Automated versus manual post-processing of perfusion-CT data in patients with acute cerebral ischemia: influence on interobserver variability.
BACKGROUND
The purpose of this study is to compare the variability of PCT results obtained by automatic selection of the arterial input function (AIF), venous output function (VOF) and symmetry axis versus manual selection.


METHODS
Imaging data from 30 PCT studies obtained as part of standard clinical stroke care at our institution in patients with suspected acute hemispheric ischemic stroke were retrospectively reviewed. Two observers performed the post-processing of 30 CTP datasets. Each observer processed the data twice, the first time employing manual selection of AIF, VOF and symmetry axis, and a second time using automated selection of these same parameters, with the user being allowed to adjust them whenever deemed appropriate. The volumes of infarct core and of total perfusion defect were recorded. The cerebral blood volume (CBV), cerebral blood flow (CBF), mean transit time (MTT) and blood-brain barrier permeability (BBBP) values in standardized regions of interest were recorded. Interobserver variability was quantified using the Bland and Altman's approach.


RESULTS
Automated post-processing yielded lower coefficients of variation for the volume of the infarct core and the volume of the total perfusion defect (15.7% and 5.8%, respectively) compared to manual post-processing (31.0% and 12.2%, respectively). Automated post-processing yielded lower coefficients of variation for PCT values (11.3% for CBV, 9.7% for CBF, and 9.5% for MTT) compared to manual post-processing (23.7% for CBV, 32.8% for CBF, and 16.7% for MTT).


CONCLUSIONS
Automated post-processing of PCT data improves interobserver agreement in measurements of CBV, CBF and MTT, as well as volume of infarct core and penumbra.
Soares
Bruno P
BP
Department of Radiology, Neuroradiology Section, University of California, 505 Parnassus Avenue, Box 0628, San Francisco, CA 94143-0628, USA.
Dankbaar
Jan Willem
JW
Bredno
Joerg
J
Cheng
SuChun
S
Bhogal
Sumail
S
Dillon
William P
WP
Wintermark
Max
M
D000368:Aged; D000369:Aged, 80 and over; D001810:Blood Volume; D001812:Blood-Brain Barrier / Q000000981:diagnostic imaging / Q000503:physiopathology; D001921:Brain / Q000098:blood supply / Q000000981:diagnostic imaging; D002545:Brain Ischemia / Q000000981:diagnostic imaging* / Q000503:physiopathology; D002199:Capillary Permeability; D002560:Cerebrovascular Circulation; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods* / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D015588:Observer Variation; D055420:Perfusion Imaging / Q000379:methods* / Q000706:statistics & numerical data; D012039:Regional Blood Flow; D012189:Retrospective Studies; D012984:Software; D020521:Stroke / Q000000981:diagnostic imaging / Q000503:physiopathology; D013997:Time Factors; D014057:Tomography, X-Ray Computed / Q000379:methods* / Q000706:statistics & numerical data