***Introduction***

Siemens Corporate Research (SCR) is participating in the caBIG-IW
community, and has a variety of technologies and expertise that could
benefit the community. In order to introduce these capabilities to
caBIG-IW, and to help define possible RSNA demonstrations, SCR has
prepared this document to describe our general capabilities in the form
of brief project descriptions. SCR is willing to lead such projects as
described, but is also willing to adapt/merge/morph these project ideas
as based on interactions with caBIG-IW colleagues. The point of contact
at SCR for caBIG-IW is John Pearson (pearson dot john at siemens dot
com).

***Background on SCR Relevant to caBIG-IW***

SCR has been in the forefront of developing technology platforms and
solutions that drive both innovation and interoperability for Siemens
Medical Solutions for over a decade, and has roughly 80 PhDs working
full time on medical imaging analysis and informatics technologies. SCR
is also now working with academic colleagues on a number of NIH grants
and cooperative groups, supplying key technology platforms to drive
clinical translation for a variety of applications, including digital
mammography (visual discrimination modeling), MR cardiology
(segmentation & analysis), to diffusive optical tommography (NTROI
multi-modal fusion & data management/collaboration). The NTROI (Network
for Translational Research: Optical Imaging) is a consortium of
approximately 20 universities and industrial partners funded by the NIH
(http://www.bli.uci.edu/ntroi/).

***Project Descriptions***

Descriptions of these project ideas were presented to the Planning
Committee at the Jan 12^th^ OSU meeting, and are posted in a separate
Powerpoint document.

***1. IDE for DICOM WG-23 Plug-ins & Imaging Apps\
***

[caBIG-IW Needs:]{.underline}

> a\. Software development methods that enable the research community to
> quickly prototype sophisticated imaging applications, and move them
> into clinical environments for clinical trials, IRB studies, etc....
>
> b\. Software development methods that enable re-use and sharing of
> proven modules, algorithms.
>
> c\. Software development methods that support the use of a variety of
> toolkits.
>
> d\. Software development methods that enable the research community to
> develop "plug-in" applications as envisaged by the emerging DICOM
> WG-23 Standard (instigated by SCR beginning in June 2003, based on
> ivRAD)

[SCR Background:]{.underline}

> SCR developed the core image analysis and visualization libraries used
> by Siemens Medical Solutions to create the Syngo platform as the
> standard for its line of medical imaging workstations. Internally, SCR
> created the ***ivRAD*** application development environment to
> facilitate its own application development through enabling re-use of
> components and rapid application development. ***ivRAD*** was also the
> inspiration for SCR's initiative to develop standards for PACS
> software interoperability, an effort now taken up by DICOM WG-23
> (Application Hosting, chaired by Lawrence Tarbox, now at WUSTL,
> formerly of SCR).

[SCR Long-term Approach:]{.underline}

> Provide & support ***ivRAD*** usage with caBIG-IW, making requested
> enhancements in keeping with the ***ivRAD*** vision.

[Long Term Deliverables]{.underline}:

> a\. ivRAD application programmers development environment

[RSNA-06 Deliverables]{.underline}:

> a\. [Core Item: 12 man-months SCR]{.underline}\
> Use ***ivRAD*** to show how existing stand-alone applications used by
> the research community can be re-engineered as an ivRAD plug-in,
> enabling the sharing of components, rapid development, and execution
> in either client/server, plug-in, or stand-alone modes. This will
> encourage other groups to dust off their code and put in a form that
> will better enable it to be shared with caBIG-IW members. A natural
> candidate here is ***OMIRAD*** (multi-modal registration, fusion,
> analysis), which SCR has developed under a current and ongoing NIH
> grant (NTROI cooperative group). The "RADicalized" OMIRAD will utilize
> modules from ITK and one or two other toolkits, showing how ivRAD
> enables drag-and-drop integration of components from multiple
> libraries, public domain and proprietary. The demo would show the
> application running as a Grid service in client/server mode, as a
> DICOM WG-23 plug-in in a Syngo workstation and a PC (perhaps the
> caBIG-IW Reference Workstation as envisioned by the Software SIG), and
> stand-alone. This shows how the research community can use a common
> development environment to rapidly develop software for clinical
> trials using a Grid infrastructure, and then transition the software
> into commercial imaging workstations that adopt the DICOM WG-23
> standard under development (chaired by Lawrence Tarbox, now of WUSTL,
> formerly of SCR).
>
> b\. [OPTION: 4 man-months SCR]{.underline}\
> Enable batch processing of OMIRAD on the Grid, and demonstrate it
> being used to register MR and DOT data sets from the NTROI.

