2012 Summer Project Week:AIM for QIN

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  • Diagram of various data types and connections that need to be organized

  • Diagram from Daniel Rubin

Key Investigators

  • BWH: Andrey Fedorov, Nicole Aucoin, Paul Mercea, Fiona Fennessy
  • Northwestern U.: Pat Mongkolwat
  • Stanford: Daniel Rubin
  • U. Iowa: Reinhard Beichel, Markus Van Tol
  • MGH: Jayashree Kalpathy-Cramer

Objective

Participants of the Quantitative Imaging Network (QIN) are in need of a standard-based or consensus-based format for consistent storage and organization of various types of data related to quantitative imaging of clinical patients undergoing cancer treatment. Typical dataset includes a subset of the following:

  • several time-points with the multi-modal imaging data at each time-point
  • segmentations of the lesions and/or reference and/or relevant anatomical structures
  • measurements/calculations derived from the images and segmentations
  • clinical and demographical information about the patient
  • information related to treatment
  • pathology correlation data

Ideally, we would like to be able to consistently organize these various types of information into a self-sufficient document/data structure to facilitate exchange of the information for subsequent analysis, presentation and archival. The possibilities currently considered include DICOM-based formats (DICOM Structured Reports), Annotation Image Markup (AIM) format, and Slicer MRML scene.

The goal of this project is to focus on the specific project of U. Iowa in longitudinal PET/CT imaging, and attempt to utilize the capabilities of AIM to organize the data provided by U. of Iowa collaborators. Specifically, the dataset we will use for experimentation includes:

  • n PET/CT datasets acquired over the course of treatment
  • binary segmentations of lesions, represented as 3d segmentations (lesions may disappear over the course of treatment)
  • binary segmentations of the reference structures

BWH and MGH teams are also participants of the QIN, and will provide input related to how the use-cases at their sites are different from U. Iowa use case. BWH will also provide expertise in 3D Slicer in discussing its capabilities in visualizing and organizing the data for the Iowa QIN use case.

Big questions we would like to answer in the end:

  • what are the capabilities of AIM with respect to addressing the needs of specific QIN use cases?
  • how these capabilities are supported by the tools from the user perspective?


Approach, Plan

  • We will have discussions and hands-on demonstrations of AIM capabilities to understand its applicability to QIN use cases.
  • Tuesday 6/19 11am to 1pm Eastern time we will have a conference call that will include Daniel Rubin and Reinhard Beichel (joining remotely); project week participants interested to join will meet at room 32-262 at MIT (on the 2nd floor of the Stata Center)
  • We will summarize our findings at the end of the project week

Progress

Delivery Mechanism

The summary of our findings will be available to the NA-MIC and QIN community on this wiki page.

References

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