DSC Perfusion
Your centralized hub for advanced perfusion processing, delivering key insights into blood vessel structure and function
If you have an MRI scanner, chances are you are also doing perfusion imaging. Conventional perfusion analysis pipelines are often slow, non-standardized, and ineffective.
With nordicMEDiVA Perfusion, you can take this to the next level. Developed for automation, quality, standardization, and collaboration, it allows for higher patient throughput while keeping you in control.
DSC
module
Automatic motion correction
Rigid-body motion correction with six degrees of freedom. Motion curves are provided as output for quality control.
Send maps to PACS automatically or read them in the nordicMEDiVA viewer
You can purchase the module just for processing or with the viewer.
Maps needed for brain tumor evaluation, such as both leakage-corrected and uncorrected CBV and CBF, can be sent to PACS automatically with a default palette tailored to your needs before sending.
Leakage correction
2 types of leakage correction, including our patented method accounting for variable MTT to provide insights into blood–brain barrier permeability and enhance the accuracy of perfusion analysis. Leakage maps:
K2 — generated using the Weisskoff leakage correction method.
rKtrans — using the Residue Function-based leakage correction method.
Flexible ROI analysis
Create and update 2D and 3D regions of interest (ROIs) as you analyze your data. Results can be exported directly as image files or sent to PACS as part of the secondary capture, ensuring seamless integration with your workflow.
Processing without AIF using auto normalization
Automatically normalize the perfusion maps to healthy white and grey matter to eliminate the variability in the choice of AIF and yield more reproducible results.
Easy quality control
As part of the output, nordicMEDiVA produces graphs of the applied motion correction and AIF for quality control.
Colormaps preserve geometry and quantitative measurements
CBV and CBF are exported with a color palette, and the original geometry is preserved. They also include the actual quantitative parametric values. It is thus possible to view and analyze the maps on any PACS or 3rd party DICOM image viewer.
Export options
Export images as secondary captures — choose the slices, planes, objects to display, and add any associated data like VOI statistics, histograms, or quality control graphs. DSC maps can also be fused with anatomical scans for visualization or multidisciplinary discussions.
We are committed to providing the highest quality on our product
-
Automation
The automatic routing feature in nordicMEDiVA is easy to set up and allows the system to automatically pre-process the raw data.
Export settings allow you to choose how output maps should be displayed in other systems, with options for “Grayscale,” “Palette color,” or “RGB color,” ensuring optimal visualization and compatibility.
The perfusion maps can be automatically exported to PACS or be viewed in nordicMEDiVA’s integrated web-based viewer for further study.
All this can be done within minutes from when the patient is scanned!
-
Patented workflow
We've patented parts of our automated perfusion workflow to maximize its potential. nordicMEDiVA generates quantitative DICOM maps of CBV and CBF, preserving the original geometry and including the actual quantitive parametric values with a predefined color palette for compatibility with PACS systems and DICOM viewers.
Our patented methods — automated normalization for repeatable results, vessel segmentation in DCE/DSC-MR imaging for blood vessel isolation, and contrast agent extravasation correction which estimates the leakage transfer constant directly from the residue function and is insensitive to changes in MTT — enhance imaging accuracy and promote repeatable results between studies.
See Patents and Licenses for more information. -
Trusted algorithms
Our first perfusion software, nordicICE (2004), has been demonstrated through independent studies to offer equal or higher reproducibility compared to other perfusion tools. The proven algorithms from nordicICE are also used in nordicMEDiVA Perfusion, ensuring consistent high standards.
-
Standardization
We follow the recommendations set out by the Quantitative Imaging Biomarker Alliance (QIBA) for DSC imaging.
Push for innovation
Deliver high quality
Listen to our customers
Value safety
Focus on ease of use
Scientific references
Below you will find a list of scientific references, papers, and guidelines we have used in the development of the nordicMEDiVA Perfusion module. More references can be found on News & events | NordicNeuroLab
-
Abstract
Dynamic susceptibility contrast (DSC)-based perfusion analysis from MR images has become an established method for analysis of cerebral blood volume (CBV) in glioma patients. To date, little emphasis has, however, been placed on quantitative perfusion analysis of these patients, mainly due to the associated increased technical complexity and lack of sufficient stability in a clinical setting. The aim of our study was to develop a fully automated analysis framework for quantitative DSC-based perfusion analysis. The method presented here generates quantitative hemodynamic maps without user interaction, combined with automatic segmentation of normal-appearing cerebral tissue. Validation of 101 patients with confirmed glioma after surgery gave mean values for CBF, CBV, and MTT, extracted automatically from normal-appearing whole-brain white and gray matter, in good agreement with literature values. The measured age-and gender-related variations in the same parameters were also in agreement with those in the literature. Several established analysis methods were compared and the resulting perfusion metrics depended significantly on method and parameter choice. In conclusion, we present an accurate, fast, and automatic quantitative perfusion analysis method where all analysis steps are based on raw DSC data only.
-
Abstract
The presence of macroscopic vessels within the tumor region is a potential confounding factor in MR-based dynamic susceptibility contrast (DSC)-enhanced glioma grading. In order to distinguish between such vessels and the elevated cerebral blood volume (CBV) of brain tumors, we propose a vessel segmentation technique based on clustering of multiple parameters derived from the dynamic contrast-enhanced first-pass curve. A total of 77 adult patients with histologically-confirmed gliomas were imaged at 1.5T and glioma regions-of-interest (ROIs) were derived from the conventional MR images by a neuroradiologist. The diagnostic accuracy of applying vessel exclusion by segmentation of glioma ROIs with vessels included was assessed using a histogram analysis method and compared to glioma ROIs with vessels included. For all measures of diagnostic efficacy investigated, the highest values were observed when the glioma diagnosis was based on vessel segmentation in combination with an initial mean transit time (MTT) mask. Our results suggest that vessel segmentation based on DSC parameters may improve the diagnostic efficacy of glioma grading. The proposed vessel segmentation is attractive because it provides a mask that covers all pixels affected by the intravascular susceptibility effect.
-
Abstract
This QIBA Profile, Dynamic-Susceptibility-Contrast Magnetic Resonance Imaging (DSC-MRI), addresses the measurement of an imaging biomarker for relative Cerebral Blood Volume (rCBV) for the evaluation of brain tumor progression or response to therapy. We note here, that this profile does not claim to be measuring quantitative rCBV due to lack of existing supporting literature; it does provide claims for a biomarker that is proportional to rCBV, which is the tissue normalized first-pass area under the contrast-agent concentration curve (AUC-TN). The AUC-TN therefore has merit as a potential biomarker for diseases or treatments that impact rCBV. This profile places requirements on Sites, Acquisition Devices, Contrast Injectors, Contrast Media, Radiologists, Physicists, Technologists, Reconstruction Software, Image Analysis Tools and Image Analysts involved in Site Conformance, Staff Qualification, Product Validation, Pre-delivery, Periodic QA, Protocol Design, Subject Handling, Image Data Acquisition, Image Data Reconstruction, Image QA, Image Distribution, Image Analysis and Image Interpretation.
https://qibawiki.rsna.org/images/d/d4/QIBA_DSC-MRI_Stage2-Consensus_Profile.pdf