Journal article
Toward fully automated processing of dynamic susceptibility contrast perfusion MRI for acute ischemic cerebral stroke
Computer methods and programs in biomedicine, Vol.98(2), pp.204-213
2010
DOI: 10.1016/j.cmpb.2009.12.005
PMID: 20060614
Abstract
We developed fully automated software for dynamic susceptibility contrast (DSC) MR perfusion-weighted imaging (PWI) to efficiently and reliably derive critical hemodynamic information for acute stroke treatment decisions.
Brain MR PWI was performed in 80 consecutive patients with acute nonlacunar ischemic stroke within 24
h after onset of symptom from January 2008 to August 2009. These studies were automatically processed to generate hemodynamic parameters that included cerebral blood flow and cerebral blood volume, and the mean transit time (MTT). To develop reliable software for PWI analysis, we used computationally robust algorithms including the piecewise continuous regression method to determine bolus arrival time (BAT), log-linear curve fitting, arrival time independent deconvolution method and sophisticated motion correction methods. An optimal arterial input function (AIF) search algorithm using a new artery-likelihood metric was also developed. Anatomical locations of the automatically determined AIF were reviewed and validated. The automatically computed BAT values were statistically compared with estimated BAT by a single observer. In addition, gamma-variate curve-fitting errors of AIF and inter-subject variability of AIFs were analyzed. Lastly, two observes independently assessed the quality and area of hypoperfusion mismatched with restricted diffusion area from motion corrected MTT maps and compared that with time-to-peak (TTP) maps using the standard approach.
The AIF was identified within an arterial branch and enhanced areas of perfusion deficit were visualized in all evaluated cases. Total processing time was 10.9
±
2.5
s (mean
±
s.d.) without motion correction and 267
±
80
s (mean
±
s.d.) with motion correction on a standard personal computer. The MTT map produced with our software adequately estimated brain areas with perfusion deficit and was significantly less affected by random noise of the PWI when compared with the TTP map. Results of image quality assessment by two observers revealed that the MTT maps exhibited superior quality over the TTP maps (88% good rating of MTT as compared to 68% of TTP).
Our software allowed fully automated deconvolution analysis of DSC PWI using proven efficient algorithms that can be applied to acute stroke treatment decisions. Our streamlined method also offers promise for further development of automated quantitative analysis of the ischemic penumbra.
Details
- Title: Subtitle
- Toward fully automated processing of dynamic susceptibility contrast perfusion MRI for acute ischemic cerebral stroke
- Creators
- Jinsuh Kim - Department of Radiology, University of Iowa, 200 Hawkins Dr., Iowa City, IA 52242, United StatesEnrique C Leira - Department of Neurology, University of Iowa, United StatesRichard C Callison - Department of Radiology, University of Iowa, 200 Hawkins Dr., Iowa City, IA 52242, United StatesBryan Ludwig - Department of Radiology, University of Iowa, 200 Hawkins Dr., Iowa City, IA 52242, United StatesToshio Moritani - Department of Radiology, University of Iowa, 200 Hawkins Dr., Iowa City, IA 52242, United StatesVincent A Magnotta - Department of Radiology, University of Iowa, 200 Hawkins Dr., Iowa City, IA 52242, United StatesMark T Madsen - Department of Radiology, University of Iowa, 200 Hawkins Dr., Iowa City, IA 52242, United States
- Resource Type
- Journal article
- Publication Details
- Computer methods and programs in biomedicine, Vol.98(2), pp.204-213
- Publisher
- Elsevier Ireland Ltd
- DOI
- 10.1016/j.cmpb.2009.12.005
- PMID
- 20060614
- ISSN
- 0169-2607
- eISSN
- 1872-7565
- Language
- English
- Date published
- 2010
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Neurology; Radiology; Psychiatry; Epidemiology; Iowa Neuroscience Institute; Neurosurgery
- Record Identifier
- 9984018753002771
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