2: Could artificial intelligence play a role in breast cancer diagnosis? – The example of HER2

HER2 is an important prognostic and predictive biomarker in breast cancer. Its detection makes it possible to define which patients will benefit from a targeted treatment. While assessment of HER2 status by immunohistochemistry in positive vs negative categories is well implemented and reproducible, the introduction of a new "HER2-low" category could raise some concerns about its scoring and reproducibility. We herein described the current HER2 testing methods and the application of innovative machine learning techniques to improve these determinations, as well as the main challenges and opportunities related to the implementation of digital pathology in the up-and-coming AI era.

Update on the current opinion, status and future development of digital pathology in Switzerland in light of COVID-19

AimsThe transition from analogue to digital pathology (DP) in Switzerland has coincided with the COVID-19 crisis. The Swiss Digital Pathology Consortium conducted a national survey to assess the experience of...

Digital Pathology: Current Status and Prospects of Clinical Application

In recent years, with the progress of image processing and network transmission technology, digital pathology (DP) is being more and more extensive applied in clinical practice, and new artificial-intelligence-assisted diagnosis technology based on digital imaging is emerging. Being a widely-used mature field, telepathology is changing the temporal and spatial scope of pathological diagnosis through remote electronic transmission of digital images. Fully digitized pathology departments are realizing the transformation of diagnostic modes and workflow from microscopic diagnosis to digital image computer review, and there have already been successful examples of large-scale fully digitized pathology departments. However, there are still many problems in the implementation of DP, for example, the quality stability and cost of the scanner, the validation of the system, the reengineering of the workflow, the training of pathologists and the change of their perception of DP, which all await further improvement. Although artificial intelligence diagnostic technology is showing great potential, its application in pathological work is still limited to the field of auxiliary diagnostics, and there is still a long way to go to the realization of comprehensive intelligent pathology. The rise of DP will bring about a profound change in the way of how pathological work is done and become a solid foundation for intelligent pathology.

Dissecting the Business Case for Adoption and Implementation of Digital Pathology: A White Paper from the Digital Pathology Association

We believe the switch to a digital pathology (DP) workflow is imminent and it is essential to understand the economic implications of conversion. Many aspects of the adoption of DP will be disruptive and have a direct financial impact, both in short term costs, such as investment in equipment and personnel, and long term revenue potential, such as improved productivity and novel tests. The focus of this whitepaper is to educate pathologists, laboratorians and other stakeholders about the business and monetary considerations of converting to a digital pathology workflow. The components of a DP business plan will be thoroughly summarized, and guidance will be provided on how to build a case for adoption and implementation as well as a roadmap for transitioning from an analog to a digital pathology workflow in various laboratory settings. It is important to clarify that this publication is not intended to list prices although some financials will be mentioned as examples. The authors encourage readers who are evaluating conversion to a DP workflow to use this paper as a foundational guide for conducting a thorough and complete assessment while incorporating in current market pricing. Contributors to this paper analyzed peer-reviewed literature and data collected from various institutions, some of which are mentioned. Digital pathology will change the way we practice through facilitating patient access to expert pathology services and enabling image analysis tools and assays to aid in diagnosis, prognosis, risk stratification and therapeutic selection. Together, they will result in the delivery of valuable information from which to make better decisions and improve the health of patients.

Diagnostic digital pathology implementation: Learning from the digital health experience.

Digital Pathology (also referred to as Telepathology and Whole Slide Imaging) is the process of producing high resolution digital images from tissue sections on glass slides. These glass slides are normally examined under a microscope by a pathologist as part of the diagnostic process. The emergence of digital pathology now means that digital images are stored on secure servers and can be viewed on computer monitors; enabling pathologists to work remotely and to collaborate with other colleagues when second opinions are needed. The implementation of digital pathology into clinical practice has many potential benefits. Although this has been long recognised, its adoption as a diagnostic tool remains low and pathologists’ projections about its future deployment are cautious. Notable early digital pathology adopters have led the way. The challenge now is to scale-up digital pathology beyond the relatively few large networks and centres of excellence. Many other areas of healthcare have accumulated experience about optimising approaches to digital health/healthcare technology deployment and sustainability. This has been done in a multi-disciplinary context and has applied theoretical/conceptual frameworks. Thus far there has been little use of similar frameworks in the planning of digital pathology deployment in clinical practice. In this essay, I will explore the scope of digital pathology implementation approaches that have been deployed in clinical practice and examine what can be learned from the wider healthcare experience of adopting, scaling-up and sustaining innovative healthcare solutions.

Recommendations for pathologic practice using digital pathology: consensus report of the Korean Society of Pathologists

Digital pathology (DP) using whole slide imaging (WSI) is becoming a fundamental issue in pathology with recent advances and the rapid development of associated technologies. However, the available evidence on its diagnostic uses and practical advice for pathologists on implementing DP remains insufficient, particularly in light of the exponential growth of this industry. To inform DP implementation in Korea, we developed relevant and timely recommendations. We first performed a literature review of DP guidelines, recommendations, and position papers from major countries, as well as a review of relevant studies validating WSI. Based on that information, we prepared a draft. After several revisions, we released this draft to the public and the members of the Korean Society of Pathologists through our homepage and held an open forum for interested parties. Through that process, this final manuscript has been prepared. This recommendation contains an overview describing the background, objectives, scope of application, and basic terminology; guidelines and considerations for the hardware and software used in DP systems and the validation required for DP implementation; conclusions; and references and appendices, including literature on DP from major countries and WSI validation studies.

Interobserver Variability in Ductal Carcinoma In Situ of the Breast.

Since most patients with ductal carcinoma in situ (DCIS) of the breast are treated upon diagnosis, evidence on its natural progression to invasive carcinoma is limited. It is estimated that around half of the screen-detected DCIS lesions would have remained indolent if they had never been detected. Many patients with DCIS are therefore probably overtreated. Four ongoing randomized noninferiority trials explore active surveillance as a treatment option. Eligibility for these trials is mainly based on histopathologic features. Hence, the call for reproducible histopathologic assessment has never sounded louder. Here, the available classification systems for DCIS are discussed in depth. This comprehensive review illustrates that histopathologic evaluation of DCIS is characterized by significant interobserver variability. Future digitalization of pathology, combined with development of deep learning algorithms or so-called artificial intelligence, may be an innovative solution to tackle this problem. However, implementation of digital pathology is not within reach for each laboratory worldwide. An alternative classification system could reduce the disagreement among histopathologists who use "conventional" light microscopy: the introduction of dichotomous histopathologic assessment is likely to increase interobserver concordance. Reproducible histopathologic assessment is a prerequisite for robust risk stratification and adequate clinical decision-making. Two-tier histopathologic assessment might enhance the quality of care.