A Dynamic Susceptibility Contrast MRI Digital Reference Object for Testing Software with Leakage Correction
H Chen1*, M Jen2, P Hou1, R Stafford1, H Liu1, (1) UT MD Anderson Cancer Center, Houston, TX, (2) University of Wisconsin-Madison, Madison, WI
Presentations
TH-IePD-TRACK 2-2 (Thursday, 7/29/2021) 3:00 PM - 3:30 PM [Eastern Time (GMT-4)]
Purpose: Relative cerebral blood volume (rCBV), derived from dynamic susceptibility contrast (DSC)-MRI, is a perfusion biomarker commonly used for evaluating brain tumors. To account for the extravasation of contrast agents, post-processing leakage correction is often applied to improve rCBV accuracy. Digital reference objects (DRO) are ideal for testing the post-processing software, because the DRO’s biophysical model can be matched to the one implemented in the software. Our aim is to develop and test such DSC-DROs.
Methods: Three DROs were generated using the Weisskoff model, each composed of nine foreground lesion objects with combinations of different levels of rCBV and contrast leakage effects. Three types of background were implemented for these DROs: 1) a multi-compartment brain-like background, 2) a sphere background with a constant signal time curve, and 3) a sphere background with signal time curve identical to that of the brain-like DRO’s white matter (WM). The DROs were then analyzed with an FDA-cleared software with and without leakage correction. Leakage correction was tested with and without brain segmentation.
Results: Accuracy of leakage correction was able to be verified using the brain-like phantom and the sphere phantom with WM background. The sphere with constant background did not perform well with leakage correction with or without brain segmentation. The DROs were able to verify that for the particular software tested, leakage correction with brain segmentation achieved the lowest error.
Conclusion: DSC-MRI DROs with biophysical model matched to that of the post-processing software can be well used for the software’s validation, provided that the background signals are also properly simulated for generating the reference time curve required by the model. Care needs to be taken to consider the interaction of the design of the DRO with the software’s implementation of brain segmentation to extract the reference time curve.
ePosters
Keywords
Phantoms, Perfusion Imaging, MRI
Taxonomy
Contact Email