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Molecular imaging generates large volumes of heterogeneous biomedical imagerywith an impelling need of guidelines for handling image data. Although severalsuccessful solutions have been implemented for human epidemiologic studies, fewand limited approaches have been proposed for animal population studies.Preclinical imaging research deals with a variety of machinery yielding tons ofraw data but the current practices to store and distribute image data areinadequate. Therefore, standard tools for the analysis of large image datasetsneed to be established. In this paper, we present an extension of XNAT forPreclinical Imaging Centers (XNAT-PIC). XNAT is a worldwide used, open-sourceplatform for securely hosting, sharing, and processing of clinical imagingstudies. Despite its success, neither tools for importing large, multimodalpreclinical image datasets nor pipelines for processing whole imaging studiesare yet available in XNAT. In order to overcome these limitations, we havedeveloped several tools to expand the XNAT core functionalities for supportingpreclinical imaging facilities. Our aim is to streamline the management andexchange of image data within the preclinical imaging community, therebyenhancing the reproducibility of the results of image processing and promotingopen science practices.

XNAT-PIC: Extending XNAT to Preclinical Imaging Centers