Quantitative Imaging Informatics for Cancer Research

PURPOSE

We 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.

METHODS

QIICR 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.

RESULTS

Fourteen 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.

CONCLUSION

Tools, 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.

Abstract 1890: Chloroquine synergizes with MEK1/2 targeted therapy through dual YAP and lysosomal inhibition in GNAQ/11 mutant uveal melanoma

GNAQ and GNA11 (GNAQ/11) mutations are found in less than 2% of all melanoma, but more than 80% of uveal melanoma. Mutations in these Gα proteins lead to constitutive activation of multiple oncogenic pathways, including MAPK (RAF->MEK1/2->ERK1/2) and YAP signaling. Metastatic uveal melanoma is refractory to all forms of pharmacologic treatment, such as FDA-approved targeted therapies inhibiting MEK1/2 (i.e. trametinib and binimetinib). We show that combining MEK1/2 inhibitors with 4-aminoquinoline antimalarials, chloroquine or hydroxychloroquine, resulted in synergistic and apoptosis-mediated cytotoxicity in GNAQ/11 mutant uveal melanoma cell lines. Interestingly, in contrast to our previous work in pancreatic and other RAS-driven cancers, the lysosomotropic role of chloroquine was not sufficient to promote cytotoxicity with MEK1/2 inhibitors, as neither lysosome inhibition with Bafilomycin A1 nor autophagy-specific and macropinocytosis-specific inhibition yielded enhanced cell death in combination with MEK1/2 inhibition. We then found that chloroquine prevented nuclear localization of the transcriptional coactivator, YAP, suggesting a novel mechanism of chloroquine. YAP inhibition combined with MEK1/2 inhibition enhanced cell death only in the presence of Bafilomycin A1. Gα-specific inhibition (inhibiting YAP and MAPK) combined with Bafilomycin A1 yielded similar results. This implies that the ability of chloroquine to inhibit both YAP signaling and lysosome function is required for promoting cell death in the presence of MEK1/2 inhibition. For in vivostudies, we utilized a hepatic colonization model using luciferized human metastatic uveal melanoma cell lines, OMM2.5 and OMM1. Daily treatment of trametinib with hydroxychloroquine in combination resulted in delayed tumor growth and increased overall survival compared to either treatment as monotherapy or chemotherapy. These findings were also recapitulated in an immunocompetent mouse model in which immortalized mouse melanocytes (Melan-A) with either a GNAQ or GNA11 activating mutation were implanted into syngeneic C57BL/6 mice. Our findings identify a novel mechanism of chloroquine and suggest a potentially effective strategy combining two FDA-approved drugs for the treatment of metastatic uveal melanoma.

Citation Format: Amanda Truong, Michael Scherzer, Conan Kinsey, John Michael Sanchez, Jae Hyuk Yoo, Jackson Richards, Donghan Shin, Phaedra Ghazi, Michael Onken, Kendall Blumer, Shannon Odelberg, Martin McMahon. Chloroquine synergizes with MEK1/2 targeted therapy through dual YAP and lysosomal inhibition in GNAQ/11 mutant uveal melanoma [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1890.

dcmqi: An Open Source Library for Standardized Communication of Quantitative Image Analysis Results Using DICOM

Quantitative analysis of clinical image data is an active area of research that holds promise for precision medicine, early assessment of treatment response, and objective characterization of the disease. Interoperability, data sharing, and the ability to mine the resulting data are of increasing importance, given the explosive growth in the number of quantitative analysis methods being proposed. The Digital Imaging and Communications in Medicine (DICOM) standard is widely adopted for image and metadata in radiology. dcmqi (DICOM for Quantitative Imaging) is a free, open source library that implements conversion of the data stored in commonly used research formats into the standard DICOM representation. dcmqi source code is distributed under BSD-style license. It is freely available as a precompiled binary package for every major operating system, as a Docker image, and as an extension to 3D Slicer. Installation and usage instructions are provided in the GitHub repository at https://github.com/qiicr/dcmqi Cancer Res; 77(21); e87-90. ©2017 AACR.

DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research

Background. Imaging biomarkers hold tremendous promise for precision medicine clinical applications. Development of such biomarkers relies heavily on image post-processing tools for automated image quantitation. Their deployment in the context of clinical research necessitates interoperability with the clinical systems. Comparison with the established outcomes and evaluation tasks motivate integration of the clinical and imaging data, and the use of standardized approaches to support annotation and sharing of the analysis results and semantics. We developed the methodology and tools to support these tasks in Positron Emission Tomography and Computed Tomography (PET/CT) quantitative imaging (QI) biomarker development applied to head and neck cancer (HNC) treatment response assessment, using the Digital Imaging and Communications in Medicine (DICOM(®)) international standard and free open-source software. Methods. Quantitative analysis of PET/CT imaging data collected on patients undergoing treatment for HNC was conducted. Processing steps included Standardized Uptake Value (SUV) normalization of the images, segmentation of the tumor using manual and semi-automatic approaches, automatic segmentation of the reference regions, and extraction of the volumetric segmentation-based measurements. Suitable components of the DICOM standard were identified to model the various types of data produced by the analysis. A developer toolkit of conversion routines and an Application Programming Interface (API) were contributed and applied to create a standards-based representation of the data. Results. DICOM Real World Value Mapping, Segmentation and Structured Reporting objects were utilized for standards-compliant representation of the PET/CT QI analysis results and relevant clinical data. A number of correction proposals to the standard were developed. The open-source DICOM toolkit (DCMTK) was improved to simplify the task of DICOM encoding by introducing new API abstractions. Conversion and visualization tools utilizing this toolkit were developed. The encoded objects were validated for consistency and interoperability. The resulting dataset was deposited in the QIN-HEADNECK collection of The Cancer Imaging Archive (TCIA). Supporting tools for data analysis and DICOM conversion were made available as free open-source software. Discussion. We presented a detailed investigation of the development and application of the DICOM model, as well as the supporting open-source tools and toolkits, to accommodate representation of the research data in QI biomarker development. We demonstrated that the DICOM standard can be used to represent the types of data relevant in HNC QI biomarker development, and encode their complex relationships. The resulting annotated objects are amenable to data mining applications, and are interoperable with a variety of systems that support the DICOM standard.

Dynamic DICOM configuration in a service-oriented medical device architecture

A surgical intervention raises additional requirements to a medical device network, be it security concerns or the demand for just-in-time integration of an additional devices. The German national flagship project OR.NET aims to satisfy these requirements by defining, implementing and validating an integration solution for safe and dynamic networking. This work presents an approach to incorporate imaging related medical devices into a dynamic plug and play operating room (OR) network utilizing the existing Digital Imaging and Communications in Medicine (DICOM) protocol. The presented approach was created as part of the OR.NET project to realize the integration of DICOM devices into the developed infrastructure, both in regard to newly created DICOM devices with direct support of the OR.NET protocol and the integration of existing DICOM devices (e.g. image archives) employing a gateway. Preliminary evaluation results indicate that the approach is viable and that no critical transmission delays are introduced by the prototypical gateway implementation.

A DICOM architecture for clinicians and researchers

Over the last years there has been a strong trend of publishing health data in anonymized format in order to make it available for research. This is also true for medical imaging where the DICOM standard is the predominant data format and network protocol. This paper proposes an extension to any DICOM networking infrastructure that permits sharing of medical images in an anonymized way. Standard DICOM software is utilized on client and server side. While offering researchers access to all images in anonymous format, the architecture enables authorized clinicians to access the same images including their original patient information (name, institution, etc.). Identifying parts and anonymous parts of the image data are stored to geologically different databases. Together with sophisticated network protocols, patient privacy is fully preserved.

Reversible anonymization of DICOM images using automatically generated policies

Many real-world applications in the area of medical imaging like case study databases require separation of identifying (IDATA) and non-identifying (MDATA) data, specifically those offering Internet-based data access. These kinds of projects also must provide a role-based access system, controlling, how patient data must be organized and how it can be accessed. On DICOM image level, different image types support different kind of information, intermixing IDATA and MDATA in a single object. To separate them, it is possible to reversibly anonymize DICOM objects by substituting IDATA by a unique anonymous token. In case that later an authenticated user needs full access to an image, this token can be used for re-linking formerly separated IDATA and MDATA, thus resulting in a dynamically generated, exact copy of the original image. The approach described in this paper is based on the automatic generation of anonymization policies from the DICOM standard text, providing specific support for all kinds of DICOM images. The policies are executed by a newly developed framework based on the DICOM toolkit DCMTK and offer a reliable approach to reversible anonymization. The implementation is evaluated in a German BMBF-supported expert network in the area of skeletal dysplasias, SKELNET, but may generally be applicable to related projects, enormously improving quality and integrity of diagnostics in a field focused on images. It performs effectively and efficiently on real-world test images from the project and other kind of DICOM images.

[The DICOM-CD-Project of the German Radiology Association--an overview of the content and results of a pilot study in 2006]

DICOM-CDs are frequently used for medical image data transfer. Many different potential advantages are known, such as improved image quality, handling simplification, and cost optimization. However, there are numerous restrictions in the daily routine. While testing DICOM-CDs at the 2006 German Radiology Congress, we found that more than 70 % of CDs have discrepancies with respect to data structure or content. The German Radiological Association and OFFIS started an initiative to improve the quality of DICOM-CDs. There are three main objectives: To provide requirements for vendors of CD-writing systems, to establish user guidelines for the handling of DICOM-CDs, and to develop a test procedure for DICOM-CDs. Radiologists using such systems should be aware of these developments and use them for RFP's.