***2. Connect NTROI SciPort (MIRC) to caGRID***

[caBIG-IW Needs:]{.underline}

> a\. Ability to interface with non-Grid distributed databases, such as
> MIRC and SciPort. These are increasingly popular "lightweight" methods
> used by individual investigators and radiology departments to organize
> and share their research data. Their "holdings" are impressive, and
> caBIG-IW needs a way to tap into it.
>
> b\. Ability to expand the caGRID to support Cooperative Groups such as
> the NTROI cooperative group with high-performance computing.

[SCR Background:]{.underline}

> SCR has developed SciPort to support the research of the NTROI funded
> by an ongoing NIH grant. SciPort shares some features with and is an
> offshoot of MIRC, currently a pure P2P distributed system developed by
> the RSNA to support sharing of teaching files, and also data
> collection for clinical trials. SciPort is structured to be the
> long-term, catch-all data organizer for a PI's lab, but also the
> vehicle for sharing and collaborating with other PI's in structured
> cooperative groups.

[SCR Long-term Approach:]{.underline}

> Build interface to enable a SciPort/MIRC network to appear as a data
> service within the Grid, and incorporate caBIG metadata ontologies
> within SciPort. Enable SciPort/MIRC users to access high-performance
> computing capabilities of caGRID.

[Long Term Deliverables]{.underline}:

> a\. Interfaces between caBIG Grid and SciPort/MIRC networks
>
> b\. Tools to enable SciPort/MIRC networks to be "caBIG compliant" in
> terms of data interoperability.

[RSNA-06 Deliverables]{.underline}:

> a\. Use a SciPort network for the demo because its use of a database
> (open source BerkelyDB) facilitates grid connectivity, and MIRC does
> not (yet) have a database. Use the NTROI's SciPort network as a source
> of data for the demo as it is loaded with multi-modality breast cancer
> data. In addition to a grid-connector for a SciPort central server, we
> would need to \"upgrade\" the SciPort metadata schemas to utilize the
> caBIG ontologies.
>
> [Tasks:]{.underline}
>
> OSU:
>
> Enable caBIG to support data sources from XML databases (BerkerleyDB
> XML) with complex XML data type mapping support in addition to
> existing RDBMS.

![](media/image1.jpeg){width="1.5868055555555556in"
height="1.8819444444444444in"}

(See Figure 5.18 on Page 48 in caCore Software Development Kit 1.0.3
Programmer's Guide.)

SCR: [7.5 man-months for essential integration, 3 man-months for
ontological integration]{.underline}

Grid Integration Architecture with MIRC/SciPort

a)  SciPort Metadata Model and Registration

> -Experiment metadata definition in CDE
>
> -Importing SciPort metadata in caDSR

b)  SciPort/MIRC Grid Services in caBIG

> -Query service for SciPort metadata
>
> -Navigation service to experiment data classification

c\) Develop ontology framework for experiment data in caBIG

\- Create controlled vocabularies and high-level concepts of experiment
data

\- Ontological queries/discovery of experiments and semantic integration
of experiment data

***3. Tool to Estimate Subjective Visual Quality & Equivalence***

[caBIG-IW Needs:]{.underline}

> Software tools that enable caBIG-IW participants to achieve
> consistently high levels of image quality during clinical trials with
> greater uniformity and harmonization across platforms, manufacturers,
> and clinical sites. Tools that reliably predict the visibility of
> differences in acquisition and reconstruction protocols, image
> processing, and display factors, enabling users to continually adjust
> their imaging procedures to maintain specified levels of image
> quality. Example applications include:
>
> a\. QA for visual equivalence of imaging protocols, especially during
> multi-vendor clinical trials;
>
> b\. QA involving visual assessment or scoring of phantom images;\
> c. Guidance for optimizing the visual quality of image processing and
> rendering/visualization methods.\
> d. Guidance for development of visually-lossless compression systems;\
> e. QA for lossy compression;

