Proscia Co-Founder Talks Impact of DICOM in Digital Pathology

By Fred Pennic

Proscia Co-Founder Talks Impact of DICOM in Digital Pathology

The world of digital pathology is undergoing a significant transformation, with the adoption of DICOM (Digital Imaging and Communications in Medicine) emerging as a game-changer. This international standard, already widely used in radiology, is poised to transform how pathology images and data are stored, shared, and analyzed.

By promoting interoperability among various hardware and software solutions, DICOM empowers laboratories to build more efficient and scalable digital pathology ecosystems. This shift not only streamlines workflows for pathologists but also unlocks new possibilities for collaboration, AI development, and data management.

In this interview, Nathan Buchbinder, Co-Founder and Chief Strategy Officer at Proscia, a provider of digital pathology solutions, delves into the profound impact of DICOM on the pathology industry. He explores the key benefits of this standardization, its implications for AI development, and how it paves the way for a more integrated and innovative future in pathology.

How does the adoption of DICOM into digital pathology represent a groundbreaking shift in the pathology industry?

Nathan Buchbinder, Chief Strategy Officer and Co-Founder at Proscia: DICOM, which stands for Digital Imaging and Communications in Medicine, is an international standard for storing, transmitting, and managing medical imaging information and related data. The standardization it introduces is what's so critical. There are dozens of formats for pathology images and metadata used in practice today. The growing adoption of DICOM is simplifying this and, in doing so, paving the way for enhanced interoperability among the variety of hardware and software solutions that laboratories require to scale their digital pathology implementations. I say "paving the way" because these solutions must support DICOM to provide this improved interoperability.

What are the benefits of enhanced interoperability?

Nathan Buchbinder: For laboratories, it overcomes one of the major complexities when it comes to building out the best digital pathology ecosystem for its needs. Some laboratories might feel locked into certain applications that are compatible with the image formats their scanners create, for example. The enhanced interoperability that DICOM delivers gives them more freedom to choose and safeguards their investments.

Pathologists benefit from more efficient workflows since images and metadata pass seamlessly among solutions and don't need to be converted to different formats. They can also collaborate on a case regardless of the platforms they are using and get a centralized view of all impactful information. By extension, radiology has already shifted to DICOM. This means that radiologists can analyze pathology imaging and data in the DICOM format and vice versa to gain a more comprehensive understanding.

How does DICOM enable long-term storage and infrastructure for pathology images and metadata?

Nathan Buchbinder: The adoption of DICOM in pathology is helping to simplify an organization's IT footprint. Considering that DICOM is already the standard for other enterprise imaging disciplines, hospitals and health systems almost certainly have IT infrastructure in place for storing DICOM images. They can leverage this same infrastructure for their DICOM pathology images and associated metadata, streamlining implementation, reducing IT overhead, and driving down costs. This is important because storage for pathology images can sometimes be expensive given the massive size (1GB or more) of a whole slide image.

How does standardization using DICOM streamline AI development and data management?

Nathan Buchbinder: Organizations have historically needed to train and validate their AI algorithms on the many image formats commonly used in routine practice. This not only takes time but also often requires significant volumes of diverse, high-quality images in the different formats.

Once DICOM fully establishes itself as the standard in digital pathology, organizations may, in theory, only need to train and validate their AI applications on DICOM images. This may accelerate AI development and provide more data for building these solutions. I should note that we're probably several years away from this happening, but it does paint a very promising picture.

As for data management, the DICOM standard is evolving to represent the various outputs of AI - overlays, text fields, and measurements, for example. It will be the only image format in pathology to include these outputs. The impact is that it may be much easier to deploy AI algorithms in practice since IT teams will not need to take any additional steps to store and manage the results that they generate.

In what ways do you anticipate the evolution of DICOM in digital pathology mirroring that of radiology?

Nathan Buchbinder: We already are seeing the evolution of DICOM in digital pathology mirror what happened in radiology. When radiology went digital, it, too, relied on a variety of proprietary image formats, and this complexity is what led to the introduction of DICOM. As DICOM increasingly established itself, it led to many of the same benefits we are seeing emerge in pathology today - workflow efficiencies, streamlined collaboration, improved decision-making, and a growing interplay among various imaging disciplines. It also helped to optimize storage and data management and drive new innovations. I anticipate that just as the impact of these benefits grew as DICOM adoption increased, we will see the same happen in pathology over the next few years.

About Nathan Buchbinder

As Co-Founder and Chief Strategy Officer, Nathan guides Proscia in continuing to set the direction for the future of pathology. He sits at the intersection of the company's customers, its products, and the broader digital pathology community, overseeing strategic growth opportunities and leading Proscia's participation in industry initiatives. Nathan has a Bachelor's Degree in Biomedical Engineering from Johns Hopkins University and a Master's degree in Biomedical Innovation and Development from the Georgia Institute of Technology.

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