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Panni P, Lapergue B, Maïer B, Finitsis S, Clarençon F, Richard S, Marnat G, Bourcier R, Sibon I, Dargazanli C, Blanc R, Consoli A, Eugène F, Vannier S, Spelle L, Denier C, Boulanger M, Gauberti M, Saleme S, Macian F, Rosso C, Naggara O, Turc G, Ozkul-Wermester O, Papagiannaki C, Albucher JF, Darcourt J, Le Bras A, Evain S, Wolff V, Pop R, Timsit S, Gentric JC, Bourdain F, Veunac L, Arquizan C, Gory B. Clinical Impact and Predictors of Diffusion Weighted Imaging (DWI) Reversal in Stroke Patients with Diffusion Weighted Imaging Alberta Stroke Program Early CT Score 0-5 Treated by Thrombectomy : Diffusion Weighted Imaging Reversal in Large Volume Stroke. Clin Neuroradiol 2022; 32:939-950. [PMID: 35412044 DOI: 10.1007/s00062-022-01156-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Accepted: 03/02/2022] [Indexed: 12/15/2022]
Abstract
PURPOSE To determine whether reversal of DWI lesions (DWIr) on the DWI-ASPECTS (diffusion weighted imaging Alberta Stroke Program CT Score) template should serve as a predictor of 90-day clinical outcome in acute ischemic stroke (AIS) patients with pretreatment diffusion-weighted imaging (DWI)-ASPECTS 0-5 treated with thrombectomy, and to determine its predictors in current practice. METHODS We analyzed data of all consecutive patients included in the prospective multicenter national Endovascular Treatment in Ischemic Stroke Registry between 1 January 2015 and 31 December 2020 with a premorbid mRS ≤ 2, who presented with a pretreatment DWI-ASPECTS 0-5 score, underwent thrombectomy and had an available 24 h post-interventional MRI follow-up. Multivariable analyses were performed to evaluate the clinical impact of DWIr on early neurological improvement (ENI), 3‑month modified Rankin scale (mRS) score distribution (shift analysis) and to define independent predictors of DWIr. RESULTS Early neurological improvement was detected in 82/211 (41.7%) of patients while 3‑month functional independence was achieved by 75 (35.5%) patients. The DWI reversal (39/211, 18.9%) resulted an independent predictor of both ENI (aOR 3.6, 95% CI 1.2-7.7; p 0.018) and 3‑month clinical outcome (aOR for mRS shift: 2.2, 95% CI 1-4.6; p 0.030). Only successful recanalization (mTICI 2c-3) independently predicted DWIr in the studied population (aOR 3.3, 95% CI 1.3-7.9; p 0.009). CONCLUSION The DWI reversal occurs in a non-negligible proportion of DWI-ASPECTS 0-5 patients subjected to thrombectomy and significantly influences clinical outcome. The mTICI 2c-3 recanalization emerged as an independent DWIr predictor.
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Affiliation(s)
- Pietro Panni
- Department of Neuroradiology, Division of Interventional Neuroradiology, Department of Neurosurgery, San Raffaele University Hospital, Milan, Italy.
