
Arrival Time Correction for Dynamic Susceptibility Contrast MR Permeability Imaging in Stroke Patients
Author(s) -
Richard Leigh,
Shyian S Jen,
Daniel D. Varma,
Argye E. Hillis,
Peter B. Barker
Publication year - 2012
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0052656
Subject(s) - receiver operating characteristic , contrast (vision) , medicine , perfusion , perfusion scanning , stroke (engine) , area under the curve , nuclear medicine , magnetic resonance imaging , radiology , artificial intelligence , computer science , mechanical engineering , engineering
Purpose To determine if applying an arrival time correction (ATC) to dynamic susceptibility contrast (DSC) based permeability imaging will improve its ability to identify contrast leakage in stroke patients for whom the shape of the measured curve may be very different due to hypoperfusion. Materials and Methods A technique described in brain tumor patients was adapted to incorporate a correction for delayed contrast delivery due to perfusion deficits. This technique was applied to the MRIs of 9 stroke patients known to have blood-brain barrier (BBB) disruption on T1 post contrast imaging. Regions of BBB damage were compared with normal tissue from the contralateral hemisphere. Receiver operating characteristic (ROC) analysis was performed to compare the detection of BBB damage before and after ATC. Results ATC improved the area under the curve (AUC) of the ROC from 0.53 to 0.70. The sensitivity improved from 0.51 to 0.67 and the specificity improved from 0.57 to 0.66. Visual inspection of the ROC curve revealed that the performance of the uncorrected analysis was worse than random guess at some thresholds. Conclusions The ability of DSC permeability imaging to identify contrast enhancing tissue in stroke patients improved considerably when an ATC was applied. Using DSC permeability imaging in stroke patients without an ATC may lead to false identification of BBB disruption.