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Logo of bmcmiBioMed Centralsearchsubmit a manuscriptregisterthis articleBMC Medical Imaging
 
BMC Med Imaging. 2012; 12: 16.
Published online 2012 July 18. doi:  10.1186/1471-2342-12-16
PMCID: PMC3423015
Automated vs manual delineations of regions of interest- a comparison in commercially available perfusion MRI software
Ivana Galinovic,corresponding author1 Ann-Christin Ostwaldt,2 Carina Soemmer,3 Helena Bros,1 Benjamin Hotter,1 Peter Brunecker,1 and Jochen B Fiebach1
1Center for Stroke Research Berlin, Charité-Universitätsmedizin Berlin, Campus Benjamin Franklin, Hindenburgdamm 30, 12200, Berlin, Germany
2International Graduate Program Medical Neurosciences, Charite-Universitätsmedizin, Berlin, Luisenstrasse 56, 10117, Berlin, Germany
3Charité-Universitätsmedizin, Berlin, Charitéplatz 1, 10117, Berlin, Germany
corresponding authorCorresponding author.
Ivana Galinovic: ivana.galinovic/at/charite.de; Ann-Christin Ostwaldt: ac.ostwaldt/at/googlemail.com; Carina Soemmer: carina.soemmer/at/charite.de; Helena Bros: hnbros/at/gmail.com; Benjamin Hotter: benjamin.hotter/at/charite.de; Peter Brunecker: peter.brunecker/at/charite.de; Jochen B Fiebach: peter.brunecker/at/charite.de
Received August 24, 2011; Accepted May 21, 2012.
Abstract
Background
In perfusion magnetic resonance imaging a manual approach to delineation of regions of interest is, due to rater bias and time intensive operator input, clinically less favorable than an automated approach would be. The goal of our study was to compare the performances of these approaches.
Methods
Using Stroketool, PMA and Perfscape/Neuroscape perfusion maps of cerebral blood flow, mean transit time and Tmax were created for 145 patients with acute ischemic stroke. Volumes of hypoperfused tissue were calculated using both a manual and an automated protocol, and the results compared between methods.
Results
The median difference between the automatically and manually derived volumes was up to 210 ml in Perfscape/Neuroscape, 123 ml in PMA and 135 ml in Stroketool. Correlation coefficients between perfusion volumes and radiological and clinical outcome were much lower for the automatic volumes than for the manually derived ones.
Conclusions
The agreement of the two methods was very poor, with the automated use producing falsely exaggerated volumes of hypoperfused tissue. Software improvements are necessary to enable highly automated protocols to credibly assess perfusion deficits.
Keywords: Magnetic resonance imaging, Perfusion MRI, Acute ischemic stroke
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