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Open Access Highly Accessed Software

DCE@urLAB: a dynamic contrast-enhanced MRI pharmacokinetic analysis tool for preclinical data

Juan E Ortuño12*, María J Ledesma-Carbayo12, Rui V Simões3, Ana P Candiota145, Carles Arús145 and Andrés Santos12

Author Affiliations

1 CIBER de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 50018 Zaragoza, Spain

2 Biomedical Image Technologies Group, Departamento de Ingeniería Electrónica, Universidad Politécnica de Madrid, 28040 Madrid, Spain

3 Department of Maternal-Fetal Medicine (ICGON), Fetal and Perinatal Medicine Research Group (IDIBAPS), Hospital Clínic, Universitat de Barcelona, Sabino de Arana 1- Helios III, 08028 Barcelona, Spain

4 Departament de Bioquímica i Biologia Molecular, Unitat de Biociències, Universitat Autònoma de Barcelona, Edifici Cs, Campus UAB, 08193 Cerdanyola del Vallès, Spain

5 Institut de Biotecnologia i de Biomedicina Vicent Villar Palasí (IBB), Universitat Autònoma de Barcelona, Edifici Cs, Campus UAB, 08193 Cerdanyola del Vallès, Spain

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BMC Bioinformatics 2013, 14:316  doi:10.1186/1471-2105-14-316

Published: 4 November 2013

Abstract

Background

DCE@urLAB is a software application for analysis of dynamic contrast-enhanced magnetic resonance imaging data (DCE-MRI). The tool incorporates a friendly graphical user interface (GUI) to interactively select and analyze a region of interest (ROI) within the image set, taking into account the tissue concentration of the contrast agent (CA) and its effect on pixel intensity.

Results

Pixel-wise model-based quantitative parameters are estimated by fitting DCE-MRI data to several pharmacokinetic models using the Levenberg-Marquardt algorithm (LMA). DCE@urLAB also includes the semi-quantitative parametric and heuristic analysis approaches commonly used in practice. This software application has been programmed in the Interactive Data Language (IDL) and tested both with publicly available simulated data and preclinical studies from tumor-bearing mouse brains.

Conclusions

A user-friendly solution for applying pharmacokinetic and non-quantitative analysis DCE-MRI in preclinical studies has been implemented and tested. The proposed tool has been specially designed for easy selection of multi-pixel ROIs. A public release of DCE@urLAB, together with the open source code and sample datasets, is available at http://www.die.upm.es/im/archives/DCEurLAB/ webcite.

Keywords:
DCE-MRI; Imaging; Levenberg-Marquardt; Fitting; Preclinical; Pharmacokinetics; Animal models; High field MR; IDL