An open-source software tool for the generation of relaxation time maps in magnetic resonance imaging

BACKGROUND: In magnetic resonance (MR) imaging, T1, T2 and T2* relaxation times represent characteristic tissue properties that can be quantified with the help of specific imaging strategies. While there are basic software tools for specific pulse sequences, until now there is no universal software program available to automate pixel-wise mapping of relaxation times from various types of images or MR systems. Such a software program would allow researchers to test and compare new imaging strategies and thus would significantly facilitate research in the area of quantitative tissue characterization. RESULTS: After defining requirements for a universal MR mapping tool, a software program named MRmap was created using a high-level graphics language. Additional features include a manual registration tool for source images with motion artifacts and a tabular DICOM viewer to examine pulse sequence parameters. MRmap was successfully tested on three different computer platforms with image data from three different MR system manufacturers and five different sorts of pulse sequences: multi-image inversion recovery T1; Look-Locker/ TOMROP T1; modified Look-Locker inversion recovery (MOLLI) T1; single-echo T2/ T2*; and multi-echo T2/ T2*. Computing times varied between 2 and 113 seconds. Estimates of relaxation times compared favorably to those obtained from non-automated curve fitting. Completed maps were exported in DICOM format and could be read in standard software packages used for analysis of clinical and research MR data. CONCLUSIONS: MRmap is a flexible cross-platform research tool that enables accurate mapping of relaxation times from various pulse sequences. The software allows researchers to optimize quantitative MR strategies in a manufacturer-independent fashion. The program and its source code were made available as open-source software on the internet

MITK-ModelFit: A generic open-source framework for model fits and their exploration in medical imaging -- design, implementation and application on the example of DCE-MRI

Many medical imaging techniques utilize fitting approaches for quantitative parameter estimation and analysis. Common examples are pharmacokinetic modeling in DCE MRI/CT, ADC calculations and IVIM modeling in diffusion-weighted MRI and Z-spectra analysis in chemical exchange saturation transfer MRI. Most available software tools are limited to a special purpose and do not allow for own developments and extensions. Furthermore, they are mostly designed as stand-alone solutions using external frameworks and thus cannot be easily incorporated natively in the analysis workflow. We present a framework for medical image fitting tasks that is included in MITK, following a rigorous open-source, well-integrated and operating system independent policy. Software engineering-wise, the local models, the fitting infrastructure and the results representation are abstracted and thus can be easily adapted to any model fitting task on image data, independent of image modality or model. Several ready-to-use libraries for model fitting and use-cases, including fit evaluation and visualization, were implemented. Their embedding into MITK allows for easy data loading, pre- and post-processing and thus a natural inclusion of model fitting into an overarching workflow. As an example, we present a comprehensive set of plug-ins for the analysis of DCE MRI data, which we validated on existing and novel digital phantoms, yielding competitive deviations between fit and ground truth. Providing a very flexible environment, our software mainly addresses developers of medical imaging software that includes model fitting algorithms and tools. Additionally, the framework is of high interest to users in the domain of perfusion MRI, as it offers feature-rich, freely available, validated tools to perform pharmacokinetic analysis on DCE MRI data, with both interactive and automatized batch processing workflows.Comment: 31 pages, 11 figures URL: http://mitk.org/wiki/MITK-ModelFi

A feasible and automatic free tool for T1 and ECV mapping

Purpose: Cardiac magnetic resonance (CMR) is a useful non-invasive tool for characterizing tissues and detecting myocardial fibrosis and edema. Estimation of extracellular volume fraction (ECV) using T1 sequences is emerging as an accurate biomarker in cardiac diseases associated with diffuse fibrosis. In this study, automatic software for T1 and ECV map generation consisting of an executable file was developed and validated using phantom and human data. Methods: T1 mapping was performed in phantoms and 30 subjects (22 patients and 8 healthy subjects) on a 1.5T MR scanner using the modified Look-Locker inversion-recovery (MOLLI) sequence prototype before and 15 min after contrast agent administration. T1 maps were generated using a Fast Nonlinear Least Squares algorithm. Myocardial ECV maps were generated using both pre- and post-contrast T1 image registration and automatic extraction of blood relaxation rates. Results: Using our software, pre- and post-contrast T1 maps were obtained in phantoms and healthy subjects resulting in a robust and reliable quantification as compared to reference software. Coregistration of pre- and post-contrast images improved the quality of ECV maps. Mean ECV value in healthy subjects was 24.5% ± 2.5%. Conclusions: This study demonstrated that it is possible to obtain accurate T1 maps and informative ECV maps using our software. Pixel-wise ECV maps obtained with this automatic software made it possible to visualize and evaluate the extent and severity of ECV alterations

Pycortex: an interactive surface visualizer for fMRI.

Surface visualizations of fMRI provide a comprehensive view of cortical activity. However, surface visualizations are difficult to generate and most common visualization techniques rely on unnecessary interpolation which limits the fidelity of the resulting maps. Furthermore, it is difficult to understand the relationship between flattened cortical surfaces and the underlying 3D anatomy using tools available currently. To address these problems we have developed pycortex, a Python toolbox for interactive surface mapping and visualization. Pycortex exploits the power of modern graphics cards to sample volumetric data on a per-pixel basis, allowing dense and accurate mapping of the voxel grid across the surface. Anatomical and functional information can be projected onto the cortical surface. The surface can be inflated and flattened interactively, aiding interpretation of the correspondence between the anatomical surface and the flattened cortical sheet. The output of pycortex can be viewed using WebGL, a technology compatible with modern web browsers. This allows complex fMRI surface maps to be distributed broadly online without requiring installation of complex software

