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Software Open access Published: 16 June 2015 Thomas S. C. Ng1,2, Naomi Santa-Maria1, Axel Montagne3, Berislav V. Zlokovic3 & …Russell E. Jacobs1 BMC Medical Imaging volume 15, Article number: 19 (2015) Cite this article 10k Accesses 5 Altmetric Metrics details AbstractBackgroundDynamic 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 Peer Review reports BackgroundThe utility of dynamic magnetic resonance imaging (MRI) studies to diagnose diseases, characterize their progression, and evaluate treatment response is a topic of vigorous research. In particular, physiological information garnered from techniques such as diffusion MRI, blood oxygen-level dependent (BOLD) MRI, iron-oxide imaging, dynamic susceptibility MRI (DSC-MRI) and dynamic contrast-enhanced MRI (DCE-MRI) [1] are being explored as imaging biomarkers in virtually all aspects of medicine, especially in oncology and neurological diseases.DCE-MRI involves the rapid serial acquisition of T1-weighted images before, during and after intravenous injection of a contrast agent (CA). The physiological properties of the tissue of interest are inferred by analyzing the image signal change kinetics induced by the CA within the tissue region of interest (ROI). Given the inherent leakiness of tumor blood vessels (which enhances the signal observed at the tumor site due to more CA leakage) [2], the majority of DCE-MRI studies have focused on oncology applications [3]. Studies have especially focused on using DCE-MRI to characterize tumor phenotypes or to evaluate the response of tumors to therapy [4]. The use of DCE-MRI has also been explored in other fields such as obstetrics [5] and the neurosciences [6, 7].Although several individual studies have demonstrated the promise of DCE-MRI as an imaging biomarker, widespread clinical adoption of this technique remains limited. This is in part because implementation and standardization of DCE-MRI is challenging. Differences in hardware such as the MRI field strength, coil setups and sequence types available at different institutions can affect the quality of the images acquired and constrain the choice of certain

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Recently, several groups have recognized that data-driven approaches in selecting the appropriate model may be important for proper physiological interpretation of the DCE-MRI data [23]. To facilitate this, ROCKETSHIP includes a nested model fitting option as well as statistical tools to analyze and compare the goodness-of-fit between different kinetic models.We selected the MATLAB environment for a number of reasons. Firstly, MATLAB is widely used for image analysis in the academic community; programs written in MATLAB can generally be run on Mac, Windows or Unix-based operating systems with minimal porting issues. Secondly, MATLAB provides several toolboxes (such as the Curve Fitting Toolbox and Parallel Computing Toolbox) that facilitated development of the current software and allows future extensions to be easily implemented. MATLAB also has a strong user-contributed library of imaging processing and statistical analysis functions that aid this endeavor. Building and testing of the software are helped by the interpretive nature of the MATLAB language. Modifications to the existing code or testing of new modules can be performed in real time. These capabilities enable users of wide-ranging expertise (from experienced programmers to biologists/clinicians with less programming experience) to use ROCKETSHIP and develop new modules and extend the software.Since it is run within the MATLAB environment, the execution time of ROCKETSHIP may be slower than other DCE-MRI software written in compiled languages (C, C++, IDL). The use of the Parallel Computing Toolboxto do the voxel-by-voxel processing in parallel mostly offsets this limitation. While this may be a disadvantage in a daily clinical workflow setup, most DCE-MRI data are analyzed offline and often in a research context. As discussed above, ROCKETSHIP will be advantageous in this scenario. Furthermore, MATLAB code can be ported to C/C++ and Julia [28] in a relatively straightforward way. Thus, once an optimal setup is developed using ROCKETSHIP, one can translate this to a lower level language and ultimately as a standalone program.The precision and accuracy of DCE-MRI parameter estimation in vivo is dependent on several factors, ranging from the type of tissue being probed, the type of image acquisition protocol/system used to the post-acquisition processing and analysis methodologies. DCE-MRI software packages address the post-acquisition portion of this pipeline. To evaluate ROCKETSHIP’s ability in this regard, simulation datasets with a range of models and parameters expected in typical studies were generated and fitted. Results demonstrate that ROCKETSHIP was able to recover DCE-MRI parameters accurately using its default configuration, on par with (or better than) similar studies using the same pharmacokinetic models implemented within currently available software packages. Furthermore, the nested model functionality, unavailable in prior software suites, was generally able to select the appropriate kinetic model for a given simulation dataset. ROCKETSHIP was also able to fit both preclinical and clinical in vivo DCE-MRI data well, demonstrating its applicability for in vivo studies.While the simulations presented cover a broad parameter range, it is likely that further modifications/tuning of ROCKETSHIP’s settings or functions will be required for specific in vivo applications in the future. Furthermore, extrinsic factors affecting the data

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Rate automatically adjusted to the maximum rate that the channel can support. Signal Ground and Shield Next Topic | Previous Topic | TOC Pin 7, Pin 1, and the shell are included in this category. Cables provide separate paths for each, but internal wiring often connects pin 1 and the cable shell/shield to signal ground on pin 7. Pin 7 - Ground All signals are referenced to a common ground, as defined by the voltage on pin 7. This conductor may or may not be connected to protective ground inside the DCE device. The existence of a defined ground potential within the cable makes the EIA232 standard different from a balanced differential voltage standard, such as EIA530, which provides far greater noise immunity. Primary Communications Channel Next Topic | Previous Topic | TOC Pin 2 - Transmitted Data (TxD) This signal is active when data is transmitted from the DTE device to the DCE device. When no data is transmitted, the signal is held in the mark condition (logic '1', negative voltage). NOTE: Pin 2 on the DCE device is commonly labeled "Received Data", although by the EIA232 standard it should still be called Transmitted Data because the data is thought to be destined for a remote DTE device. Pin 3 - Received Data (RxD) This signal is active when the DTE device receives data from the DCE device. When no data is transmitted, the signal is held in the mark condition (logic '1', negative voltage). NOTE: Pin 3 on the DCE device is commonly labeled "Transmitted Data", although by the EIA232 standard it should still be called Received Data because the data is thought to arrive from a remote DTE device. Pin 4 - Request to Send (RTS) This signal is asserted (logic '0', positive voltage) to prepare the DCE device for accepting transmitted data from the DTE device. Such preparation might include enabling the receive circuits, or setting up the channel direction in half-duplex applications. When the DCE is ready, it acknowledges by asserting Clear to Send. NOTE: Pin 4 on the DCE device is commonly labeled "Clear to Send", although by the EIA232 standard it should still be called Request to Send because the request is thought to be destined for a remote DTE device. Pin 5 - Clear to Send (CTS) This signal is asserted (logic '0', positive voltage) by the DCE device to inform the DTE device that transmission may begin. RTS and CTS are commonly used as handshaking signals to moderate the flow of data into the DCE device. NOTE: Pin 5 on the DCE device is commonly labeled "Request to Send", although by the EIA232 standard it should still be called Clear to Send because the signal is thought to originate from a remote DTE device. Secondary Communications Channel Next Topic | Previous Topic | TOC Pin 14 - Secondary Transmitted Data (STxD)Pin 16 - Secondary Received Data (SRxD)Pin 19 - Secondary Request to Send (SRTS)Pin 13 - Secondary Clear to Send (SCTS). הצעות. Dce tools 64 bit; Dce tools; Downloads dce tools; Photoshop plugins dce tools; Dce tools portrait skin cleaner; Digital camera dce 2 software הצעות. Dce tools 64 bit; Dce tools; Downloads dce tools; Photoshop plugins dce tools; Dce tools portrait skin cleaner; Digital camera dce 2 software