European Radiology

, Volume 26, Issue 11, pp 4204–4212 | Cite as

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

  • Lars-Arne SchaafsEmail author
  • David Porter
  • Heinrich J. Audebert
  • Jochen B. Fiebach
  • Kersten Villringer



Perfusion imaging (PI) is susceptible to confounding factors such as motion artefacts as well as delay and dispersion (D/D). We evaluate the influence of different post-processing algorithms on hypoperfusion assessment in PI analysis software packages to improve the clinical accuracy of stroke PI.


Fifty patients with acute ischaemic stroke underwent MRI imaging in the first 24 h after onset. Diverging approaches to motion and D/D correction were applied. The calculated MTT and CBF perfusion maps were assessed by volumetry of lesions and tested for agreement with a standard approach and with the final lesion volume (FLV) on day 6 in patients with persisting vessel occlusion.


MTT map lesion volumes were significantly smaller throughout the software packages with correction of motion and D/D when compared to the commonly used approach with no correction (p = 0.001–0.022). Volumes on CBF maps did not differ significantly (p = 0.207–0.925). All packages with advanced post-processing algorithms showed a high level of agreement with FLV (ICC = 0.704–0.879).


Correction of D/D had a significant influence on estimated lesion volumes and leads to significantly smaller lesion volumes on MTT maps. This may improve patient selection.

Key Points

Assessment on hypoperfusion using advanced post-processing with correction for motion and D/D.

CBF appears to be more robust regarding differences in post-processing.

Tissue at risk is estimated more accurately by correcting software algorithms.

Advanced post-processing algorithms show a higher agreement with the final lesion volume.


MRI Perfusion Stroke Software Image processing 



arterial input function


cerebral blood flow


singular value decomposition with a block-circulant matrix


delay and dispersion


final lesion volume


intraclass correlation coefficient


mean transit time


singular value decomposition


standard truncated singular value decomposition



The scientific guarantor of this publication is PD Dr. Jochen Fiebach. Jochen B. Fiebach reports receiving consulting, lecture and advisory board fees from BMS, Siemens, Perceptive, Synarc, BioImaging Technologies, Novartis, Wyeth, Pfizer, Boehringer Ingelheim, Lundbeck and Sygnis. This study received funding from the Federal Ministry of Education and Research via the Center for Stroke Research Berlin grant (01EO0801 and 01EO01301). One of the authors has significant statistical expertise. Institutional Review Board approval was obtained. Written informed consent was obtained from all subjects (patients) in this study. Methodology: prospective and retrospective, observational, performed at one institution. Parts of this study are included in the medical thesis of Lars-Arne Schaafs.


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Copyright information

© European Society of Radiology 2016

Authors and Affiliations

  1. 1.Department of RadiologyCharité-UniversitätsmedizinBerlinGermany
  2. 2.Academic Neuroradiology, Department of Neurology and Center for Stroke ResearchCharité-UniversitätsmedizinBerlinGermany
  3. 3.Fraunhofer Institute for Medical Image Computing MEVISBremenGermany
  4. 4.Department of Neurology with Experimental NeurologyCharité-UniversitätsmedizinBerlinGermany

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