[SCR Background:]{.underline}

> SCR staff members have pioneered in the development of visual image
> quality metrics for the last decade in a variety of imaging domains,
> including a strong concentration in medical imaging for the last eight
> years, working with leading radiologists at several university medical
> centers. The refinement and validation of Visual Image Quality Metrics
> (VIQM) methods and software for medical imaging has been conducted in
> numerous government-funded projects, including three research grants
> from the NIH. Research areas have included softcopy displays and
> processing for digital mammography, lossy and visually lossless image
> compression, 3D JPEG2000 compression of multi-slice CT data, and the
> optimization of image acquisition and processing for MRI, x-ray
> fluoroscopy, and ultrasound. Results of these investigations have
> appeared in more than two dozen papers and conference presentations.

[SCR Long-term Approach:]{.underline}

> Provide, support, and enhance VIQM for use by caBIG-IW participants
> (for research purposes only).

[Long Term Deliverables]{.underline}:

> a\. VIQM executable, documentation, manuals, workshops at SCR, etc...

[RSNA-06 Deliverables]{.underline}:

> Workstation demonstrating the use of VIQM to evaluate dosage protocols
> for chest CT exams. Multiple sets of axial images with simulated
> variable dose (10 to 180 mAs) will be accessed on the caBIG Grid. The
> VIQM tool will generate and display two-dimensional, just-noticeable
> difference (JND) maps and composite metrics representing the predicted
> visibility of image noise and normal and abnormal features, enabling
> quantitative assessment of image quality and utility as a function of
> dose. Users may select images and ROIs in any image for closer
> examination.
>
> *Baseline demo*: VIQM tool with GUI operating on a workstation with CT
> images distributed on the caBIG Grid. \[16 staff-weeks\]
>
> *Option 1*: Extend the baseline demo to include interactive noise
> filtering for enhancing images to effectively higher doses. \[4
> staff-weeks\]
>
> *Option 2*: Scalable, client-server version of VIQM running on the
> caBIG Grid:
>
> \(a\) Full VIQM simulation distributed by image \[3 staff-weeks\];
>
> \(b\) Restructured VIQM algorithm for parallel computing \[6
> staff-weeks\].
>
> *Option 3*: Additional demo showing VIQM analysis for 3D JPEG2000
> compression of multi-slice CT datasets as a function of compression
> ratio and reconstruction (slice) parameters. \[16 staff-weeks\]

[caBIG-IW SIG Issues/Requests]{.underline}:

> **VCDE**: The terminology commonly used in the field of image quality
> models draws from psychophysics and the various engineering
> application domains to which the models have been applied. The VCDE
> will guide the refinement/specialization of this terminology to
> harmonize with medical imaging.
>
> **SIO**: SIO will advise on the protocols and methodologies for
> utilizing VIQM in medical imaging applications.
>
> **Software:** This SIG will advise on how to structure VIQM software
> development to maximize access by the community.
>
> **Testbed:** The methods for implementing the VIQM software within the
> caGRID are guided by this SIG. Of special concern are the methods for
> establishing VIQM as a web-service, and for performing data
> parallelization.

***4. Tools for Imaging/Bioinformatic Decision Support***

[caBIG-IW Needs:]{.underline}

> a\. A grid-based platform for integrating the data and tools of
> imaging and bioinformatics to enable new studies exploring how these
> disparate domains can provide complementary information. There are a
> large number of caBIG bioinformatics tools available from other
> workspaces.

[SCR Long-term Approach:]{.underline}

> We intend to help construct a software framework that allows the user
> to specify and integrate all forms of biomedical data and construct
> key applications on the data. In conjunction with other caBIG
> workspaces, tools must also be built to demonstrate utility of the
> combined data. All such tools must be caBIG-compliant..

