Multicenter validation of synthetic FLAIR as a substitute for FLAIR sequence in acute ischemic stroke

被引:1
作者
Hamon, Guillaume [1 ]
Legrand, Laurence [1 ,2 ,3 ]
Hmeydia, Ghazi [2 ]
Turc, Guillaume [1 ,3 ,4 ]
Hassen, Wagih Ben [1 ,2 ,3 ]
Charron, Sylvain [1 ,3 ]
Debacker, Clement [1 ,2 ,3 ]
Naggara, Olivier [1 ,2 ,3 ]
Thirion, Bertrand [5 ]
Chen, Bailiang [6 ]
Lapergue, Bertrand [7 ]
Oppenheim, Catherine [1 ,2 ,3 ]
Benzakoun, Joseph [1 ,2 ,3 ]
机构
[1] Univ Paris Cite, Inst Psychiat & Neurosci Paris, INSERM U1266, Paris, France
[2] GHU Paris Psychiat & Neurosci, Dept Neuroradiol, Site St Anne,1 Rue Cabanis, F-75014 Paris, France
[3] Univ Paris Cite, FHU Neurovasc, Paris, France
[4] GHU Paris Psychiat & Neurosci, Dept Neurol, Paris, France
[5] INRIA, PARIETAL Team, Saclay, France
[6] Univ Lorraine, CIC IT 1433, INSERM, Nancy, France
[7] Versailles St Quentin En Yvelines Univ, Foch Hosp, Dept Neurol, Suresnes, France
关键词
Acute stroke; ischemic stroke; DWI-FLAIR mismatch; synthetic FLAIR; ATTENUATED INVERSION-RECOVERY; SIGNAL INTENSITY; IDENTIFY STROKE; SYMPTOM ONSET; TIME; DIFFUSION; THROMBOLYSIS; MISMATCH;
D O I
10.1177/23969873241263418
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Purpose: To evaluate performance of synthetic and real FLAIR for identifying early stroke in a multicenter cohort. Methods: This retrospective study was conducted using DWI and FLAIR extracted from the Endovascular Treatment in Ischemic Stroke image registry (2017-2021). The database was partitioned into subsets according to MRI field strength and manufacturer, and randomly divided into training set (70%) used for model fine-tuning, validation set (15%), and test set (15%). In test set, five readers, blinded to FLAIR sequence type, assessed DWI-FLAIR mismatch using real and synthetic FLAIR. Interobserver agreement for DWI-FLAIR rating and concordance between synthetic and real FLAIR were evaluated with kappa statistics. Sensitivity and specificity for identification of <= 4.5 h AIS were compared in patients with known onset-to-MRI delay using McNemar's test. Results: 1454 complete MRI sets (1172 patients, median (IQR) age: 73 years (62-82); 762 women) acquired on 125 MRI units were analyzed. In test set (207 MRI), interobserver reproducibility for DWI-FLAIR mismatch labeling was substantial for real and synthetic FLAIR (Fleiss kappa = 0.79 (95%CI: 0.73-0.84) and 0.77 (95%CI: 0.71-0.82), respectively). After consensus, concordance between real and synthetic FLAIR was excellent (kappa = 0.85 (95%CI: 0.78-0.92)). In 141 MRI sets with known onset-to-MRI delay, diagnostic performances for <= 4.5 h AIS identification did not differ between real and synthetic FLAIR (sensitivity: 60/71 (85%) vs 59/71 (83%), p = .56; specificity: 65/70 (93%) vs 65/70 (93%), p > 0.99). Conclusion: A deep-learning-based FLAIR fine-tuned on multicenter data can provide comparable performances to real FLAIR for early AIS identification. This approach may help reducing MR protocol duration and motion artifacts.
引用
收藏
页码:161 / 171
页数:11
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