# Sustaining the Integrative Imaging Informatics for Cancer Research (I3CR) Center

> **NIH NIH U24** · WASHINGTON UNIVERSITY · 2024 · $802,142

## Abstract

Abstract
Artificial intelligence (AI) and other computationally intensive methods have the potential to
revolutionize cancer imaging research and patient care. The broad adoption of these
technologies depends on the availability development of imaging informatics tools to assist
users in managing massive data sets, generating well-curated annotations, and accessing
scalable computing resources. The Integrative Imaging Informatics for Cancer Research (I3CR)
Center has played a lead role in implementing cancer imaging informatics technology, with a
focus on expanding the widely used open source XNAT informatics platform to better support
computational workflows in cancer imaging. I3CR has also developed knowledge management
tools to better track data processing and analysis, including tools for orchestrating and tracking
container-based computing pipelines. As result of this work, XNAT has emerged as the most
widely used imaging informatics platform in cancer research. It is deployed in over 200
organizations across academia and industry and has been adopted across a wide range of
research contexts, including preclinical imaging, multi-site clinical trials, and clinical translation.
As the I3CR informatics platform has matured and been widely adopted, the Center is now
evolving to the next phase of development to more broadly sustain the platform. In the work
proposed here, we will sustain the I3CR’s ongoing engineering initiatives and expand its
outreach efforts. The Center’s sustainment activities will build on and extend the I3CR
platform’s expansive set of data and knowledge management capabilities, with a focus on
addressing key emergent needs within our user base. In Aim 1, we will continue to develop the
XNAT-based data management platform, including adding standards-based clinical interfaces,
developing a cohort discovery service with natural language processing support, implementing a
task automation service, and extending its container-based computing service to support high
performance computing and cloud computing environments. In Aim 2, we will implement a suite
of integrations with complementary image analysis and data sharing platforms, including The
Cancer Image Archive and the NCI Imaging Data Commons. In Aim 3, we will expand the
I3CR’s outreach initiatives to ensure broad and effective adoption of the I3CR informatics
platforms. The Center’s training program will utilize the XNAT Academy education platform to
host a series of online training programs directed at specific audiences including developers,
data scientists, integrators, and system administrators. A suite of supporting cloud services will
be implemented assist the community in adopting and developing on the I3CR platform.

## Key facts

- **NIH application ID:** 10817030
- **Project number:** 5U24CA258483-04
- **Recipient organization:** WASHINGTON UNIVERSITY
- **Principal Investigator:** Daniel Scott Marcus
- **Activity code:** U24 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $802,142
- **Award type:** 5
- **Project period:** 2021-04-06 → 2026-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10817030

## Citation

> US National Institutes of Health, RePORTER application 10817030, Sustaining the Integrative Imaging Informatics for Cancer Research (I3CR) Center (5U24CA258483-04). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10817030. Licensed CC0.

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