[Long Term Deliverables]{.underline}:

-   caBIG-compliant software tools for navigation of integrated data
    sets and knowledge discovery on integrated biomedical data.

-   Documentation, training materials, and training workshops for these
    tools

-   Proof-of-concept studies showing utility of tools on real biomedical
    research problems

[RSNA-06 Deliverables]{.underline}: \~ 16 man-months

> The deliverable will be a caBIG-compliant tool which manages imaging
> and non-imaging data and allows the user to explore the data set. We
> believe that a useful demonstration must show tools in the context of
> a compelling study, and we propose to study data which is relevant to
> whether a colorectal tumor has become regionalized and requires
> surgical resection.
>
> The data for the demonstration would be taken from a study done in
> conjunction with the Cancer Institute of New Jersey (an NCI
> Comprehensive Cancer Center) collaboration with Dr. Notterman
> (Professor and Head, Core Microarray Facility), Dr. Foran (Pathology
> and Radiology), and Dr. August (Surgical Oncology). Approximately
> 25-50 patients with primary colorectal tumors who are undergoing
> surgical resection as part of their clinical care would be recruited.
> PET, CT, and possibly MR and ultrasound data will be available for
> these patients, as well as standard clinical data. The resected tissue
> will undergo analysis to determine if the cancer was regionalized, and
> the primary tumor will be sampled and analyzed at the molecular level.
> At a minimum, a histology report and microarray gene expression data
> will be gathered. We also propose to test for the hypermethylation
> (CIMP) and microsatellite instability (MSI) phenotypes, and for
> mutations in key oncogene regions such as p53, K-RAS, APC, etc.

An overview of the project plan would be as follows:

-   Develop a SciPort-compatible XML schema to represent the clinical
    data and metadata.

-   Assemble a set of tools for extracting information (metadata) from
    the relevant imaging and non-imaging data, utilizing existing
    caBIG-compliant tools where possible.

-   Develop an API which can be used to link the tools into workflows
    and populate the metadata portion of the database

-   Assemble a set of tools for constructing associations between
    independent and dependent variables

-   Construct a GUI which allows navigation and visualization of the
    combined patient data and metadata.

-   Construct a graphical tool which allows the user to explore the
    correlations between different variables, to find related subsets
    (clustering / unsupervised learning) and to learn the relationships
    between sets of independent variables and a dependent variable of
    interest (supervised learning). This task will also likely rely on
    interfacing to external tools.

