VivoQuant™ is a DICOM compliant post-processing suite for image data combining fundamental viewing functionality with powerful analysis capabilities. VivoQuant (“VQ”) supports data from most imaging modalities including MR, PET, SPECT, CT, and Optical. Multiple display modes including orthogonal views, slice views, special co-registration multi-views as well as 3D MIPs and volume renderings allow users to optimally view information of interest. Built-in features allow imaging scientists to extract the information they need with minimal effort, including powerful tools for fine-tuning images and isolating, drawing and analyzing 3D regions of interest. VivoQuant’s integration with iPACS, a full image study data management platform, offers sophisticated data management, reporting and data sharing tools of VivoQuant-generated data.
Supports the visualization and analysis of both static and dynamic image data sets across multiple modalities (CT, PET, SPECT, MR, and Optical; over 32 data formats). Extensive viewing features including slice view, orthogonal views, multiple planar reconstruction (MPR), multi-dataset view, and tile view.
Image Registration and Pre-processing Tools
Multi-modal registration (automated, manual or user-provided fiducial markers). Additional features include filtering, cropping, smoothing, and re-scaling functionality.
Easy-to-use Analysis Packages
3D ROI segmentation via automatic, semi-automatic and manual tools. Supports Plugin Modules for brain and whole body atlas based segmentation and tracer-kinetic modeling. MR analysis toolkits for generating T1, T2, ADC, and fat quantification maps and performing fMRI analysis.
Data Publication Tools
Publish analysis data in tabular and graphical output. Plotting tools for time-activity and time-signal curves, contours and histograms. Image and movie generation for all viewing functions in a broad range of file formats.
Image and analysis data can be managed by the iPACS platform delivering integrated data management, reporting, and sharing capabilities.
Tracer Kinetic Modeling
Tracer Kinetic modeling is a functional imaging technique that is used to analyze the concentration of a tracer molecule in a specific target tissue. inviCRO’s Compartmental Modeling tool allows users to take advantage of the 3D ROI tool for region- and voxel-level analysis across various compartmental models (specified below). Currently, the Tracer Kinetic Modeling tool empowers the user to estimate parameters in a ROI or individual voxel and provides the ability to preserve user-defined variables when switching between methods (ex. k2’ for SRTM2 and MRTM2)
Sample Graphical Output of the Modeling Tool Method Applications Model Inputs 2-tissue compartmental model (2TCM) (Mintun et al, 1984; Hong and Fryer, 2010) To estimate radioligand kinetic parameters when radioligand kinetics can be described by a 3 compartment model that includes 2-tissue compartments and 1 blood compartment Metabolite-corrected arterial plasma curve, tissue time activity curves 1-tissue compartmental model (1TCM) (Laurelle et al, 2002; Hong and Fryer 2010) To estimate radioligand kinetic parameters when radioligand kinetics can be described by a 2 compartment model that includes 1-tissue compartment and 1 blood compartment Metabolite-corrected arterial plasma curve, tissue time activity curves Logan graphical method (Logan et al, 1990) A graphical, linear method to estimate VT Metabolite-corrected arterial plasma curve, tissue time activity curves Logan reference graphical method (Logan et al, 1996) A graphical, linear method to estimate BPND for ligands for which there exists a reference region Tissue time activity curves and a reference tissue time activity curve Simplified reference tissue model (SRTM) (Lammertsma et al, 1996; Gunn et al, 1997) A simplified model-based method to estimate BPND for ligands for which there exists a reference region and for which the target region can be described by 1TCM kinetics Tissue time activity curves and a reference tissue time activity curve SRTM2 (Wu and Carson, 2002; Gunn et al, 1997) To reduce noise in parametric images estimated by SRTM Tissue time activity curves, a reference tissue time activity curve, k2’ value (determined from a prior run of SRTM) Patlak plot (Patlak et al, 1985) A graphical, linear method to estimate Ki, the rate of trapping of irreversibly bound tracers Metabolite-corrected arterial plasma curve, tissue time activity curves
3D Brain Atlas
This plug-in module is designed to provide a robust means of analyzing pre-clinical brain images. Support is provided for quantification of single acquisition and/or dynamic response across brain regions in PET, SPECT, and MRI scans. Integrated with the iPACS and VivoQuant for easy extraction and management of analysis endpoints
- Automated fusion routines register application-specific brain atlas to preclinical image data.
