Literature DB >> 20075362

Impact of baseline tissue status (diffusion-weighted imaging lesion) versus perfusion status (severity of hypoperfusion) on hemorrhagic transformation.

Jong Hun Kim1, Oh Young Bang, David S Liebeskind, Bruce Ovbiagele, Gyeong-Moon Kim, Chin Sang Chung, Kwang Ho Lee, Jeffrey L Saver.   

Abstract

BACKGROUND AND
PURPOSE: The frequency of hemorrhagic transformation (HT) on gradient echo imaging and its impact on stroke outcomes continues to be debated. We investigated the factors associated with HTs and the influence of the HTs observed on gradient echo imaging on the early course after a stroke.
METHODS: We analyzed the data from a prospectively maintained registry of patients who were eligible for recanalization therapy. Serial diffusion-weighted imaging and perfusion-weighted imaging were performed, and HTs were assessed on follow-up gradient echo imaging. Tmax perfusion lesion maps were generated and hypoperfused regions were divided into severe (Tmax >or=8 seconds) delay and mild (Tmax >or=2 seconds but Tmax <8 seconds) delay. The factors associated with HTs, including the mode of recanalization therapy, pretreatment diffusion-weighted imaging and perfusion-weighted imaging lesion volumes, and reperfusion indices, were evaluated. The early clinical outcome was assessed during the first 7 days of admission.
RESULTS: A total of 184 patients were included in this study. HTs were noted in 73 (39.7%) patients. Multiple logistic regression analysis identified aggressive treatment (OR, 5.12; 95% CI, 1.73 to 15.18) and a large area of severe perfusion delay (OR for highest quartile of Tmax >8 seconds, 12.91; 95% CI, 3.69 to 45.17) as independent predictors of HTs. Neither risk factor profiles nor diffusion-weighted imaging lesion volumes were associated with HTs. There was a poor correlation between the radiological (HT types) and clinical (asymptomatic or symptomatic) categories of HTs. Even a parenchymal hematoma was not always associated with symptomatic worsening or affected the early clinical outcomes.
CONCLUSIONS: The results of this study indicate that the perfusion status (severe perfusion delay) rather than the tissue status (diffusion-weighted imaging lesions) and aggressive treatment were independently associated with HTs. HT on gradient echo imaging was common but usually associated with severe hypoperfusion and not always associated with clinical deterioration.

Entities:  

Mesh:

Year:  2010        PMID: 20075362     DOI: 10.1161/STROKEAHA.109.563122

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


  15 in total

Review 1.  Physiologic imaging in acute stroke: Patient selection.

Authors:  Clinton D Morgan; Marcus Stephens; Scott L Zuckerman; Magarya S Waitara; Peter J Morone; Michael C Dewan; J Mocco
Journal:  Interv Neuroradiol       Date:  2015-06-10       Impact factor: 1.610

2.  Reperfusion of very low cerebral blood volume lesion predicts parenchymal hematoma after endovascular therapy.

Authors:  Nishant K Mishra; Søren Christensen; Anke Wouters; Bruce C V Campbell; Matus Straka; Michael Mlynash; Stephanie Kemp; Carlo W Cereda; Roland Bammer; Michael P Marks; Gregory W Albers; Maarten G Lansberg
Journal:  Stroke       Date:  2015-03-31       Impact factor: 7.914

3.  Refining the definition of the malignant profile: insights from the DEFUSE-EPITHET pooled data set.

Authors:  Michael Mlynash; Maarten G Lansberg; Deidre A De Silva; Jun Lee; Soren Christensen; Matus Straka; Bruce C V Campbell; Roland Bammer; Jean-Marc Olivot; Patricia Desmond; Geoffrey A Donnan; Stephen M Davis; Gregory W Albers
Journal:  Stroke       Date:  2011-04-07       Impact factor: 7.914

4.  Severe cerebral hypovolemia on perfusion CT and lower body weight are associated with parenchymal haemorrhage after thrombolysis.

Authors:  S Tsetsou; M Amiguet; A Eskandari; R Meuli; P Maeder; B Jiang; M Wintermark; P Michel
Journal:  Neuroradiology       Date:  2016-12-27       Impact factor: 2.804

5.  MRI blood-brain barrier permeability measurements to predict hemorrhagic transformation in a rat model of ischemic stroke.

Authors:  Angelika Hoffmann; Jörg Bredno; Michael F Wendland; Nikita Derugin; Jason Hom; Tibor Schuster; Claus Zimmer; Hua Su; Peter T Ohara; William L Young; Max Wintermark
Journal:  Transl Stroke Res       Date:  2012-09-16       Impact factor: 6.829

6.  Advanced imaging improves prediction of hemorrhage after stroke thrombolysis.

Authors:  Bruce C V Campbell; Søren Christensen; Mark W Parsons; Leonid Churilov; Patricia M Desmond; P Alan Barber; Kenneth S Butcher; Christopher R Levi; Deidre A De Silva; Maarten G Lansberg; Michael Mlynash; Jean-Marc Olivot; Matus Straka; Roland Bammer; Gregory W Albers; Geoffrey A Donnan; Stephen M Davis
Journal:  Ann Neurol       Date:  2013-02-26       Impact factor: 10.422

7.  Worse stroke outcome in atrial fibrillation is explained by more severe hypoperfusion, infarct growth, and hemorrhagic transformation.

Authors:  Hans T H Tu; Bruce C V Campbell; Soren Christensen; Patricia M Desmond; Deidre A De Silva; Mark W Parsons; Leonid Churilov; Maarten G Lansberg; Michael Mlynash; Jean-Marc Olivot; Matus Straka; Roland Bammer; Gregory W Albers; Geoffrey A Donnan; Stephen M Davis
Journal:  Int J Stroke       Date:  2013-03-12       Impact factor: 5.266

8.  Automated core-penumbra quantification in neonatal ischemic brain injury.

Authors:  Nirmalya Ghosh; Xiangpeng Yuan; Christine I Turenius; Beatriz Tone; Kamalakar Ambadipudi; Evan Y Snyder; Andre Obenaus; Stephen Ashwal
Journal:  J Cereb Blood Flow Metab       Date:  2012-08-29       Impact factor: 6.200

9.  Radiological predictors of hemorrhagic transformation after acute ischemic stroke: An evidence-based analysis.

Authors:  Nada Elsaid; Wessam Mustafa; Ahmed Saied
Journal:  Neuroradiol J       Date:  2020-01-23

10.  Validation of hyperintense middle cerebral artery sign in acute ischemic stroke: Comparison between magnetic resonance imaging and angiography.

Authors:  Gang Guo; Yonggui Yang; Weiqun Yang
Journal:  Neural Regen Res       Date:  2012-01-25       Impact factor: 5.135

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