***caBIG-IW Project Dashboard***

> The figure below highlights some of the salient features of these
> projects. It is suggested that this kind of "dashboard" would be
> generally useful to the caBIG-IW leadership and planners as they
> develop the caBIG-IW project portfolio. The break-out of project
> level-of-effort (below in purple) by SIG reflects our qualitative
> understanding of how these projects relate to the aims of the SIGs. We
> take as the SIG definitions information distributed via the Listserver
> in January (copied below). The numbers represent the minimal level of
> effort from SCR (in units of full-time equivalent staff, fte), needed
> to produce a minimal RSNA demo from the project.
>
> ![](media/image2.wmf){width="6.36875in" height="2.06875in"}
>
> **VCDE, Vocabularies and Common Data Elements**
>
> The scope of the VCDE SIG of the caBIG In Vivo Imaging (IVI) Workspace
> encompasses the creation, adoption, and use of terminologies,
> ontologies, and common data elements (CDEs) for medical imaging. The
> mission of the VCDE SIG is (1) to promote, support, develop, and
> evaluate standards-based vocabularies, ontologies, and CDEs for
> radiology and allied imaging fields, and (2) to complement and augment
> the activities that are underway in other SIGs within the IVI
> Workspace, in the VCDE Workspace, as well as throughout the entire
> caBIG effort. This mission includes participating in the design of the
> testbed and providing the VCDE- and ontology-related elements required
> by the testbed. In particular, the VCDI SIG, in collaboration with
> other SIGS, will help develop the standards for creating, storing, and
> retrieving image metadata and image annotations, will harmonize VCDEs
> developed in the VCDE SIG with those being created by the VCDE
> workspace, and will develop VCDE-specific tools and resources that can
> be deployed on the grid to help realize the strategic vision of the
> caBIG effort.
>
> Specific goals of the VCDE SIG encompass the following major areas of
> work: (1) to develop vocabularies, ontologies, and CDEs for medical
> imaging to meet the needs of the IVIWS; (2) to harmonize these VCDEs
> across the caBIG workspaces as well as to augment existing VCDE
> resources; (3) to create tools and schemas to make radiological
> information explicit and computable, collected either directly from
> practitioners in structured form or extracted from unstructured free
> text; and (4) to associate the structured information with
> radiological images through standards and tools to enable intelligent
> image retrieval and analysis.
>
> **SIO, Standards and Interoperability**
>
> The Standards and Interoperability Special Interest Group (SIOSIG) is
> focused on the promotion and use of appropriate technical standards
> and frameworks to insure the compatibility of caBIG Imaging activities
> within caBIG and with clinical imaging and information systems that
> are often the source of image and non-image data vital to cancer
> research. To achieve this goal, the SIOSIG has identified a number of
> priorities. The SIOSIG would like to sponsor a delegation from the
> Imaging Workspace to the DICOM and HL7 (and possibly other) standards
> development organizations so as to proactively represent the interests
> of the research imaging community. The SIOSIG is preparing a white
> paper comparing the clinical and clinical trial imaging workflows as
> one step in identifying gaps in standards with respect to clinical
> trial imaging. With respect to standardizing clinical trial imaging
> acquisition, the SIOSIG is going to convoke a group to work with
> existing entities such as UPICT in specifying protocols. SIOSIG will
> work to then promulgate these standard mechanisms. Similar use of
> standards will need to be developed for annotation and markup of
> images for both clinical and clinical trial purposes. SIOSIG will
> assist other SIGs in identifying standard reference data sets. Lastly,
> SIOSIG will work closely with the Software and Architecture SIGs to
> develop open source standards based tools and facilitate their
> demonstration in public venues.
>
> **Software**
>
> The goal of the Software SIG is to create and adapt open source
> software tools to promote and enhance the use of imaging in cancer
> research. The primary foci of the SIG are tools for image acquisition,
> management and analysis for use in clinical trials. The SIG will
> identify existing tools, and define requirements for new, open source
> tools that need to be developed. Based on the results of an initial
> workshop at the Imaging Workspace face-to-face meeting in December,
> 2005, the Software SIG will begin work on the following items: (1)
> viewing and annotation software that can make use of the caBIG grid
> infrastructure to retrieve images and information from a distributed
> database; (2) image acquisition and redistribution software to acquire
> de-identified data from multiple sites and redistribute this data to
> multiple reader/analysis sites using the caBIG grid infrastructure;
> and (3) database resources and software for change analysis including
> methodologies for software and algorithm validation.
>
> **Testbed**
>
> The testbed SIG is responsible for design, development and
> implementation of an in-vivo imaging testbed along with key
> architectural components needed to enable the testbed effort. The
> testbed will span multiple Cancer Centers and will be a grid based
> platform that will support storage, access, processing and
> visualization of images and correlative clinical and molecular data.
> The testbed will be used to carry out: 1) translational research
> directed by Cancer Center and Cooperative Group principle
> investigators and 2) systematic evaluation of computer aided diagnosis
> (CAD) and other image quantification algorithms. In addition,
> investigators will be able to use the testbed to carry out exploratory
> studies involving substantial collections of deidentified image and
> correlative data. The testbed working group will also collaborate with
> other SIGs to develop key testbed architectural components such as
> DICOM and IHE compliant grid services and workflow components able to
> execute in environments provided by proprietary imaging workstations.
>
> The initial products of the testbed group will be to develop: 1)
> demonstration projects at the caBIG 2006 Annual meeting, RSNA 2006 and
> Supercomputing 2006, 2) working persistent testbed (in effect a type
> of image research RHIO) by RSNA 2006 and 3) development of key
> architectural components.