CTSC IGT, BWH

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Mission

Mark Anderson at Surgical Planning and Channing labs currently manages data for many investigators, pulling data from PACS into the research environment. There is interest in setting up a parallel channel by which the data are also enrolled into an XNAT database and accessed from client, and comparing its ease of use with the existing infrastucture. To explore XNAT as a possible long-term informatics solution for the NCIGT project, Mark will be uploading retrospective data for a number of NCIGT efforts (and PIs):

• NCIGT_Brain_Function (SS/AG)
  • Key Investigators:
  • Brief Description:
• NCIGT_Tumor_Resection (HK/AG)
  • Key Investigators:
  • Brief Description:
• NCIGT_Prostate (HE/CT)
  • Key Investigators:
  • Brief Description:
• NCIGT_Prostate_Fully_Segmented (HE/CT)
  • Key Investigators:
  • Brief Description:
• NCIGT_Brain_Biopsy (FT)
  • Key Investigators:
  • Brief Description:

Use-Case Goals

Step 1. Data Management

• Anonymize, apply DICOM metadata and upload retrospective datasets; confirm appropriate organization and naming scheme via web GUI.

Step 2. Query & Retrieval

• Make specific queries using XNAT web services,
• Download data conforming to specific naming convention and directory structure, using XNAT web services

Each effort listed above will have different requirements for being able to query, retrieve and use data collections. Brief description of how retrospective data will be used within the NCIGT is described below:

• NCIGT_Brain_Function:
• NCIGT_Tumor_Resection:
• NCIGT_Prostate:
• NCIGT_Prostate_Fully_Segmented:
• NCIGT_Brain_Biopsy:

Step 3. Disseminating & Sharing

• In addition to NCIGT mandate to share data, each effort listed above will have different requirements for being able to make data available to collaborating and other interested groups.

Outcome Metrics

Step 1. Data Management

Step 2. Query & Retrieval

Step 3. Dissemination & Sharing

Participants

• Mark Anderson
• Tina Kapur

Workflows

Target Data Management Process (Step 1.) Option A.

• Create new project using web GUI
• Manage project: Configure settings to automatically place data into the archive (no pre-archive)
• Create a subject template
• Create a spreadsheet conforming to subject template
• Upload spreadsheet to create subjects
• Run CLI Tool for batch anonymization (See here for HowTo: http://nrg.wustl.edu/projects/DICOM/DicomBrowser/batch-anon.html)
• Need pointer for script to do batch upload & apply DICOM metadata.
• Confirm data is uploaded & represented properly with web GUI

Target Data Management Process (Step 1.) Option B. (web services API) CURRENTLY BEING TESTED!

• Run CLI Tool for batch anonymization (See here for HowTo: http://nrg.wustl.edu/projects/DICOM/DicomBrowser/batch-anon.html)
• Create new project using web GUI
• Manage project: Configure settings to automatically place data into the archive (no pre-archive)
• Write script that uses curl or XNATRestClient (See here to download XNATRestClient in xnat_tools.zip from here: http://nrg.wikispaces.com/XNAT+REST+API+Usage)

1. Authenticate with server and create new session; use the response as a sessionID ($JSessionID) to use in subsequent queries

curl -d POST $XNE_Svr/REST/JSESSION -u $XNE_UserName:$XNE_Password 
or, use the XNATRestClient
XNATRestClient -host $XNE_Svr -u $XNE_UserName -p $XNE_Password -m P OST -remote /REST/JSESSION

2. Create subject

 XNATRestClient -host $XNE_Svr -user_session $JSessionID -m PUT /REST/projects/$ProjectID/subjects/s0001 (This would create a subject called 'S0001' within the project $ProjectID)

A script can be written to automatically create all subjects for the project. No demographics are applied to each subject by default. To apply demographics, either:

• xml can be generated an uploaded with the subject, or
• see the following shortcuts that can be crafted on commandline: http://nrg.wikispaces.com/XNAT+REST+XML+Path+Shortcuts

3. Anonymize & Upload scan data

See here for new (possibly buggy) command line options: http://nrg.wustl.edu/projects/DICOM/DicomBrowser-cli.html

4. Confirm data is uploaded & represented properly with web GUI