SA SIG

Small Animal Imaging

SA SIG

SA SIG

FACT

• Most humans are all animal

• Not all animals are human

• You have a head on your shoulders…

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Quick History

• Long long ago… Beginnings of Human Imaging.

• Late ‘70s digital imaging “tomography.”

• Human based on the *scientific concept of the crown.

*Archimedes

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State-of-the-Art

Human Imaging

VS

non-human animal imaging.

THUS

Reverse Translation of Human Imaging to Animal Imaging Technology Required.

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Visualization and Quantification of Fat

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Models: Prostate Cancer

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

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Imaging: Radiology to Histology

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Imaging: MRI Histology

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Novel Contrast Agents

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Contrast Agents: In-Vivo, In-Vitro

NISTNINDSGUMC

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Concept of Integrated Imaging

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Pre-Post Intervention Link

• Free text is perhaps not the best annotation for preclinical research data. Classification may be needed. VOCABULARY

*Adapted from Dr. T. J. FitzGerald, Quality Assurance Review Center Director’s Thursday Presentation.

*

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Stereotaxic Surgery

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Stereotaxic Imaging

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Histological Sectioning

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Today’s Products

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Some Industry SAI Leaders:

MRI/NMR Bruker-BioSpin Corp. Varian, Inc. Siemens AG Advanced Veterinary Technologies, Inc. microPet/SPECT Philips Medical Concorde Microsystems Proportional Technolo gies, Inc. Gamma Medica, Inc. Suinsa

Optical Imaging Advanced Research Technologies Berthold Techn ologies GmbH & Co. Comecer Corp. Kodak Scientific Imaging OptoSonincs, Inc. VisualSonics Xenogen Mauna Kea Technolog ies Hamamatsu Photonics LabLogic Systems Ltd. VisEN Medical

microCT GE Medical Imtek, Inc. Faxitron X-Ray Corporation SCANCO Medical AG SkyScan TeraRecon

Accessories Spin Systems Ltd Rapid Biomedical, GmbH Doty Scientific, Inc. Resonance Research, Inc. SA Instruments, Inc. Luxtron Corporation Tecomet Insight Neuroimaging Systems, Inc.

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SOME Collaborating Institutions:

John's Hopkins University

U-Robotics Laboratory, Urological Institute (Baltimore, MD)

Johns Hopkins University, Bloomberg School, Neurotoxicology & Molecular Imaging (Baltimore, MD)

NIST, (Gaithersberg, MD)

University of Virginia, Radiology & Biomedical Engineering, Small Animal Multi-Modality Imaging Center (Charlottesville, VA)

NIH-NINDS, Laboratory of Functional and Molecular Imaging (Bethesda, MD)

Thomas Jefferson University

(Philadelphia, PA)

University of the District of Columbia

(Washington, DC)

Georgetown University

(Washington, DC)

ASI Instruments Inc.

(Warren, MI)

You Too can become a part of this!

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Objectives:

• Establish overall structure and scope for Small Animal Imaging projects.

• Prioritize Small Animal imaging projects for Workspace.

• Define requirements for Small Animal Imaging data management standards.

• Propose integration requirements for “caBIG™ Compliant” In Vivo Imaging data management software and tools.

• Define operational requirements and procedures for caBIG™ integration of relevant small animal medical imaging commercial software systems.

• Prioritize tool and software development requirements.

• Create specifications against prioritized tools and activities.

• Develop test and validation requirement standards for Workspace software and tools.

• Review completed tools and projects, and evaluate against initial specification, test and validation requirements.

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Establish overall structure and scope for Small Animal Imaging projects.

• Call to Industry and SAILs centers• Import/export of image data, meta file data.• Link to associated data, spectroscopy,

histology, etc. (to be defined.)• Visualization tools (“veterinary radiology”

space.), mapping of multimodality data.• Identifier/classification labeling.• Annotation + CAD.

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Prioritize Small Animal imaging projects for Workspace.

• Call to Industry.

• Call to major small animal imaging centers.

• Use of survey material

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Define requirements for Small Animal Imaging data management standards.

• Read/import image data from all digital imaging sources (DICOM may not be correctly implemented on these systems.)

• Read/import metafile information (not always part of header, sometimes separate file or not available.)

• Link radiological image data to histological image data and potentially.

• Map animal data to relevant human disease (Jackson Lab).

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Define requirements for Small Animal Imaging data management standards.

(Continued)

• White paper on SAI data sources/formats.• Identifier/classification labeling (modality(ies),

species, type of animal model (genetic, induced, xenograft, mode of induction)

• Link data to genetic/other data.• Veterinary coordinate system

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Propose integration requirements for “caBIG™ Compliant” In Vivo Imaging data management

software and tools.

• Linear Methodology.• Call to Standards and Interoperability (SIO).• Call to Software • Suggest standards to industry and SAILs perhaps

through NCI, NCRR and other relevant funding agencies.

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Define operational requirements and procedures for caBIG™ integration of relevant

small animal medical imaging commercial software systems.

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Prioritize tool and software development requirements.

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Create specifications against prioritized tools and activities.

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Develop test and validation requirement standards for Workspace software and

tools.

• Call to test bed “what are you doing” (remember: emulation is the highest form of flattery) I.e. evaluate tumor volume with model (growth) and treatment (smaller??).

• Co-register modalities, phantom work.

SA SIGReview completed tools and projects, and

evaluate against initial specification, test and validation requirements.

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Summary

• Vocabulary: Species, Models, contrast agents/tracers/ligans, Coordinates (rostral…), “Identifiers”.