| | - Bertrand Lapergue
- Department of Neurology, Foch Hospital, Versailles Saint-Quentin en Yvelines University, Suresnes, France
| | - Benjamin Maïer
- Department of Interventional Neuroradiology, Rothschild Foundation, Paris, France
| | - Stephanos Finitsis
- AHEPA Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | | | - Sébastien Richard
- CHRU-Nancy, Department of Neurology, Stroke Unit, Université de Lorraine, 54000, Nancy, France.,CIC-P 1433, INSERM U1116, CHRU-Nancy, 54000, Nancy, France
| | - Gaultier Marnat
- Department of Diagnostic and Interventional Neuroradiology, University Hospital of Bordeaux, Bordeaux, France
| | - Romain Bourcier
- Department of Interventional Neuroradiology, Rothschild Foundation, Paris, France
| | - Igor Sibon
- Neurology, University Hospital of Bordeaux, Bordeaux, France
| | - Cyril Dargazanli
- Department of Interventional Neuroradiology, CHRU Gui de Chauliac, Montpellier, France
| | - Raphaël Blanc
- Department of Neuroradiology, University Hospital of Nantes, Nantes, France
| | - Arturo Consoli
- Diagnostic and Interventional Neuroradiology, Foch Hospital, Versailles Saint-Quentin en Yvelines University, Suresnes, France
| | - François Eugène
- Department of Neuroradiology, University Hospital of Rennes, Rennes, France
| | | | | | | | | | | | | | | | - Charlotte Rosso
- Department of Neurology, CHU Pitié-Salpétrière, Paris, France
| | | | - Guillaume Turc
- Department of Neurology, Hôpital Saint-Anne, Paris, France
| | | | | | | | | | - Anthony Le Bras
- Department of Neuroradiology, CHBA Bretagne Atlantique, Vannes, France
| | - Sarah Evain
- Neurology, CHBA Bretagne Atlantique, Vannes, France
| | - Valérie Wolff
- Department of Neurology, CHU Strasbourg, Strasbourg, France
| | - Raoul Pop
- Neuroradiology, CHU Strasbourg, Strasbourg, France
| | - Serge Timsit
- Department of Neurology, CHU Brest, Brest, France
| | | | | | | | | | - Benjamin Gory
- CHRU-Nancy, Department of Diagnostic and Therapeutic Neuroradiology, Université de Lorraine, 54000, Nancy, France.,IADI, INSERM U1254, Université de Lorraine, 54000, Nancy, France
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Wu D, Zhou Y, Cho J, Shen N, Li S, Qin Y, Zhang G, Yan S, Xie Y, Zhang S, Zhu W, Wang Y. The Spatiotemporal Evolution of MRI-Derived Oxygen Extraction Fraction and Perfusion in Ischemic Stroke. Front Neurosci 2021; 15:716031. [PMID: 34483830 PMCID: PMC8415351 DOI: 10.3389/fnins.2021.716031] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 07/12/2021] [Indexed: 12/13/2022] Open
Abstract
Purpose This study aimed to assess the spatiotemporal evolution of oxygen extraction fraction (OEF) in ischemic stroke with a newly developed cluster analysis of time evolution (CAT) for a combined quantitative susceptibility mapping and quantitative blood oxygen level-dependent model (QSM + qBOLD, QQ). Method One hundred and fifteen patients in different ischemic stroke phases were retrospectively collected for measurement of OEF of the infarcted area defined on diffusion-weighted imaging (DWI). Clinical severity was assessed using the National Institutes of Health Stroke Scale (NIHSS). Of the 115 patients, 11 underwent two longitudinal MRI scans, namely, three-dimensional (3D) multi-echo gradient recalled echo (mGRE) and 3D pseudo-continuous arterial spin labeling (pCASL), to evaluate the reversal region (RR) of the initial diffusion lesion (IDL) that did not overlap with the final infarct (FI). The temporal evolution of OEF and the cerebral blood flow (CBF) in the IDL, the RR, and the FI were assessed. Results Compared to the contralateral mirror area, the OEF of the infarcted region was decreased regardless of stroke phases (p < 0.05) and showed a declining tendency from the acute to the chronic phase (p = 0.022). Five of the 11 patients with longitudinal scans showed reversal of the IDL. Relative oxygen extraction fraction (rOEF, compared to the contralateral mirror area) of the RR increased from the first to the second MRI (p = 0.044). CBF was about 1.5-fold higher in the IDL than in the contralateral mirror area in the first MRI. Two patients showed penumbra according to the enlarged FI volume. The rOEF of the penumbra fluctuated around 1.0 at earlier scan times and then decreased, while the CBF decreased continuously. Conclusion The spatiotemporal evolution of OEF and perfusion in ischemic lesions is heterogeneous, and the CAT-based QQ method is feasible to capture cerebral oxygen metabolic information.
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Affiliation(s)
- Di Wu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yiran Zhou
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Junghun Cho
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States.,Department of Biomedical Engineering, Cornell University, Ithaca, NY, United States
| | - Nanxi Shen
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shihui Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuanyuan Qin
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Guiling Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Su Yan
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan Xie
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shun Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yi Wang
- Department of Radiology, Weill Cornell Medicine, New York, NY, United States.,Department of Biomedical Engineering, Cornell University, Ithaca, NY, United States
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