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The combination of baseline magnetic resonance perfusion-weighted imaging-derived tissue volume with severely prolonged arterial-tissue delay and diffusion-weighted imaging lesion volume is predictive of MCA-M1 recanalization in patients treated with endovascular thrombectomy
INTRODUCTION: Indices of collateral flow deficit derived from MR perfusion imaging that are predictive of MCA-M1 recanalization after intravenous thrombolysis have been recently reported. Our objective was to test the performance of such MRI-derived collateral flow indices for prediction of recanali...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3913850/ https://www.ncbi.nlm.nih.gov/pubmed/24337610 http://dx.doi.org/10.1007/s00234-013-1310-2 |
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author | Nicoli, F. Scalzo, F. Saver, J. L. Pautot, F. Mitulescu, A. Chaibi, Y. Girard, N. Salamon, N. Liebeskind, D. S. |
author_facet | Nicoli, F. Scalzo, F. Saver, J. L. Pautot, F. Mitulescu, A. Chaibi, Y. Girard, N. Salamon, N. Liebeskind, D. S. |
author_sort | Nicoli, F. |
collection | PubMed |
description | INTRODUCTION: Indices of collateral flow deficit derived from MR perfusion imaging that are predictive of MCA-M1 recanalization after intravenous thrombolysis have been recently reported. Our objective was to test the performance of such MRI-derived collateral flow indices for prediction of recanalization after endovascular thrombectomy. METHODS: Fifty-seven patients with MCA-M1 occlusion evaluated with multimodal MRI prior to thrombectomy were included. Bayesian processing allowed quantification of collateral perfusion indices like the volume of tissue with severely prolonged arterial-tissue delay (>6 s) (VolATD6). Baseline DWI lesion volume was also measured. Correlations with angiographic collateral flow grading and post-thrombectomy recanalization were assessed. RESULTS: VolATD6 < 27 ml or DWI lesion volume <15 ml provide the most accurate diagnosis of excellent collateral supply (p < 0.0001). The combination of VolATD6 > 27 ml and DWI lesion volume >15 ml significantly discriminates recanalizers versus nonrecanalizers (whole cohort, p = 0.032; MERCI cohort (n = 50), p = 0.024). When both criteria are positive, 76.2 % of the patients treated with the MERCI retriever do not fully recanalize (p = 0.024). In multivariate analysis, the aforementioned combined criterion and the angiographic collateral grade are the only independent predictors of recanalization with the MERCI retriever (p = 0.015 and 0.029, respectively). CONCLUSION: Bayesian arterial-tissue delay maps and DWI maps provide a non-invasive assessment of the degree of collateral flow and a combined index that is predictive of MCA-M1 recanalization after endovascular thrombectomy. Further studies are needed to evaluate the accuracy of this index in patients treated with novel stent retriever devices. |
format | Online Article Text |
id | pubmed-3913850 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-39138502014-02-10 The combination of baseline magnetic resonance perfusion-weighted imaging-derived tissue volume with severely prolonged arterial-tissue delay and diffusion-weighted imaging lesion volume is predictive of MCA-M1 recanalization in patients treated with endovascular thrombectomy Nicoli, F. Scalzo, F. Saver, J. L. Pautot, F. Mitulescu, A. Chaibi, Y. Girard, N. Salamon, N. Liebeskind, D. S. Neuroradiology Diagnostic Neuroradiology INTRODUCTION: Indices of collateral flow deficit derived from MR perfusion imaging that are predictive of MCA-M1 recanalization after intravenous thrombolysis have been recently reported. Our objective was to test the performance of such MRI-derived collateral flow indices for prediction of recanalization after endovascular thrombectomy. METHODS: Fifty-seven patients with MCA-M1 occlusion evaluated with multimodal MRI prior to thrombectomy were included. Bayesian processing allowed quantification of collateral perfusion indices like the volume of tissue with severely prolonged arterial-tissue delay (>6 s) (VolATD6). Baseline DWI lesion volume was also measured. Correlations with angiographic collateral flow grading and post-thrombectomy recanalization were assessed. RESULTS: VolATD6 < 27 ml or DWI lesion volume <15 ml provide the most accurate diagnosis of excellent collateral supply (p < 0.0001). The combination of VolATD6 > 27 ml and DWI lesion volume >15 ml significantly discriminates recanalizers versus nonrecanalizers (whole cohort, p = 0.032; MERCI cohort (n = 50), p = 0.024). When both criteria are positive, 76.2 % of the patients treated with the MERCI retriever do not fully recanalize (p = 0.024). In multivariate analysis, the aforementioned combined criterion and the angiographic collateral grade are the only independent predictors of recanalization with the MERCI retriever (p = 0.015 and 0.029, respectively). CONCLUSION: Bayesian arterial-tissue delay maps and DWI maps provide a non-invasive assessment of the degree of collateral flow and a combined index that is predictive of MCA-M1 recanalization after endovascular thrombectomy. Further studies are needed to evaluate the accuracy of this index in patients treated with novel stent retriever devices. Springer Berlin Heidelberg 2013-12-15 2014 /pmc/articles/PMC3913850/ /pubmed/24337610 http://dx.doi.org/10.1007/s00234-013-1310-2 Text en © The Author(s) 2013 https://creativecommons.org/licenses/by/2.0/ Open Access This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. |
spellingShingle | Diagnostic Neuroradiology Nicoli, F. Scalzo, F. Saver, J. L. Pautot, F. Mitulescu, A. Chaibi, Y. Girard, N. Salamon, N. Liebeskind, D. S. The combination of baseline magnetic resonance perfusion-weighted imaging-derived tissue volume with severely prolonged arterial-tissue delay and diffusion-weighted imaging lesion volume is predictive of MCA-M1 recanalization in patients treated with endovascular thrombectomy |
title | The combination of baseline magnetic resonance perfusion-weighted imaging-derived tissue volume with severely prolonged arterial-tissue delay and diffusion-weighted imaging lesion volume is predictive of MCA-M1 recanalization in patients treated with endovascular thrombectomy |
title_full | The combination of baseline magnetic resonance perfusion-weighted imaging-derived tissue volume with severely prolonged arterial-tissue delay and diffusion-weighted imaging lesion volume is predictive of MCA-M1 recanalization in patients treated with endovascular thrombectomy |
title_fullStr | The combination of baseline magnetic resonance perfusion-weighted imaging-derived tissue volume with severely prolonged arterial-tissue delay and diffusion-weighted imaging lesion volume is predictive of MCA-M1 recanalization in patients treated with endovascular thrombectomy |
title_full_unstemmed | The combination of baseline magnetic resonance perfusion-weighted imaging-derived tissue volume with severely prolonged arterial-tissue delay and diffusion-weighted imaging lesion volume is predictive of MCA-M1 recanalization in patients treated with endovascular thrombectomy |
title_short | The combination of baseline magnetic resonance perfusion-weighted imaging-derived tissue volume with severely prolonged arterial-tissue delay and diffusion-weighted imaging lesion volume is predictive of MCA-M1 recanalization in patients treated with endovascular thrombectomy |
title_sort | combination of baseline magnetic resonance perfusion-weighted imaging-derived tissue volume with severely prolonged arterial-tissue delay and diffusion-weighted imaging lesion volume is predictive of mca-m1 recanalization in patients treated with endovascular thrombectomy |
topic | Diagnostic Neuroradiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3913850/ https://www.ncbi.nlm.nih.gov/pubmed/24337610 http://dx.doi.org/10.1007/s00234-013-1310-2 |
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