- Atlases available for mouse, rat, cynomologus, rhesus, and beagle species and customized mappings.
- Eliminates need to hand-draw ROIs.
- Flexible atlas/key structure enables user-definable region groups within existing atlases.
- Advanced statistical methods provide both rapid and reproducible volume and signal quantification.
- Integrated with the 3D ROI and Reorientation Tools for easy QC and manual correction
Whole Body Atlas
Inter active plug-in module for automated segmentation of user-defined regions of interest (ROI) from a reference library of image data sets. Integrated with the iPACS and VivoQuant for easy extraction and management of analysis endpoints.
- Save time and reduce user error with automated routines.
- Customizable library and ROI sets.
- Use image data from any species or animal model.
- Streamlined workflows with the 3D ROI tool for manual correction.
- Full integration with the iPACS platform for data management and batch processing.
fMRI/phMRI Brain Analysis
The fMRI/phMRI analysis module takes advantage of VivoQuant’s extensive data format support to analyze a wide variety of dynamic MRI data. Standard pre-processing techniques are available for brain segmentation, motion correction, spatial smoothing, spatial normalization, bandpass filtering, and atlas registration. General Linear Model (GLM) regression analysis is available for fMRI and phMRI studies to generate statistical brain maps and percent change in sBOLD at voxel and region of interest levels. Integrated with the iPACS and VivoQuant for easy extraction and management of analysis endpoints.
Additionally, inviCRO’s image analysis services team is able to extend individual animal analysis with group-level mixed effects analyses to study and compare multiple cohorts. It can also employ functional connectivity methods using sophisticated correlation analysis for unsupervised discovery of highly connected networks and seed-region driven GLM.
- In-house-developed functional and pharmacological MRI platform, including functional connectivity.
- MRI voxel-based & deformation-based morphometry.
- Application of standard, custom developed and novel DCE. MRI analysis methodologies.
- Advanced volume estimation tools.
- Arterial spin labeling and cerebral blood flow analysis.
- MRS capabilities
Cryo-Imaging Quantitative Tomography
CiQuant (Cryo-Imaging Quantitative Tomography) is specifically designed for traditional 2D and new 3D qualitative and quantitative analysis of ex vivo-imaged tissue samples across many modalities. This new capability presents a bridge between discovery and development in preclinical imaging with advancements within the field of 3D cryoimaging. CiQuant simplifies and enhances the reconstruction, visualization, and quantification of preclinical and translational imaging. Innovative image analysis allows users to take advantage of 3D cryoimaging, turning detailed samples into readily applicable data. Virtual reconstruction allows users to render tangible and complete 3D models using slices of tissue. Users are given expanded capabilities with new approaches for observing site specific localization of test materials. Using VivoQuant’s registration tools, multiple ex vivo modalities can be registered to one another as well as to in vivo modalities (MR, PET, etc.)
- Applications in autoradiography, fluorescence, histology, bioluminescence, optical and more.
- Transforms individual 2D cryosections into 3D while providing micrometer spatial resolution and nanocurie resolution of signal.
- Sophisticated segmentation approaches with rapid viewing and quantification of CiQUANT image leveraging VivoQUant’s suite of well-established 3D viewing, automated segmentation and co-registration and quantification tools.
- CiQuant supports standard 2D autoradiogaphy workflows as well.
- A temporary license will be issued for a trial period. You will be required to provide your name , email, and institution. Follow the instructions below to register for a license once the software is installed on your computer. An inviCRO team member will follow up to provide additional information about the software and its use.
- Recommended System Requirements:
- Windows 7/8/10, in 32 or 64 bit (a 64 bit PC windows computer is recommended).
- Mac OS X (10.7 and higher).
- Linux (RHEL 5 and higher).
- Minimum 8GB RAM (increased RAM dependent upon user applications).
- OpenGL supported graphics card
- Internet speeds – 4mbps downstream and 1mbps upstream.
If you wish to download the alpha/beta version or the previous release of VivoQuant, please click here.
After you have successfully downloaded and installed the software, please load VivoQuant and go to Help -> Registration and submit a license registration ticket. You will then receive a trial license shortly thereafter via email.