AI Results

AI Results specifies how medical imaging analysis results are reliably stored, retrieved, and displayed. The central use case involves results generated by artificial intelligence (AI Model) algorithms.

Summary

This profile standardizes storage & display of AI Results for image interpretation. It establishes baseline data handling and presentation capabilities for an image display product to be “AI-Ready”. Result generation products can leverage these data formats to be compatible with a variety of displays and site workflows.

AIR defines:

a set of result “primitives”
Encoding requirements for each primitive (DICOM-based storage)
transactions for moving that content around
Baseline display requirements for each primitive

Benefits

Interoperable Results:

Results need to be presented to radiologists in their reading environment. This profile provides interoperability between result generation products and radiology reading workstation systems/software.

Study Integrated Results:

Radiologists expect AI-generated results to be presented in the context of the study to which they apply and expect them to supplement (rather than replace) traditional image analysis results and thus a given study will be composed of acquired images, AI results, and traditional clinical data. The result objects defined in this profile are defined for the existing imaging data storage infrastructure.

Effective Presentation:

Effective use of results hinges on presenting them in conjunction with the associated images during the busy process of reading the study.

Convergence of Result Encoding:

Many AI results are results that a human could otherwise have produced, and those human results may be used as training data for the AI. Analysis results might also be used by other AIs, e.g., in a GAN (generative adversarial network). AI and non-AI results need to be handled together. Convergent encoding of results facilitates this, as well as data pooling and sharing between sites.

Display Primitives:

It is unrealistic to expect radiology displays to implement specific display capabilities for each of the myriad of algorithms being developed. To minimize implementation complexity for displays, and avoid needing different software for each new analysis result, compose analysis results from a reasonable set of primitives.

Details

<A few paragraphs, if appropriate, providing more details (mostly in user-speak, not tech-speak) on what the profile does and how it works.>

AI Result Primitives:

Qualitative Findings: E.g. Breast composition is Extremely Dense, Pneumothorax is Present
Measurements: E.g. Adrenal Gland Nodule Length = 52mm
Locations: E.g. Blood clot at (123.9, 57.2, 752.3)
Segmentations: E.g. Lung Nodule surface
Parametric Maps: E.g. Saliency Map for pneumonia
Tracking IDs: E.g. Primary tumor for patient 32457 (longitudinal)
Image References: E.g. Best view of brain hemorrhage

Systems Affected

AI Analysis Software - encodes results as specified
Image Manager (PACS) - stores and manages AI result objects as part of study
Image Display - retrieves results and displays as specified

Actors & Transactions:

<Insert an actor-transaction diagram, and or list of Content Definitions>

Specification

Profile Status: Trial Implementation

Documents: AI Results Profile - TI

For an overview of the scope and goals, see "Introduction to this Supplement", and Volume 3 Section 6.5.1.
For an overview of the participating actors and the transactions between them, see Volume 1 Section 49.1 and Section 49.4.2.
For key concepts that affect implementation and deployment and may be helpful in understanding the rest of the profile, see Volume 1 Section 49.4.1.
For the key technical requirements on encoding and displaying analysis results, see Volume 3 Section 6.5.3 and Volume 2 Section 4.136.4.1.3 respectively.

Underlying Standards:

DICOM

AI Results

Contents

Summary

Benefits

Details

Systems Affected

Specification

See Also

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