Which MR-derived perfusion parameters are the best predictors of infarct growth in hyperacute stroke? Comparative study between relative and quantitative measurements.
OBJECTIVE
To compare predictors of infarct growth in hyperacute stroke from a retrospective review of various relative and quantitative parameters calculated at perfusion-weighted magnetic resonance (MR) imaging performed within 6 hours after ictus.


METHODS
Fluid-attenuated inversion recovery and diffusion- and perfusion-weighted images were obtained in 66 patients. The initial infarct was delineated on diffusion-weighted images; the hemodynamic disturbance, on apparent mean transit time (MTT) maps; and the final infarct, on follow-up fluid-attenuated inversion recovery images. Relative (without and with deconvolution) and quantitative values of the bolus arrival time, time to peak (TTP), apparent MTT or MTT, cerebral blood volume (CBV), peak height, and cerebral blood flow (CBF) index or CBF were calculated for initial infarct, infarct growth (final minus initial infarct contour), viable hemodynamic disturbance (apparent MTT minus final infarct contour), and contralateral mirror regions. Univariate and multivariate analyses (receiver operating characteristic curves and discriminant analysis) were performed to compare the diagnostic performance of these parameters for predicting infarct growth.


RESULTS
At univariate analysis, relative peak height and quantitative CBF were the best predictors of infarct growth; at multivariate analysis, a function of peak height and TTP for relative measurements and CBF alone for quantitative measurements. Quantitative and relative measurements (without or with deconvolution) worked equally well. A combined relative peak height or TTP threshold (<54% or >5.2 seconds, respectively) had a sensitivity of 71% and a specificity of 98%. A quantitative CBF threshold (<35 mL/min/100 g) had a sensitivity of 69% and a specificity of 85%.


CONCLUSIONS
A combination of relative peak height and TTP measurements allowed the best prediction of infarct growth, which obviates more complex quantitative calculation.
Grandin
Cécile B
CB
Department of Medical Imaging, MRI Section, Cliniques Universitaires St Luc, Université Catholique de Louvain, 10 Avenue Hippocrate, B-1200 Brussels, Belgium. grandin@rdgn.ucl.ac.be
Duprez
Thierry P
TP
Smith
Anne M
AM
Oppenheim
Catherine
C
Peeters
André
A
Robert
Annie R
AR
Cosnard
Guy
G
D000208:Acute Disease; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000704:Analysis of Variance; D001783:Blood Flow Velocity; D002560:Cerebrovascular Circulation; D016002:Discriminant Analysis; D018450:Disease Progression; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D012372:ROC Curve; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D020521:Stroke / Q000175:diagnosis / Q000503:physiopathology*