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Currently being developed but will be in the microAIM data service.

DICOM Working Group 30

While the challenges of integrating small animal/co-clinical data with data on humans are steep, given the lack of common data standards, the potential rewards are great. These rewards depend on a common data standard for human and small animal data and support by equipment manufacturers for the standard.

The goal of the Small Animal/Co-clinical Improved DICOM Compliance and Data Integration sub-project is to directly compare data from co-clinical animal models to real-time clinical data from TCGA. The team will accomplish this by applying common data elements used in TCGA with animal applicability, such as estrogen-receptor (ER) negative and positive, to a co-clinical data set. Specifically, this sub-project will:

• Develop a supplement to the DICOM standard to accommodate small animal imaging.
• Identify a pilot co-clinical data set to integrate with TCIA and TCGA.

For example, consider the following research question, made possible through increased DICOM compliance by small animal/co-clinical data.

• If you treat a mouse with an estrogen-receptor (ER) negative tumor with a certain drug, how does the outcome compare to that of a human with the same tumor and ER status?

With small animal/co-clinical data meeting the DICOM standard, researchers could find a mouse with the same kind of tumor and compare its response to various therapies that could help generate sophisticated diagnoses and treatment plans.

Factors that may influence an image

If we want to collect data that describes how the data about the animal was captured, we needed standard how an animal image was acquired and which factors could influence the image–was the housing clean or dirty, housing manufacturer

This project generated Supplement 187 to the DICOM standard. The working group that worked on this was DICOM working group 30.

Pull out factors from TOC

Google Genomics

-        https://cloud.google.com/genomics/

Radiology Image Annotation and Markup

-        AIM Data Service (AIME)

Pathology Image Annotation and Markup

-        uAIM Data Service (uAIME)

Preclinical data

-        customized database at Emory

Clinical Data

-        TCGA

-        Customized database at Emory

Radiology Image (human and animal)

-        TCIA

Pathology Images (human and animal)

-        caMicroscope

DICOM Working Group 30

While the challenges of integrating small animal/co-clinical data with data on humans are steep, given the lack of common data standards, the potential rewards are great. These rewards depend on a common data standard for human and small animal data and support by equipment manufacturers for the standard.

The goal of the Small Animal/Co-clinical Improved DICOM Compliance and Data Integration sub-project is to directly compare data from co-clinical animal models to real-time clinical data from TCGA. The team will accomplish this by applying common data elements used in TCGA with animal applicability, such as estrogen-receptor (ER) negative and positive, to a co-clinical data set. Specifically, this sub-project will:

• Develop a supplement to the DICOM standard to accommodate small animal imaging.
• Identify a pilot co-clinical data set to integrate with TCIA and TCGA.

For example, consider the following research question, made possible through increased DICOM compliance by small animal/co-clinical data.

• If you treat a mouse with an estrogen-receptor (ER) negative tumor with a certain drug, how does the outcome compare to that of a human with the same tumor and ER status?

With small animal/co-clinical data meeting the DICOM standard, researchers could find a mouse with the same kind of tumor and compare its response to various therapies that could help generate sophisticated diagnoses and treatment plans.

Factors that may influence an image

If we want to collect data that describes how the data about the animal was captured, we needed standard how an animal image was acquired and which factors could influence the image–was the housing clean or dirty, housing manufacturer

This project generated Supplement 187 to the DICOM standard. The working group that worked on this was DICOM working group 30.

Pull out factors from TOC

correction proposals

DICOM WG 6 has processed all of the ballot comments and produced the final text for Sup 187, and CPs 1457, 1470, 1471, 1472, 1473 and 1478.

We are still waiting to finalize the new agreement with SNOMED (IHTSDO), so any new SNOMED codes included in Sup 187 and CP 1478 are constrained until then.

So the supplement and CP 1478 are released with this caveat:

"This draft includes SNOMED codes pending approval by IHTSDO for inclusion in the DICOM subset. Until they are so approved, they may be used without a license or fee only in IHTSDO member countries"

which will be removed as soon as the SNOMED agreement is done.

The target date for the SNOMED agreement is the RSNA DICOM Standards Committee meeting on 12/3, though there is no guarantee that we will make that, but it is looking promising.

ftp://medical.nema.org/MEDICAL/Dicom/Supps/WC/sup187_wc_preclinicalanimalacquisitioncontext.pdf

ftp://medical.nema.org/MEDICAL/Dicom/Final/cp1457_ft_smallanimalidentification.pdf

ftp://medical.nema.org/MEDICAL/Dicom/Final/cp1470_ft_smallanimalanatomy.pdf

ftp://medical.nema.org/MEDICAL/Dicom/Final/cp1471_ft_clinicaltrialsresearch.pdf

ftp://medical.nema.org/MEDICAL/Dicom/Final/cp1472_ft_additionalresponsiblepersons.pdf

ftp://medical.nema.org/MEDICAL/Dicom/Final/cp1473_ft_transversepositioning.pdf

ftp://medical.nema.org/MEDICAL/Dicom/CP/cp1478_wc_speciesandstrain.pdf

ftp://medical.nema.org/MEDICAL/Dicom/Supps/WC/sup187_wc2_preclinicalanimalacquisitioncontext.pdf

 correction proposals

Small Animal/Co-clinical Data Integration

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