Abstract
PURPOSEWe summarize Quantitative Imaging Informatics for Cancer Research (QIICR; U24 CA180918), one of the first projects funded by the National Cancer Institute (NCI) Informatics Technology for Cancer Research program.METHODSQIICR was motivated by the 3 use cases from the NCI Quantitative Imaging Network. 3D Slicer was selected as the platform for implementation of open-source quantitative imaging (QI) tools. Digital Imaging and Communications in Medicine (DICOM) was chosen for standardization of QI analysis outputs. Support of improved integration with community repositories focused on The Cancer Imaging Archive (TCIA). Priorities included improved capabilities of the standard, toolkits and tools, reference datasets, collaborations, and training and outreach.RESULTSFourteen new tools to support head and neck cancer, glioblastoma, and prostate cancer QI research were introduced and downloaded over 100,000 times. DICOM was amended, with over 40 correction proposals addressing QI needs. Reference implementations of the standard in a popular toolkit and standalone tools were introduced. Eight datasets exemplifying the application of the standard and tools were contributed. An open demonstration/connectathon was organized, attracting the participation of academic groups and commercial vendors. Integration of tools with TCIA was improved by implementing programmatic communication interface and by refining best practices for QI analysis results curation.CONCLUSIONTools, capabilities of the DICOM standard, and datasets we introduced found adoption and utility within the cancer imaging community. A collaborative approach is critical to addressing challenges in imaging informatics at the national and international levels. Numerous challenges remain in establishing and maintaining the infrastructure of analysis tools and standardized datasets for the imaging community. Ideas and technology developed by the QIICR project are contributing to the NCI Imaging Data Commons currently being developed.
Highlights
Medical imaging is increasingly important in cancer applications.[1,2] Few existing imaging biomarkers are used to guide clinical decisions.[3]
Quantitative Imaging Informatics for Cancer Research (QIICR) was motivated by the 3 use cases from the National Cancer Institute (NCI) Quantitative Imaging Network. 3D Slicer was selected as the platform for implementation of open-source quantitative imaging (QI) tools
Ideas and technology developed by the QIICR project are contributing to the NCI Imaging Data Commons currently being developed
Summary
Medical imaging is increasingly important in cancer applications.[1,2] Few existing imaging biomarkers are used to guide clinical decisions.[3] Major efforts are underway to identify, validate, and deploy new imaging tools in the clinic These efforts rely on the discovery of novel quantitative imaging (QI) biomarkers, which promise to support objective and reproducible characterization of disease and allow for more personalized approaches to diagnosis and therapy. One such effort is led by the National Cancer Institute (NCI) via its Quantitative Imaging Network (QIN) initiative,[4,5,6] with primary goals including collecting data from ongoing imaging clinical trials, developing innovative methods for data collection and analysis, and establishing consensus on QI methods.[4]. The Informatics Technology for Cancer Research (ITCR) program (https://itcr.cancer.gov/) was established by NCI to support development and Quantitative Imaging Informatics for Cancer Research
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