XNAT Docs Index

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This documentation is for XNAT versions 1.6.0 - 1.6.5. You can find the latest documentation for XNAT 1.7 at https://xnat.org/documentation

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The core data-model used in XNAT is defined in an XSD document here. This schema is extended by other XSD document on a site by site basis to build customized representations of neuro-imaging data. There are three core data-types in the xnat.xsd; Projects, Subjects & Experiments. Most of ther data-types in XNAT can be defined by their relationship to one of those core data-types.

Projects (xnat:projectData)

A project us used to define a collection of data stored in XNAT. These often correlate directly to an IRB approved study, or a multi-site data aquisition program. Within XNAT, the project is used to define a security structure for data. Users are given certain permissions for data within certain projects (usually via a user group like Owner, Member, & Collaborator). Data is then assigned to certain projects. In turn, XNAT can control which data users can access based on the project permissions.

Subjects (xnat:subjectData)

A subject is anyone who participates in a study. XNAT has traditionally focused on human studies. However, in practice, a subject could be a non-human subject as well. A subject cannot exist outside the context of a project. A subject record is 'owned' by the project which created it. Additionally, subjects can be registered (shared) with other projects (to capture longitudinal data from various studies).

Experiments (xnat:experimentData)

An experiment is an event by which data is acquired. This data can be imaging data, or non-imaging data. Similar to subject, an experiment cannot exist outside the context of a project. It is owned by the project which first added it. It can additionally be shared into other projects.

Experiments are usually extended within XNAT to be specific kinds of experiments. Most experiments in XNAT are extended as Subject Assessments. In turn, subject assessments can be Imaging Sessions. Imaging Sessions can be MR Sessions, PET Sessions, CT Sessions, etc.

Subject Assessments (xnat:subjectAssessorData)

A subject assessment is a specific kind of experiment which is associated with a subject. It contains a foreign key to the subject. Subject Assessments are a common extension point in XNAT. If a user is trying to model new data, it is usually an extension of subject assessments. Only one extension of subject assessment is provided in the default XNAT install (Imaging Session). However, many XNAT installations create their own subject assessments to model a variety of subject tests, forms, etc.

Imaging Sessions (xnat:imageSessionData)

The Imaging Sesssion is an extension of the Subject Assessment. It is used to capture the data acquired in the normal course of Imaging studies. It adds a collection of image scans, reconstructions, and image assessments, to capture the data as scanned, preprocessed, and processed.

MR Session/ PET Session/ CT Session/ ETC

Most data stored in a standard XNAT fits into one of these extensions of the Imaging Session data-type. They correlate to the types defined by the DICOM standard.

Imaging Sessions introduce a collection of sub-elements which are used to capture imaging data.

Scans

Scans are children of any Imaging Session type. They are used to model individual scan series from a single scanning session. A single Session will usually contain multiple scans of different types. The Imaging Scans are usually extended by modality to be MR scans or PET scans, etc. They also specify the files which make up that scanning series (usually including the RAW data).

Reconstructions

A single imaging session can contain multiple image reconstructions. These are typically the results of a pre-processing stream. Averaged Atlas results. Gain field corrected images. etc.

Image Assessments

A single imaging session can contain multiple imaging assessments. They are typically the results of a processing stream and can contain both generated images and statistics. To capture imaging assessments, it is necessary to model the processing results in an XSD. Example imaging assessments would include freesurfer or fsl results.

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