ROCKETSHIP: a flexible and modular software tool for the planning, processing and analysis of dynamic MRI studies

BMC Medical Imaging

Software

Naomi Santa-Maria¹  Samuel R. Barnes¹  Russell E. Jacobs¹  Thomas S. C. Ng²  Berislav V. Zlokovic³  Axel Montagne³ 

[1] Division of Biology and Biological Engineering, California Institute of Technology, 91125, Pasadena, CA, USA;Division of Biology and Biological Engineering, California Institute of Technology, 91125, Pasadena, CA, USA;Department of Medicine, University of California, Irvine Medical Center, Orange, CA, USA;Zilkha Neurogenetic Institute and Department of Physiology and Biophysics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA;

关键词: DCE-MRI;    Imaging;    ADC;    Parametric mapping;    Data-driven kinetic modelling;    MATLAB;    MRI;    Nested model;   

DOI  :  10.1186/s12880-015-0062-3

 received in 2015-01-04, accepted in 2015-05-29,  发布年份 2015

来源: Springer

【 摘 要 】

BackgroundDynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a promising technique to characterize pathology and evaluate treatment response. However, analysis of DCE-MRI data is complex and benefits from concurrent analysis of multiple kinetic models and parameters. Few software tools are currently available that specifically focuses on DCE-MRI analysis with multiple kinetic models. Here, we developed ROCKETSHIP, an open-source, flexible and modular software for DCE-MRI analysis. ROCKETSHIP incorporates analyses with multiple kinetic models, including data-driven nested model analysis.ResultsROCKETSHIP was implemented using the MATLAB programming language. Robustness of the software to provide reliable fits using multiple kinetic models is demonstrated using simulated data. Simulations also demonstrate the utility of the data-driven nested model analysis. Applicability of ROCKETSHIP for both preclinical and clinical studies is shown using DCE-MRI studies of the human brain and a murine tumor model.ConclusionA DCE-MRI software suite was implemented and tested using simulations. Its applicability to both preclinical and clinical datasets is shown. ROCKETSHIP was designed to be easily accessible for the beginner, but flexible enough for changes or additions to be made by the advanced user as well. The availability of a flexible analysis tool will aid future studies using DCE-MRI.A public release of ROCKETSHIP is available at https://github.com/petmri/ROCKETSHIP.

【 授权许可】

Unknown   
© Barnes et al. 2015. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

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