# Presentation: 877368

## Applications of caBIG

**Joel Saltz, MD, PhD**
**Chair Biomedical Informatics**
**Ohio State Comprehensive Cancer Center**
**College of Medcine**
**The Ohio State University**
**saltz@bmi.osu.edu****NIH Natcher Center October 18, 2007**

## Roadmap

**Images, Cooperative Research Groups and the Grid**
**Grid Based Discovery and Analysis Platforms**
**Integrative Biomedicine**
**Analytic Tools**

## caBIGTM In Vivo Imaging Workspace

- Project 1: Middleware
- Project 2: XIP: Extensible Imaging Platform
- Project 3: AIM: Annotation and Image Markup
- Project 4: Vocabulary

**Notes:**
Here you give an overview of the system and then describe things in detail in the following slides.

## Goals of Imaging Related Cooperative Group Efforts

- ATC, QARC, ITC, CALGB, ACRIN, RTOG,  NTROI, Children’s Oncology Group
- Maximize reproducibility in staging, grading of cancer
- Maximize reproducibility in radiation treatment planning and delivery
- Accurate characterization of  disease to target treatment
- Maximize anatomic and functional precision in targeting tumors
- Imaging as a biomarker

**Notes:**
Here you give an overview of the system and then describe things in detail in the following slides.

- Slide from Walter Bosch

## Typical Cooperative Group Review Process

## caGrid Enabled CERR

**Access images, store review results at ATC, QARC, ACRIN, CALGB image archives**
**Matlab code can run locally or on remote clusters**
**Markup annotation of images via caBIG AIM standard**

## Central Review/CAD Demonstration Project (joint with U Maryland)

**Expose data in PACS servers as caGrid Data Service**
**Open source DICOM server — PixelMed, GridFTP based date transfer**
**Participating sites include: Columbus, Chicago, LA, NCIA-Washington DC, QARC Providence, Brazil and Turkey**
**Set stage for workspace effort to support ACRIN/QARC/CALGB/ATC (View) central review**

**NCIA**

**Columbus**

**7 Participating Data Services**

**Los Angeles**

**Argonne**

**OSC**

**QARC**

**Turkey**

**Brazil**

**Notes:**
Here you give an overview of the system and then describe things in detail in the following slides.
NEED to modify slide to show participating sites

## GridIMAGE Support for CALGB Imaging Core (Michael Knopp MD): Central Review; IDL CT/PET Analysis 

## Pathology Coordinated Review

**caMicroscope**

**Multiheaded Microscope**

- Portal

**Track specimens using caTissue**
**Support coordinated review of digitized slides using NCIA, caMicroscope**

## caMicroscope Architecture

- Image Data Services that store images in Aperio SVS format
- Analytical service that pulls images from the image server and executes MATLAB programs on a cluster
- All services are caGrid 1.0, use gridFTP for high performance bulk data transfer
- The Client allows multi-resolution browsing of the images, invoke MATLAB programs and examine the MATLAB output images

## caMicroscope parallel processingChildren’s Oncology Group - Neuroblastoma

- `

**Whole-slide image**

**Image tiles (40X magnification)**

- Hiro Shimada CHLA, Metin Gurcan OSU

## Roadmap

**Images, Cooperative Research Groups and the Grid**
**Grid Based Discovery and Analysis Platforms**
**Integrative Biomedicine**
**Analytic Tools**

## National Cancer Imaging Archive

**Searchable repository of *****in vivo***** cancer images in DICOM format**
**Archive currently contains over 2 million DICOM images plus annotation files and curation data**
**Data Access**
- Web portal available for accessing repository
- caGrid access
- caCORE generated toolkit API
- Cedara visualization and markup
- Node-to-Node communication
**Online searching for cases/images based on criteria such as Image Modality, Slice Thickness, Collection, curation data, etc.**
**Users can download DICOM data bundled with annotation files and curation data.  **
- Web portal system operates based on “shopping cart” feature
**Federated searches and image downloads enabled via the implementation of the NCIA data service**

## Image Submission and Federated Search (3.0)

**MIRC Storage Service**

**MIRC DICOM Service**

**MIRC Database Service (Adapter)**

**Firewall**

**MIRC  *****(Tomcat) ***

**Image Submission**

**Hibernate**

**NCIA caCORE API**

**Data Manager**

**Data Manager**

**CSM API**
** **

**Processors**
**Query, Result set, User Registration, Lookup Manager, CSM, Export**

**Hibernate**

**Hibernate**

**MDB**
**(Image zipping,**
**Curation Data Upload)**

**Retrieval**

**(Researchers)**

***DICOMHTTP***
***HTTPS***

***Cancer Centers / ***
***Academia /***
***Industry***

***Data***
***Access***
***Layer***

***HTTPS, FTP***

**BDT**

***caGrid  Clients***

**Java Server Faces (JSF) **

***Cedara ***
***I-Response client***

**Verify Submission Tool**

**QC Tool**

**** ... 1***

**Cedara ISG Server**

**Grid Security**

**Grid Client**

**Query Portal**

**Online Search **

***Generic Grid ***
***Services***

***NCIA Grid***
***Services***

***NCIA Nodes***

**NCIA Grid Broker**

**Notes:**
-Field Centers at Remote Clinical Sites
-BEFORE AFTER SLIDES SHOWING WHAT HAS BEEN ADDED WITH BLANKS

- David J. Foran, Ph.D.

**Multi-institutional, Grid-enabled Digital Pathology Testbed**
**Lead Investigators: Foran and Saltz**

## Image Mining for Performing Comparative Analysis of Expression Patterns in Tissue Microarray(1RO1LM009239-01A1) 

- David J. Foran, Ph.D.

