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Bryan Stunkel, Co-Founder | Chairman & President, ZebreBryan Stunkel, co-founder, chairman & president of Zebre, has over 20 years of experience modernizing and supporting deployments of healthcare data storage, protection, and cloud-based infrastructure architectures. Over that time, he observed the expansion of imaging volumes and the emergence of Digital Imaging and Communications in Medicine (DICOM) files as the standard for storing, transferring, and archiving clinical images. As file sizes grew rapidly, healthcare providers kept investing in storage and infrastructure, often without a practical alternative. Stunkel stepped back, recognized the pattern, and pursued a file-level approach that optimizes DICOM data.
Zebre is the result of that insight. It is a medical imaging discovery and optimization platform that reduces DICOM storage needs by 40 to 50 percent while preserving diagnostic integrity.
“For the first time, DICOM can be optimized at the file level; completely agnostic of storage and PACS platform(s),” says Stunkel.
How does Zebre integrate with existing PACS environments without requiring system replacement efforts?
His idea took shape in 2020 through a collaboration with the vice chairman of radiology at an academic medical center in Nashville, TN. Together, they authored patented methods for solving the problem of caching, storing, and managing large DICOM datasets that became the company’s foundation. At the Radiological Society of North America (RSNA) annual meeting in Chicago, feedback on the platform’s capabilities was striking: “You’re the only ones doing this.”
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For the first time, DICOM can be optimized at the file level; completely agnostic of storage and PACS platform(s).
Zebre works adjacent to existing Picture Archiving and Communication Systems (PACS), so hospitals don’t need new viewers or system replacements. Deployed within the health system’s network, Zebre analyzes repositories in place and outputs non-PII reporting for planning and governance. It can discover, analyze, and optimize files across deployments. Most PACS approaches focus on moving files or applying limited optimization within a single system, which leaves an operational gap that Zebre addresses through cross-environment, file-level DICOM optimization that preserves clinical value.
Why are discovery and optimization tools important in large multi-PACS healthcare environments today?
Building on that foundation, Zebre created two tools, AnalyZE and OptimiZE, that operate as a unified system. AnalyZE is the discovery engine that scans imaging ecosystems across hospitals and departments to identify active PACS platforms, assess data growth rates, and surface decision-level optimization intelligence organizations didn’t have before. Once a health system understands its data, it can deploy OptimiZE, which applies filespecific strategies to reduce size while protecting clinical integrity. It applies two patented methods, derived image and region-of-interest optimization, along with format conversion and expired-file cleanup. These capabilities provide more control than native PACS tools, enabling administrators to reduce storage without compromising diagnostic value.
To what extent does source-level optimization reduce recurring cloud storage migration costs effectively?
Cloud migrations highlight the impact of file-level optimization. As new PACS deployments move to the cloud, hospitals face recurring storage fees that begin immediately. In many scenarios, healthcare providers migrate entire datasets simply because they lack visibility into their data, including duplicate or expired studies that now incur monthly costs indefinitely. Through AnalyZE and OptimiZE, organizations migrate only relevant data while optimizing retained datasets to reduce redundant and non-diagnostic content, lowering recurring cloud storage costs. By optimizing data at the source prior to migration, organizations also benefit from smaller datasets that transfer more efficiently to the cloud.
This is particularly important for large, multi-PACS environments, where organizations often manage several imaging systems and lack a unified view of what they are storing. With both tools deployed and adoption accelerating across larger healthcare providers, Zebre is shifting the industry from reacting to DICOM growth to optimizing it at the point where it is created.
Advancing Enterprise Imaging Economics Through Intelligent DICOM Optimization
Enterprise imaging leaders face a financial strain that traditional systems have failed to correct. Medical imaging volumes continue to rise across radiology, cardiology and specialty service lines, yet the underlying DICOM standard remains inherently storage-intensive. Each new modality increases file size, retention policies extend indefinitely and multi-site health systems inherit fragmented archives after every acquisition. The result is a compounding financial burden tied not to clinical value but to file weight and duplication.
PACS vendors have focused on workflow, interoperability and viewer functionality. Storage providers have concentrated on capacity and cloud migration. Neither addresses the root constraint embedded in the file itself. DICOM objects are large, frequently replicated and difficult to rationalize across environments. Health systems migrating from on-premise infrastructure to cloud architectures confront this reality directly. Reimbursement occurs once, yet storage costs recur monthly. Leadership teams must question the sustainability of the current model.
Executives evaluating modern imaging platforms should look beyond feature expansion and examine whether a solution directly alters the economics of data stewardship. One dimension involves visibility. Large health systems often lack a precise understanding of what resides across disparate PACS deployments. Without granular intelligence on modality mix, file composition and duplication patterns, migration strategies default to moving everything. That approach increases transfer time, bandwidth consumption and long-term cloud expense. A platform that can analyze heterogeneous environments and quantify the true composition of DICOM archives creates decision leverage before capital is committed.
Another dimension involves optimization at the file level rather than at the storage tier. Many native PACS tools offer compression or format conversion, yet these capabilities are typically platform-bound and inconsistently applied across enterprise estates. Health systems operating five or more PACS environments cannot depend on isolated features embedded within each system. What changes the financial trajectory is the ability to optimize directly against the DICOM standard itself, irrespective of vendor architecture. Techniques such as region-of-interest optimization and elimination of redundant derived images alter storage requirements without disrupting diagnostic integrity. When reductions materially shrink the existing footprint, the conversation shifts from incremental savings to structural improvement.
