Literature DB >> 19017923

Prediction of infarct growth based on apparent diffusion coefficients: penumbral assessment without intravenous contrast material.

Charlotte Rosso1, Nidiyare Hevia-Montiel, Sandrine Deltour, Eric Bardinet, Didier Dormont, Sophie Crozier, Sylvain Baillet, Yves Samson.   

Abstract

PURPOSE: To compare predicted and final infarct lesion volumes determined by processing apparent diffusion coefficient (ADC) maps derived at admission diffusion-weighted (DW) magnetic resonance (MR) imaging in patients with acute stroke and to verify that predicted areas of infarct growth reflect at-risk penumbral regions based on recanalization status.
MATERIALS AND METHODS: The French legislation waived the requirement for informed patient consent for the described research, which was based on patient medical files. However, patients and/or their relatives were informed that they could decline to participate in the research. Authors tested a semiautomated proprietary image analysis procedure in 98 patients with middle cerebral artery (MCA) stroke by modeling infarct growth on DW imaging-derived ADC maps. Predicted infarct growth (PIG) areas and predicted infarct volumes were correlated with final observed data. In addition, the effect of MCA recanalization on the correlation between predicted and observed infarct growth volumes was qualitatively assessed.
RESULTS: Predicted and final infarct volumes (rho = 0.828; 95% confidence interval [CI]: 0.753, 0.882; P < .0001) and infarct growth volumes (rho = 0.506; 95% CI: 0.342, 0.640; P < .0001) were significantly correlated. Visual comparative examination revealed satisfactory qualitative consistency between predicted and follow-up lesion masks. In patients without MCA recanalization, PIG did not differ significantly from final observed infarct growth (median PIG obtained with 0.93 ADC ratio cutoff [PIG(ratio)] of 27.1 cm(3) vs median infarct growth of 19.8 cm(3), P = .17). MCA recanalization revealed an overestimation of PIG (median PIG(ratio) of 24.8 cm(3) vs median infarct growth of 12 cm(3), P = .005), suggesting that the PIG area was part of ischemic penumbra.
CONCLUSION: Data show the feasibility of identifying at-risk ischemic tissue in patients with acute MCA stroke by using semiautomated analysis of ADC maps derived at DW imaging, without intravenous contrast material-enhanced perfusion-weighted imaging. (c) RSNA, 2008.

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Year:  2008        PMID: 19017923     DOI: 10.1148/radiol.2493080107

Source DB:  PubMed          Journal:  Radiology        ISSN: 0033-8419            Impact factor:   11.105


  16 in total

Review 1.  Clinical MRI of acute ischemic stroke.

Authors:  R Gilberto González
Journal:  J Magn Reson Imaging       Date:  2012-08       Impact factor: 4.813

2.  Sustained diffusion reversal with in-bore reperfusion in monkey stroke models: Confirmed by prospective magnetic resonance imaging.

Authors:  Kyung Sik Yi; Chi-Hoon Choi; Sang-Rae Lee; Hong Jun Lee; Youngjeon Lee; Kang-Jin Jeong; Jinwoo Hwang; Kyu-Tae Chang; Sang-Hoon Cha
Journal:  J Cereb Blood Flow Metab       Date:  2016-01-01       Impact factor: 6.200

3.  The hemodynamic status within 24 h after intravenous thrombolysis predicts infarct growth in acute ischemic stroke.

Authors:  José Fidel Baizabal-Carvallo; Charlotte Rosso; Marlene Alonso-Juarez; Christine Pires; Yves Samson
Journal:  J Neurol       Date:  2011-11-05       Impact factor: 4.849

4.  Hyperglycemia and the fate of apparent diffusion coefficient-defined ischemic penumbra.

Authors:  C Rosso; Y Attal; S Deltour; N Hevia-Montiel; S Lehéricy; S Crozier; D Dormont; S Baillet; Y Samson
Journal:  AJNR Am J Neuroradiol       Date:  2011-03-31       Impact factor: 3.825

5.  Tissue at risk in the deep middle cerebral artery territory is critical to stroke outcome.

Authors:  Charlotte Rosso; Olivier Colliot; Romain Valabrègue; Sophie Crozier; Didier Dormont; Stéphane Lehéricy; Yves Samson
Journal:  Neuroradiology       Date:  2011-07-26       Impact factor: 2.804

Review 6.  Use of magnetic resonance imaging to predict outcome after stroke: a review of experimental and clinical evidence.

Authors:  Tracy D Farr; Susanne Wegener
Journal:  J Cereb Blood Flow Metab       Date:  2010-01-20       Impact factor: 6.200

7.  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

8.  Geography, structure, and evolution of diffusion and perfusion lesions in Diffusion and perfusion imaging Evaluation For Understanding Stroke Evolution (DEFUSE).

Authors:  Jean-Marc Olivot; Michael Mlynash; Vincent N Thijs; Archana Purushotham; Stephanie Kemp; Maarten G Lansberg; Lawrence Wechsler; Garry E Gold; Roland Bammer; Michael P Marks; Gregory W Albers
Journal:  Stroke       Date:  2009-08-13       Impact factor: 7.914

Review 9.  Diffusion MRI at 25: exploring brain tissue structure and function.

Authors:  Denis Le Bihan; Heidi Johansen-Berg
Journal:  Neuroimage       Date:  2011-11-20       Impact factor: 6.556

10.  Prominent vessel sign on susceptibility-weighted imaging in acute stroke: prediction of infarct growth and clinical outcome.

Authors:  Chia-Yuen Chen; Chin-I Chen; Fong Y Tsai; Ping-Huei Tsai; Wing P Chan
Journal:  PLoS One       Date:  2015-06-25       Impact factor: 3.240

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