DPA–ESDIP–JSDP Task Force for Worldwide Adoption of Digital Pathology

Eloy, Catarina; Bychkov, Andrey; Pantanowitz, Liron; Fraggetta, Filippo; Bui, MarilynM; Fukuoka, Junya; Zerbe, Norman; Hassell, Lewis; Parwani, Anil V.

doi:10.4103/jpi.jpi_65_21

Cited by 8 publications

(2 citation statements)

References 19 publications

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“…Diagnostic merits of WSI are evidenced in scores of investigations reporting significantly high concordance rates with conventional microscopy throughout numerous disciplines and increasingly for arenas formerly posing hurdles curtailing digital adoption, e.g., cytopathology [ 7 , 8 , 9 , 10 ]. Obstacles in modeling business viability for laboratory digitization are surmounted as advanced technology enables a similar roadmap to ubiquitous DP diagnostics already traversed by radiology [ 10 ]. The interconnectivity of pathologists, staff, and resources observed following WSI implementation at The Ohio State University reflect a primary endpoint of laboratory digitization.…”

Section: Introductionmentioning

confidence: 99%

Cultivating Clinical Clarity through Computer Vision: A Current Perspective on Whole Slide Imaging and Artificial Intelligence

Patel

Shaker

Mohanty³

et al. 2022

Diagnostics

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Diagnostic devices, methodological approaches, and traditional constructs of clinical pathology practice, cultivated throughout centuries, have transformed radically in the wake of explosive technological growth and other, e.g., environmental, catalysts of change. Ushered into the fray of modern laboratory medicine are digital imaging devices and machine-learning (ML) software fashioned to mitigate challenges, e.g., practitioner shortage while preparing clinicians for emerging interconnectivity of environments and diagnostic information in the era of big data. As computer vision shapes new constructs for the modern world and intertwines with clinical medicine, cultivating clarity of our new terrain through examining the trajectory and current scope of computational pathology and its pertinence to clinical practice is vital. Through review of numerous studies, we find developmental efforts for ML migrating from research to standardized clinical frameworks while overcoming obstacles that have formerly curtailed adoption of these tools, e.g., generalizability, data availability, and user-friendly accessibility. Groundbreaking validatory efforts have facilitated the clinical deployment of ML tools demonstrating the capacity to effectively aid in distinguishing tumor subtype and grade, classify early vs. advanced cancer stages, and assist in quality control and primary diagnosis applications. Case studies have demonstrated the benefits of streamlined, digitized workflows for practitioners alleviated by decreased burdens.

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Section: Introductionmentioning

confidence: 99%

Cultivating Clinical Clarity through Computer Vision: A Current Perspective on Whole Slide Imaging and Artificial Intelligence

Patel

Shaker

Mohanty³

et al. 2022

Diagnostics

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“…As the transition to DP continues to evolve nationally and internationally, there is now comprehensive literature on DP validation for diagnostic reporting5 6 and increasing numbers of experiential commentaries on DP implementation,2 7–12 with national and international groups being established to support the pathology community in the transition, and onward to the development and use of artificial intelligence (AI) 13–16. However, similar support for trainees is lacking.…”

Section: Introductionmentioning

confidence: 99%

Impact of the transition to digital pathology in a clinical setting on histopathologists in training: experiences and perceived challenges within a UK training region

et al. 2022

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AimsWith increasing utility of digital pathology (DP), it is important to consider the experiences of histopathologists in training, particularly in view of the varied access to DP across a training region and the consequent need to remain competent in reporting on glass slides (GS), which is also relevant for the Fellowship of the Royal College of Pathologists part 2 examination. Understanding the impact of DP on training is limited but could aid development of guidance to support the transition. We sought to investigate the perceptions of histopathologists in training around the introduction of DP for clinical diagnosis within a training region, and the potential training benefits and challenges.MethodsAn anonymous online survey was circulated to 24 histopathologists in training within a UK training region, including a hospital which has been fully digitised since summer 2020.Results19 of 24 histopathologists in training responded (79%). The results indicate that DP offers many benefits to training, including ease of access to cases to enhance individual learning and teaching in general. Utilisation of DP for diagnosis appears variable; almost half of the (10 of 19) respondents with DP experience using it only for ancillary purposes such as measurements, reporting varying levels of confidence in using DP clinically. For those yet to undergo the transition, there was a perceived anxiety regarding digital reporting despite experience with DP in other contexts.ConclusionsThe survey evidences the need for provision of training and support for histopathologists in training during the transition to DP, and for consideration of their need to maintain competence and confidence with GS reporting.

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The Evolving Role of Artificial Intelligence in Gastrointestinal Histopathology: An Update

Codipilly,

Faghani,

Hagan

et al. 2024

Clinical Gastroenterology and Hepatology

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DPA–ESDIP–JSDP Task Force for Worldwide Adoption of Digital Pathology

Cited by 8 publications

References 19 publications

Cultivating Clinical Clarity through Computer Vision: A Current Perspective on Whole Slide Imaging and Artificial Intelligence

Cultivating Clinical Clarity through Computer Vision: A Current Perspective on Whole Slide Imaging and Artificial Intelligence

Impact of the transition to digital pathology in a clinical setting on histopathologists in training: experiences and perceived challenges within a UK training region

The Evolving Role of Artificial Intelligence in Gastrointestinal Histopathology: An Update

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