A third dimension concerns deployment neutrality. Imaging environments evolve through mergers, specialty expansion and cloud transition. A platform that requires wholesale replacement of PACS infrastructure introduces friction and clinical risk. Executives should favor technology that layers into existing estates, performs discovery and optimization across vendors and supports both on-premise and cloud strategies. This flexibility becomes particularly valuable during large-scale migrations, where understanding what to move and what to rationalize can materially accelerate timelines and reduce recurring cloud charges.
Zebre presents a distinctive response to these pressures. It does not function as a PACS replacement but as a discovery and optimization layer purpose-built for DICOM environments. Its AnalyZE capability assesses complex estates, identifying platform mix, data growth patterns and optimization potential before any migration or transformation initiative proceeds.
Its OptimiZE platform applies region-of-interest optimization and derived-image deduplication alongside standardized conversion techniques, enabling measurable storage reduction across heterogeneous systems. For executives responsible for long-term imaging economics, Zebre represents a disciplined path to controlling storage growth, accelerating cloud transitions and aligning imaging data strategy with financial reality.
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Medical Imaging Platforms Info
Q1
What Role Do Medical Imaging Platforms Play in Modern Imaging Data Strategy?
Medical Imaging Platforms help healthcare organizations manage the growing volume, cost, and complexity of diagnostic image data. Beyond image viewing, the category increasingly includes discovery, optimization, storage planning, migration support, and governance functions. Effective platforms give leaders clearer visibility into DICOM archives, reduce unnecessary data movement, and support imaging operations without disrupting clinical workflows. This matters as imaging data grows across departments, retention periods lengthen, and infrastructure teams face pressure to control costs without limiting access to clinically useful studies.
Q2
How Does Zebre Apply This Category to DICOM Storage Optimization?
Zebre shows how Medical Imaging Platforms can address imaging economics at the file level. Its platform focuses on DICOM discovery and optimization rather than replacing PACS infrastructure. Zebre’s approach includes AnalyZE, which scans imaging ecosystems and identifies active PACS platforms, data growth, and optimization potential, and OptimiZE, which applies file-specific actions to reduce storage demands while protecting diagnostic integrity. The platform is designed to reduce DICOM storage needs by 40 to 50 percent while remaining storage- and PACS-agnostic.
Q3
Why Do Storage Visibility and Data Discovery Matter Before Cloud Migration?
Healthcare organizations often move large imaging archives to the cloud without fully knowing what the datasets contain. Medical Imaging Platforms can reveal duplicate, expired, redundant, or non-diagnostic content before migration decisions are made. That visibility helps teams avoid transferring unnecessary data, shorten migration timelines, and reduce recurring cloud storage charges tied to oversized DICOM repositories. It also gives decision makers a clearer view of which data should be retained, optimized, converted, or removed before long-term storage commitments increase.
Q4
What Capabilities Should Organizations Look for in an Imaging Optimization Platform?
Organizations should evaluate whether a platform can work across existing systems, analyze DICOM data in place, and support governance without exposing patient information. Medical Imaging Platforms should also preserve diagnostic value while improving storage efficiency. Useful capabilities may include file-level optimization, region-of-interest strategies, derived-image handling, format conversion, expired-file cleanup, and reporting that translates technical findings into planning insight. The strongest platforms are practical for enterprise estates where imaging archives are fragmented across departments, vendors, and deployment models.
Q5
What Makes Zebre Relevant for Multi-PACS Imaging Environments?
Zebre is relevant because it works adjacent to existing PACS environments instead of requiring new viewers or system replacement. In large estates, Medical Imaging Platforms need to operate across departments and deployments, not only within one vendor system. Zebre analyzes repositories within the health system’s network, provides non-PII reporting, and supports optimization across heterogeneous imaging environments. Its patented methods include derived-image and region-of-interest optimization, giving administrators more control than platform-bound tools typically provide.
Q6
How Can Imaging Platforms Create Long-Term Operational Value?
Long-term value comes from controlling storage growth while maintaining clinical confidence. Medical Imaging Platforms can support better capacity planning, more efficient cloud transition, and cleaner imaging data stewardship. When optimization happens at the source, organizations can retain clinically meaningful information, reduce infrastructure pressure, and make imaging strategy less reactive as modalities, retention demands, and archive sizes continue to expand. This kind of approach helps align imaging data management with financial planning, operational resilience, and ongoing clinical access.
Company
Zebre
Management
Bryan Stunkel, Co-Founder | Chairman & President, Brent Savoie, MD/JD, Director, Clinical & Regulatory Strategy, Joe Christopher, Fractional CTO, Technology & Platform Strategy, Dan Karl, Go-to-Market & Commercial Scale Advisor, Zebre
Description
Zebre is a medical-imaging platform that helps healthcare organizations understand and manage DICOM storage. Its AnalyZE tool identifies waste and cost drivers, while OptimiZE applies data-cleanup actions securely. It reduces storage costs and improves imaging-data efficiency without exposing patient information.