Comparison of T1 mapping techniques for ECV quantification. histological validation and reproducibility of ShMOLLI versus multibreath-hold T1 quantification equilibrium contrast CMR

BACKGROUND: Myocardial extracellular volume (ECV) is elevated in fibrosis or infiltration and can be quantified by measuring the haematocrit with pre and post contrast T1 at sufficient contrast equilibrium. Equilibrium CMR (EQ-CMR), using a bolus-infusion protocol, has been shown to provide robust measurements of ECV using a multibreath-hold T1 pulse sequence. Newer, faster sequences for T1 mapping promise whole heart coverage and improved clinical utility, but have not been validated. METHODS: Multibreathhold T1 quantification with heart rate correction and single breath-hold T1 mapping using Shortened Modified Look-Locker Inversion recovery (ShMOLLI) were used in equilibrium contrast CMR to generate ECV values and compared in 3 ways.Firstly, both techniques were compared in a spectrum of disease with variable ECV expansion (n=100, 50 healthy volunteers, 12 patients with hypertrophic cardiomyopathy, 18 with severe aortic stenosis, 20 with amyloid). Secondly, both techniques were correlated to human histological collagen volume fraction (CVF%, n=18, severe aortic stenosis biopsies). Thirdly, an assessment of test:retest reproducibility of the 2 CMR techniques was performed 1 week apart in individuals with widely different ECVs (n=10 healthy volunteers, n=7 amyloid patients). RESULTS: More patients were able to perform ShMOLLI than the multibreath-hold technique (6% unable to breath-hold). ECV calculated by multibreath-hold T1 and ShMOLLI showed strong correlation (r(2)=0.892), little bias (bias -2.2%, 95%CI -8.9% to 4.6%) and good agreement (ICC 0.922, range 0.802 to 0.961, p<0.0001). ECV correlated with histological CVF% by multibreath-hold ECV (r(2)= 0.589) but better by ShMOLLI ECV (r(2)= 0.685). Inter-study reproducibility demonstrated that ShMOLLI ECV trended towards greater reproducibility than the multibreath-hold ECV, although this did not reach statistical significance (95%CI -4.9% to 5.4% versus 95%CI -6.4% to 7.3% respectively, p=0.21). CONCLUSIONS: ECV quantification by single breath-hold ShMOLLI T1 mapping can measure ECV by EQ-CMR across the spectrum of interstitial expansion. It is procedurally better tolerated, slightly more reproducible and better correlates with histology compared to the older multibreath-hold FLASH techniques

Brain connectivity Patterns Dissociate action of specific Acupressure Treatments in Fatigued Breast cancer survivors

Funding This work was supported by grants R01 CA151445 and 2UL1 TR000433-06 from the National Institutes of Health. The funding source had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. We thank the expert assistance by Dr. Bradley Foerster in acquisition of 1H-MRS and fMRI data.Peer reviewedPublisher PD

Partial volume correction for arterial spin labeling sequences in magnetic resonance imaging. 3DSlicer extension

Arterial spin labeling is becoming an increasingly popular method for evaluating the cerebral blood flow. However, one of the major limitations of arterial spin labeling (and other perfusion assessment methods like PET) is the partial volume effect, by which each voxel of the image contains a mixture of tissues due to the low spatial resolution of ASL. Partial volume correction is required to retrieve the perfusion contribution of each of these tissues, which is important in the study of neurodegenerative diseases such as Alzheimer’s disease. A new partial volume correction method (3D weighted least squares) based on an existing state-of-the-art method (Asllani’s algorithm) is presented in this work. The new algorithm improves the previous algorithm by operating in a 3D way instead of a 2D way and including a weighting to the regression problem as a function of the distance between the voxels.The new method was tested over simulated cerebral perfusion images, giving better results than the Asllani’s algorithm. The algorithm was also implemented as a graphical user interface extension for the open source platform 3DSlicer. This extension automates all the correction process and allows the researchers processing the ASL images rapidly and easily. Using this extension, a real perfusion study was conducted to compare the cerebral perfusion between Alzheimer and control groups in resting state. Alzheimer group showed a significantly lower perfusion in the thalamus, caudate nucleus, hippocampus and cuneus. These regions have been reported in the literature to present atrophies in Alzheimer subjects and are involved in cognitive functions that are negatively affected by the disease. These results provide further validation for the 3DWLS as a suitable correction method and for the extension as a useful research tool.Ingeniería Biomédic

Obtaining optimal data length for FMRI images

Interest in brain hemodynamics has led to a substantial increase in state of the art research within the field of functional Magnetic Resonance Imaging (fMRI). FMRI enables research to be conducted on brain mapping in healthy individuals, as well as in patient populations. The need for accurate functional images is required. The primary objective was the development of a method to determine the optimal number of time points required to obtain reliable activation maps. The second phase involved the development of a program, which enabled the conversion of functional magnetic resonance images to a format that the neurosurgeon\u27s scanner could read. Obtaining an accurate functional activation map by reducing the number of time points, in addition to converting it to a format which allows the surgeon to view the images in real-time on his scanner during stereo-tactic surgery will increase the success rate in brain surgery

Polarized Helium to Image the Lung

The main findings of the european PHIL project (Polarised Helium to Image the Lung) are reported. State of the art optical pumping techniques for polarising ^3He gas are described. MRI methodological improvements allow dynamical ventilation images with a good resolution, ultimately limited by gas diffusion. Diffusion imaging appears as a robust method of lung diagnosis. A discussion of the potential advantage of low field MRI is presented. Selected PHIL results for emphysema are given, with the perspectives that this joint work opens up for the future of respiratory medicine.Comment: To be published in Proc. ICAP 2004 (19th Int. Conf. on Atomic Physics, Rio, July 26-30 2004