By Jason An, Ph.D., CEO, Medicus
Last updated: 2026-10

A pathology image management system (IMS) is the software layer that ingests, stores, organizes, displays and shares whole slide images (WSI) and their metadata — linking them to cases in the laboratory information system (LIS) and making them available to pathologists, researchers and AI tools. A good IMS is vendor-neutral: it works with images from multiple scanners instead of locking each scanner's output into its own silo.

Why the IMS decision matters more than the scanner decision

Digital pathology has moved from research into clinical practice. In April 2017 the U.S. FDA permitted marketing of the first whole slide imaging system for reviewing digital surgical pathology slides, through the de novo pathway, based on a study of about 2,000 surgical pathology cases [1]. The pivotal multicenter study behind that decision — 1,992 cases, 16 pathologists, 15,925 reads — found WSI noninferior to microscopy for primary diagnosis, with major discordance rates of 4.9% for WSI and 4.6% for microscopy [2].

Once a department scans routinely, the bottleneck shifts from capturing images to managing them. Scanners are replaced and added over time, often from different manufacturers. Each may produce its own file format and viewer. Without a common management layer, pathology and IT teams end up maintaining parallel systems, and data that could train or validate AI is scattered and hard to find.

The Digital Pathology Association's practical guide to WSI describes implementation as a multifaceted, inherently multidisciplinary effort requiring pathologists, technologists and executive leadership [3]. The IMS is where those requirements meet, so it deserves the most careful evaluation.

What a pathology IMS does

Core functions

• Ingestion from one or more scanners, with automatic case matching via barcode or accession number.
• Storage and lifecycle management — tiered storage, retention rules, archiving and retrieval.
• Viewing — fast pan/zoom, multi-slide comparison, annotation and measurement.
• Worklists and case management — assignment, prioritization, status tracking, sign-out workflow integration with the LIS.
• Sharing and collaboration — consultations, tumor boards, education, multi-site reading.
• Integration — LIS, EMR/HIS, enterprise archives, and AI/image analysis applications.
• Governance — user roles, audit trails, de-identification for research, export controls.

Where "vendor-neutral" fits

Vendor neutrality means the IMS can ingest, display and manage WSI from different scanner manufacturers and expose them through open interfaces. This is where the DICOM standard matters. DICOM Working Group 26 (Pathology) develops the standard so that pathology can handle whole slide images and related data and interoperate with other healthcare systems [4]. Its Supplement 145, "Whole Slide Microscopic Image IOD and SOP Classes," was finalized in 2010 [5].

Clunie notes that proprietary formats and closed single-vendor platforms still prevail and depend on multiformat conversion libraries — workable for small deployments but not sustainable at industrial scale — while DICOM allows reuse of enterprise infrastructure for storage, security and business continuity, and supports color consistency via ICC profiles and annotation encoding [6]. Herrmann et al. implemented DICOM across a multisite, multivendor network, encoding image data from four vendor-specific formats together with patient and specimen metadata, and accessed them through RESTful web services using existing archive software. They also found that the choice of compression method has a major impact on data access efficiency [7].

Practical takeaway: ask not only "Do you support DICOM?" but "Which DICOM objects, which transfer syntaxes, and can you prove it with images from our scanners?"

Validation and regulatory considerations

• Laboratory validation. The College of American Pathologists (CAP) guideline on validating WSI for diagnostic purposes, updated in 2021–2022, contains three strong recommendations and nine good practice statements. It reaffirms a validation set of at least 60 cases, intraobserver concordance between WSI and glass slides, and a 2-week washout period between modalities, and flags overall WSI–glass concordance below 95% as a particular concern [8][9]. Your IMS should make it easy to run and document such a validation.
• Device regulation. The FDA's 2016 final guidance on technical performance assessment of WSI devices describes how to characterize the technical components that affect image quality and performance [10]. If the system will be used for primary diagnosis, confirm the regulatory status of the specific viewer and display configuration in your jurisdiction (e.g., FDA in the U.S., MFDS in Korea).
• Research vs. clinical. Many institutions use one IMS for both. Make sure research exports are de-identified and logged, and that clinical records remain unaltered.

RFP checklist: must-have vs. nice-to-have

Questions to ask every vendor

1. Which scanner models and file formats are supported today, in production, at a reference site?
2. Can we export all images, annotations and metadata in DICOM or another documented open format without additional fees?
3. How is a third-party AI algorithm deployed, and how are its results stored and displayed?
4. What happens to performance when we double our slide volume?
5. How are research exports de-identified and audited?
6. Which components, if any, carry regulatory clearance for primary diagnosis, and for which configurations?

