Literature DB >> 20413735

The physiological significance of the time-to-maximum (Tmax) parameter in perfusion MRI.

Fernando Calamante1, Søren Christensen, Patricia M Desmond, Leif Ostergaard, Stephen M Davis, Alan Connelly.   

Abstract

BACKGROUND AND
PURPOSE: Many perfusion-related MRI parameters are used to investigate the penumbra in stroke. Although time-to-maximum (Tmax) of the residue function has been suggested as a very promising parameter, its physiological meaning and sensitivity to experimental conditions are not well-understood.
METHODS: We used simulations to further our understanding of the practical meaning of Tmax and to provide recommendations for its use in clinical investigations. We interpret in vivo examples guided by the simulation findings.
RESULTS: Whereas Tmax has several attractive properties for clinical use, it is shown that its physiological interpretation is complex and affected by experimental conditions. Tmax is found to reflect a combination of delay, dispersion, and, to a lesser degree, mean transit time. It should therefore mainly be considered a measure of macrovascular characteristics. Furthermore, based on the simulations, use of temporal-interpolation is highly recommended, as is correction for slice-acquisition timing differences.
CONCLUSIONS: Special care should be taken when setting-up Tmax thresholds for data acquired with different protocols (eg, multicenter studies) because various factors can influence the measured Tmax. Because of its complementary information, used in conjunction with delay-insensitive cerebral blood-flow, cerebral blood volume, and mean transit time maps, Tmax should provide important additional information on brain hemodynamic status.

Entities:  

Mesh:

Year:  2010        PMID: 20413735     DOI: 10.1161/STROKEAHA.110.580670

Source DB:  PubMed          Journal:  Stroke        ISSN: 0039-2499            Impact factor:   7.914


  56 in total

Review 1.  The alphabet soup of perfusion CT and MR imaging: terminology revisited and clarified in five questions.

Authors:  Carlos Leiva-Salinas; James M Provenzale; Kohsuke Kudo; Makoto Sasaki; Max Wintermark
Journal:  Neuroradiology       Date:  2012-04-10       Impact factor: 2.804

2.  Susceptibility of Tmax to tracer delay on perfusion analysis: quantitative evaluation of various deconvolution algorithms using digital phantoms.

Authors:  Kohsuke Kudo; Makoto Sasaki; Leif Østergaard; Soren Christensen; Ikuko Uwano; Masako Suzuki; Kuniaki Ogasawara; Hiroki Shirato; Akira Ogawa
Journal:  J Cereb Blood Flow Metab       Date:  2010-09-22       Impact factor: 6.200

3.  Predicting ischemic stroke tissue fate using a deep convolutional neural network on source magnetic resonance perfusion images.

Authors:  King Chung Ho; Fabien Scalzo; Karthik V Sarma; William Speier; Suzie El-Saden; Corey Arnold
Journal:  J Med Imaging (Bellingham)       Date:  2019-05-22

4.  Regional prediction of tissue fate in acute ischemic stroke.

Authors:  Fabien Scalzo; Qing Hao; Jeffry R Alger; Xiao Hu; David S Liebeskind
Journal:  Ann Biomed Eng       Date:  2012-05-17       Impact factor: 3.934

5.  Validating a local Arterial Input Function method for improved perfusion quantification in stroke.

Authors:  Lisa Willats; Soren Christensen; Henry K Ma; Geoffrey A Donnan; Alan Connelly; Fernando Calamante
Journal:  J Cereb Blood Flow Metab       Date:  2011-06-01       Impact factor: 6.200

6.  Multimodal imaging in acute ischemic stroke.

Authors:  William A Copen
Journal:  Curr Treat Options Cardiovasc Med       Date:  2015-03

7.  Increased volumes of mildly elevated capillary transit time heterogeneity positively predict favorable outcome and negatively predict intracranial hemorrhage in acute ischemic stroke with large vessel occlusion.

Authors:  A Potreck; S Loebel; J Pfaff; L Østergaard; K Mouridsen; A Radbruch; M Bendszus; S Mundiyanapurath
Journal:  Eur Radiol       Date:  2019-03-18       Impact factor: 5.315

8.  Quantitative accuracy of computed tomography perfusion under low-dose conditions, measured using a hollow-fiber phantom.

Authors:  Kazufumi Suzuki; Hiroyuki Hashimoto; Eiji Okaniwa; Hiroshi Iimura; Shingo Suzaki; Kayoko Abe; Shuji Sakai
Journal:  Jpn J Radiol       Date:  2017-04-27       Impact factor: 2.374

9.  Accuracy and reliability assessment of CT and MR perfusion analysis software using a digital phantom.

Authors:  Kohsuke Kudo; Soren Christensen; Makoto Sasaki; Leif Østergaard; Hiroki Shirato; Kuniaki Ogasawara; Max Wintermark; Steven Warach
Journal:  Radiology       Date:  2012-12-06       Impact factor: 11.105

10.  Reliable estimation of capillary transit time distributions using DSC-MRI.

Authors:  Kim Mouridsen; Mikkel Bo Hansen; Leif Østergaard; Sune Nørhøj Jespersen
Journal:  J Cereb Blood Flow Metab       Date:  2014-06-18       Impact factor: 6.200

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