Abstract
BackgroundDCE@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.ResultsPixel-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.ConclusionsA 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/.
Highlights
Dynamic contrast-enhanced (DCE)@urLAB is a software application for analysis of dynamic contrast-enhanced magnetic resonance imaging data (DCE-Magnetic resonance imaging (MRI))
The software tool provides detailed information of the estimated pharmacokinetic model at pixel level; if the left mouse button is pressed when the pointer is located over the region of interest (ROI), the adjusted curve of the parametric model associated to the selected pixel is plotted together with the Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) sequence values
Validation using simulated data Tofts and extended Tofts models have been validated with the Quantitative Imaging Biomarkers Alliance (QIBA) DCE-MRI synthetic data, which are publicly available at http://dblab.duhs.duke.edu
Summary
Validation using simulated data Tofts and extended Tofts models have been validated with the Quantitative Imaging Biomarkers Alliance (QIBA) DCE-MRI synthetic data, which are publicly available at http://dblab.duhs.duke.edu. Taking into account graphs in their page 612: the estimated kep value in this case was 0.75 min−1, for tumours with a volume (60–80 mm3) similar to our GL261 (69±43 mm3) In both cases, the differences observed in the MR signal time courses between well-perfused and badly perfused (hypoxic regions) agree with the ones described by authors in [15,57]. It has been experimentally verified that the computing time needed to perform a pharmacokinetic analysis depends linearly on the number of pixels contained in the ROI and the number of dynamic frames of DCE dataset. Because tumor ROIs are smaller, the complete analysis using the Tofts model of the whole DCE dynamic slice (128 × 128 = 16384 pixels) and 40 dynamic frames, took about 5 minutes in the personal computer formerly described. Another possibility is to install the IDL virtual machine (version 6.4 or posterior), which can be downloaded freely and does not require a license
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
