XNAT-PIC: Extending XNAT to Preclinical Imaging Centers

TL;DR

This paper introduces XNAT-PIC, an extension of the XNAT platform designed to better support preclinical imaging data management, processing, and sharing, addressing the unique challenges of animal imaging studies.

Contribution

The paper presents new tools and functionalities that expand XNAT to handle large, multimodal preclinical image datasets and processing pipelines, which were previously unsupported.

Findings

Enhanced data management for preclinical imaging

Improved reproducibility of image analysis results

Facilitated open science practices in preclinical research

Abstract

Molecular imaging generates large volumes of heterogeneous biomedical imagery with an impelling need of guidelines for handling image data. Although several successful solutions have been implemented for human epidemiologic studies, few and limited approaches have been proposed for animal population studies. Preclinical imaging research deals with a variety of machinery yielding tons of raw data but the current practices to store and distribute image data are inadequate. Therefore, standard tools for the analysis of large image datasets need to be established. In this paper, we present an extension of XNAT for Preclinical Imaging Centers (XNAT-PIC). XNAT is a worldwide used, open-source platform for securely hosting, sharing, and processing of clinical imaging studies. Despite its success, neither tools for importing large, multimodal preclinical image datasets nor pipelines for processing whole imaging studies are yet available in XNAT. In order to overcome these limitations, we have developed several tools to expand the XNAT core functionalities for supporting preclinical imaging facilities. Our aim is to streamline the management and exchange of image data within the preclinical imaging community, thereby enhancing the reproducibility of the results of image processing and promoting open science practices.