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

Barnes, Samuel R. and Ng, Thomas S. C. and Santa-Maria, Naomi and Montagne, Axel and Zlokovic, Berislav V. and Jacobs, Russell E. (2015) ROCKETSHIP: a flexible and modular software tool for the planning, processing and analysis of dynamic MRI studies. BMC Medical Imaging, 15 . Art. No. 19. ISSN 1471-2342. PMCID PMC4466867. https://resolver.caltech.edu/CaltechAUTHORS:20150617-080626134

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Abstract

Background: Dynamic 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. Results: ROCKETSHIP 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. Conclusion: A 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.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1186/s12880-015-0062-3DOIArticle
http://www.biomedcentral.com/1471-2342/15/19PublisherArticle
https://github.com/petmri/ROCKETSHIPOrganizationProject Website
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4466867/PubMed CentralArticle
ORCID:
AuthorORCID
Barnes, Samuel R.0000-0002-1065-8442
Zlokovic, Berislav V.0000-0002-6802-8232
Jacobs, Russell E.0000-0002-1382-8486
Additional Information:© 2015 Barnes et al. This is an Open Access article distributed 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. Received: 4 January 2015; Accepted: 29 May 2015; Published: 16 June 2015. Samuel R. Barnes and Thomas S. C. Ng contributed equally to this work. The authors thank Drs. David Colcher and Andrew Raubitschek for providing the mouse tumor model for this study, Dr. Meng Law for providing the clinical data, Dr. Andrey Demyanenko, Hargun Sohi, Bita Alaghebandan and Sharon Lin for their technical assistance. Drs. Scott Fraser and Kazuki Sugahara provided helpful advice and support. This work was funded in part by NIBIB R01 EB000993, NIH R01 EB00194, NRSA T32GM07616, City of Hope Lymphoma SPORE Grant (P50 CA107399), the Beckman Institute, the Caltech/City of Hope Biomedical Initiative, and R37NS34467, R37AG23084, and R01AG039452. Authors’ contributions: SB, TN, NSM, AM and REJ participated in the design and refinement of the software application. SB and TN implemented the software. All authors helped draft the manuscript, provided critical revisions, and approved the final version. Availability and requirements: Project name: ROCKETSHIP v.1.1 Project homepage: https://github.com/petmri/ROCKETSHIP Operating system(s): Windows/Mac OS X/Linux Programming language: MATLAB Other requirements: None, but image processing programs such as ImageJ or MRIcro are useful to pre-process inputs. License: GPL-2.0 Competing interests: The authors declare that they have no competing interests.
Funders:
Funding AgencyGrant Number
NIHR01 EB000993
NIHR01 EB00194
NIH Predoctoral FellowshipT32GM07616
City of Hope Lymphoma SPORE GrantP50 CA107399
Caltech Beckman InstituteUNSPECIFIED
Caltech/City of Hope Biomedical InitiativeUNSPECIFIED
NIHR37NS34467
NIHR37AG23084
NIHR01AG039452
Subject Keywords:DCE-MRI, Imaging, ADC, Parametric mapping, Data-driven kinetic modelling, MATLAB, MRI, Nested model
PubMed Central ID:PMC4466867
Record Number:CaltechAUTHORS:20150617-080626134
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20150617-080626134
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:58303
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:17 Jun 2015 16:44
Last Modified:09 Mar 2020 13:19

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