Dynamic susceptibility contrast (DSC) MRI methods allow the creation of relative cerebral blood volume (rCBV) maps that have the potential to provide more specific information about brain tumor biology and vasculature than compared to standard anatomical MR images. It has been shown that MRI-derived rCBV may:  1) better differentiate histologic brain tumor types than conventional MRI; 2) provide information to predict glial tumor grade; and 3) provide key insights for helping predict survival. In addition, rCBV maps may aid in differentiating post-treatment radiation effects from tumor and predict local recurrence or malignant transformation earlier than conventional anatomical MR imaging.

Not all leakage correction packages are the same. IB Neuro™ provides a significant leap in magnetic resonance (MR) perfusion analysis. The technology is based on over decades of proven scientific research and has proven superior over other commercially available packages in terms of accuracy and repeatability. In addition, IB Neuro is the only perfusion solution that automatically generates quantitative rCBV values using an exclusive machine learned image calibration patent, independent of time, scanner, field strength, or patient.


  • Platform-independent library allows for seamless integration into existing server and workstation applications.
  • Instantaneously computes and displays a complete set of perfusion maps from dynamic susceptibility contrast MR imaging data using push-button processing including; rCBV, CBF, MTT, TTP, and Tmax
  • Automatically corrects for artifacts in rCBV maps caused by contrast agent leakage across disruptions in the blood brain barrier
  • Displays the dynamic MR signal time course for any chosen brain location
  • Automatically exports perfusion parameter maps to the same medical imaging examination in DICOM compatible format
  • Automatically generates a report with summary statistics
  • Integrates with multiple PACS to assess data and distribute results
  • Normalizes perfusion parameters to Normal Appearing White Matter (NAWM) to facilitate comparisons across serial imaging studies in the same patient, and comparisons between patients
  • Automated selection of arterial input functions (AIFs) for CBF
  • CT Perfusion post-processing
  • Longitudinal reporting capability
  • Ability to output maps fused to anatomical with registration

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