Implementation roadmap

1. Inventory scanners, formats, storage, LIS interfaces and current slide volume.
2. Define use cases — primary diagnosis, consultation, education, research, AI — and rank them.
3. Pilot with real slides from every scanner and one AI integration.
4. Validate per CAP guidance for each intended diagnostic use [8].
5. Scale in phases by subspecialty, with storage and network monitoring.
6. Build the data foundation — curated, searchable, governed datasets for research and AI.

How Medicus approaches this

Medicus, Inc. built MeDIAuto® — an AI-based integrated pathology data infrastructure — for the problems described above: whole slide images fragmented across scanners and solution vendors, operational burden on pathology and IT teams, and the lack of a data foundation for AI and research. MeDIAuto standardizes WSI from different sources so they can be collected, managed, analyzed and used for research in one place. According to our company timeline, MeDIAuto is under a supply contract with Seoul St. Mary's Hospital (December 2025). MeDIAuto is now in routine clinical use at the hospital.

For research and AI development on sensitive data, our Cloud Safe Zone provides an analysis environment where only designated users can work and data import/export is controlled. Once images are organized, teams can extend into quantitative analysis such as spatial biomarkers.

To discuss your scanner mix and RFP requirements, contact our team.

FAQ

What is the difference between a pathology IMS and a scanner viewer?

A scanner viewer typically opens images from one manufacturer's scanner. An IMS manages images from many sources, ties them to LIS cases, controls access, and connects to downstream tools such as AI applications and archives.

What does vendor-neutral WSI mean?

It means whole slide images from different scanner manufacturers can be stored, viewed and exchanged through one system using open formats and interfaces, such as DICOM WSI, rather than each vendor's proprietary stack [5][6].

Is DICOM required for digital pathology?

It is not universally mandated, but DICOM WSI support is increasingly important for interoperability, long-term archiving and reuse of enterprise imaging infrastructure [6][7]. Treat it as a must-have in an RFP.

How many cases are needed to validate a digital pathology system?

The CAP guideline reaffirms a validation set of at least 60 cases, establishing intraobserver concordance between WSI and glass slides with a 2-week washout period between modalities. Laboratories should be particularly concerned if overall WSI–glass concordance is below 95% [8][9].

Can a pathology IMS run on the cloud?

Many systems support cloud or hybrid deployment. The decision depends on network bandwidth, data-residency rules, security requirements and cost; ask vendors for reference architectures and data-egress controls.

How does an IMS support pathology AI?

By consolidating images and metadata, providing APIs for algorithms, storing and displaying results, and enabling de-identified datasets for training and validation. Without this layer, AI projects often stall on data collection.

This guide is educational and is not clinical or regulatory advice.

References

1. U.S. Food and Drug Administration. FDA allows marketing of first whole slide imaging system for digital pathology. Press release, April 12, 2017. fda.gov
2. Mukhopadhyay S, Feldman MD, Abels E, et al. Whole slide imaging versus microscopy for primary diagnosis in surgical pathology: a multicenter blinded randomized noninferiority study of 1992 cases (pivotal study). Am J Surg Pathol. 2018;42(1):39-52. PubMed 28961557
3. Zarella MD, Bowman D, Aeffner F, et al. A practical guide to whole slide imaging: a white paper from the Digital Pathology Association. Arch Pathol Lab Med. 2019;143(2):222-234. PubMed 30307746
4. DICOM Standards Committee. WG-26 Pathology. dicomstandard.org
5. DICOM Standards Committee, Working Group 26. Supplement 145: Whole Slide Microscopic Image IOD and SOP Classes. Final text, 2010-08-24. dicomstandard.org (PDF)
6. Clunie DA. DICOM format and protocol standardization—a core requirement for digital pathology success. Toxicol Pathol. 2021;49(4):738-749. PubMed 33063645
7. Herrmann MD, Clunie DA, Fedorov A, et al. Implementing the DICOM standard for digital pathology. J Pathol Inform. 2018;9:37. PubMed 30533276
8. Evans AJ, Brown RW, Bui MM, et al. Validating whole slide imaging systems for diagnostic purposes in pathology. Arch Pathol Lab Med. 2022;146(4):440-450. PubMed 34003251
9. College of American Pathologists. Validating Whole Slide Imaging for Diagnostic Purposes in Pathology (guideline page). cap.org
10. U.S. Food and Drug Administration. Technical Performance Assessment of Digital Pathology Whole Slide Imaging Devices. Final guidance, April 2016. fda.gov