**Much of the difficulty in rendering consistent evaluation of **
**expression patterns in cancer tissue microarrays arises from **
**subjective impressions of observers. The central **
**objective of this project is to design, develop, deploy and evaluate  a grid-enabled system for performing quick, reliable comparative  analysis of expression patterns for research and discovery.  Supports IBM sponsored Help Defeat Cancer project which 100, 000 imaged histology specimens originating from breast,  head & neck, colorectal cancers. **

## Color-Decomposition and High-Throughput Analysis of Tissue Microarrays

- David J. Foran, Ph.D.

## Roadmap

- Images, Cooperative Research Groups and the Grid
- Grid Based Discovery and Analysis Platforms
- Integrative Biomedicine
- Analytic Tools

## Data IntegrationDifferent parts of the same story

**Multi-Modal**
**Imaging**

**Data Analysis**
**And Modeling**

- The Cardiovascular Research Grid (PI Rai Winslow  -- JHU, OSU, UCSD)
- The D. W. Reynolds Cardiovascular Clinical Research Center

- Slide from Rai Winslow

## The CVRG Project

- R24 NHLBI Resource, start date 3/1/07
- 3 development teams:
- Winslow, Geman, Miller, Naiman, Ratnanather, Younes (JHU)
- Saltz, Kurc (OSU)
- Ellisman, Grethe (UCSD)
- Organization
**Project 1**: The CVRG Core Infrastructure (JHU, OSU, UCSD)
**Project 2**: Electrophysiological Data Management and Dissemination (JHU)
**Project 3**: Mathematical Characterization of Cardiac Ventricular Anatomic Shape and Motion (JHU)
**Project 4**: Grid Tools for Cardiac Computational Anatomy (JHU)
**Project 5**: Statistical Learning with Multi-Scale Cardiovascular Data (JHU)
**Project 6**: Resource Management (JHU)

- Slide from Rai Winslow

## caGrid Infrastructure used to Support Data Integration

- Data collected by the Reynolds project investigators
- Integration of SNP, Image, and ECG data
- Datasets coming from a common group of patients
- Ability to execute integrative analysis and investigate phenotype-genotype correlations
- CGEMS SNP caGrid service; HL7aECG caGrid service

- ECG data in caGrid HL7aECG
- Data service

- Raw data,
- SNP calls,
- Analysis results

- MRI/CT data
- Image analysis

- CVRG

- caGrid
- Services

## Roadmap

- Images, Cooperative Research Groups and the Grid
- Grid Based Discovery and Analysis Platforms
- Integrative Biomedicine
- Analytic Tools

## Grid-enabling Analytical Servicesand geWorkbench

**geWorkbench - Java based integrative genomics platform**
- Component based architecture allows for complex applications to be added as individual plug-in.
**caGrid as a geWorkbench Plug-in**
- Discover grid services, invoke grid services, retrieve the results, and use other components of the framework for tasks such as visualization.
**caGrid Exposed Analytical Services**
- Hierarchical Clustering
- Som Clustering
- Aracne

## geWorkbench

**Discover geWorkbench service**

- Invoke geWorkbench
- Service

## GeneConnect: Identifier Mapping Problem

- Several bioinformatics databases have different  identifiers
- More than 80 identifier types in UniProt Knowledgebase
- Individual databases may not provide mappings of their own identifiers to others
- Researchers want to collect all the available information , which requires :
- Knowing all the possible identifiers for a given biological entity or system – Quite unrealistic
- Knowing partial set of identifiers – Missing information
- Knowing “key set” of identifiers – _Mapping between “key set” of identifiers for full information accessibility_

## Identifier Mapping in caBIGTM

- _Second Step:_ A mapping service to facilitate interoperability by interlinking genomic identifiers

## Protein Information Resource (PIR)

- Integrated protein informatics resource for genomic and proteomic research

- UniProt Universal Protein Resource: Central Resource of Protein Sequence and Function
- PIRSF Family Classification System: Protein Classification and Functional Annotation
- iProClass Integrated Protein Knowledgebase: Data Integration and Functional Analysis
- iProLINK: Source for Protein Literature Mining and Ontology Development

**http://pir.georgetown.edu**

- Slide from Baris E. Suzek

## Conclusion

**Have presented small subset of caBIG****TM**** applications and tools as examples**
**Many other applications – Peter Covitz listed a number of these **
**To reiterate – Resources include:**
- caBIG Web site http://cabig.nci.nih.gov
- Electronic Newsletters
- What’s BIG this Week (weekly)
- caBIGTM Links (monthly)

## Thank you

## Acknowledgments

- The caGrid team:caGrid 1.0: Scott Oster, Stephen Langella, Shannon Hastings, David Ervin, Ravi Madduri, Tahsin Kurc, Frank Siebenlist, Ian Foster, Krishnakant Shanbhag, Peter Covitz
- OSU Imaging Informatics/HPC team: Berkant Barla Cambazoglu Ph.D., Umit V. Catalyurek Ph.D., Metin N. Gurcan Ph. D. ,Kun Huang Ph.D.,Tony C. Pan M.S., Ashish Sharma Ph.D., Manuel Ujaldon Ph.D. Olcay Sertel Antonio Ruiz, Vijay Kumar
- Jim Purdy, Walter Bosch from Advanced Technology Consortium
- Eliot Siegel, Paul Mulhorn, Michael McNitt-Gray, all SMEs and participants in the caBIG in-vivo imaging workspace
- Baris Suzek (Georgetown), Kiran Keshav (Columbia), Rakesh Nagarajan (Wash U), Carl Blake, Anand Basu, John Freymann (NCIA project)