Abstract #4377
Weighted-average model curve preprocessing strategy for quantification of DSC perfusion imaging metrics from image-guided tissue samples in patients with brain tumors
Janine M Lupo 1 , Qiuting Wen 1 , Joanna J Phillips 2,3 , Susan M Chang 2 , and Sarah J Nelson 1
1
Radiology and Biomedical Imaging, University
of California, San Francisco, CA, United States,
2
Neurological
Surgery, University of California, San Francisco, CA,
United States,
3
Pathology,
University of California, San Francisco, CA, United
States
In this study we propose a new method for pre-processing
DSC data collected preoperatively for the analysis of
image-guided tissue samples that takes a weighted
average of dynamic curves based on their percentage
overlap with the tissue sample mask and excludes voxels
with no signal. This strategy minimized variability in
parameter calculation and showed better correspondence
with histopathological measures of vascular morphology
than two commonly used approaches for quantification of
perfusion metrics from image-guided tissue samples.
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