Digital Pathology Bears Fruit

Fully digitising pathology operations has led to greater efficiency, cost savings, and quicker diagnosis for the Laboratory of Pathology East Netherlands (LabPON).

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This article was written by Mark Nicholls and was originally published in Healthcare-in-Europe on 03.03.2022. It is republished here with their kind permission.

Details were outlined to the 8th Digital Pathology and AI Congress in London by Alexi Baidoshvili, Professor of Pathology, who specialises in digital and computational pathology at LabPON. He reported that LabPON had completely digitised its diagnostic routines for clinical cases in July 2015 and has continued to evolve the technology and processes ever since. Additional milestones were the development and introduction of AI software for image analysis in 2018 and a new Image Management System (IMS) in 2021, with further AI development and integration planned for 2022.

In his presentation, the expert discussed the investments necessary to introduce digital pathology. Areas to be considered include flow analysis in the laboratory, storage, scanners, the need for a robust IMS, training of staff, consultation workflows, software and enabling remote working. On average, setting up a laboratory for digital pathology requires at least 1.5 million euros per year, he calculated, with AI systems not included. However, investments might be a bit lower for institutions that already have a robust IT infrastructure in place. “It is very important to choose the right IMS,” he added, pointing out desirable features such as open architecture, integration with commonly used scanner types, robustness, scalability, support for external consultation and – not least – a user-friendly interface.

 

Safer, Happier, More Productive

Details were outlined to the 8th Digital Pathology and AI Congress in London by Alexi Baidoshvili, Professor of Pathology, who specialises in digital and computational pathology at LabPON. He reported that LabPON had completely digitised its diagnostic routines for clinical cases in July 2015 and has continued to evolve the technology and processes ever since. Additional milestones were the development and introduction of AI software for image analysis in 2018 and a new Image Management System (IMS) in 2021, with further AI development and integration planned for 2022.

In his presentation, the expert discussed the investments necessary to introduce digital pathology. Areas to be considered include flow analysis in the laboratory, storage, scanners, the need for a robust IMS, training of staff, consultation workflows, software and enabling remote working. On average, setting up a laboratory for digital pathology requires at least 1.5 million euros per year, he calculated, with AI systems not included. However, investments might be a bit lower for institutions that already have a robust IT infrastructure in place. “It is very important to choose the right IMS,” he added, pointing out desirable features such as open architecture, integration with commonly used scanner types, robustness, scalability, support for external consultation and – not least – a user-friendly interface.

 

Current and Future AI benefits

After transitioning to digital diagnosis, and the seamless integration of interoperable AI, Baidoshvili noted an ‘impressive’ accuracy of the system, for example in cancer detection and Gleason grading of cases. Referencing the lab’s experience with prostate AI solutions Concentriq from Proscia and Galen from Ibex, he praised their seamless and intuitive workflows, with initial results showing the potential to reduce immunohistochemistry costs, subject to further validation.

The expert also pointed out the potential of automatic report generation with AI assistance. ‘Thanks to AI, we can save 1:18 minutes of diagnostic time in every colon diagnosis.’ Applying this to the 500+ cases LabPON processed in 2020, Baidoshvili calculated more than 11 hours of saved diagnosis time for pathologists.

Overall, the switch to digitisation had widespread benefits with much- improved logistics, handy tools in IMS resulting in high efficiency, flexible and remote working, easy access to computer archives, better and more efficient diagnostic quality and improved diagnostic logistics, leading to a happier pathology workforce.

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Alexi Baidoshvili, Professor of Pathology, DT Medical University, Georgia.

He specialises in digital and computational pathology at the Laboratory of Pathology East Netherlands (LabPON), an institution with 120 employees, 18 pathologists and 90 lab technicians.

Furthermore, Prof Baidoshvili is an active board member of several international organisations and organiser of conferences. At LabPON, he and his team are working on the development of various image recognition programs.