Literature DB >> 21346342

Fully automated postprocessing carries a risk of substantial overestimation of perfusion deficits in acute stroke magnetic resonance imaging.

Ivana Galinovic1, Peter Brunecker, Ann-Christin Ostwaldt, Carina Soemmer, Benjamin Hotter, Jochen B Fiebach.   

Abstract

BACKGROUND AND
PURPOSE: Due to the risk of rater bias and time restrictions in clinical practice, an automated approach to delineation of hypoperfused tissue in patients with acute ischemic stroke would be preferred to a manual one. We tested the hypothesis that existing software solutions, on account of numerous artifacts, produce hypoperfused tissue even in a cohort of patients with no ischemia.
METHODS: Thirty-nine patients, all admitted for exclusion of cerebral ischemia or hemorrhage and without a final diagnosis of stroke imaged between September 2008 and May 2009 were included in the study. Using 3 different software packages (PerfScape/NeuroScape, PMA and Stroketool), perfusion maps of mean transit time, cerebral blood flow and T(max) were created for each patient. Three different thresholds were applied to each parameter map, and subsequent volumes of hypoperfused tissue were calculated.
RESULTS: The median volume of hypoperfused tissue for all the subjects was 92.9 ml (interquartile range, IQR: 13.3-323.4 ml) when calculated by PerfScape/NeuroScape, 30.42 ml (IQR: 13.9-71.4 ml) when calculated by PMA and 78.71 ml (IQR: 40.3-140.8 ml) when calculated by Stroketool. The volumes derived via the different software applications mostly showed only a weak-to-moderate association with each other (Spearman's correlation coefficient between 0.02 and 0.76).
CONCLUSIONS: Although automated protocols show promise, the programs Stroketool, PerfScape and PMA require substantial improvement in order to be able to automatically and reliably differentiate between patients with a credible region of ischemia-related hypoperfusion and those without.
Copyright © 2011 S. Karger AG, Basel.

Entities:  

Mesh:

Year:  2011        PMID: 21346342     DOI: 10.1159/000323212

Source DB:  PubMed          Journal:  Cerebrovasc Dis        ISSN: 1015-9770            Impact factor:   2.762


  6 in total

1.  Statistical properties of cerebral CT perfusion imaging systems. Part I. Cerebral blood volume maps generated from nondeconvolution-based systems.

Authors:  Ke Li; Charles M Strother; Guang-Hong Chen
Journal:  Med Phys       Date:  2019-09-20       Impact factor: 4.071

2.  Optimising MR perfusion imaging: comparison of different software-based approaches in acute ischaemic stroke.

Authors:  Lars-Arne Schaafs; David Porter; Heinrich J Audebert; Jochen B Fiebach; Kersten Villringer
Journal:  Eur Radiol       Date:  2016-02-06       Impact factor: 5.315

Review 3.  Refining the mismatch concept in acute stroke: lessons learned from PET and MRI.

Authors:  Jan Sobesky
Journal:  J Cereb Blood Flow Metab       Date:  2012-04-18       Impact factor: 6.200

4.  Comparison of perfusion- and diffusion-weighted imaging parameters in brain tumor studies processed using different software platforms.

Authors:  Mikhail V Milchenko; Dhanashree Rajderkar; Pamela LaMontagne; Parinaz Massoumzadeh; Ronald Bogdasarian; Gordon Schweitzer; Tammie Benzinger; Dan Marcus; Joshua S Shimony; Sarah Jost Fouke
Journal:  Acad Radiol       Date:  2014-08-01       Impact factor: 3.173

5.  Automated vs manual delineations of regions of interest- a comparison in commercially available perfusion MRI software.

Authors:  Ivana Galinovic; Ann-Christin Ostwaldt; Carina Soemmer; Helena Bros; Benjamin Hotter; Peter Brunecker; Jochen B Fiebach
Journal:  BMC Med Imaging       Date:  2012-07-18       Impact factor: 1.930

6.  MRI software for diffusion-perfusion mismatch analysis may impact on patients' selection and clinical outcome.

Authors:  Silvia Pistocchi; Davide Strambo; Bruno Bartolini; Philippe Maeder; Reto Meuli; Patrik Michel; Vincent Dunet
Journal:  Eur Radiol       Date:  2021-08-05       Impact factor: 5.315

  6 in total

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